Intelligent terminal cooperative multiplexing method and device based on power quality abnormal dynamic perception

Abstract

This application relates to a method and apparatus for collaborative multiplexing of smart terminals based on dynamic perception of power quality anomalies. The method includes: perceiving power quality anomalies based on power quality indicators calculated from synchronous sampling sequences output by smart IoT power meters to identify power quality anomaly events; non-intrusive identification of load operating states within the same time period based on the power quality anomaly events to obtain a first target electrical device and its start-stop timing information; based on the first target electrical device and its corresponding start-stop timing information, combined with the first disturbance start time and disturbance type of the power quality anomaly event, determining a second target electrical device with a causal relationship to the power quality anomaly; and performing state detection on the power supply circuit associated with the second target electrical device to obtain circuit state perception results. This method can improve the safety response capability to anomaly events in complex disturbance scenarios.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a method and apparatus for collaborative reuse of intelligent terminals based on dynamic perception of power quality anomalies. Background Technology

[0002] As urban energy structures transition towards low-carbon models, the large-scale integration of distributed energy resources and electric vehicles places higher demands on the power quality of distribution systems. Currently, in low-voltage distribution systems, to monitor abnormal power quality events, a common approach is to deploy independently operating power quality monitoring units, user electricity consumption behavior identification units, and electrical safety early warning units within smart terminals. These units each collect local electrical signals and perform analysis tasks according to preset rules to identify and issue warnings for power quality issues such as voltage sags, harmonic distortion, and three-phase imbalance.

[0003] However, traditional power quality anomaly monitoring methods struggle to comprehensively perceive and respond to complex disturbances, easily leading to missed detections or delayed responses. Summary of the Invention

[0004] Therefore, it is necessary to provide a method and device for collaborative reuse of intelligent terminals based on dynamic perception of power quality anomalies, which can improve the security response capability to abnormal events in complex disturbance scenarios and address the above-mentioned technical problems.

[0005] Firstly, this application provides a collaborative multiplexing method for intelligent terminals based on dynamic sensing of power quality anomalies, including:

[0006] Power quality anomalies are detected and identified based on power quality indicators calculated from the synchronous sampling sequence output by smart IoT power meters.

[0007] Based on power quality anomaly events, the load operation status within the same time period is identified non-intrusively to obtain the first target electrical equipment and its start-stop sequence information;

[0008] Based on each first target electrical device and its corresponding start-stop timing information, combined with the start time and type of the first disturbance corresponding to the power quality anomaly event, the second target electrical device with a causal relationship to the occurrence of the power quality anomaly is determined.

[0009] The status of the power supply circuit associated with the second target electrical equipment is detected to obtain the circuit status perception result.

[0010] Secondly, this application also provides a smart terminal collaborative multiplexing device based on dynamic perception of power quality anomalies, comprising:

[0011] The power quality anomaly sensing module is used to sense power quality anomalies based on power quality indicators calculated from the synchronous sampling sequence output by the smart IoT power meter, and to identify power quality anomaly events.

[0012] The non-intrusive identification module is used to non-intrusively identify the load operation status within the same time period based on power quality abnormality events, and obtain the first target electrical equipment and its start-stop sequence information.

[0013] The causal relationship determination module is used to determine the second target electrical equipment that has a causal relationship with the occurrence of power quality anomalies, based on each first target electrical equipment and its corresponding start-stop timing information, combined with the first disturbance start time and disturbance type corresponding to the power quality anomaly event.

[0014] The loop status sensing module is used to detect the status of the power supply loop associated with the second target electrical equipment and obtain the loop status sensing result.

[0015] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the method provided in the first aspect above.

[0016] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method provided in the first aspect above.

[0017] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps in the method provided in the first aspect above.

[0018] The aforementioned intelligent terminal collaborative multiplexing method, device, computer equipment, computer-readable storage medium, and computer program product based on dynamic perception of power quality anomalies calculate power quality indicators through synchronous sampling sequences output by smart IoT power meters. This enables the perception and identification of power quality anomalies, obtaining the initial disturbance start time and disturbance type of the anomaly event. This solves the problem that power quality monitoring functional units can only detect parameter exceeding limits but lack disturbance information. Based on the anomaly event results, non-intrusive identification of the load operating status within the same time period is performed to obtain the first target electrical equipment and its start-stop timing information, establishing a correlation between the anomaly event and the operating status of the electrical equipment. This avoids the problem that user electricity consumption behavior identification functional units cannot correlate equipment operating status with the time of power quality anomaly occurrence. Based on the first target electrical equipment and its start-stop timing information, combined with the initial disturbance start time and disturbance type corresponding to the anomaly event, a second target electrical equipment with a causal relationship to the occurrence of power quality anomalies can be identified. This clarifies the disturbance source equipment attributes of the power quality anomaly and solves the problem that functional units cannot coordinate to obtain disturbance cause information. Based on the status detection of the power supply circuit associated with the second target electrical equipment, the circuit status perception result is obtained. Thus, by using the electrical early warning function, targeted monitoring work can be carried out, which makes up for the deficiency of the electrical safety early warning function unit in that it cannot accurately improve the monitoring intensity due to the lack of disturbance cause information.

[0019] Therefore, it realizes that instead of operating each functional module in the smart terminal in isolation, a collaborative response mechanism is formed around power quality anomalies. This ultimately solves the problem that the isolated operation of each functional unit makes it impossible to collaboratively perceive and accurately respond to complex power quality anomalies. It enables the overall perception of complex disturbance events within a single terminal through functional reuse and event-driven mechanisms, thereby improving the safety response capability to anomalies in complex disturbance scenarios. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart illustrating a smart terminal collaborative reuse method based on dynamic perception of power quality anomalies in one embodiment.

[0022] Figure 2 This is a flowchart illustrating a non-invasive identification process in one embodiment;

[0023] Figure 3 This is a structural block diagram of an intelligent terminal collaborative multiplexing device based on dynamic perception of power quality anomalies in one embodiment.

[0024] Figure 4 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0026] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0027] In traditional low-voltage power distribution systems, monitoring power quality anomalies typically involves deploying independently operating power quality monitoring, user electricity behavior identification, and electrical safety early warning units within smart terminals. Each of these units collects local electrical signals and performs analysis tasks according to preset rules to identify and alert on power quality issues such as voltage sags, harmonic distortion, and three-phase imbalance. However, these units lack a time synchronization and information linkage mechanism based on the same electrical event. When a complex power quality disturbance occurs due to the start-up or shutdown of specific electrical equipment (e.g., voltage sags superimposed with high-order harmonics caused by the start-up of an electric vehicle charging station), the power quality monitoring unit can detect parameter exceedances but cannot determine the equipment attributes of the disturbance source; the user electricity behavior identification unit can identify the equipment's operating status but does not establish a correlation with the timing of the power quality anomaly; and the electrical safety early warning unit, lacking information on the cause of the disturbance, struggles to specifically enhance monitoring intensity. This functional fragmentation prevents the system from holistically perceiving and responding to complex disturbances, easily leading to missed detections or delayed responses.

[0028] Based on this, the intelligent terminal collaborative reuse method, device, computer equipment, computer-readable storage medium and computer program product based on dynamic perception of power quality anomalies provided in this application can solve the technical problem that it is impossible to collaboratively perceive and accurately respond to complex power quality anomaly events due to the isolated operation of each functional unit. It realizes the overall perception of complex disturbance events in a single terminal through functional reuse and event-driven mechanism, and improves the safety response capability to anomaly events in complex disturbance scenarios.

[0029] In one exemplary embodiment, see [reference] Figure 1 , Figure 1 This is a flowchart illustrating the intelligent terminal collaborative reuse method based on dynamic sensing of power quality anomalies provided in this application. In this embodiment, the executing entity of the intelligent terminal collaborative reuse method based on dynamic sensing of power quality anomalies is a terminal management device. Therefore, the intelligent terminal collaborative reuse method based on dynamic sensing of power quality anomalies includes:

[0030] Step 10: Based on the power quality indicators calculated from the synchronous sampling sequence output by the smart IoT power meter, power quality anomaly detection is performed to determine power quality anomaly events.

[0031] Optionally, the terminal management device acquires the synchronous sampling sequence output by the smart IoT energy meter, wherein the synchronous sampling sequence is a continuous data sequence generated by the smart IoT energy meter synchronously collecting electrical parameters in the power supply line according to a preset sampling frequency.

[0032] Electrical parameters include at least one of voltage, current, active power, reactive power, frequency, and harmonic content. The preset sampling frequency is not less than 50 Hz to ensure that the sampling data can fully reflect the real-time electrical status of the power supply line. Each sampling data in the synchronous sampling sequence corresponds to a unique sampling time to ensure the time consistency of the sampling data of each electrical parameter.

[0033] Furthermore, the terminal management device preprocesses the acquired synchronous sampling sequence. This preprocessing includes data verification, outlier removal, and data smoothing. Data verification involves the terminal management device determining whether each sampled data point in the synchronous sampling sequence is within a preset reasonable range. This preset reasonable range is determined based on the rated parameters of the power supply line. For example, for a residential power supply line with a rated voltage of 220 volts, the reasonable range for voltage sampling data is set to 198 volts to 242 volts. Sampled data exceeding this range is considered invalid. Outlier removal involves the terminal management device deleting invalid data detected during verification, as well as abruptly changing abnormal data caused by interference during the sampling process (i.e., data whose difference from adjacent sampled data exceeds a preset difference threshold, set according to the type of electrical parameter; for example, the voltage parameter difference threshold is set to 10 volts). Data smoothing involves the terminal management device using a moving average method to process the synchronous sampling sequence after outlier removal. The moving average window size is set to 5 sampling points, meaning the smoothed value for each sampling point is the average of that sampling point and the two sampling points before and after it. Data smoothing eliminates the influence of sampling noise on subsequent calculations, ensuring the stability of the sampled data.

[0034] Furthermore, after preprocessing, the terminal management device calculates various power quality indicators based on the preprocessed synchronous sampling sequence. These power quality indicators include at least one of the following: voltage deviation, frequency deviation, total harmonic distortion, voltage fluctuation, voltage swell, voltage drop, and voltage interruption. The calculation of each power quality indicator uses algorithms described in words, and the specific calculation process is as follows:

[0035] 1. Voltage Deviation Calculation: The terminal management device extracts all voltage sampling data from the preprocessed synchronous sampling sequence, calculates the average value of all voltage sampling data, uses this average value as the actual operating voltage, then calculates the difference between the actual operating voltage and the rated voltage of the power supply line, and multiplies the ratio of this difference to the rated voltage by 100% to obtain the voltage deviation.

[0036] 2. Frequency deviation calculation: Extract all frequency sampling data from the preprocessed synchronous sampling sequence, calculate the average value of all frequency sampling data, take the average value as the actual operating frequency, and then calculate the difference between the actual operating frequency and the rated frequency (e.g., 50 Hz) to obtain the frequency deviation.

[0037] 3. Calculation of total harmonic distortion rate: Perform harmonic analysis on the preprocessed voltage sampling sequence, extract the fundamental voltage and each harmonic voltage (e.g., 2nd to 30th), calculate the effective value of each harmonic voltage, then calculate the sum of squares of the effective values ​​of all harmonic voltages, take the square root of the sum of squares to obtain the total effective value of harmonics, and multiply the ratio of the total effective value of harmonics to the effective value of the fundamental voltage by 100% to obtain the total harmonic distortion rate.

[0038] 4. Voltage fluctuation calculation: Extract voltage sampling data from the preprocessed synchronous sampling sequence, divide the voltage sampling data into several consecutive time periods in chronological order, set the duration of each time period to 1 second, calculate the maximum and minimum values ​​of the voltage sampling data in each time period, obtain the voltage fluctuation value in each time period (i.e., the difference between the maximum and minimum voltage values ​​in that time period), and then calculate the average value of the voltage fluctuation values ​​in all time periods to obtain the voltage fluctuation.

[0039] 5. Voltage Surge, Voltage Sag, and Voltage Interruption Calculation: Thresholds for voltage surge, voltage sag, and voltage interruption are set. The threshold for voltage surge is 110% of the rated voltage, the threshold for voltage sag is 90% of the rated voltage, and the threshold for voltage interruption is 10% of the rated voltage. The voltage sampling data is plotted over time. A voltage surge is defined as follows: when the actual operating voltage is consistently higher than 110% of the rated voltage for a period of time, and the duration is between 0.5 seconds and 60 seconds; a voltage sag is defined as follows: when the actual operating voltage is consistently lower than 90% of the rated voltage for a period of time, and the duration is between 0.5 seconds and 60 seconds; a voltage interruption is defined as follows: when the actual operating voltage is consistently lower than 10% of the rated voltage for a period of time, and the duration is not less than 0.5 seconds. The start time (i.e., the sampling time when the first threshold is reached) and end time (i.e., the sampling time when the voltage first recovers to the threshold range) of each voltage surge, voltage sag, and voltage interruption are recorded.

[0040] Furthermore, after the calculation of each power quality indicator is completed, the terminal management device compares each calculated power quality indicator with the corresponding power quality standard threshold. The power quality standard threshold is set according to the relevant national power quality standards. For example, the standard threshold for voltage deviation is ±7%, the standard threshold for frequency deviation is ±0.2 Hz, the standard threshold for total harmonic distortion is 5%, and the standard threshold for voltage fluctuation is 0.5%. If at least one power quality indicator exceeds the corresponding standard threshold, the terminal management device determines that a power quality abnormality has occurred and identifies a power quality abnormality event.

[0041] Specifically, for power quality anomalies, the starting time of the anomaly (i.e., the first disturbance start time, which is the sampling time when the power quality index is first detected to exceed the standard threshold), the ending time of the anomaly, the power quality indexes involved in the anomaly, the actual values ​​of each anomaly index, the standard thresholds corresponding to the anomaly indexes, and the disturbance type must be clearly recorded. The disturbance type is determined based on the power quality index that exceeds the standard threshold. For example, if the voltage deviation exceeds the standard threshold, the disturbance type is voltage deviation disturbance; if the total harmonic distortion exceeds the standard threshold, the disturbance type is harmonic disturbance; if the voltage sag, the disturbance type is voltage sag disturbance, and so on.

[0042] If all power quality indicators are within the corresponding standard threshold range, the terminal management device determines that no power quality abnormality has occurred and does not generate a power quality abnormality event.

[0043] In one embodiment, taking the 220V power supply line of China Southern Power Grid as an example, the terminal management device obtains the synchronous sampling sequence output by the smart IoT energy meter. The preset sampling frequency is 100 Hz. The synchronous sampling sequence includes sampling data of voltage, current, frequency, and harmonic content. The sampling duration is 10 seconds, with a total of 1000 sampling points.

[0044] The synchronous sampling sequence was preprocessed as follows: the reasonable range for voltage sampling data was set to 198 volts to 242 volts, the reasonable range for current sampling data to 0 amps to 30 amps, and the reasonable range for frequency sampling data to 49.5 Hz to 50.5 Hz. The difference thresholds were set to 10 volts (voltage), 2 amps (current), and 0.1 Hz (frequency). During the verification process, it was found that the voltage sampling data of the 501st sampling point was 250 volts, which was outside the reasonable range, and the frequency sampling data of the 700th sampling point was 48 Hz, which was outside the reasonable range. These two sampling points were determined to be invalid data and were removed. A sliding average method with a sliding window size of 5 sampling points was used to smooth the data of the 998 sampling points after removing invalid data to eliminate sampling noise.

[0045] After preprocessing, the terminal management device calculates various power quality indicators:

[0046] 1. Extract all preprocessed voltage sampling data and calculate its average value as 238 volts. The rated voltage of the civilian power supply line is 220 volts. The voltage deviation = (238-220) / 220*100%≈8.2%;

[0047] 2. Extract all preprocessed frequency sampling data and calculate its average value as 50.3 Hz. The rated frequency is 50 Hz, and the frequency deviation is 50.3 - 50 = 0.3 Hz.

[0048] 3. Harmonic analysis was performed on the voltage sampling sequence. The effective value of the fundamental voltage was 237 volts. The sum of the squares of the effective values ​​of the 2nd to 30th harmonic voltages was 1416.25, the total effective value of the harmonics was 37.63 volts, and the total harmonic distortion rate was approximately 15.9% (37.63 / 237*100%).

[0049] 4. Divide the voltage sampling data into 10 time periods with each time period being 1 second. Calculate the difference between the maximum and minimum voltage values ​​in each time period. The 10 voltage fluctuation values ​​are 8V, 7V, 9V, 8V, 10V, 7V, 8V, 9V, 7V, and 8V, with an average value of 8.1V.

[0050] 5. Voltage swell, droop, and interruption determination: The voltage swell threshold was set to 242 volts (220*110%), the droop threshold to 198 volts (220*90%), and the interruption threshold to 22 volts (220*10%). After plotting the voltage change curve, it was found that the voltage did not fall below 198 volts, did not fall below 22 volts, and did not remain above 242 volts for any period of time. Therefore, there were no voltage swell, droop, or interruption phenomena.

[0051] Subsequently, the terminal management device compares various power quality indicators with standard thresholds, including voltage deviation standard thresholds of ±7%, frequency deviation standard thresholds of ±0.2 Hz, total harmonic distortion standard thresholds of 5%, and voltage fluctuation standard thresholds of 0.5%. The comparison shows that the voltage deviation of 8.2% exceeds the standard threshold of ±7%, the frequency deviation of 0.3 Hz exceeds the standard threshold of ±0.2 Hz, the total harmonic distortion of 15.9% exceeds the standard threshold of 5%, and the voltage fluctuation of 8.1 volts exceeds the standard threshold of 0.5% (220 volts * 0.5% = 1.1 volts).

[0052] Therefore, the terminal management device determines that a power quality anomaly has occurred, identifies the power quality anomaly event, records the start time of the anomaly as the first sampling time (0 milliseconds), and the end time of the anomaly as the 1000th sampling time (10000 milliseconds). The power quality indicators involved in the anomaly are voltage deviation, frequency deviation, total harmonic distortion, and voltage fluctuation. The actual values ​​of each anomaly indicator are 8.2%, 0.3 Hz, 15.9%, and 8.1 V, respectively, and the corresponding standard thresholds are ±7%, ±0.2 Hz, 5%, and 1.1 V, respectively. The disturbance types are voltage deviation disturbance, frequency deviation disturbance, harmonic disturbance, and voltage fluctuation disturbance.

[0053] Step 20: Based on the power quality anomaly event, perform non-intrusive identification of the load operation status within the same time period to obtain the first target electrical equipment and its start-stop sequence information.

[0054] Optionally, the terminal management device can control the power consumption behavior identification module to lock the abnormal time period (i.e., from the start time of the abnormality to the end time of the abnormality) corresponding to the power quality abnormality event as the trigger condition, and perform non-intrusive identification of the overall load operation status of the power supply line during the time period. Non-intrusive identification does not require individual wiring detection for each electrical device, but only by analyzing the overall electrical parameter change characteristics of the power supply line to identify the operating status of the electrical device.

[0055] Optionally, in the identification process of this application embodiment, the electricity consumption behavior identification module combines the change patterns of electrical parameters such as current and power in the preprocessed synchronous sampling sequence to distinguish the differences in electrical characteristics of different electrical devices during operation, and screens out the electrical devices that are in operation or undergo start-stop changes during the abnormal time period, and identifies them as the first target electrical devices.

[0056] Furthermore, the electricity consumption behavior recognition module extracts the start-stop event sequence corresponding to each first target electrical device as start-stop timing information. The start-stop event sequence is a sequence formed by arranging all start and stop events of the electrical device in chronological order during the abnormal time period. The rising edge switching time in the start-stop event sequence is the start time of the electrical device (i.e., the moment when the electrical parameters change abruptly from zero to one and from small to large, reaching the device start threshold), and the falling edge switching time is the stop time of the electrical device (i.e., the moment when the electrical parameters change abruptly from one to one and from large to small, falling below the device operation threshold).

[0057] Step 30: Based on each first target electrical device and its corresponding start-stop timing information, combined with the first disturbance start time and disturbance type corresponding to the power quality anomaly event, determine the second target electrical device that has a causal relationship with the occurrence of the power quality anomaly.

[0058] Optionally, the terminal management device performs causal correlation judgment logic based on each first target electrical device and its corresponding start-stop timing information, as well as the first disturbance start time (abnormal start time) and disturbance type corresponding to the power quality abnormal event. It judges each first target electrical device one by one. The core of the judgment is to verify whether the start-up behavior of the first target electrical device and the power quality abnormality satisfy the causal correlation relationship. The causal correlation relationship is specifically represented by two core conditions: First, time coincidence, that is, the time difference between the start-up time of the first target electrical device and the first disturbance start time is within a preset time threshold (the preset time threshold is set according to the actual scenario to ensure the temporal correlation between the start-up behavior and the occurrence of the abnormality); Second, electrical characteristic disturbance consistency, that is, the type of electrical disturbance generated when the first target electrical device starts up matches the disturbance type of the power quality abnormal event (for example, the device starts up and generates harmonic disturbance, while the disturbance type of the abnormal event includes harmonic disturbance).

[0059] Furthermore, the terminal management device sequentially verifies the above two conditions for each first target electrical device. If both conditions are met, the first target electrical device is determined to be the second target electrical device that has a causal relationship with the power quality abnormality. If both conditions are not met (only one condition is met or neither condition is met), the first target electrical device is determined to have no causal relationship with the power quality abnormality and is not considered as the second target electrical device.

[0060] Step 40: Perform status detection on the power supply circuit associated with the second target electrical equipment to obtain the circuit status perception result.

[0061] Optionally, the terminal management device controls the power consumption early warning module to lock each second target electrical device, query the associated power supply circuit (i.e., the dedicated circuit or shared circuit that provides power to the second target electrical device) corresponding to each second target electrical device, and perform comprehensive status detection on each associated power supply circuit. The core of the status detection is to obtain the real-time operating parameters of the circuit and determine whether there is an abnormal state in the circuit. The detection content includes, but is not limited to, the voltage stability, current load, line temperature, contact resistance, insulation performance, etc. of the circuit. The power consumption early warning module integrates and analyzes the detected data to obtain the circuit status perception result.

[0062] This application's embodiments achieve the goal of no longer operating each functional module in the smart terminal in isolation, but instead forming a collaborative response mechanism around power quality anomaly events. Ultimately, it solves the problem that the isolated operation of each functional unit makes it impossible to collaboratively perceive and accurately respond to complex power quality anomaly events. It realizes the overall perception of complex disturbance events within a single terminal through functional reuse and event-driven mechanisms, thereby improving the safety response capability to anomaly events in complex disturbance scenarios.

[0063] Optionally, such as Figure 2 As shown, step 20 may include steps 201 to 204, specifically including:

[0064] Step 201: Determine the time window corresponding to the power quality anomaly event based on the start and end times of the power quality anomaly event in the synchronous sampling sequence.

[0065] Optionally, the terminal management device extracts the abnormal start time (i.e., the first disturbance start time, which is the sampling time when the power quality index is first detected to exceed the standard threshold) and the abnormal termination time (which is the sampling time when the power quality index is first detected to return to the standard threshold range) of the power quality abnormal event record.

[0066] Furthermore, the terminal management device uses the abnormal start time of the power quality anomaly event as the starting endpoint of the time window and the abnormal end time as the ending endpoint of the time window to determine a time window that completely corresponds to the power quality anomaly event. The time window is a continuous time period, the length of which is equal to the difference between the abnormal end time and the abnormal start time. It is used to accurately lock the time range in which non-intrusive identification of load operation status is required, ensuring that the identification range is completely consistent with the time period of the power quality anomaly event, and avoiding the introduction of irrelevant load data due to an excessively large identification range, or the omission of load status changes within the abnormal time period due to an excessively small identification range.

[0067] It should be noted that the start and end points of the time window precisely correspond to the sampling time of the synchronous sampling sequence, maintaining consistency with the sampling time accuracy of the synchronous sampling sequence output by the smart IoT energy meter. This ensures that relevant data within the time window can be accurately extracted from the synchronous sampling sequence subsequently. If no power quality anomaly event is detected in step 10 (i.e., all power quality indicators are within the standard threshold range), the terminal management device will not execute the steps of this embodiment.

[0068] Continuing with the above embodiment, the power quality anomaly event determined in step 10 has an anomaly start time (first disturbance start time) of the first sampling time of the synchronous sampling sequence, corresponding to an actual time of 0 milliseconds, and an anomaly termination time of the 1000th sampling time of the synchronous sampling sequence, corresponding to an actual time of 10000 milliseconds (because the preset sampling frequency of the synchronous sampling sequence is 100 Hz, the time interval between each sampling point is 10 milliseconds, and the duration corresponding to 1000 sampling points is 1000 * 10 milliseconds = 10000 milliseconds).

[0069] The start time (0 milliseconds) and end time (10000 milliseconds) of the anomaly are retrieved. Using 0 milliseconds as the start endpoint and 10000 milliseconds as the end endpoint of the time window, the time window corresponding to the power quality anomaly event is determined to be from 0 to 10000 milliseconds, with a duration of 10000 milliseconds. This is completely consistent with the occurrence period of the power quality anomaly event, and the time precision of this time window is consistent with the sampling time precision of the synchronous sampling sequence, which can accurately match the sampling data in the synchronous sampling sequence.

[0070] Step 202: Extract the current signal waveform data within the time window from the synchronous sampling sequence, and calculate the instantaneous active power sequence based on the current signal waveform data.

[0071] Optionally, the terminal management device retrieves the synchronous sampling sequence that has been acquired and preprocessed in step 10 based on the time window, accurately extracts all current sampling data within the time window (i.e., between the start and end points of the time window) from the synchronous sampling sequence, and arranges all the extracted current sampling data in the order of their corresponding sampling times to form current signal waveform data within the time window. The current signal waveform data can completely reflect the current change state of the power supply line within the time window, and each current sampling data corresponds to a unique sampling time, which corresponds one-to-one with the time range of the time window.

[0072] Furthermore, based on the intercepted current signal waveform data, the terminal management device combines the voltage sampling data at the same sampling time corresponding to the current signal waveform data in the synchronous sampling sequence (the voltage sampling data has been preprocessed and is collected synchronously with the current sampling data, and the time consistency meets the requirements) to calculate the instantaneous active power sequence within the time window.

[0073] Optionally, the algorithm for calculating instantaneous active power in this embodiment is as follows: for each sampling moment within the time window, take the preprocessed voltage sampling data corresponding to that sampling moment and the preprocessed current sampling data corresponding to the same sampling moment, multiply the two data to obtain the instantaneous active power value at that sampling moment; arrange the instantaneous active power values ​​of all sampling moments within the time window in the order of their corresponding sampling moments to form an instantaneous active power sequence. Each instantaneous active power value in the instantaneous active power sequence corresponds to a unique sampling moment, which corresponds one-to-one with the sampling moments of the current signal waveform data and the voltage sampling data, and the length of the instantaneous active power sequence is consistent with the length of the truncated current signal waveform data (i.e., the number of sampling points is the same). It should be noted that when extracting current signal waveform data, it is necessary to ensure that no current sampling data within the time window is missed, nor any current sampling data outside the time window is included, so as to avoid affecting the calculation accuracy of the subsequent instantaneous active power sequence. The calculation of instantaneous active power must strictly correspond to the voltage and current sampling data at the same sampling time to ensure that the calculation results can truly reflect the instantaneous active power status of the power supply line at that time.

[0074] Continuing with the above embodiment, the time window is 0 to 10000 milliseconds, the preset sampling frequency of the synchronous sampling sequence is 100 Hz, and the time window contains a total of 1000 sampling points (0 to 10000 milliseconds, one sampling point every 10 milliseconds). The terminal management device accurately extracts all current sampling data corresponding to these 1000 sampling points from the preprocessed synchronous sampling sequence, arranges them in the order of sampling time, and forms current signal waveform data. This data contains 1000 current sampling values, with the time range covering 0 to 10000 milliseconds.

[0075] The terminal management device retrieves the preprocessed voltage sampling data (a total of 1000, corresponding one-to-one with the current sampling data) at the same time corresponding to these 1000 sampling points in the synchronous sampling sequence, and calculates the instantaneous active power value at each sampling time: for example, the voltage sampling data corresponding to the first sampling time (0 milliseconds) is 230 volts and the current sampling data is 2 amps, so the instantaneous active power value at this time = 230 volts * 2 amps = 460 watts; the voltage sampling data corresponding to the second sampling time (10 milliseconds) is 231 volts and the current sampling data is 2.1 amps, so the instantaneous active power value at this time = 231 volts * 2.1 amps = 485.1 watts;

[0076] By analogy, the instantaneous active power values ​​corresponding to 1000 sampling times are calculated. After being arranged in the order of sampling times, an instantaneous active power sequence containing 1000 instantaneous active power values ​​is formed. This sequence corresponds completely to the sampling times of the current signal waveform data and voltage sampling data.

[0077] Step 203: Based on the location and direction of amplitude abrupt change points in the instantaneous active power sequence, determine the active power step change points. Each active power step change point corresponds to a load state switching moment.

[0078] Optionally, the terminal management device performs point-by-point analysis on the instantaneous active power sequence, identifies the location and direction of all amplitude abrupt change points in the sequence, and then determines the active power step change point.

[0079] The amplitude mutation point refers to the sampling point in the instantaneous active power sequence where the difference between the instantaneous active power value at a certain sampling moment and the instantaneous active power value at the adjacent previous sampling moment exceeds the preset amplitude mutation threshold. The preset amplitude mutation threshold is set according to the rated power of the power supply line, the starting power of common electrical equipment, and the actual application scenario. The value range is from 10 watts to 100 watts and can be adjusted adaptively according to actual needs. However, after adjustment, it needs to be clearly set to ensure the accuracy of mutation point identification. In this embodiment, the preset amplitude mutation threshold is set to 50 watts.

[0080] Optionally, the direction of change of amplitude mutation points is divided into two types: upward and downward. If the instantaneous active power value at the sampling time corresponding to a certain amplitude mutation point is greater than the instantaneous active power value at the adjacent previous sampling time, and the difference between the two exceeds the preset amplitude mutation threshold, then the direction of change of the amplitude mutation point is upward. If the instantaneous active power value at the sampling time corresponding to a certain amplitude mutation point is less than the instantaneous active power value at the adjacent previous sampling time, and the difference between the two (taking the absolute value) exceeds the preset amplitude mutation threshold, then the direction of change of the amplitude mutation point is downward.

[0081] Furthermore, the terminal management device identifies all amplitude abrupt change points as active power step change points. Each active power step change point corresponds to a load state switching moment, which is the sampling moment corresponding to the amplitude abrupt change point. Specifically, active power step change points with an upward direction of change correspond to the state switching moment when the load switches from a stopped state to a started state or when the load power increases; active power step change points with a downward direction of change correspond to the state switching moment when the load switches from a started state to a stopped state or when the load power decreases. It should be noted that when analyzing amplitude abrupt change points, the instantaneous active power values ​​of two adjacent sampling moments in the instantaneous active power sequence must be compared point by point to ensure that no potential abrupt change point is missed. If the difference between the instantaneous active power values ​​of two adjacent sampling moments does not exceed the preset amplitude abrupt change threshold, then the point corresponding to that sampling moment is neither an amplitude abrupt change point nor an active power step change point, and the corresponding load is in a stable operating state without state switching.

[0082] Continuing with the above embodiments, the instantaneous active power sequence contains instantaneous active power values ​​at 1000 sampling times, the preset amplitude mutation threshold is set to 50 watts, and the terminal management device performs point-by-point comparative analysis on the sequence.

[0083] Analysis revealed that the instantaneous active power value at the 100th sampling time (990 milliseconds) was 500 watts, while the instantaneous active power value at the adjacent previous sampling time (99th, 980 milliseconds) was 430 watts. The difference between the two was 70 watts, exceeding the preset amplitude change threshold of 50 watts. Furthermore, the instantaneous active power value at this time was greater than that at the previous time. Therefore, the point corresponding to this sampling time was an amplitude change point, with the change direction being upward. It was determined to be a step change point in active power, and the corresponding load state switching time was 990 milliseconds.

[0084] The instantaneous active power value corresponding to the 500th sampling time (4990 milliseconds) is 800 watts, and the instantaneous active power value corresponding to the adjacent previous sampling time (499th, 4980 milliseconds) is 860 watts. The difference between the two (absolute value) is 60 watts, which exceeds the preset amplitude change threshold of 50 watts. Moreover, the instantaneous active power value at this time is less than that at the previous time. Therefore, the point corresponding to this sampling time is the amplitude change point, and the direction of change is decreasing. It is determined to be the active power step change point, and the corresponding load state switching time is 4990 milliseconds.

[0085] The instantaneous active power value corresponding to the 800th sampling time (7990 ms) is 320 watts, and the instantaneous active power value corresponding to the adjacent previous sampling time (799th, 7980 ms) is 260 watts. The difference between the two is 60 watts, which exceeds the preset amplitude change threshold of 50 watts. The change direction is upward, and it is determined to be the active power step change point. The corresponding load state switching time is 7990 ms.

[0086] The difference between two adjacent instantaneous active power values ​​at other sampling times did not exceed the preset amplitude change threshold of 50 watts, and therefore did not belong to amplitude change points or constitute active power step change points. In the end, a total of 3 active power step change points were determined in this instantaneous active power sequence, corresponding to 3 load state switching times: 990 milliseconds, 4990 milliseconds, and 7990 milliseconds.

[0087] Step 204: Divide the time window into multiple continuous steady-state operating segments based on each step change point of active power, and determine the first target electrical equipment and its start-stop sequence information based on the average value of instantaneous active power and the average value of instantaneous reactive power in each steady-state operating segment.

[0088] Optionally, the terminal management device divides the time window into multiple consecutive steady-state operation segments, using the load state switching time corresponding to each active power step change point as the dividing point. The division rule in this embodiment is as follows: the starting endpoint of the first steady-state operation segment is the starting endpoint of the time window, and the ending endpoint is the load state switching time corresponding to the first active power step change point; the starting endpoint of the second steady-state operation segment is the load state switching time corresponding to the first active power step change point, and the ending endpoint is the load state switching time corresponding to the second active power step change point; and so on, the starting endpoint of the last steady-state operation segment is the load state switching time corresponding to the last active power step change point, and the ending endpoint is the ending endpoint of the time window; if no active power step change point is identified within the time window, then the entire time window is a steady-state operation segment.

[0089] Optionally, within each steady-state operating section, the load operating state of the power supply line remains stable with no significant power step change, and the terminal management device calculates the average instantaneous active power and the average instantaneous reactive power within each steady-state operating section.

[0090] The algorithm for calculating the average instantaneous active power is as follows:

[0091] The instantaneous active power values ​​at all sampling times within the steady-state operating section are summed to obtain the total active power. The total active power is then divided by the number of sampling points within the steady-state operating section to obtain the average instantaneous active power of the steady-state operating section.

[0092] The algorithm for calculating the average instantaneous reactive power is as follows:

[0093] Retrieve preprocessed voltage and current sampling data corresponding to all sampling moments within the steady-state operating segment from the synchronous sampling sequence, calculate the instantaneous reactive power value at each sampling moment (instantaneous reactive power value = voltage sampling data at the same sampling moment * current sampling data at the same sampling moment * sine function value, where the sine function value corresponds to the phase difference between voltage and current), sum all instantaneous reactive power values ​​to obtain the total reactive power, and divide the total reactive power by the number of sampling points within the steady-state operating segment to obtain the average instantaneous reactive power of the steady-state operating segment.

[0094] Continuing with the above embodiment, the time window is from 0 to 10000 milliseconds. A total of 3 active power step change points were identified, corresponding to 3 load state switching times: 990 milliseconds, 4990 milliseconds, and 7990 milliseconds.

[0095] The terminal management device divides the time window into four consecutive steady-state operating segments, using these three load state switching moments as dividing points:

[0096] 1. First steady-state operation segment: starting point 0 ms, ending point 990 ms, containing 99 sampling points (0 to 980 ms); calculate the average instantaneous active power of this segment, sum the instantaneous active power values ​​of the 99 sampling times in this segment to obtain 44550 watts, the average instantaneous active power = 44550 watts / 99 = 450 watts; at the same time, calculate the average instantaneous reactive power of this segment as 120 VAR.

[0097] 2. Second steady-state operation section: starting point 990 ms, ending point 4990 ms, containing 400 sampling points (990 to 4980 ms); calculate the average instantaneous active power of this section, sum the 400 instantaneous active power values ​​to get 200,000 watts, average instantaneous active power = 200,000 watts / 400 = 500 watts; average instantaneous reactive power is 150 VAR.

[0098] 3. Third steady-state operating section: starting point 4990 ms, ending point 7990 ms, containing 300 sampling points (4990 to 7980 ms); calculate the average instantaneous active power of this section, sum the 300 instantaneous active power values ​​to get 240000 watts, average instantaneous active power = 240000 watts / 300 = 800 watts; average instantaneous reactive power is 200 VAR.

[0099] 4. Fourth steady-state operating segment: starting point 7990 ms, ending point 10000 ms, containing 201 sampling points (7990 to 10000 ms); calculate the average instantaneous active power of this segment, sum the 201 instantaneous active power values ​​to get 64320 watts, average instantaneous active power = 64320 watts / 201 = 320 watts; average instantaneous reactive power is 90 VAR.

[0100] Furthermore, the terminal management device determines the first target electrical equipment and its start-stop timing information based on the average instantaneous active power and average instantaneous reactive power in each steady-state operating segment.

[0101] This application embodiment does not require individual wiring and testing for each electrical device. It can accurately identify the load operating status within the corresponding time period of the power quality anomaly event simply by reusing the synchronous sampling sequence data. This effectively solves the problems of inaccurate load identification range, untimely capture of load status switching, and redundant identification data. It ensures the coordination and accuracy of the entire power quality anomaly detection and related device identification process, thereby improving the safety response capability of anomaly events in complex disturbance scenarios.

[0102] Optionally, determining the first target electrical equipment and its start-stop timing information based on the average instantaneous active power and average instantaneous reactive power within each steady-state operating segment may include steps 2041 to 2044. Wherein:

[0103] Step 2041: Based on the average instantaneous active power and average instantaneous reactive power in each steady-state operating segment, determine the two-dimensional electrical feature vector, and based on the active power amplitude range and reactive power amplitude range of various types of electrical equipment in the pre-constructed electrical feature library of electrical equipment under steady-state operating conditions, obtain the candidate electrical equipment combination that matches the two-dimensional electrical feature vector of each steady-state operating segment.

[0104] Optionally, the terminal management device determines a two-dimensional electrical characteristic vector for each steady-state operating segment based on the average instantaneous active power and average instantaneous reactive power within each steady-state operating segment. The two-dimensional electrical characteristic vector is a quantitative indicator characterizing the overall electrical characteristics of the load within the steady-state operating segment. It is composed of the average instantaneous active power and average instantaneous reactive power for each steady-state operating segment, with the two values ​​arranged in a fixed order of "average instantaneous active power, average instantaneous reactive power," ensuring a unified comparison standard for the two-dimensional electrical characteristic vectors of different steady-state operating segments.

[0105] Furthermore, the terminal management device pre-builds an electrical characteristic database of electrical equipment. This database stores the electrical characteristic parameters of various common electrical equipment under steady-state operating conditions. The database contains the unique equipment identifier, equipment name, equipment category, and active power amplitude range and reactive power amplitude range under steady-state operating conditions for each type of electrical equipment. The steady-state operating conditions refer to the operating conditions under which the electrical equipment operates stably and the power does not fluctuate significantly after normal startup. The active power amplitude range refers to the continuous range between the maximum and minimum values ​​of instantaneous active power that may occur when the electrical equipment is operating in steady state. The reactive power amplitude range refers to the continuous range between the maximum and minimum values ​​of instantaneous reactive power that may occur when the electrical equipment is operating in steady state.

[0106] Optionally, the construction logic of the electrical feature database of electrical equipment in this application embodiment is as follows: The terminal management device collects the rated electrical parameters of various common electrical equipment (such as televisions, air conditioners, rice cookers, washing machines, lights, etc.), and combines them with actual operation test data to determine the active power amplitude range and reactive power amplitude range of each type of electrical equipment under steady-state operation conditions, ensuring the accuracy and coverage of the range. At the same time, a unique equipment identifier and a clear equipment category are assigned to each type of electrical equipment, and a one-to-one correspondence is established between the equipment name, equipment identifier, equipment category and the two power amplitude ranges. The data in the database can be dynamically supplemented and modified according to the needs of adding new types of electrical equipment, updating equipment parameters, etc. The modified data needs to be updated synchronously to ensure the timeliness of the data in the database.

[0107] Furthermore, the terminal management device performs a matching operation on the two-dimensional electrical feature vector of each steady-state operating segment. The matching logic of this embodiment is as follows: it determines whether the average instantaneous active power in the two-dimensional electrical feature vector falls within the active power amplitude range of a certain type of electrical equipment, and at the same time determines whether the average instantaneous reactive power in the two-dimensional electrical feature vector falls within the reactive power amplitude range of that type of electrical equipment; if both conditions are met, then that type of electrical equipment is a candidate device for the steady-state operating segment; the terminal management device traverses all electrical equipment types in the electrical feature library of electrical equipment, filters out all electrical equipment that meets the above matching conditions, and combines them to form a candidate electrical equipment combination corresponding to the steady-state operating segment. The candidate electrical equipment combination may include a single electrical equipment or multiple electrical equipment (i.e., when multiple electrical equipment are running simultaneously, their overall average instantaneous active power and average instantaneous reactive power exactly match the two-dimensional electrical feature vector of the steady-state operating segment).

[0108] It should be noted that the matching process must strictly follow the "simultaneous satisfaction" principle, that is, only when the average value of instantaneous active power and the average value of instantaneous reactive power both fall within the corresponding power amplitude range of a certain type of electrical equipment can that type of electrical equipment be included in the candidate electrical equipment combination.

[0109] If a certain type of electrical equipment meets only one of the power range requirements but not the other, it will not be included in the candidate range to avoid inaccurate matching of candidate equipment.

[0110] If, after traversing all types of electrical equipment, no type of electrical equipment meets the matching conditions, the terminal management device records that there are no candidate combinations of electrical equipment in the steady-state operating segment and triggers a re-verification process to verify whether the calculation of the instantaneous average active power and instantaneous average reactive power in the steady-state operating segment is accurate, and whether there are any missing data in the electrical feature library of electrical equipment.

[0111] Continuing with the above embodiments, the terminal management device has divided the time window into four steady-state operation segments. The average instantaneous active power and average instantaneous reactive power of each segment are as follows: First segment (0-990 ms): 450 W, 120 VAR; Second segment (990-4990 ms): 500 W, 150 VAR; Third segment (4990-7990 ms): 800 W, 200 VAR; Fourth segment (7990-10000 ms): 320 W, 90 VAR.

[0112] The pre-built electrical characteristic library of electrical equipment includes parameters for the following common types of electrical equipment (only equipment types relevant to this embodiment are listed): 1. Lighting: active power range of 300-350 watts, reactive power range of 80-100 VAR, equipment category: lighting; 2. Rice cooker: active power range of 400-500 watts, reactive power range of 110-130 VAR, equipment category: cooking; 3. Television: active power range of 100-150 watts, reactive power range of 40-60 VAR, equipment category: audio-visual; 4. Air conditioner (low cooling setting): active power range of 750-850 watts, reactive power range of 180-220 VAR, equipment category: cooling.

[0113] The terminal management device performs matching on the two-dimensional electrical feature vector of each section:

[0114] 1. First segment: The two-dimensional electrical feature vector is (450 watts, 120 VAT). The equipment in the database is judged as follows: the active power amplitude of the rice cooker is 400-500 watts (450 watts falls within the range), and the reactive power amplitude is 110-130 VAT (120 VAT falls within the range), which meets the matching conditions; the other equipment does not meet the two power range requirements at the same time. Therefore, the candidate electrical equipment combination in the first segment is {rice cooker}.

[0115] 2. Second section: The two-dimensional electrical feature vector is (500 watts, 150 VAT). The equipment in the database is judged as follows: the active power amplitude of the rice cooker is 400 watts-500 watts (500 watts falls within the range), and the reactive power amplitude is 110 VAT-130 VAT (150 VAT does not fall within the range); the other equipment does not meet the two power range requirements at the same time. Therefore, the candidate electrical equipment combination in the second section is {rice cooker} (500 watts is the upper limit of the active power of the rice cooker, which is still considered to fall within the range).

[0116] 3. Third section: The two-dimensional electrical feature vector is (800 watts, 200 VAT). The equipment in the database is judged to have an active power range of 750 watts-850 watts (800 watts falls within the range) and a reactive power range of 180 VAT-220 VAT (200 VAT falls within the range), which meets the matching conditions. The other equipment does not meet the two power range requirements at the same time. Therefore, the candidate electrical equipment combination in the third section is {air conditioner (low cooling level)}.

[0117] 4. Fourth Section: The two-dimensional electrical feature vector is (320 watts, 90 VAR). Judging from the equipment in the database: the active power amplitude of the lighting lamp is 300-350 watts (320 watts falls within the range), and the reactive power amplitude is 80-100 VAR (90 VAR falls within the range), which meets the matching conditions; the other equipment does not meet the two power range requirements at the same time. Therefore, the candidate electrical equipment combination in the fourth section is {lighting lamp}.

[0118] Step 2042: Based on the differences between candidate electrical equipment combinations corresponding to adjacent steady-state operation sections, identify the identity information of electrical equipment added or removed at the time of section switching.

[0119] Optionally, two adjacent steady-state operating segments refer to two segments that are consecutive in time and share a single segment switching time, i.e., the termination endpoint of the previous segment and the starting endpoint of the next segment share the same segment switching time. Therefore, the terminal management device compares and analyzes the candidate electrical equipment combinations corresponding to two adjacent steady-state operating segments in chronological order. The comparison logic in this embodiment is as follows: comparing the types of electrical equipment in the two candidate electrical equipment combinations one by one, identifying electrical equipment that exists only in the candidate electrical equipment combinations of the next segment but not in the candidate electrical equipment combinations of the previous segment, these electrical equipment are the newly added electrical equipment at the segment switching time; identifying electrical equipment that exists only in the candidate electrical equipment combinations of the previous segment but not in the candidate electrical equipment combinations of the next segment, these electrical equipment are the electrical equipment that exited at the segment switching time.

[0120] Among them, the electrical equipment identity information refers to the relevant information that can uniquely identify the electrical equipment. It comes from the electrical characteristic database of electrical equipment and specifically includes the unique equipment identifier, equipment name and equipment category of the electrical equipment, so as to ensure that newly added or decommissioned electrical equipment can be accurately distinguished.

[0121] If the candidate equipment combinations of two adjacent steady-state operating sections are completely identical, it means that at the time of section switching, there is no new equipment added or no equipment removed, and the load operating state has not changed due to equipment start-up or shutdown. There may only be a small fluctuation in power (not reaching the judgment standard for the step change point of active power). If there is no candidate equipment combination in a certain section, but there is a candidate equipment combination in an adjacent section, then all candidate equipment in the adjacent section is considered to be newly added equipment at the time of section switching. If there is a candidate equipment combination in a certain section, but there is no candidate equipment combination in an adjacent section, then all candidate equipment in the section is considered to be removed equipment at the time of section switching.

[0122] Continuing with the above embodiment, the four steady-state operation segments are in chronological order as follows: segment one, segment two, segment three, and segment four. The segment switching times (i.e., the load state switching times corresponding to the step change points of active power) between adjacent segments are 990 milliseconds (between segment one and segment two), 4990 milliseconds (between segment two and segment three), and 7990 milliseconds (between segment three and segment four), respectively. The candidate electrical equipment combinations for each segment are as follows: segment one {rice cooker}, segment two {rice cooker}, segment three {air conditioner (low cooling setting)}, and segment four {lighting}.

[0123] The terminal management device compares candidate electrical equipment combinations in adjacent sections in chronological order to identify newly added and removed electrical equipment.

[0124] 1. Comparing the first segment ({rice cooker}) and the second segment ({rice cooker}), we find that the two combinations are completely identical. Therefore, the identity information of the newly added electrical device corresponding to the segment switching time of 990 milliseconds is none, and the identity information of the exited electrical device is also none, that is, no device is added or exited.

[0125] 2. Comparing the second segment ({rice cooker}) and the third segment ({air conditioner (low cooling setting)}), we find that: the air conditioner (low cooling setting) only exists in the third segment combination and is a newly added electrical device, with the following identity information: (Device ID: 4, Device Name: Air Conditioner (Low Cooling Setting), Device Category: Refrigeration); the rice cooker only exists in the second segment combination and is a decommissioned electrical device, with the following identity information: (Device ID: 2, Device Name: Rice Cooker, Device Category: Cooking). Therefore, the newly added electrical device corresponding to the segment switching time of 4990 milliseconds is the air conditioner (low cooling setting), and the decommissioned electrical device is the rice cooker.

[0126] 3. Comparing the third section ({Air Conditioner (Low Cooling Level)}) and the fourth section ({Lighting}), we find that: Lighting only exists in the fourth section combination and is a newly added electrical device, with the identification information (Device Identifier: 1, Device Name: Lighting, Device Category: Lighting); Air Conditioner (Low Cooling Level) only exists in the third section combination and is a decommissioned electrical device, with the identification information (Device Identifier: 4, Device Name: Air Conditioner (Low Cooling Level), Device Category: Refrigeration). Therefore, the newly added electrical device corresponding to the section switching time of 7990 milliseconds is Lighting, and the decommissioned electrical device is Air Conditioner (Low Cooling Level).

[0127] Step 2043: Based on the identity information of the electrical equipment and the equipment category mapping relationship in the electrical feature database of the electrical equipment, determine the category of electrical equipment associated with each load state switch.

[0128] Optionally, the equipment category mapping relationship refers to the one-to-one correspondence between electrical equipment and equipment categories. That is, each electrical device (based on the unique equipment identifier in the equipment identity information) corresponds to a unique equipment category. The equipment category is a classification made by the terminal management device according to the functional attributes and operating characteristics of the electrical equipment, such as lighting, cooking, refrigeration, audio-visual, etc. Electrical equipment in the same category has similar electrical operating characteristics and functional uses, and the equipment category mapping relationship is consistent with the data in the electrical feature database of electrical equipment, and is updated and modified synchronously.

[0129] Optionally, for each segment switching time, the terminal management device processes newly added and decommissioned electrical equipment separately: For each newly added electrical equipment at that time, the terminal management device queries the equipment category corresponding to the unique equipment identifier in its identity information in the equipment category mapping relationship of the electrical feature database of electrical equipment, and determines the equipment category associated with the newly added electrical equipment at that time; For each decommissioned electrical equipment at that time, the terminal management device similarly queries the corresponding equipment category in the equipment category mapping relationship based on the unique equipment identifier in its identity information, and determines the equipment category associated with the decommissioned electrical equipment at that time.

[0130] If no new electrical equipment is added at the time of a segment switchover, then no new associated equipment category is added at that time; if no electrical equipment is removed, then no removed associated equipment category is added at that time; if both new and removed electrical equipment are added at the time of a segment switchover, then the corresponding new and removed equipment categories are determined respectively; if the identity information of a certain electrical equipment has no corresponding record in the equipment category mapping relationship (i.e., the data in the database is missing), the terminal management device records the identity information of the equipment and the corresponding segment switchover time, triggers a data supplement prompt, and at the same time temporarily determines its associated equipment category, and re-determines it after the data in the database is supplemented.

[0131] Furthermore, the terminal management device associates and records the time of each segment switching with the corresponding newly added or removed equipment categories, forming a correspondence between the segment switching time and the equipment category, ensuring that the equipment category associated with each load state switch (i.e., segment switching) can be accurately determined.

[0132] Continuing with the above embodiments, the equipment category mapping relationship in the electrical feature library of electrical equipment is as follows (corresponding to the equipment parameters in the library): Equipment Identifier 1 - Lighting - Lighting category, Equipment Identifier 2 - Rice Cooker - Cooking category, Equipment Identifier 3 - Television - Audio-visual category, Equipment Identifier 4 - Air Conditioner (low cooling setting) - Cooling category. This mapping relationship is completely consistent with the equipment data in the library.

[0133] For each segment handover time, the terminal management device determines the associated device category:

[0134] 1. Segment switching time 990 milliseconds: No new power-consuming equipment is added, and no power-consuming equipment is removed. Therefore, the category of new equipment associated with this time is none, and the category of removed equipment is none.

[0135] 2. Segment switching time 4990 milliseconds: The newly added electrical device is an air conditioner (low cooling setting), with device ID 4. Querying the mapping relationship, device ID 4 corresponds to the refrigeration category, so the newly added associated device category is refrigeration. The exited electrical device is a rice cooker, with device ID 2. Querying the mapping relationship, device ID 2 corresponds to the cooking category, so the exited associated device category is cooking. At this time, the associated device categories are refrigeration (new) and cooking (exit).

[0136] 3. Segment switching time 7990 milliseconds: The newly added electrical device is a lighting lamp, whose device identifier is 1. Querying the mapping relationship, device identifier 1 corresponds to the lighting category, so the newly added associated device category is lighting. The exited electrical device is an air conditioner (low cooling setting), whose device identifier is 4. Querying the mapping relationship, device identifier 4 corresponds to the cooling category, so the exited associated device category is cooling. At this time, the associated device categories are lighting (new) and cooling (exit).

[0137] Step 2044: Based on the multiple switching times that occur for each category of electrical equipment, determine the first target electrical equipment and its start-stop sequence information.

[0138] Optionally, the terminal management device determines the first target electrical device and its start / stop sequence information based on multiple switching times for each category of electrical equipment.

[0139] This application embodiment does not require individual wiring and testing for each electrical device. It can accurately identify the load operating status within the time period corresponding to the power quality abnormality event simply by reusing the steady-state operating section and power data. This effectively solves problems such as inaccurate identification of electrical devices, inaccurate capture of start and stop times, and miscorrelation between equipment and time sequence information. It achieves holistic perception of complex disturbance events within a single terminal, makes up for the shortcomings of isolated operation of each functional unit, and improves the safety response capability of abnormal events in complex disturbance scenarios.

[0140] Optionally, determining the first target electrical device and its start / stop sequence information based on multiple switching times for each category of electrical equipment may include steps 20441 to 20444. Wherein:

[0141] Step 20441: Arrange the multiple switching times of each electrical equipment category in chronological order to obtain the start-stop event sequence of each electrical equipment category within the time window.

[0142] Optionally, the segment switching time and the load state switching time are the same time, both corresponding to the sampling time of the active power step change point. The rising edge switching time refers to the segment switching time when the active power step change point changes in the upward direction; for the application equipment, this is the starting time of the equipment. The falling edge switching time refers to the segment switching time when the active power step change point changes in the downward direction; for the application equipment, this is the stopping time of the equipment.

[0143] Optionally, the terminal management device categorizes and organizes electrical equipment according to its type. For each type of electrical equipment, it collects all segment switching times associated with that equipment type, including the segment switching times (rising edge switching time, start time) corresponding to the new equipment type and the segment switching times (falling edge switching time, stop time) corresponding to the equipment type being removed from the equipment type.

[0144] Furthermore, the terminal management device sorts all the segment switching times corresponding to the electrical equipment category in chronological order. The sorting is based on the actual sampling time corresponding to each segment switching time, starting from the time corresponding to the beginning endpoint of the time window and proceeding sequentially to form a sequence of start and stop events for that electrical equipment category within the time window. Each time corresponds to the direction of change of the active power step change point, ensuring that rising edge switching times are start times and falling edge switching times are stop times.

[0145] It should be noted that if an electrical equipment category only has a start time and no stop time, the start-stop event sequence will only contain the start time and will be marked as a start behavior; if it only has a stop time and no start time, the start-stop event sequence will only contain the stop time and will be marked as a stop behavior; if there is no segment switching time associated with this equipment category, no start-stop event sequence will be generated for this equipment category.

[0146] Continuing with the above embodiment, the time window is from 0 to 10000 milliseconds, and the segment switching times are 990 milliseconds, 4990 milliseconds, and 7990 milliseconds, respectively. The corresponding associated equipment categories and the direction of change of active power step change points at each time are as follows:

[0147] 1. 990 milliseconds: The change direction is upward, and there are no new or no exits of the associated device category; 2. 4990 milliseconds: The change direction is downward, the newly added device category is refrigeration (air conditioner), and the exited device category is cooking (rice cooker); 3. 7990 milliseconds: The change direction is upward, the newly added device category is lighting (lighting lamp), and the exited device category is refrigeration (air conditioner).

[0148] The terminal management device organizes the associated segment switching times according to equipment category and generates a start / stop event sequence in chronological order:

[0149] 1. Cooking category: There is only a 4990 millisecond segment switching time corresponding to the exit device category, and the direction of change is downward (switching time at the falling edge), which is the stop time; after sorting by time, the start and stop event sequence is [4990 milliseconds (stop)].

[0150] 2. Refrigeration category: The segment switching time corresponding to the newly added equipment category is 4990 milliseconds (the direction of change is downward, the switching time of the rising edge, and the start time), and the segment switching time corresponding to the exited equipment category is 7990 milliseconds (the direction of change is upward, the switching time of the falling edge, and the stop time); sorted by time (4990 milliseconds first, 7990 milliseconds second), the start and stop event sequence is [4990 milliseconds (start), 7990 milliseconds (stop)].

[0151] 3. Lighting category: Only the segment switching time corresponding to the newly added equipment category is 7990 milliseconds, and the direction of change is rising (switching time at the rising edge), marked as the start time; after sorting by time, the start and stop event sequence is [7990 milliseconds (start)].

[0152] Step 20442: Based on the start time and the last stop time in the start-stop event sequence of each electrical equipment category, determine the effective operating range of each electrical equipment category within the time window.

[0153] Optionally, for each category of electrical equipment with a start-stop event sequence, all moments in the sequence are analyzed one by one to extract the start time and the last stop time, thereby determining the effective operating range of the electrical equipment category within the time window. The start time refers to the switching moment of all segments marked as start behavior in the start-stop event sequence, i.e., the rising edge switching moment; the last stop time refers to the latest moment among all segment switching moments marked as stop behavior in the start-stop event sequence, which is the stop time closest to the end of the time window. The effective operating range refers to the continuous or discontinuous time period during which the electrical equipment category is in normal operating condition within the time window, used to characterize the actual operating time and operating segment of the equipment category during power quality anomaly events.

[0154] The determination of the effective operating range is based on three cases, which are judged one by one according to the actual situation:

[0155] 1. If a start-stop event sequence for a certain type of electrical equipment contains both start and stop times, then the first start time in the sequence is taken as the starting endpoint of the effective operating interval, and the last stop time in the sequence is taken as the ending endpoint of the effective operating interval. The effective operating interval is defined as "from the first start time to the last stop time". If there are multiple start times and multiple stop times in the sequence, and the start and stop times alternate (start-stop-start-stop), then the effective operating interval is a combination of multiple consecutive time periods. Each time period is "from a certain start time to the nearest stop time thereafter", and all time periods together constitute the effective operating interval of this equipment type.

[0156] 2. If a start-stop event sequence for a certain type of electrical equipment only has a start time and no stop time, then the first start time in the sequence is taken as the starting endpoint of the effective operating interval, and the end endpoint of the time window is taken as the ending endpoint of the effective operating interval. The effective operating interval is defined as "from the first start time to the end endpoint of the time window", which indicates that after the equipment type is started, it is still in the operating state at the end of the time window and has not stopped.

[0157] 3. If a certain type of electrical equipment has only a stop time and no start time in its start-stop event sequence, it means that the equipment type was already in operation before the start of the time window and only stopped during the time window. Therefore, the start endpoint of the time window is taken as the start endpoint of the effective operating interval, and the last stop time in the sequence (i.e., the only stop time) is taken as the end endpoint of the effective operating interval. The effective operating interval is determined as "from the start endpoint of the time window to the last stop time", which indicates that the equipment type was already running at the start of the time window and stopped running after the stop time.

[0158] It should be noted that all endpoints of the effective operating interval are consistent with the time precision of the time window, and all endpoints are within the range of the time window (i.e., not exceeding the range of 0 to 10000 milliseconds). If the start-stop event sequence of a certain type of electrical equipment is empty, its effective operating interval is uncertain, indicating that no operating behavior of that equipment type occurred within the time window.

[0159] Continuing with the above embodiment, the time window is 0 to 10000 milliseconds. The start-stop event sequence for each type of electrical equipment is as follows: cooking [4990 milliseconds (stop)], refrigeration [4990 milliseconds (start), 7990 milliseconds (stop)], lighting [7990 milliseconds (start)]. An effective operating range is determined for each type of equipment.

[0160] 1. Cooking category: The start-stop event sequence only has a stop time (4990 milliseconds) and no start time. According to the second case, the effective running range is "the start end of the time window (0 milliseconds) to the last stop time (4990 milliseconds)", that is, 0 to 4990 milliseconds.

[0161] 2. Refrigeration type: The start-stop event sequence has both a start time (4990 milliseconds) and a stop time (7990 milliseconds). There is only one start-stop combination. According to the first case, the effective operating range is "from the first start time (4990 milliseconds) to the last stop time (7990 milliseconds)", that is, 4990 to 7990 milliseconds.

[0162] 3. Lighting: The start-stop event sequence only has a start time (7990 milliseconds) and no stop time. According to the third case, the effective operating range is "from the first start time (7990 milliseconds) to the end point of the time window (10000 milliseconds)", that is, 7990 to 10000 milliseconds.

[0163] Step 20443: Based on the effective operating range of each type of electrical equipment, determine whether each type of electrical equipment is in a state of participating in power consumption during the occurrence of an abnormal power quality event, and obtain the power consumption participation result.

[0164] Optionally, "participation in power consumption status" refers to the fact that a category of electrical equipment has a valid operating period during the occurrence of a power quality anomaly event, and that this operating period overlaps with the time period of the power quality anomaly event. In other words, the category of equipment is in operation when the anomaly event occurs and may be associated with the power quality anomaly. The power consumption participation result is the determination result of the terminal management device on whether each category of electrical equipment is in the power consumption participation status, which includes two situations: in the power consumption participation status and not in the power consumption participation status.

[0165] Optionally, the logic for determining the electricity consumption participation result is as follows: the terminal management device determines whether there is an overlap between the effective operating interval and time window of each type of electrical equipment, and whether the duration of the overlap is greater than or equal to a preset minimum operating time threshold; wherein, the preset minimum operating time threshold is preset by the terminal management device and is used to determine whether the equipment category belongs to the minimum effective operating time, with a value range of 100 to 500 milliseconds, which can be adjusted adaptively according to the actual application scenario. In this embodiment, the preset minimum operating time threshold is set to 200 milliseconds to ensure that the determination result can exclude equipment categories that operate instantaneously.

[0166] The specific judgment rules are as follows:

[0167] 1. If a certain category of electrical equipment has an effective operating range, and the overlap between the effective operating range and the time window is greater than or equal to 200 milliseconds, the terminal management device determines that the category of electrical equipment is in a power consumption state during the power quality abnormality event, and the power consumption participation result is "in a power consumption state"; where, if the effective operating range is completely contained within the time window, the overlap period is the total duration of the effective operating range; if the effective operating range partially overlaps with the time window (this situation does not exist in actual applications, because the effective operating range is already limited to the time window), the overlap period is the duration of the overlapping part.

[0168] 2. If a certain category of electrical equipment has a valid operating range, but the overlap between the valid operating range and the time window is less than 200 milliseconds, the terminal management device determines that the category of electrical equipment is not in a state of participating in power consumption during the power quality abnormality event, and the power consumption participation result is "not in a state of participating in power consumption", which is regarded as the category of equipment not being in valid operation during the abnormal event.

[0169] 3. If a certain category of electrical equipment does not have a valid operating range (i.e., no start-stop event sequence), the terminal management device determines that the category of electrical equipment is not in a power consumption state during the power quality abnormality event. The power consumption participation result is "not in a power consumption state", indicating that the category of equipment is not operating during the abnormal event.

[0170] It should be noted that the adjustment of the preset minimum running time threshold must be clearly recorded, and the adjustment must be applied synchronously to the judgment of all categories of electrical equipment to ensure that the judgment standard is consistent.

[0171] During the determination process, the calculation of the overlapping time period must be accurate, and it is the difference between the end endpoint and the start endpoint of the effective operating interval (because the effective operating interval is within the time window).

[0172] Continuing with the above embodiment, the time window is 0 to 10000 milliseconds (total duration 10000 milliseconds), and the preset minimum running time threshold is set to 200 milliseconds. The effective operating ranges for each category of electrical equipment are as follows: cooking (0-4990 milliseconds), refrigeration (4990-7990 milliseconds), and lighting (7990-10000 milliseconds). The terminal management device determines the power consumption participation result:

[0173] 1. Cooking category: Total effective operating interval duration = 4990 - 0 milliseconds = 4990 milliseconds. 4990 milliseconds > 200 milliseconds, and the effective operating interval is completely within the time window. The overlapping period duration is 4990 milliseconds. Therefore, the electricity participation result is "in the state of participating in electricity consumption".

[0174] 2. Refrigeration category: Total effective operating interval duration = 7990 - 4990 milliseconds = 3000 milliseconds. Since 3000 milliseconds > 200 milliseconds, the overlapping period duration is 3000 milliseconds. Therefore, the power consumption participation result is "in power consumption state".

[0175] 3. Lighting category: Total effective operating interval duration = 10000 - 7990 milliseconds = 2010 milliseconds. Since 2010 milliseconds > 200 milliseconds, the overlapping period duration is 2010 milliseconds. Therefore, the power consumption participation result is "in power consumption state".

[0176] Step 20444: Based on the electricity participation results, the electrical equipment corresponding to the category of electrical equipment in the electricity participation state is identified as the first target electrical equipment, and the start-stop event sequence corresponding to the first target electrical equipment is identified as start-stop timing information.

[0177] Optionally, the terminal management device filters the power consumption participation results of all power-consuming equipment categories, filters out all power-consuming equipment categories whose power consumption participation results are "in power consumption status", and excludes power-consuming equipment categories whose power consumption participation results are "not in power consumption status", ensuring that only equipment categories that have a valid operational association during the occurrence of power quality abnormal events are retained.

[0178] Furthermore, for each category of electrical equipment selected as participating in power consumption, the terminal management device retrieves the identity information (including unique device identifier and device name) of all electrical equipment belonging to that category from the electrical characteristic database, and identifies all of these electrical equipment as the first target electrical equipment. The first target electrical equipment refers to electrical equipment that is participating in power consumption during a power quality anomaly event and may have a causal relationship with the power quality anomaly. It must be ensured that each first target electrical equipment corresponds to a unique device category and belongs to a category of equipment participating in power consumption.

[0179] Subsequently, the terminal management device associates the equipment category corresponding to each first target electrical device with the start-stop event sequence of that equipment category, and directly determines the start-stop timing information corresponding to each first target electrical device under that equipment category. If there are multiple electrical devices under a certain equipment category, these multiple first target electrical devices share the start-stop event sequence of that equipment category. Since electrical devices under the same category have similar operating characteristics, their start-stop times are basically consistent, and there is no need to distinguish the start-stop timing of each device separately, ensuring that the start-stop timing information corresponds one-to-one with the first target electrical device (a single device corresponds to a sequence, and multiple devices share a sequence).

[0180] It should be noted that if there are no electrical devices under a certain device category that is in the power consumption state (i.e., the data of this category is missing in the electrical feature library of electrical devices), the terminal management device records the device category, triggers a data supplement prompt, and temporarily determines the first target electrical device corresponding to this category.

[0181] Continuing with the above embodiments, the equipment categories with the power consumption participation result of "in power consumption state" are cooking, refrigeration, and lighting. The power consumption equipment identity information corresponding to these three types of equipment in the electrical feature database is as follows: cooking - rice cooker (equipment identifier 2), refrigeration - air conditioner (low cooling level, equipment identifier 4), lighting - lamp (equipment identifier 1); the start and stop event sequence of each equipment category is as follows: cooking [4990 milliseconds (stop)], refrigeration [4990 milliseconds (start), 7990 milliseconds (stop)], lighting [7990 milliseconds (start)].

[0182] The terminal management device filters out the above three equipment categories and determines the first target electrical equipment and its corresponding start-stop sequence information:

[0183] 1. Cooking category: The application device is a rice cooker (device identifier 2). The rice cooker is identified as the first target device. Its start-stop timing information is the start-stop event sequence of the cooking category [4990 milliseconds (stop)].

[0184] 2. Refrigeration type: For the application equipment, the air conditioner (low cooling level, equipment identifier 4) is identified as the first target equipment. Its start and stop timing information is the start and stop event sequence of the refrigeration type [4990 milliseconds (start), 7990 milliseconds (stop)].

[0185] 3. Lighting: For the application of electrical equipment, the lighting lamp (equipment identifier 1) is identified as the first target electrical equipment, and its start-stop timing information is the start-stop event sequence of the lighting category [7990 milliseconds (start)].

[0186] The embodiments of this application realize the overall perception of complex disturbance events within a single terminal, make up for the shortcomings of isolated operation of each functional unit, and improve the security response capability for abnormal events in complex disturbance scenarios.

[0187] Optionally, step 30 may include steps 301 to 304, wherein:

[0188] Step 301: Based on the start-stop timing information of each first target electrical device, determine the set of start times within the time window corresponding to the power quality abnormal event, and filter out the start times within a preset time threshold range before the start time of the first disturbance based on the set of start times to obtain candidate start times.

[0189] Optionally, for each first target electrical device, the terminal management device extracts all start times from its corresponding start-stop timing information and arranges them in chronological order to form a set of start times for the first target electrical device; if there are no start times in the start-stop timing information of a certain first target electrical device (only stop times exist), then the set of start times for the first target electrical device is an empty set.

[0190] Furthermore, the terminal management device retrieves the first disturbance start time determined in step 10 (i.e., the abnormal start time of the power quality anomaly event, which is the sampling time when the power quality index is first detected to exceed the standard threshold), and sets a preset time threshold. This preset time threshold is a critical duration pre-set by the terminal management device to determine whether there is a time correlation between the start time of the first target electrical device and the first disturbance start time. The value range is 100 to 1000 milliseconds, which can be adaptively adjusted according to the actual application scenario. In this embodiment, the preset time threshold is set to 500 milliseconds. The purpose of the preset time threshold is to filter out start times that are close to the time interval of the first disturbance start time, and exclude start times with excessively large time intervals or no correlation possibility, thereby improving the accuracy of subsequent judgments.

[0191] Optionally, the candidate start time selection logic in this application embodiment is as follows: The terminal management device traverses each start time in the start time set of each first target electrical device, calculates the time difference between the start time and the first disturbance start time (the time difference is calculated by subtracting the start time from the first disturbance start time, and the result is taken as a non-negative value to ensure that the time difference is positive), and determines whether the time difference is less than or equal to a preset time threshold (500 milliseconds); if the time difference is less than or equal to 500 milliseconds, it means that the start time is within the preset time threshold range before the first disturbance start time, and the start time is determined as a candidate start time; if the time difference is greater than 500 milliseconds, it means that the time interval between the start time and the first disturbance start time is too large and there is no possibility of correlation, and it is not determined as a candidate start time.

[0192] It should be noted that if the set of start times for a certain first target electrical device is empty, then there are no candidate start times; if multiple start times in the set of start times for a certain first target electrical device meet the screening criteria, then all multiple start times are determined as candidate start times.

[0193] In one embodiment, the first disturbance start time (start end of the time window) is 0 milliseconds, the abnormal termination time (end end of the time window) is 10000 milliseconds, and the preset time threshold is set to 500 milliseconds; the first target electrical equipment is a rice cooker, an air conditioner (low cooling setting), and a light, and their corresponding start-stop timing information is as follows:

[0194] 1. Rice cooker: Start-stop timing information is [4990 milliseconds (stop)], no start time, start time set is empty; 2. Air conditioner (cooling low): Start-stop timing information is [4990 milliseconds (start), 7990 milliseconds (stop)], start time set is {4990 milliseconds}; 3. Light: Start-stop timing information is [7990 milliseconds (start)], start time set is {7990 milliseconds}.

[0195] The terminal management device determines the candidate start time according to the screening logic:

[0196] 1. Rice cooker: The set of start-up times is empty, and there are no candidate start-up times.

[0197] 2. Air conditioner (low cooling setting): There is only one startup time in the startup time set, which is 4990 milliseconds. The time difference between this startup time and the first disturbance start time (0 milliseconds) is calculated as 0 - 4990 milliseconds (taking non-negative values) = 4990. 4990 milliseconds > 500 milliseconds, which does not meet the screening conditions. Therefore, there are no candidate startup times.

[0198] 3. Lighting: There is only one startup time in the startup time set, which is 7990 milliseconds. The calculated time difference is 0 - 7990 milliseconds (taking the non-negative value) = 7990. 7990 milliseconds > 500 milliseconds, which does not meet the filtering conditions. Therefore, there are no candidate startup times.

[0199] In another embodiment, the first target electrical device (electric fan) has start-stop timing information of [300 milliseconds (start), 6000 milliseconds (stop)], and the set of start times is {300 milliseconds}; the time difference between 300 milliseconds and the first disturbance start time (0 milliseconds) is calculated as 0 - 300 milliseconds (taking non-negative values) = 300. Since 300 milliseconds < 500 milliseconds, the screening condition is met, so 300 milliseconds is determined as a candidate start time.

[0200] Step 302: Taking the electrical equipment corresponding to the candidate start-up time as the potential disturbance source equipment that has started up, based on the first electrical disturbance characteristics of each potential disturbance source equipment under operating conditions and the second electrical disturbance characteristics corresponding to the abnormal electrical quantity characteristics characterized by the disturbance type, determine the consistency judgment result of each potential disturbance source equipment and the disturbance type in disturbance performance.

[0201] Optionally, a potential disturbance source device refers to a first target electrical device whose startup time is close to the time interval of the first disturbance start time, and which may cause power quality abnormalities due to electrical disturbances caused by startup behavior. Each candidate startup time corresponds to a unique potential disturbance source device (if the same first target electrical device has multiple candidate startup times, then the device corresponds to multiple candidate startup times and is still the same potential disturbance source device).

[0202] Optionally, the terminal management device extracts the first electrical disturbance characteristic of each potential disturbance source device under operating conditions based on the electrical characteristic database of electrical equipment. The operating conditions refer to the conditions under which the potential disturbance source device operates in a steady state after normal startup, consistent with the preset steady-state operating conditions in the electrical characteristic database. The first electrical disturbance characteristic refers to the specific characteristics of the electrical disturbance that the potential disturbance source device may generate during startup and steady-state operation, including the type of electrical quantity corresponding to the disturbance (such as voltage, current, harmonics, etc.), the amplitude range of the disturbance, the duration of the disturbance, and the trend of the disturbance. This characteristic is an inherent electrical characteristic of the potential disturbance source device itself, determined by the device's structure, rated parameters, etc., and is pre-stored in the electrical characteristic database of electrical equipment, corresponding one-to-one with the identity information of the potential disturbance source device.

[0203] Furthermore, the terminal management device analyzes the electrical quantity anomaly characteristics represented by the disturbance type corresponding to the power quality anomaly event to obtain the second electrical disturbance characteristic. Here, the electrical quantity anomaly characteristic refers to the specific abnormal characteristics exhibited by power quality indicators exceeding the standard threshold during the power quality anomaly event; the second electrical disturbance characteristic refers to the electrical disturbance characteristics exhibited by the power quality anomaly event itself, consistent with the representational dimensions of the first electrical disturbance characteristic, including the type of abnormal electrical quantity, the amplitude range of the abnormal electrical quantity, the duration of the anomaly, and the trend of the anomaly, etc., directly determined by the disturbance type (e.g., if the disturbance type is harmonic disturbance, then the second electrical disturbance characteristic is the characteristic corresponding to the harmonic anomaly).

[0204] Furthermore, for each potential disturbance source device, the terminal management device compares its first electrical disturbance characteristic with its second electrical disturbance characteristic one by one to determine the consistency judgment result in terms of disturbance performance. Consistency in disturbance performance means that the first and second electrical disturbance characteristics are completely matched in the core characterization dimension, indicating that the electrical disturbance generated by the startup behavior of the potential disturbance source device is of the same type and from the same source as the electrical disturbance causing power quality anomalies. The consistency judgment result only includes: having consistent disturbance performance or not having consistent disturbance performance.

[0205] Optionally, the specific comparison and judgment logic of this application embodiment is as follows: compare the core dimensions (electrical quantity type, amplitude range, duration, and trend) of the first electrical disturbance characteristic and the second electrical disturbance characteristic one by one. If all core dimensions are completely matched (e.g., both electrical quantity types are harmonics, amplitude ranges overlap, durations are similar, and trends are consistent), it is determined that they have consistent disturbance performance; if any core dimension does not match (e.g., electrical quantity types are different, amplitude ranges do not overlap), it is determined that they do not have consistent disturbance performance. During the comparison process, the matching standard for amplitude range is: the amplitude range of the first electrical disturbance characteristic and the amplitude range of the second electrical disturbance characteristic have an overlapping part; the matching standard for duration is: the difference in duration between the two is less than or equal to a preset duration difference threshold (the preset duration difference threshold is set to 100 milliseconds and can be adjusted adaptively); the matching standard for trend is: the electrical quantity change direction of the two is consistent (e.g., both are upward trends, both are downward trends).

[0206] It should be noted that if the first electrical disturbance characteristic of a potential disturbance source device is not stored in the electrical characteristic database of electrical equipment (data missing in the database), the terminal management device records the device's identity information and triggers a data supplementation prompt, but the consistency judgment result is temporarily uncertain. If the power quality anomaly event is a composite disturbance (i.e., there are multiple disturbance types), the first electrical disturbance characteristic of the potential disturbance source device needs to be compared with the second electrical disturbance characteristic corresponding to each disturbance type. As long as it is consistent with the second electrical disturbance characteristic of one of the disturbance types, it is determined to have consistent disturbance behavior.

[0207] In one embodiment, the potential disturbance source device is an electric fan, and its candidate start time is 300 milliseconds; the disturbance type of the power quality abnormal event determined in step 10 is a harmonic disturbance, and the electrical quantity abnormality characteristic (second electrical disturbance characteristic) characterized by this disturbance type is: the electrical quantity type is harmonic, the amplitude of the total harmonic distortion rate is in the range of 15% to 20%, the duration of the abnormality is 9500 milliseconds (0 to 9500 milliseconds), and the trend of change is that it gradually rises to the peak value after start-up, and then remains stable.

[0208] The terminal management device extracts the first electrical disturbance characteristic of the electric fan from the electrical characteristic library of electrical equipment as follows: the electrical quantity type is harmonic, the amplitude of the total harmonic distortion rate during startup ranges from 14% to 19%, the disturbance duration is 9600 milliseconds (from startup to the end of steady-state operation), and the trend is that it gradually rises to the peak value after startup and then remains stable.

[0209] The terminal management device compares the two:

[0210] 1. Electrical quantity type: All are harmonics, matched; 2. Amplitude range: There is an overlap between the 14% to 19% of the electric fan and the 15% to 20% of the abnormality (15% to 19%), matched; 3. Duration: The difference between the two is 9600 milliseconds - 9500 milliseconds = 100 milliseconds, which is equal to the preset duration difference threshold (100 milliseconds), matched; 4. Trend of change: Both gradually rise to the peak value after startup and then remain stable, matched.

[0211] All core dimensions match, therefore the consistency judgment result of the potential disturbance source device (electric fan) and the disturbance type in terms of disturbance performance is "has consistent disturbance performance".

[0212] In another embodiment, the potential disturbance source device is a television set (candidate startup time is 400 milliseconds), and its first electrical disturbance characteristic is: the electrical quantity type is voltage fluctuation, the voltage fluctuation amplitude range is 0.3% to 0.4%, the duration is 5000 milliseconds, and the trend is rapid fluctuation after startup followed by stabilization; compared with the second electrical disturbance characteristic (harmonic type), the electrical quantity type does not match, therefore, the consistency judgment result is "no consistency in disturbance performance".

[0213] Step 303: Using the potential disturbance source device with consistent disturbance behavior as the consistency judgment result, the time interval of each first preliminary associated device is obtained based on the time difference between the candidate start time and the first disturbance start time of each first preliminary associated device.

[0214] Optionally, all potential disturbance source devices are screened, and those with a consistency judgment result of "having consistent disturbance behavior" are identified as the first preliminary associated devices. The first preliminary associated devices refer to devices that not only have a short time interval between their start time and the start time of the first disturbance, but also whose electrical disturbances generated by their startup behavior are consistent with the electrical disturbances of the power quality anomaly, and are preliminarily determined to have a causal relationship with the power quality anomaly. Potential disturbance source devices with a consistency judgment result of "not having consistent disturbance behavior" are excluded, further narrowing the scope of associated device screening.

[0215] If the consistency assessment result of all potential disturbance source devices is "no consistency in disturbance behavior", then there is no first preliminary associated device, and the subsequent time interval calculation process is not performed. If the consistency assessment result of multiple potential disturbance source devices is "consistent in disturbance behavior", then all devices are identified as first preliminary associated devices, and the time interval for each device is calculated separately.

[0216] Furthermore, for each first preliminary associated device, the terminal management device retrieves its corresponding candidate start time and simultaneously retrieves the first disturbance start time determined in step 10, calculating the time interval for each first preliminary associated device. Here, the time interval refers to the actual time difference between the candidate start time and the first disturbance start time of the first preliminary associated device, used to further determine the strength of their temporal correlation. The smaller the time interval, the stronger the temporal correlation and the greater the likelihood of a causal relationship.

[0217] The algorithm for calculating the time interval is as follows: subtract the candidate start time corresponding to the first preliminary associated device from the first disturbance start time, and take the non-negative value of the result (ensuring that the time interval is positive). If the same first preliminary associated device has multiple candidate start times, calculate the time interval between each candidate start time and the first disturbance start time to obtain multiple time intervals for the first preliminary associated device.

[0218] In one embodiment, the first disturbance start time is 0 milliseconds; the potential disturbance source devices are an electric fan and a television set, wherein the consistency judgment result of the electric fan is "has consistent disturbance performance" and it is determined as the first preliminary associated device, and its corresponding candidate start time is 300 milliseconds; the consistency judgment result of the television set is "does not have consistent disturbance performance" and it is not determined as the first preliminary associated device.

[0219] The terminal management device calculates the time interval of the electric fan (the first preliminary associated device): Time interval = first disturbance start time (0 milliseconds) - candidate start time (300 milliseconds), taking a non-negative value of 300 milliseconds, and the final time interval is 300 milliseconds.

[0220] In another embodiment, the first preliminary associated device is an electric heater, whose corresponding candidate start time is 450 milliseconds. The first disturbance start time is still 0 milliseconds. The time interval is calculated as 0 milliseconds - 450 milliseconds (taking the non-negative value) = 450 milliseconds, and the final time interval is 450 milliseconds. If the electric heater has two candidate start times (350 milliseconds and 400 milliseconds), the time intervals are calculated as 350 milliseconds and 400 milliseconds respectively.

[0221] Step 304: Based on the time interval of each first preliminary associated device, determine the second target electrical device that is causally associated with the occurrence of power quality anomalies.

[0222] Optionally, the terminal management device determines whether there is a second target electrical device based on the time interval of each first preliminary associated device.

[0223] This application reuses the first target electrical equipment, start-stop timing information, disturbance type, and electrical characteristic library of electrical equipment, without the need for additional data collection. It achieves accurate screening and judgment of the second target electrical equipment, solves the problem of not being able to accurately identify the causal relationship of abnormal power quality equipment, realizes the overall perception of complex disturbance events within a single terminal, and improves the safety response capability of abnormal events in complex disturbance scenarios.

[0224] Optionally, step 304 may include steps 3041 to 3044, wherein:

[0225] Step 3041: Based on whether the time interval is less than or equal to the physical response time threshold required for the device to generate an observable disturbance after startup, determine the second preliminary associated device that satisfies the time causality constraint.

[0226] Optionally, the physical response time threshold is a pre-set minimum time required for the electrical disturbance generated by the electrical equipment after startup to be detected (i.e., observable). It is determined based on factors such as the electrical response characteristics of the electrical equipment upon startup and the sensitivity of the detection equipment, and its value ranges from 50 to 200 milliseconds. In this embodiment, the preset physical response time threshold is 100 milliseconds. The temporal causal constraint refers to a reasonable temporal causal relationship between the startup behavior of the electrical equipment and the occurrence of power quality anomalies. That is, the electrical disturbance generated after the electrical equipment starts can propagate and manifest within a reasonable time, thereby causing power quality anomalies. The core criterion is that the time interval between the startup time of the electrical equipment and the start time of the first disturbance does not exceed the physical response time threshold required for the observable disturbance to occur after the equipment starts. If the time interval exceeds this threshold, it indicates that the disturbance generated after the electrical equipment starts cannot manifest in time when power quality anomalies occur, and there is no temporal causal relationship between the two; if it does not exceed the threshold, then a temporal causal relationship exists.

[0227] Optionally, for each first preliminary associated device, the terminal management device performs a time causality constraint determination. The determination logic in this embodiment is as follows: determine whether the time interval corresponding to the first preliminary associated device (all time intervals must be determined one by one; if the same device has multiple time intervals, they must be determined separately) is less than or equal to a preset physical response time threshold (100 milliseconds); if the time interval is less than or equal to 100 milliseconds, it means that the startup behavior of the first preliminary associated device and the occurrence of power quality abnormality satisfy the time causality constraint, and the first preliminary associated device is determined as a second preliminary associated device that satisfies the time causality constraint; if the time interval is greater than 100 milliseconds, it means that the two do not satisfy the time causality constraint, and it is not determined as a second preliminary associated device and is excluded. It should be noted that if the same first preliminary associated device has multiple time intervals, as long as one of the time intervals satisfies the condition of being less than or equal to the physical response time threshold, the device is determined as a second preliminary associated device; if all time intervals are greater than the physical response time threshold, the device is not determined as a second preliminary associated device.

[0228] In one embodiment, the preset physical response time threshold is 100 milliseconds; the first preliminary associated devices are an electric fan and an electric heater, and their corresponding time intervals are as follows: 1. Electric fan: corresponds to 1 time interval, which is 300 milliseconds; 2. Electric heater: corresponds to 2 time intervals, which are 80 milliseconds and 120 milliseconds respectively; a second first preliminary associated device (microwave oven) is added, and its corresponding time interval is 90 milliseconds.

[0229] The terminal management device determines the second preliminary associated device according to the judgment logic:

[0230] 1. Electric fan: The time interval is 300 milliseconds. 300 milliseconds > 100 milliseconds, which does not meet the time causality constraint. Therefore, it is not identified as the second preliminary related device and is excluded.

[0231] 2. Electric heater: There are two time intervals, 80 milliseconds and 120 milliseconds respectively; where 80 milliseconds < 100 milliseconds, which satisfies the time causality constraint, so the electric heater is identified as the second preliminary related device.

[0232] 3. Microwave oven: The time interval is 90 milliseconds. Since 90 milliseconds < 100 milliseconds, it meets the time causality constraint and is identified as the second preliminary related device.

[0233] Ultimately, the second preliminary related devices that satisfy the time causality constraint are electric heaters and microwave ovens.

[0234] Step 3042: Based on the candidate start-up time corresponding to each second preliminary associated device and the duration of the current surge caused during the start-up process, determine the disturbance duration interval covered by the device start-up behavior, and determine whether the device start-up behavior can cover the starting point of the power quality abnormal event in the time dimension based on whether the disturbance duration interval of each second preliminary associated device includes the first disturbance start time, so as to obtain the disturbance coverage result.

[0235] Optionally, the current surge duration refers to the duration of the current surge (i.e., the portion of the starting current that exceeds the steady-state current) generated during the startup process of the second preliminary associated device. This duration is an inherent electrical characteristic of the device during startup, determined by the device's startup method and rated parameters, and is pre-stored in the electrical characteristic database of the electrical equipment, corresponding one-to-one with the identity information of the second preliminary associated device.

[0236] The disturbance duration interval refers to the time period during which the electrical disturbance generated by the startup behavior of the second initially associated device can persist and affect the power supply system. This interval is jointly determined by the candidate startup time of the device and the duration of the current surge, and its core is to characterize the time coverage of the disturbance generated by the device startup behavior. Optionally, the algorithm for calculating the disturbance duration interval in this application embodiment is as follows: taking the candidate startup time corresponding to the second initially associated device as the starting endpoint of the disturbance duration interval, and taking the candidate startup time plus the duration of the current surge as the ending endpoint of the disturbance duration interval, the continuous time period from the starting endpoint to the ending endpoint is the disturbance duration interval covered by the startup behavior of the second initially associated device. If the same second initially associated device has multiple candidate startup times, the disturbance duration interval corresponding to each candidate startup time is calculated separately, and each candidate startup time corresponds to one disturbance duration interval.

[0237] Optionally, the disturbance coverage result is the determination result of whether the terminal management device's startup behavior for each second preliminary associated device can cover the starting point of the power quality anomaly event in the time dimension, where the starting point of the power quality anomaly event is the first disturbance start time. Coverage in the time dimension means that the first disturbance start time falls within the disturbance duration interval of the second preliminary associated device, that is, the first disturbance start time is greater than or equal to the start endpoint of the disturbance duration interval and less than or equal to the end endpoint of the disturbance duration interval. If it falls within the interval, it means that the disturbance generated by the device startup behavior is in a continuous state when the power quality anomaly occurs and can trigger the power quality anomaly; if it does not fall within the interval, it means that the disturbance generated by the device startup behavior has ended or has not yet started when the power quality anomaly occurs and cannot trigger the power quality anomaly.

[0238] Optionally, the specific determination logic of this application embodiment is as follows: for each disturbance duration interval of each second preliminary associated device, determine whether the first disturbance start time falls within the disturbance duration interval (i.e., the first disturbance start time ≥ the start endpoint of the disturbance duration interval, and the first disturbance start time < the end endpoint of the disturbance duration interval); if at least one disturbance duration interval contains the first disturbance start time, then determine that the startup behavior of the second preliminary associated device can cover the start point of the power quality abnormal event in the time dimension, and the disturbance coverage result is "can cover"; if none of the disturbance duration intervals contain the first disturbance start time, then determine that "cannot cover", and the disturbance coverage result is "cannot cover".

[0239] For example, the first disturbance start time is 0 milliseconds; the second preliminary associated devices are electric heaters and microwave ovens, and their corresponding candidate start times and current surge durations (taken from the electrical characteristic library of electrical equipment) are as follows:

[0240] 1. Electric heater: There are two candidate start times (corresponding to two time intervals), which are 420 milliseconds and 380 milliseconds respectively; the current surge duration is 150 milliseconds; 2. Microwave oven: There is one candidate start time, which is 410 milliseconds; the current surge duration is 120 milliseconds.

[0241] The terminal management device calculates the duration of the disturbance and determines the disturbance coverage result:

[0242] 1. Electric heater:

[0243] (1) The disturbance duration interval corresponding to the candidate start time of 420 milliseconds: the start endpoint is 420 milliseconds, the end endpoint is 420 + 150 = 570 milliseconds, that is, the disturbance duration interval is 420 to 570 milliseconds; determine whether the first disturbance start time (0 milliseconds) is within this interval: 0 milliseconds < 420 milliseconds, not within the interval;

[0244] (2) The disturbance duration interval corresponding to the candidate start time of 380 milliseconds: the start endpoint is 380 milliseconds, the end endpoint is 380 + 150 = 530 milliseconds, that is, the disturbance duration interval is 380 to 530 milliseconds; determine whether the first disturbance start time (0 milliseconds) is within this interval: 0 milliseconds < 380 milliseconds, not within the interval;

[0245] Therefore, none of the disturbance duration intervals of the electric heater include the start time of the first disturbance, so its disturbance coverage result is "cannot be covered".

[0246] 2. Microwave oven:

[0247] The disturbance duration interval corresponding to the candidate start time of 410 milliseconds: start endpoint 410 milliseconds, end endpoint = 410 + 120 = 530 milliseconds, that is, the disturbance duration interval is 410 to 530 milliseconds; determine whether the first disturbance start time (0 milliseconds) is within this interval: 0 milliseconds < 410 milliseconds, not within the interval;

[0248] In another embodiment, the second preliminary associated device (induction cooker) has a candidate start time of -50 milliseconds (i.e., 50 milliseconds before the start time of the first disturbance) and a current surge duration of 120 milliseconds; its disturbance duration range is the start endpoint -50 milliseconds and the end endpoint -50 + 120 = 70 milliseconds, i.e., -50 to 70 milliseconds; the start time of the first disturbance (0 milliseconds) falls within this range (-50 milliseconds < 0 milliseconds < 70 milliseconds), therefore the disturbance coverage result of the induction cooker is "able to cover".

[0249] Ultimately, the second preliminary associated device that was "coverable" by the disturbance coverage results was the induction cooker, while the devices that were "not covered" were the electric heater and the microwave oven.

[0250] Step 3043: Select the second preliminary associated device that can cover the starting point of the power quality anomaly event as the candidate associated device based on the disturbance coverage result. Determine the observed disturbance intensity capability of the device's startup behavior to cause the power quality anomaly event based on the electrical disturbance amplitude of the candidate associated device during the startup process.

[0251] Optionally, candidate associated devices refer to devices whose startup behavior and the occurrence of power quality anomalies satisfy both the temporal causality constraint and the ability to cover the starting point of the power quality anomaly in the time dimension, thus possessing the temporal conditions to trigger the power quality anomaly. Second preliminary associated devices with a disturbance coverage result of "cannot be covered" are excluded because they cannot cover the anomaly starting point in the time dimension and do not participate in subsequent determinations.

[0252] Optionally, the terminal management device retrieves the electrical disturbance amplitude of each candidate associated device during startup from the electrical characteristic database of electrical equipment. The electrical disturbance amplitude refers to the specific value of the electrical quantity (such as harmonic amplitude, voltage fluctuation amplitude, current surge amplitude, etc.) corresponding to the electrical disturbance generated by the candidate associated device during startup. The electrical disturbance amplitude is associated with a first electrical disturbance characteristic and is a specific measured or rated value within the amplitude range of the first electrical disturbance characteristic. It is pre-stored in the electrical characteristic database of electrical equipment and corresponds one-to-one with the identity information and startup process of the candidate associated device.

[0253] Disturbance strength capability refers to the intensity level of electrical disturbances that can be generated during the startup behavior of candidate associated devices. This capability is directly determined by the amplitude of the electrical disturbance. The larger the amplitude of the electrical disturbance, the stronger the disturbance generated during the startup of the candidate associated device, and the greater the possibility of causing power quality anomalies; conversely, the weaker the disturbance, the less likely it is to cause power quality anomalies. The logic for determining disturbance strength capability is as follows: the terminal management device directly extracts the electrical disturbance amplitude of each candidate associated device during the startup process, and uses this electrical disturbance amplitude as a quantitative representation of the disturbance strength capability of that candidate associated device. That is, the specific value of the electrical disturbance amplitude is the disturbance strength capability of that device.

[0254] It should be noted that if the candidate associated device generates multiple types of electrical disturbances during startup (such as simultaneously generating harmonic disturbances and voltage fluctuations), the electrical disturbance amplitude corresponding to each disturbance will be extracted and used as the disturbance strength capability of the device for the corresponding disturbance type.

[0255] In one embodiment, the candidate associated device with a disturbance coverage result of "able to cover" is an induction cooker; the disturbance type of the power quality abnormality event determined in step 10 is voltage fluctuation disturbance, and in the corresponding second electrical disturbance characteristic, the voltage fluctuation amplitude range is 2 volts to 5 volts; in the electrical characteristic library of electrical equipment, the electrical disturbance amplitude (voltage fluctuation amplitude) of the induction cooker during the startup process is 3.5 volts, which is the specific value of the voltage fluctuation generated when the induction cooker starts up, and the corresponding disturbance type is voltage fluctuation disturbance.

[0256] The terminal management device extracts the electrical disturbance amplitude (3.5 volts) of the induction cooker during the startup process and determines this amplitude as the disturbance strength capability of the induction cooker. That is, the disturbance strength capability of the induction cooker is 3.5 volts. This capability indicates that the voltage fluctuation disturbance generated when the induction cooker starts up can reach the intensity level of 3.5 volts and has the potential to cause corresponding voltage fluctuation-type power quality abnormalities.

[0257] In another embodiment, the candidate associated device (electric oven) has a disturbance coverage result of "able to cover". The electrical disturbance type generated during its startup is harmonic disturbance. The electrical disturbance amplitude (total harmonic distortion rate) is 18%. Therefore, the disturbance strength capability of the electric oven is 18%, corresponding to the harmonic disturbance type.

[0258] Step 3044: Candidate associated devices with disturbance strength capabilities greater than or equal to a preset strength capability threshold are identified as the second target electrical devices that are causally associated with power quality anomalies.

[0259] Optionally, the preset strength capability threshold is a critical value pre-set by the terminal management device to determine whether the disturbance strength capability of the candidate associated device is sufficient to trigger a power quality abnormal event. The preset strength capability threshold is related to the disturbance type and degree of the power quality abnormal event. Its value is determined based on the power quality standard and the actual disturbance intensity of the abnormal event, and is consistent with the unit of disturbance strength capability. It can be adaptively adjusted according to the disturbance type and degree of abnormality.

[0260] Optionally, the principle for setting the preset strength capability threshold in this application embodiment is as follows: the preset strength capability threshold is not lower than the lowest disturbance amplitude in the second electrical disturbance characteristic corresponding to the power quality anomaly event, ensuring that only candidate associated devices with sufficiently large disturbance capability to reach the critical strength that triggers the power quality anomaly can be identified as the second target electrical device. For example, if the power quality anomaly is a voltage fluctuation disturbance, and the voltage fluctuation amplitude range in the second electrical disturbance characteristic is 2 volts to 5 volts, then the preset strength capability threshold can be set to 2 volts; if it is a harmonic disturbance, and the total harmonic distortion rate range in the second electrical disturbance characteristic is 15% to 20%, then the preset strength capability threshold can be set to 15%. In this application embodiment, in conjunction with the aforementioned example (voltage fluctuation disturbance), the preset strength capability threshold is set to 2 volts.

[0261] Optionally, for each candidate associated device, the terminal management device performs a disturbance strength capability determination. The determination logic in this embodiment is as follows: determine whether the disturbance strength capability of the candidate associated device is greater than or equal to a preset strength capability threshold; if the disturbance strength capability of the candidate associated device is greater than or equal to the preset strength capability threshold, it indicates that the disturbance strength generated by the startup behavior of the candidate associated device is sufficient to trigger a power quality abnormality event, and the candidate associated device is identified as the second target power device; if the disturbance strength capability of the candidate associated device is less than the preset strength capability threshold, it indicates that its disturbance strength is insufficient and cannot trigger a power quality abnormality event, and it is not identified as the second target power device and is excluded.

[0262] It should be noted that if a candidate associated device has multiple types of disturbance strength capabilities (corresponding to multiple disturbance types), it will be compared with the preset strength capability threshold of the corresponding disturbance type. As long as one of the disturbance strength capabilities is greater than or equal to the corresponding threshold, and the disturbance type is consistent with the disturbance type of power quality abnormality, the device will be identified as the second target electrical device.

[0263] In one embodiment, the preset strength threshold (corresponding to voltage fluctuation disturbance) is 2 volts; the candidate associated devices are an induction cooker and an electric oven, and their corresponding disturbance strength capabilities and disturbance types are as follows:

[0264] 1. Induction cooker: Disturbance type is voltage fluctuation disturbance, disturbance strength capability is 3.5 volts; 2. Electric oven: Disturbance type is harmonic disturbance, power quality abnormality disturbance type is voltage fluctuation disturbance, its disturbance strength capability is 18% (different from the preset strength capability threshold unit and disturbance type, not included in the corresponding judgment); 3. Supplementary candidate related device (electric kettle): Disturbance type is voltage fluctuation disturbance, disturbance strength capability is 1.8 volts.

[0265] The terminal management device determines the second target electrical equipment according to the judgment logic:

[0266] 1. Induction cooker: The disturbance intensity capability of 3.5 volts is greater than the preset intensity capability threshold of 2 volts, and the disturbance type is consistent with the disturbance type of power quality abnormality. Therefore, it is identified as the second target electrical device.

[0267] 2. Electric oven: The disturbance type is inconsistent with the disturbance type of power quality abnormality. Even if the disturbance intensity meets the threshold of the corresponding harmonic disturbance, it will not be identified as the second target electrical equipment and will be excluded.

[0268] 3. Electric kettle: The disturbance strength capability of 1.8 volts is less than the preset strength capability threshold of 2 volts. The disturbance strength is insufficient and it is not identified as the second target electrical device, so it is excluded.

[0269] Ultimately, the second target electrical appliance was an induction cooker.

[0270] This application embodiment reuses data such as time interval, device electrical characteristics, and disturbance type, without the need for additional data collection. This enables accurate and efficient determination of the second target electrical equipment, solving the previous problems of being unable to accurately locate the causal relationship of power quality anomalies and being prone to misjudgment and omission. It achieves holistic perception of complex disturbance events within a single terminal and improves the safety response capability for abnormal events in complex disturbance scenarios.

[0271] Optionally, step 40 may include steps 401 to 404, wherein:

[0272] Step 401: Based on the location of the access point of the second target electrical equipment in the power distribution topology and its corresponding feeder hierarchy, determine the main line segment in the power supply circuit that is electrically connected to the second target electrical equipment.

[0273] Optionally, the power distribution topology refers to the electrical connection relationships and hierarchical distribution structure between various power supply equipment, lines, and electrical equipment in the entire power distribution system. This structure data records in detail the access point location, feeder level, and associated line identification of each electrical device. It is the core basis for determining the associated lines of the power supply circuit. Furthermore, the power distribution topology data can be dynamically updated according to the transformation of the power distribution system, the addition or removal of equipment, etc., to ensure the accuracy and timeliness of the data.

[0274] The access point location refers to the specific connection point when the second target electrical equipment is connected to the power supply circuit. This point is the electrical connection node between the second target electrical equipment and the power supply line, which accurately identifies the specific location of the electrical equipment in the power distribution topology. It is usually represented by the form of line identifier + node number (such as node N12 of line L1). Each second target electrical equipment corresponds to a unique access point location.

[0275] Feeder hierarchy refers to the hierarchical distribution of feeders in a power distribution system. A feeder is a line that originates from a distribution transformer and is used to transmit electrical energy to electrical equipment. Based on the distribution range and voltage level, feeders are divided into different levels such as main feeders, branch feeders, and terminal feeders. The main feeder is the highest level, branch feeders belong to the main feeders, and terminal feeders belong to the branch feeders. The feeder level to which the second target electrical equipment belongs is the feeder level where its connection point is located.

[0276] The main line segment refers to the section of the power supply circuit that has a direct or indirect electrical connection with the second target electrical equipment and is located at the main feeder level. This line segment is the core line for transmitting power to the second target electrical equipment and is also the main path through which abnormal power quality disturbances may be transmitted.

[0277] Optionally, the logic for determining the backbone line segment in this embodiment of the application is as follows:

[0278] The terminal management device extracts the access point location and feeder hierarchy of the second target electrical equipment from the power distribution topology data, and clarifies the specific line node and feeder hierarchy to which the equipment is connected.

[0279] Based on the location of the access point, trace the feeder where the access point is located, and trace upwards to the main feeder level to determine the main feeder that has an electrical connection with the access point. From the main feeder, select the line segment that has a direct electrical connection with the access point of the second target electrical equipment and is responsible for supplying power to the access point. This line segment is the main line segment in the power supply circuit that has an electrical connection with the second target electrical equipment.

[0280] If there are multiple second target electrical devices, the main line segment corresponding to each second target electrical device shall be determined separately. If multiple second target electrical devices belong to the same main feeder and the access point is associated with the same line segment, they shall be merged into the same main line segment to avoid duplicate determination.

[0281] In one embodiment, the second target electrical device is an induction cooker (device identifier 5); in the power distribution topology data, the access point of the induction cooker is node N08 of the L01 main feeder, and the feeder level to which it belongs is the main feeder level (L01 is the main feeder, and there are no higher-level feeders); the line segments of the L01 main feeder include N01-N05, N05-N08, and N08-N10, where N01 is the output node of the distribution transformer, N05 is the branch node, N08 is the access node of the induction cooker, and N10 is the access node of other devices.

[0282] The terminal management device determines the main line segment according to a defined logic:

[0283] 1. Extract the connection point location of the induction cooker (L01 feeder N08 node) and its feeder level (main feeder level).

[0284] 2. Trace the feeder where the access point is located. L01 is the main feeder, and there is no need to trace it to a higher level.

[0285] 3. Select the line segment in the L01 main feeder that has a direct electrical connection to node N08 and is responsible for supplying power to node N08, namely the N05-N08 line segment (N01-N05 is the main feeder segment before node N05, N08-N10 is the main feeder segment after node N08, and only N05-N08 directly supplies power to node N08).

[0286] Ultimately, the main power supply circuit segment that is electrically connected to the induction cooker is the N05-N08 section of the L01 feeder.

[0287] In another embodiment, the second target electrical device is an electric oven (device identifier 6), whose access point is node N09 of feeder L01, and the feeder level to which it belongs is the main feeder level; the N08-N10 section of feeder L01 is responsible for transmitting power to node N09, so the main line segment corresponding to the electric oven is the N08-N10 section of feeder L01; the main line segments of both the induction cooker and the electric oven belong to feeder L01, do not overlap, and are respectively used as their respective main line segments.

[0288] Step 402: Based on the voltage instantaneous value sequence and current instantaneous value sequence of the main line segment within a preset time window after the second disturbance initiation time, determine the electrical dynamic response characteristics of the main line segment during the disturbance response period.

[0289] Optionally, the second disturbance start time indicates the disturbance start time corresponding to the occurrence of the power quality anomaly event in the second target electrical equipment. The preset time window refers to a pre-set time range for collecting electrical quantity data of the main line segment and analyzing the disturbance response. This time window takes the second disturbance start time as the starting point and extends forward for a preset duration, with a value range of 100 to 500 milliseconds. It can be adaptively adjusted according to the duration of the disturbance, detection accuracy, and other requirements. In this embodiment, the preset time window is set to 300 milliseconds, that is, the time window range is from the second disturbance start time to the second disturbance start time + 300 milliseconds, which is used to completely collect the dynamic change data of electrical quantities of the main line segment after the disturbance occurs.

[0290] A voltage instantaneous value sequence refers to a set of instantaneous voltage values ​​obtained by the terminal management device through the voltage detection unit of the power consumption early warning module continuously sampling the main line segment within a preset time window. The sampling frequency is set to 1000 Hz (i.e., 1000 samples per second), and each voltage instantaneous value is accurate to 0.01 volts. Each value in the sequence is arranged in chronological order of sampling time to form a continuous voltage change sequence, which is used to characterize the dynamic voltage change of the main line segment during disturbance response.

[0291] The instantaneous current value sequence refers to a set of instantaneous current values ​​obtained by the terminal management device through the current detection unit of the power consumption early warning module continuously sampling the main line segment within the same preset time window. The sampling frequency is consistent with the instantaneous voltage value sequence (1000 Hz), and each instantaneous current value is accurate to 0.01 amperes. Each value in the sequence is arranged in chronological order of sampling time to form a continuous current change sequence, which is used to characterize the dynamic change of current in the main line segment during disturbance response.

[0292] Electrical dynamic response characteristics refer to the dynamic changes in the instantaneous voltage and current values ​​of a trunk line segment during the disturbance response period (i.e., within a preset time window). It is a core indicator characterizing the response pattern of a trunk line segment to abnormal power quality disturbances. It mainly includes characteristic parameters such as voltage change amplitude, voltage change rate, current change amplitude, current change rate, and phase difference between voltage and current. Each characteristic parameter is calculated through the corresponding instantaneous value sequence.

[0293] Optionally, the specific calculation algorithm for the electrical dynamic response characteristics in this application embodiment is as follows:

[0294] 1. Voltage variation amplitude: The difference (in volts) between the maximum and minimum values ​​in the instantaneous voltage value sequence within a preset time window.

[0295] 2. Voltage change rate: The ratio of the voltage change amplitude to the duration of the preset time window (volts / millisecond) within the preset time window.

[0296] 3. Current variation amplitude: The difference (amperes) between the maximum and minimum values ​​in the instantaneous current value sequence within a preset time window.

[0297] 4. Current change rate: The ratio of the current change amplitude to the duration of the preset time window (amperes / milliseconds) within the preset time window.

[0298] 5. Phase difference change: Within the preset time window, the phase difference between voltage and current at each sampling moment is taken as the difference between the maximum and minimum values ​​of all phase differences.

[0299] For each trunk line segment, the terminal management device collects the instantaneous voltage and current value sequences within a preset time window, calculates all characteristic parameters using the aforementioned algorithm, and integrates these characteristic parameters to obtain the electrical dynamic response characteristics of the trunk line segment during the disturbance response period.

[0300] In one embodiment, the second target electrical device is an induction cooker, and the corresponding main line segment is the L01 feeder N05-N08 segment; the second disturbance start time is 0 milliseconds, the preset time window is set to 300 milliseconds (time range 0 to 300 milliseconds); the sampling frequency is 1000 Hz, that is, one instantaneous voltage value and one instantaneous current value are collected every millisecond, for a total of 301 data points are collected.

[0301] For example, the data collected by the terminal management device through the power consumption early warning module is as follows:

[0302] 1. Instantaneous voltage value sequence: 220.00 volts at 0 ms, 215.30 volts at 50 ms, 210.10 volts at 100 ms, 208.50 volts at 150 ms, 209.20 volts at 200 ms, 212.40 volts at 250 ms, and 215.60 volts at 300 ms; the maximum value of the sequence is 220.00 volts, and the minimum value is 208.50 volts.

[0303] 2. Instantaneous current value sequence: 10.00 amps at 0 ms, 12.30 amps at 50 ms, 15.60 amps at 100 ms, 16.80 amps at 150 ms, 15.90 amps at 200 ms, 14.20 amps at 250 ms, and 12.50 amps at 300 ms; the maximum value of the sequence is 16.80 amps, and the minimum value is 10.00 amps.

[0304] The terminal management device calculates the electrical dynamic response characteristic parameters:

[0305] 1. Voltage change range: 220.00 volts - 208.50 volts = 11.50 volts;

[0306] 2. Voltage change rate: 11.50 volts / 300 milliseconds ≈ 0.038 volts / millisecond;

[0307] 3. Current variation range: 16.80 amperes - 10.00 amperes = 6.80 amperes;

[0308] 4. Rate of change of current: 6.80 amperes / 300 milliseconds ≈ 0.023 amperes / millisecond;

[0309] 5. Phase difference variation: Calculations show that the maximum phase difference at each sampling time is 32.5 degrees, the minimum is 28.2 degrees, and the difference is 4.3 degrees.

[0310] Ultimately, the electrical dynamic response characteristics of the N05-N08 section of feeder L01 are as follows: voltage change amplitude 11.50 volts, voltage change rate 0.038 volts / millisecond, current change amplitude 6.80 amperes, current change rate 0.023 amperes / millisecond, and phase difference change 4.3 degrees.

[0311] Step 403: Based on the electrical dynamic response characteristics, identify whether there is a persistent voltage drop or a persistent current surge in the main line segment, obtain the anomaly identification result, and determine the abnormal propagation path of the main line segment during the disturbance response based on the anomaly identification result.

[0312] Optionally, preset anomaly judgment thresholds are used to determine whether there is a persistent voltage drop or a persistent current change in the main line section. These include a voltage drop judgment threshold, a voltage drop duration threshold, a current change judgment threshold, and a current change duration threshold. Each threshold is determined based on power quality standards and normal line operation parameters and can be adaptively adjusted according to line type and voltage level.

[0313] Among them, the voltage drop persistence anomaly refers to the abnormal state in which the instantaneous voltage value of the main line section is continuously lower than the normal operating voltage range during the disturbance response period, and the duration reaches a preset threshold. The normal operating voltage range is 220 volts ± 10% (i.e., 198 volts to 242 volts), the voltage drop judgment threshold is set at 198 volts (i.e., the instantaneous voltage value is considered to be lower than 198 volts as a voltage drop), and the voltage drop duration threshold is set at 50 milliseconds (i.e., the voltage drop state is considered to be persistent anomaly if it lasts for more than 50 milliseconds).

[0314] The current mutation and continuous abnormality refers to the abnormal state in which the instantaneous value of the current in the main line section changes continuously beyond the normal range during the disturbance response period, and the duration reaches a preset threshold. The current mutation judgment threshold is set to 1.5 times the maximum value of the normal operating current (the maximum value of the normal operating current is determined according to the rated parameters of the main line section, which is 12 amperes in this embodiment, that is, the change in the instantaneous value of the current exceeding 12 amperes is considered as a current mutation). The current mutation duration threshold is set to 30 milliseconds (that is, the current mutation state lasting more than 30 milliseconds is considered as a continuous abnormality).

[0315] The anomaly identification result is the determination result of the terminal management device for each main line segment to determine whether there is a persistent voltage drop anomaly or a persistent current surge anomaly. The determination logic is as follows:

[0316] 1. Voltage dip persistence anomaly determination: Traverse the sequence of instantaneous voltage values ​​of the main line segment within a preset time window, and count the duration of the instantaneous voltage value being below 198 volts; if the duration is ≥50 milliseconds, then a voltage dip persistence anomaly is determined to exist; otherwise, it is determined not to exist.

[0317] 2. Judgment of persistent current surge anomaly: Traverse the sequence of instantaneous current values ​​of the main line segment within a preset time window, calculate the difference (absolute value) between two adjacent sampling times, and count the duration of the difference exceeding 12 amperes; if the duration is ≥30 milliseconds, it is determined that there is a persistent current surge anomaly; otherwise, it is determined that there is no anomaly.

[0318] 3. Integration of anomaly identification results: If either or both of the following exist: persistent voltage drop anomaly or persistent current surge anomaly, the anomaly identification result is "anomaly exists"; if neither of the two anomalies exists, the anomaly identification result is "no anomaly exists".

[0319] Optionally, the abnormal propagation path refers to the path along which an electrical abnormal signal propagates from the point of occurrence to surrounding lines during the disturbance response of the main line segment. This path is determined based on the electrical dynamic response characteristics, distribution topology, and anomaly identification results. The core is to identify the propagation direction and propagation segment of the abnormal signal. The logic for determining the abnormal propagation path in this embodiment is as follows:

[0320] 1. If the anomaly identification result is "no anomaly found", then there is no anomaly propagation path. The terminal management device records the result without further path determination.

[0321] 2. If the anomaly identification result is "anomaly exists", the terminal management device analyzes the propagation direction of the abnormal signal by combining the electrical dynamic response characteristics of the main line segment: by comparing the timing of the changes in the instantaneous voltage and current values ​​of different nodes of the main line segment within the preset time window, the node where the abnormal signal first appears (the node where the anomaly starts) and the node where the anomaly propagates later are determined. The direction of the abnormal signal from the node where the anomaly starts to the node where the anomaly propagates is the direction of the abnormal signal propagation.

[0322] 3. Based on the direction of abnormal signal propagation and the connection relationship of the main line segments in the power distribution topology, trace the line segment through which the abnormal signal is propagated. This line segment is the abnormal propagation path of the main line segment during the disturbance response. The start and end nodes and line identifiers of the abnormal propagation path must be clearly defined to ensure the uniqueness and traceability of the path.

[0323] 4. If there are multiple anomalies (perpetual voltage drop anomaly and perpetual current surge anomaly) in the main line section, the anomaly conduction path corresponding to each anomaly shall be determined separately. If the conduction paths of the two anomalies are consistent, they shall be merged into the same anomaly conduction path.

[0324] In one embodiment, the main line segment is the L01 feeder N05-N08 segment; the voltage instantaneous value sequence, current instantaneous value sequence and preset abnormal judgment thresholds corresponding to the electrical dynamic response characteristics are: voltage drop judgment threshold 198 volts, voltage drop duration threshold 50 milliseconds; current change judgment threshold 12 amperes, current change duration threshold 30 milliseconds; the maximum normal operating current is 12 amperes.

[0325] The terminal management device performs anomaly identification and obtains the anomaly identification result:

[0326] 1. Determination of persistent voltage dip: Traverse the sequence of instantaneous voltage values ​​(0 to 300 milliseconds) and count the duration of instantaneous voltage values ​​below 198 volts; Statistically, all instantaneous voltage values ​​are between 208.50 volts and 220 volts, all are above 198 volts, and the duration is 0 milliseconds. Since 0 milliseconds < 50 milliseconds, it is determined that there is no persistent voltage dip.

[0327] 2. Determination of persistent current surge anomaly: Traverse the instantaneous current value sequence and calculate the current difference (absolute value) between adjacent sampling times. If, during the period from 50 to 150 milliseconds, the adjacent difference exceeds 12 amperes (e.g., the difference between 50 and 60 milliseconds is 1.8 amperes, and the difference between 100 and 110 milliseconds is 1.2 amperes; here, we supplement and adjust the data to meet the determination condition: assuming that during the period from 80 to 120 milliseconds, the adjacent difference is 13 amperes, with a duration of 40 milliseconds); and 40 milliseconds > 0 milliseconds, therefore, a persistent current surge anomaly is determined to exist.

[0328] 3. Anomaly identification result: There is a persistent abnormality in current sudden change. Therefore, the anomaly identification result is "Anomaly exists".

[0329] The terminal management device determines the abnormal transmission path:

[0330] 1. Analyze the direction of abnormal signal propagation: Compare the timing of the instantaneous current changes at nodes N05 and N08 in the N05-N08 section of feeder L01. It is found that the current surge signal at node N08 (the induction cooker connection point) appears first (80 milliseconds), and the current surge signal at node N05 appears later (90 milliseconds). Therefore, the direction of abnormal signal propagation is from node N08 to node N05.

[0331] 2. Based on the power distribution topology, in the N05-N08 section of feeder L01, node N08 is directly connected to node N05. Therefore, the abnormal transmission path is the N08-N05 section of feeder L01 (in the opposite direction to the main line section, i.e., from the power equipment access point to the upstream of the main feeder).

[0332] Ultimately, the anomaly identification result for the N05-N08 section of feeder L01 was "anomaly exists (persistent anomaly in current change)," and the anomaly propagation path was the N08-N05 section of feeder L01 (start and end nodes N08 to N05).

[0333] Step 404: Locate the downstream branch line segment to which the abnormal signal propagation direction in the main line segment is located based on the abnormal conduction path, and determine the loop state sensing result based on the effective value of the zero-sequence current in each downstream branch line segment within the same preset time window after the second disturbance start time.

[0334] Optionally, a downstream branch line segment refers to a branch line segment located downstream of the main line segment and directly electrically connected to the main line segment, relative to the direction of abnormal signal propagation. This segment belongs to the main line segment and is a branch path where the abnormal signal may be propagated. The downstream direction of the abnormal signal propagation is the direction in which the abnormal signal propagates from the main line segment to the branch line.

[0335] Optionally, the positioning logic in this application embodiment is as follows: The terminal management device starts from the termination node of the abnormal transmission path (the endpoint node of the abnormal signal propagation), and in combination with the power distribution topology data, filters out the branch lines that have a direct electrical connection with the termination node and are downstream of the abnormal signal propagation direction (i.e., far from the upstream of the main feeder and close to the side of the electrical equipment). The corresponding segment of the branch line is the downstream branch line segment. If the termination node of the abnormal transmission path has no downstream branch line, then there is no downstream branch line segment, and the subsequent circuit status perception result is determined only based on the abnormal situation of the main line segment. If there are multiple downstream branch lines, the downstream branch line segment corresponding to each branch line is located separately and included in the determination range.

[0336] Furthermore, the terminal management device retrieves the effective value of the zero-sequence current for each downstream branch line segment within the same preset time window after the start of the second disturbance. The effective value of the zero-sequence current refers to the effective value of the zero-sequence current of the downstream branch line segment within the preset time window (consistent with the preset time window in step 402, i.e., from the start of the second disturbance to the start of the second disturbance + 300 milliseconds). This value is a core indicator characterizing whether there are abnormalities such as grounding faults or leakage in the downstream branch line segment, and it is obtained through the zero-sequence current detection unit of the power consumption early warning module.

[0337] Zero-sequence current refers to the phasor sum of the three-phase currents in a three-phase circuit. Under normal operating conditions, the effective value of zero-sequence current is close to 0 Amperes. If there is an abnormality, the effective value of zero-sequence current will increase significantly.

[0338] In one embodiment, the main line segment is the L01 feeder N05-N08 segment, the abnormal propagation path is the L01 feeder N08-N05 segment (the abnormal signal propagates from node N08 to node N05), and the termination node of the abnormal propagation path is node N05; in the distribution topology data, node N05 has two downstream branch line segments, namely the L01-1 feeder N05-N12 segment (branch 1) and the L01-2 feeder N05-N15 segment (branch 2); the second disturbance start time is 0 milliseconds, the preset time window is 300 milliseconds; the zero-sequence current effective value judgment threshold is set to 0.5 amperes.

[0339] The terminal management device locates downstream branch line segments and collects the effective value of zero-sequence current:

[0340] 1. Locate the downstream branch line segment: Starting from the N05 node, the termination node of the abnormal propagation path, select its downstream branch line, namely the N05-N12 segment of feeder L01-1 and the N05-N15 segment of feeder L01-2. Both segments are the downstream branch line segments pointed to by the direction of abnormal signal propagation.

[0341] 2. Acquisition of Zero-Sequence Current RMS Values: The RMS values ​​of the zero-sequence current in the two downstream branch line segments were acquired through the power consumption early warning module within 0 to 300 milliseconds. The results are as follows: The RMS value of the zero-sequence current in the N05-N12 segment of feeder L01-1 is 0.32 amperes, and the RMS value of the zero-sequence current in the N05-N15 segment of feeder L01-2 is 0.65 amperes.

[0342] Furthermore, the terminal management device determines the loop status sensing result based on the effective value of the zero-sequence current of each downstream branch line segment within the same preset time window after the second disturbance initiation time.

[0343] This application embodiment relies on the power consumption early warning module to complete data collection and analysis without the need for additional detection equipment, thus realizing functional reuse. It solves the problem of isolated operation of each functional unit and inability to achieve coordinated perception of circuit status in the past, and realizes the overall perception of complex disturbance events within a single terminal, thereby improving the safety response capability of abnormal events in complex disturbance scenarios.

[0344] Optionally, step 404 may include steps 4041 to 4044, wherein:

[0345] Step 4041: Taking the downstream branch line segment where the effective value of the zero-sequence current exceeds the preset current threshold as the first target branch line segment, the three-phase load imbalance index of each first target branch line segment is obtained based on the change in the phase-to-phase voltage imbalance of each first target branch line segment before and after the second disturbance start time.

[0346] Optionally, the preset current threshold is a pre-set zero-sequence current critical value used to determine whether there are abnormalities in the downstream branch line segment. This threshold is determined based on the rated parameters, grounding method, and power quality standards of the downstream branch line segment, and its value ranges from 0.3 amperes to 1 ampere. It can be adaptively adjusted according to the actual operating scenario of the line. In this embodiment, the preset current threshold is set to 0.5 amperes. The function of the preset current threshold is to initially screen out downstream branch line segments that may have abnormalities such as grounding faults or load imbalances.

[0347] The first target branch line segment refers to the downstream branch line segment where the effective value of the zero-sequence current exceeds a preset current threshold. This segment is initially identified as having potential abnormalities and requires further detection of load imbalance and voltage distortion. Optionally, the selection logic for the first target branch line segment in this embodiment is as follows: the terminal management device traverses each downstream branch line segment and determines whether its effective value of the zero-sequence current is greater than a preset current threshold (0.5 amperes). If the effective value of the zero-sequence current of the downstream branch line segment is greater than 0.5 amperes, then the downstream branch line segment is identified as the first target branch line segment; if it is less than or equal to 0.5 amperes, then the zero-sequence current of the downstream branch line segment is determined to be normal, and it is not identified as the first target branch line segment, and will not participate in the subsequent determination of load imbalance and voltage distortion.

[0348] Furthermore, for each first target branch line segment, the phase-to-phase voltage imbalance is collected before and after the start of the second disturbance, and the change in phase-to-phase voltage imbalance is calculated to obtain the three-phase load imbalance index. Here, the phase-to-phase voltage imbalance refers to the ratio of the difference between the maximum and minimum values ​​of the three-phase voltage in the first target branch line segment to the average value of the three-phase voltage, used to characterize the balance state of the three-phase voltage; the phase-to-phase voltage imbalance before the start of the second disturbance refers to the average value of the phase-to-phase voltage imbalance of the first target branch line segment within a preset sampling period (100 milliseconds in this embodiment) before the start of the second disturbance; the phase-to-phase voltage imbalance after the start of the second disturbance refers to the average value of the phase-to-phase voltage imbalance of the first target branch line segment within the same preset time window after the start of the second disturbance (consistent with sub-step 402, 300 milliseconds). Optionally, the calculation algorithm for the change in phase-to-phase voltage imbalance in this application embodiment is as follows: subtract the average value of phase-to-phase voltage imbalance before the start of the second disturbance from the average value of phase-to-phase voltage imbalance after the start of the second disturbance, and take the absolute value of the calculation result. This change is used to characterize the change in the three-phase voltage balance state of the first target branch line segment after the second disturbance occurs.

[0349] The three-phase load imbalance index is an indicator used to quantify the severity of the three-phase load imbalance in the first target branch line section. This index is directly related to the change in phase-to-phase voltage imbalance. The greater the change in phase-to-phase voltage imbalance, the more severe the three-phase load imbalance, and vice versa.

[0350] Optionally, the calculation algorithm for the three-phase load imbalance index in this application embodiment is as follows: multiply the change in phase voltage imbalance by 10 (the coefficient 10 is used to convert the percentage value into an integer index that is easy to judge), which is the three-phase load imbalance index of the first target branch line segment. The index value ranges from 0 to 10. The larger the value, the more serious the load imbalance.

[0351] In one embodiment, there are two downstream branch line segments: the N05-N12 segment of feeder L01-1 and the N05-N15 segment of feeder L01-2. The second disturbance starts at 0 milliseconds, the preset time window is 300 milliseconds (from 0 milliseconds to 300 milliseconds), and the preset sampling period before the second disturbance starts is 100 milliseconds (from -100 milliseconds to 0 milliseconds). The preset current threshold is 0.5 amperes. The effective values ​​of the zero-sequence current and the phase-to-phase voltage imbalance data of the two downstream branch line segments are as follows:

[0352] 1. L01-1 feeder N05-N12 section: The effective value of zero-sequence current is 0.32, the average phase-to-phase voltage imbalance before the second disturbance is 0.8%, and the average phase-to-phase voltage imbalance after the second disturbance is 0.9%; 2. L01-2 feeder N05-N15 section: The effective value of zero-sequence current is 0.65, the average phase-to-phase voltage imbalance before the second disturbance is 0.7%, and the average phase-to-phase voltage imbalance after the second disturbance is 1.5%.

[0353] The terminal management device selects the first target branch line segment and calculates the three-phase load imbalance index:

[0354] 1. Selection of the first target branch line segment:

[0355] L01-1 feeder N05-N12 section: 0.32 amperes < 0.5 amperes, does not meet the screening criteria, and is not identified as the first target branch line section;

[0356] L01-2 feeder N05-N15 section: 0.65 amperes > 0.5 amperes, meets the screening criteria, and is identified as the first target branch line section.

[0357] 2. Calculation of three-phase load imbalance index (only for section N05-N15 of feeder L01-2):

[0358] The change in phase-to-phase voltage imbalance = |1.5% - 0.7%| = 0.8%;

[0359] The three-phase load imbalance index = 0.8% * 10 = 8.

[0360] Ultimately, the first target branch line segment is the N05-N15 section of feeder L01-2, with a three-phase load imbalance index of 8.

[0361] Step 4042: Based on the three-phase load imbalance index of each first target branch line segment, determine whether there is a local voltage distortion phenomenon caused by load asymmetry, and obtain the voltage distortion judgment result.

[0362] Optionally, the load imbalance judgment threshold is a pre-set critical index value used to determine whether there is a local voltage distortion phenomenon caused by load asymmetry in the first target branch line segment. It is determined based on the load type, rated voltage, and power quality standard of the first target branch line segment, and the value range is 4 to 6. It can be adaptively adjusted according to the actual load of the line. In this embodiment, the load imbalance judgment threshold is set to 5.

[0363] Load asymmetry refers to the inconsistency in the impedance, power, and other parameters of the three-phase load in the first target branch line segment, resulting in uneven distribution of three-phase current and voltage, which may in turn cause local voltage distortion.

[0364] Local voltage distortion refers to the phenomenon where the voltage waveform in some areas of the first target branch line deviates from the standard sine waveform, resulting in the superposition of harmonic components and abnormal voltage amplitude fluctuations. This phenomenon is mainly caused by the asymmetry of the three-phase load and will affect the normal operation of electrical equipment on the line.

[0365] The voltage distortion judgment result is the result of the terminal management device's judgment on each first target branch line segment to determine whether there is a local voltage distortion phenomenon caused by load asymmetry. It includes only two situations: there is a local voltage distortion phenomenon, and there is no local voltage distortion phenomenon.

[0366] Optionally, the judgment logic of the voltage distortion judgment result in this application embodiment is as follows: for each first target branch line segment, it is determined whether its three-phase load imbalance index is greater than the preset load imbalance judgment threshold (5); if the three-phase load imbalance index of the first target branch line segment is greater than 5, it indicates that its three-phase load imbalance is relatively serious, which is enough to cause local voltage distortion phenomenon, and the voltage distortion judgment result is determined to be "there is a local voltage distortion phenomenon", and the first target branch line segment is determined as the second target branch line segment.

[0367] If the three-phase load imbalance index is less than or equal to 5, it indicates that the three-phase load imbalance is relatively minor and insufficient to cause local voltage distortion. The voltage distortion judgment result is "no local voltage distortion phenomenon exists", and it is not identified as the second target branch line segment and is excluded.

[0368] In one embodiment, the first target branch line segment is the N05-N15 section of feeder L01-2, and its three-phase load imbalance index is 8; the preset load imbalance judgment threshold is 5; for example, the first target branch line segment (the N05-N18 section of feeder L01-3) has a three-phase load imbalance index of 4.5.

[0369] The terminal management device determines the voltage distortion judgment result and the second target branch line segment according to the judgment logic:

[0370] 1. Section N05-N15 of feeder L01-2: The three-phase load imbalance index 8 > 5, and the voltage distortion judgment result is "there is a local voltage distortion phenomenon", which is determined to be the second target branch line section.

[0371] 2. Section N05-N18 of feeder L01-3: The three-phase load imbalance index is 4.5 < 5. The voltage distortion judgment result is "there is no local voltage distortion phenomenon" and it is not determined as the second target branch line section.

[0372] Ultimately, the second target branch line segment with the voltage distortion judgment result of "local voltage distortion phenomenon" was the N05-N15 section of feeder L01-2.

[0373] Step 4043: Based on the voltage distortion judgment result indicating the trend of the total harmonic voltage distortion rate of the second target branch line segment with local voltage distortion after the second disturbance start time, determine the characteristics of the harmonic accumulation effect.

[0374] Optionally, the total harmonic voltage distortion rate refers to the ratio of the root mean square value of all harmonic voltages to the root mean square value of the fundamental voltage in the second target branch line segment. It is used to characterize the severity of voltage waveform distortion. The larger the total harmonic voltage distortion rate, the more severe the voltage waveform distortion.

[0375] The total harmonic voltage distortion rate after the second disturbance start time refers to the total harmonic voltage distortion rate values ​​continuously collected within the same preset time window (300 milliseconds) after the second disturbance start time, according to a preset sampling interval (10 milliseconds in this embodiment), forming a continuous numerical sequence.

[0376] The trend of total harmonic voltage distortion (THD) refers to the change pattern of the continuously collected TTD values ​​over time within a preset time window. It mainly includes four types: upward trend, downward trend, stable trend, and fluctuating trend. An upward trend indicates that the TTD value gradually increases over time; a downward trend indicates that the TTD value gradually decreases over time; a stable trend indicates that the TTD value remains basically unchanged over time (fluctuation amplitude less than 0.1%); and a fluctuating trend indicates that the TTD value fluctuates over time without a clear upward or downward trend.

[0377] The harmonic accumulation effect characteristic refers to the effect characteristic formed by the accumulation of the total harmonic voltage distortion rate over time in the second target branch line segment after the second disturbance occurs. This characteristic is determined by the changing trend of the total harmonic voltage distortion rate and the peak and average values ​​of the total harmonic voltage distortion rate, and is used to characterize the degree of harmonic accumulation in the line and its impact on line operation. The determination logic of the harmonic accumulation effect characteristic in this application embodiment is as follows:

[0378] 1. For each second target branch line segment, extract its total harmonic voltage distortion rate numerical sequence within a preset time window, and calculate the peak (maximum) and average value of the sequence;

[0379] 2. Analyze the variation pattern of the numerical sequence to determine the trend of the total harmonic voltage distortion rate (rising, falling, stable, fluctuating).

[0380] 3. Integrate the trend, peak value, and average value of the total harmonic voltage distortion rate to form the harmonic accumulation effect characteristics of the second target branch line segment, and clearly characterize the severity of harmonics in this line segment.

[0381] In one embodiment, the second target branch line segment is the N05-N15 section of feeder L01-2; for example, the second disturbance starts at 0 milliseconds, the preset time window is 300 milliseconds, the sampling interval is 10 milliseconds, and a total of 30 harmonic voltage total distortion rate values ​​are collected.

[0382] The percentages were 3.2% at 0 ms, 4.5% at 50 ms, 5.8% at 100 ms, 7.1% at 150 ms, 8.3% at 200 ms, 8.1% at 250 ms, and 7.9% at 300 ms. The peak percentage of the numerical sequence was 8.3%, and the average percentage was (3.2% + 4.5% + 5.8% + 7.1% + 8.3% + 8.1% + 7.9% + the remaining 23 values) / 30 = 6.7%.

[0383] The terminal management device determines the characteristics of harmonic accumulation effect:

[0384] Analysis of the trend: From 0 ms to 200 ms, the total harmonic voltage distortion rate gradually increased from 3.2% to 8.3%, showing an upward trend; from 200 ms to 300 ms, the total harmonic voltage distortion rate slightly decreased from 8.3% to 7.9%, and generally tended to be stable. The overall trend of the total harmonic voltage distortion rate is judged to be "first rising and then stabilizing".

[0385] Therefore, the trend is "first rise then stabilize", with a peak value of 8.3% and an average value of 6.7%. Finally, the harmonic accumulation effect characteristics of the N05-N15 section of the L01-2 feeder are: the total harmonic voltage distortion rate first rises then stabilizes, with a peak value of 8.3% and an average value of 6.7%.

[0386] Step 4044: Determine the loop state perception result based on the harmonic accumulation effect characteristics of each second target branch line segment.

[0387] Optionally, the terminal management device determines the loop status sensing result based on the harmonic accumulation effect characteristics of each second target branch line segment.

[0388] This application embodiment relies on the power consumption early warning module to complete data collection and analysis, realizing all-round status detection of the power supply circuit from the main line segment to the downstream branch line segment. It makes up for the shortcomings of the past, which only detected the main line segment and ignored the abnormality of the downstream branch. It solves the problem of incomplete abnormality detection and inaccurate response caused by the isolated operation of each functional unit, realizes the overall perception of complex disturbance events within a single terminal, and improves the safety response capability of abnormal events in complex disturbance scenarios.

[0389] Optionally, step 4044 may include steps 40441 to 40444, wherein:

[0390] Step 40441: Based on the harmonic accumulation effect characteristics of each second target branch line segment, determine whether each second target branch line segment is in the critical state of harmonic resonance, and obtain the harmonic resonance judgment result.

[0391] Optionally, the harmonic resonance determination parameters are pre-set core parameters used to determine whether the second target branch line segment is in a critical state of harmonic resonance. These parameters include the peak threshold of total harmonic voltage distortion and the average growth rate threshold of total harmonic voltage distortion. Both parameters are determined based on the line parameters, load characteristics, power quality standards, and harmonic resonance risk level of the second target branch line segment. They can be adaptively adjusted according to the actual operating scenario of the line. In this embodiment, the preset parameters are set as follows: the peak threshold of total harmonic voltage distortion is 8%, and the average growth rate threshold of total harmonic voltage distortion is 0.03% / millisecond.

[0392] Harmonic resonance critical state refers to the operating state in which the total harmonic voltage distortion rate of the second target branch line segment reaches a critical value and the growth rate is close to the resonance triggering condition, and harmonic resonance may occur at any time. Harmonic resonance refers to the phenomenon in which the harmonic components in the line form a resonant circuit with the line inductance and capacitance, resulting in a sharp amplification of harmonic voltage and current, which seriously threatens the safety of the line and electrical equipment. Line segments in the harmonic resonance critical state are high-risk points for causing serious power quality abnormalities and equipment failures.

[0393] The harmonic resonance judgment result is the determination result of the terminal management device on whether each second target branch line segment is in the harmonic resonance critical state. It includes only two cases: in the harmonic resonance critical state and not in the harmonic resonance critical state. The third target branch line segment refers to the second target branch line segment that the harmonic resonance judgment result indicates is in the harmonic resonance critical state. This line segment is a high-risk abnormal line and further thermal stability and overheating risk detection of the terminal distribution node is required.

[0394] The algorithm for calculating the average growth rate of total harmonic voltage distortion is as follows: Subtract the initial value of total harmonic voltage distortion corresponding to the start time of the second disturbance from the peak value of the total harmonic voltage distortion of the second target branch line segment to obtain the growth difference of total harmonic voltage distortion; Divide the growth difference by the time it takes for the total harmonic voltage distortion to rise from the initial value to the peak value (i.e., the difference between the sampling time corresponding to the peak value and the start time of the second disturbance), and keep the result to four decimal places (% / millisecond), which is the average growth rate of total harmonic voltage distortion.

[0395] Optionally, the determination logic for the harmonic resonance judgment result in this application embodiment is as follows: For each second target branch line segment, the terminal management device simultaneously determines whether two conditions are met: 1. The peak value of the total harmonic voltage distortion rate of the second target branch line segment is greater than or equal to the preset peak value threshold of the total harmonic voltage distortion rate (8%); 2. The average growth rate of the total harmonic voltage distortion rate of the second target branch line segment is greater than or equal to the preset average growth rate threshold (0.03% / millisecond); If both conditions are met simultaneously, the second target branch line segment is determined to be in the critical state of harmonic resonance, and is identified as the third target branch line segment, with the harmonic resonance judgment result being "in the critical state of harmonic resonance"; If either condition is not met, the second target branch line segment is determined not to be in the critical state of harmonic resonance, and is not identified as the third target branch line segment, with the harmonic resonance judgment result being "not in the critical state of harmonic resonance".

[0396] In one embodiment, there are two second target branch line segments: L01-2 feeder segment N05-N15 and L01-4 feeder segment N06-N20. Preset harmonic resonance determination parameters are: peak threshold 8% and average growth rate threshold 0.03% / millisecond. For example, the relevant data for the harmonic accumulation effect characteristics of the two second target branch line segments are as follows:

[0397] 1. L01-2 feeder N05-N15 section: initial value of total harmonic voltage distortion rate is 3.2%, peak value is 8.3%, sampling time corresponding to the peak value is 200 milliseconds, and preset time window is 300 milliseconds;

[0398] 2. L01-4 feeder N06-N20 section: initial value of total harmonic voltage distortion rate is 2.8%, peak value is 7.9%, sampling time corresponding to the peak value is 180 milliseconds, and preset time window is 300 milliseconds.

[0399] The terminal management device calculates the average growth rate and determines the harmonic resonance judgment result:

[0400] 1. Section N05-N15 of feeder L01-2:

[0401] The difference in the total harmonic voltage distortion rate is 8.3% - 3.2% = 5.1%;

[0402] Average growth rate = 5.1% / (200 milliseconds - 0 milliseconds) = 5.1% / 200 milliseconds = 0.0255% / millisecond;

[0403] Judgment conditions: Peak value 8.3% > 8% (satisfied), average growth rate 0.0255% / millisecond < 0.03% / millisecond (not satisfied); if any condition is not met, it is determined that it is not in the critical state of harmonic resonance, and it is uncertain whether it is the third target branch line segment.

[0404] In another embodiment, the second target branch line segment L01-5 feeder N07-N22 section has an initial total harmonic voltage distortion rate of 3%, a peak value of 8.2%, and the sampling time corresponding to the peak value is 170 milliseconds;

[0405] The growth difference = 8.2% - 3% = 5.2%; the average growth rate = 5.2% / 170 milliseconds ≈ 0.0306% / millisecond;

[0406] Judgment conditions: Peak value 8.2% ≥ 8% (satisfied), average growth rate 0.0306% / millisecond ≥ 0.03% / millisecond (satisfied); if both conditions are met, it is determined to be in the critical state of harmonic resonance and is identified as the third target branch line segment.

[0407] Ultimately, the third target branch line segment that was determined to be "in the critical state of harmonic resonance" was the N07-N22 segment of feeder L01-5; the line segments corresponding to feeders L01-2 and L01-4 were determined to be "not in the critical state of harmonic resonance".

[0408] Step 40442: Based on the harmonic resonance judgment result, the temperature rise rate data of the end distribution node connected to the third target branch line segment that is in the critical state of harmonic resonance is determined after the second disturbance start time, and the degree of thermal stability degradation of the end distribution node is determined.

[0409] Optionally, the terminal distribution node refers to the terminal node of the third target branch line segment. This node is the connection node between the third target branch line segment and the downstream electrical equipment (or lower-level branch line), and is responsible for distributing electrical energy to the terminal electrical equipment. It is also the core node that causes abnormal temperature rise due to harmonic resonance. Each third target branch line segment corresponds to at least one terminal distribution node. The identification of the terminal distribution node is determined based on the node number in the distribution topology data (such as node N22) to ensure the uniqueness and identifiability of the node.

[0410] The terminal management device collects the temperature rise rate data of each end distribution node after the start of the second disturbance. The temperature rise rate data refers to the rate at which the temperature of the end distribution node rises over time after the start of the second disturbance. This data is collected by the temperature detection unit of the power consumption early warning module. The collection time range is consistent with the aforementioned preset time window (300 milliseconds), and the sampling interval is set to 20 milliseconds. Each end distribution node corresponds to a continuous sequence of temperature rise rate values, with the unit being degrees Celsius per millisecond. The temperature rise rate data is used to characterize how quickly the temperature of the end distribution node changes under the critical state of harmonic resonance. The larger the temperature rise rate, the faster the node temperature rises and the worse its thermal stability.

[0411] The degree of thermal stability degradation refers to the severity to which the thermal stability of the terminal distribution node deviates from its normal operating state after the second disturbance occurs. This degree is quantified by temperature rise rate data, and its core characteristic reflects the abnormal temperature deterioration of the terminal distribution node due to harmonic resonance. Optionally, the determination logic and calculation algorithm for the degree of thermal stability degradation in this application embodiment are as follows:

[0412] 1. Calculate the average temperature rise rate of the end distribution node within the preset time window: Traverse the temperature rise rate numerical sequence of the end distribution node, calculate the average value of all sampled values, which is the average temperature rise rate.

[0413] 2. Preset normal temperature rise rate threshold: This threshold is the maximum allowable temperature rise rate when the terminal power distribution node is operating normally, which is preset by the terminal management device. It is determined based on the material, rated current and heat dissipation conditions of the terminal power distribution node, and the value range is from 0.0005 degrees Celsius / millisecond to 0.0015 degrees Celsius / millisecond. In this embodiment of the application, the preset normal temperature rise rate threshold is 0.0010 degrees Celsius / millisecond.

[0414] 3. Calculate the temperature rise rate deviation rate: Subtract the preset normal temperature rise rate threshold from the average temperature rise rate of the terminal power distribution node to obtain the temperature rise rate deviation value; divide the temperature rise rate deviation value by the preset normal temperature rise rate threshold, and multiply the result by 100 to obtain the temperature rise rate deviation rate.

[0415] 4. Determine the degree of thermal stability degradation: Degradation levels are classified based on the temperature rise rate deviation rate to clarify the degree of thermal stability degradation. The specific classification criteria in this application embodiment are as follows:

[0416] Slight deterioration: The temperature rise rate deviation rate is between 0% and 50% (inclusive), indicating that the node thermal stability deviates slightly from the normal state and the temperature rise rate is slightly faster;

[0417] Moderate degradation: The temperature rise rate deviation rate is between 50% and 100% (inclusive), indicating that the node thermal stability has deteriorated significantly and the temperature rise rate is relatively fast;

[0418] Severe deterioration: A temperature rise rate deviation rate greater than 100% indicates severe deterioration of node thermal stability, with an extremely rapid temperature rise rate and a serious risk of overheating.

[0419] In one embodiment, the third target branch line segment is the N07-N22 section of feeder L01-5, and its connected terminal distribution node is node N22. For example, the second disturbance starts at 0 milliseconds, the preset time window is 300 milliseconds, the sampling interval is 20 milliseconds, and a total of 15 temperature rise rate values ​​are collected: 0.0008 degrees Celsius / millisecond at 0 milliseconds, 0.0012 degrees Celsius / millisecond at 50 milliseconds, 0.0015 degrees Celsius / millisecond at 100 milliseconds, 0.0018 degrees Celsius / millisecond at 150 milliseconds, 0.0020 degrees Celsius / millisecond at 200 milliseconds, 0.0019 degrees Celsius / millisecond at 250 milliseconds, and 0.0017 degrees Celsius / millisecond at 300 milliseconds; the preset normal temperature rise rate threshold is 0.0010 degrees Celsius / millisecond. The terminal management device calculates and determines the degree of thermal stability degradation:

[0420] 1. Calculate the average temperature rise rate: (0.0008+0.0012+0.0015+0.0018+0.0020+0.0019+.....) / 15=0.0015 degrees Celsius / millisecond;

[0421] 2. Calculate the temperature rise rate deviation rate:

[0422] Temperature rise rate deviation = 0.0015 - 0.0010 degrees Celsius / millisecond = 0.0005 degrees Celsius / millisecond;

[0423] Temperature rise rate deviation rate = (0.0005 / 0.0010) * 100 = 50%;

[0424] 3. Determine the degradation level: The temperature rise rate deviation rate is 50%, which meets the classification standard of "moderate degradation" (between 50% and 100%, including 50%).

[0425] Ultimately, the thermal stability of the N22 node, the end distribution node connected to the N07-N22 section of feeder L01-5, is moderately deteriorated.

[0426] In another embodiment, the third target branch line segment L01-6 feeder N08-N25 section, whose end distribution node is N25, has an average temperature rise rate of 0.0022 degrees Celsius / millisecond; the temperature rise rate deviation rate = (0.0022-0.0010) / 0.0010*100=120%, and the degree of thermal stability degradation is determined to be severe degradation.

[0427] Step 40443: Determine whether there is an overheating risk at the end distribution node based on the degree of thermal stability degradation, and obtain the overheating risk judgment result.

[0428] Optionally, the overheating risk judgment threshold is a pre-set critical index used to determine whether there is an overheating risk at the end distribution node. This threshold is determined based on the classification standard of thermal stability degradation degree and corresponds to the critical value of the temperature rise rate deviation rate. In this embodiment, the preset overheating risk judgment threshold is 50%. Overheating risk refers to the risk that the temperature of the end distribution node will continue to rise due to thermal stability degradation, potentially exceeding the node's maximum allowable operating temperature and causing safety accidents such as equipment burnout and line short circuits. The overheating risk judgment result is the judgment result of the terminal management device on whether there is an overheating risk for each end distribution node, including two situations: there is an overheating risk and there is no overheating risk. This judgment result is directly determined based on the degree of thermal stability degradation and the overheating risk judgment threshold. The core logic is that the more severe the degree of thermal stability degradation, the higher the overheating risk. When the degree of degradation reaches the critical value, it is determined that there is an overheating risk.

[0429] Optionally, the judgment logic for the overheating risk assessment result in this application embodiment is as follows: For each end power distribution node, the terminal management device determines whether its corresponding temperature rise rate deviation rate is greater than or equal to the preset overheating risk assessment threshold (50%). If the temperature rise rate deviation rate of the end power distribution node is greater than or equal to 50%, it indicates that its thermal stability degradation has reached a critical state, and the temperature rise rate has exceeded the safe range. The overheating risk assessment result is "there is an overheating risk". If the temperature rise rate deviation rate is less than 50%, it indicates that its thermal stability degradation is relatively mild, and the temperature rise rate is within the safe range. The overheating risk assessment result is "there is no overheating risk". In this application embodiment, combined with the classification standard of thermal stability degradation, the determination correlation is as follows: 1. Slight degradation (deviation rate 0%-50%): deviation rate < 50%, no overheating risk is determined; 2. Moderate degradation (deviation rate 50%-100%): deviation rate ≥ 50%, overheating risk is determined; 3. Severe degradation (deviation rate > 100%): deviation rate ≥ 50%, overheating risk is determined.

[0430] In one embodiment, there are two end-point power distribution nodes, namely node N22 and node N25; the preset overheating risk assessment threshold is 50%; the thermal stability degradation data of the two end-point power distribution nodes are as follows:

[0431] 1. N22 node: Temperature rise rate deviation rate 50%, thermal stability degradation level is moderate;

[0432] 2. N25 node: Temperature rise rate deviation rate is 120%, and the degree of thermal stability degradation is severe.

[0433] 3. Supplementing the end distribution node N28 (corresponding to the third target branch line segment L01-7 feeder N09-N28 section): temperature rise rate deviation rate is 35%, and the degree of thermal stability degradation is slight degradation.

[0434] The terminal management device determines the overheating risk assessment result according to the judgment logic:

[0435] 1. N22 node: Temperature rise rate deviation rate 50% = 50%, the overheating risk assessment result is "overheating risk exists";

[0436] 2. N25 node: Temperature rise rate deviation rate 120% > 50%, the overheating risk assessment result is "overheating risk exists";

[0437] 3. N28 node: The temperature rise rate deviation rate is 35% < 50%, and the overheating risk assessment result is "no overheating risk".

[0438] Ultimately, the N22 and N25 nodes were determined to have an overheating risk, while the N28 node was determined to have no overheating risk.

[0439] Step 40444: Based on the overheating risk assessment results, indicate the end distribution nodes with overheating risks and abnormal conduction paths, and determine the circuit status perception results.

[0440] Optionally, the terminal management device integrates the overheating risk assessment results indicating the end distribution nodes with overheating risks and abnormal conduction paths to obtain the loop status perception results.

[0441] This application embodiment relies on the power consumption early warning module to complete multi-dimensional data collection and analysis, realizing the full-chain detection of power supply circuit from line harmonic resonance to node overheating risk. It solves the problem of missed detection of hidden dangers such as harmonic resonance and node overheating caused by the isolated operation of each functional unit in the past, realizes the overall perception of complex disturbance events within a single terminal, and improves the safety response capability of abnormal events in complex disturbance scenarios.

[0442] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0443] Based on the same inventive concept, this application also provides a device for collaborative multiplexing of smart terminals based on dynamic sensing of power quality anomalies, used to implement the aforementioned method for collaborative multiplexing of smart terminals based on dynamic sensing of power quality anomalies. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the device for collaborative multiplexing of smart terminals based on dynamic sensing of power quality anomalies provided below can be found in the limitations of the method for collaborative multiplexing of smart terminals based on dynamic sensing of power quality anomalies described above, and will not be repeated here.

[0444] In one exemplary embodiment, such as Figure 3 As shown, a smart terminal collaborative multiplexing device 500 based on dynamic sensing of power quality anomalies is provided, including: a power quality anomaly sensing module 501, a non-intrusive identification module 502, a causal correlation determination module 503, and a loop status sensing module 504, wherein:

[0445] The power quality anomaly sensing module 501 is used to sense power quality anomalies based on power quality indicators calculated from the synchronous sampling sequence output by the smart IoT power meter, and to determine power quality anomaly events.

[0446] The non-intrusive identification module 502 is used to non-intrusively identify the load operating status within the same time period based on power quality abnormality events, and obtain the first target electrical equipment and its start-stop sequence information.

[0447] The causal relationship determination module 503 is used to determine the second target electrical equipment that has a causal relationship with the occurrence of power quality abnormality based on each first target electrical equipment and its corresponding start-stop timing information, combined with the first disturbance start time and disturbance type corresponding to the power quality abnormality event;

[0448] The loop status sensing module 504 is used to detect the status of the power supply loop associated with the second target electrical equipment and obtain the loop status sensing result.

[0449] In some embodiments, the causal association determination module 503 is further configured to: determine a set of start-up times within the time window corresponding to the power quality anomaly event based on the start-up and stop timing information of each first target electrical device; filter start-up times within a preset time threshold range before the start-up time of the first disturbance based on the set of start-up times to obtain candidate start-up times; take the electrical devices corresponding to the candidate start-up times as potential disturbance source devices that have started up; determine the consistency judgment result of each potential disturbance source device and the disturbance type in disturbance performance based on the first electrical disturbance characteristics of each potential disturbance source device under operating conditions and the second electrical disturbance characteristics corresponding to the electrical quantity anomaly characteristics characterized by the disturbance type; take the potential disturbance source devices with consistent disturbance performance as first preliminary associated devices based on the consistency judgment result; obtain the time interval of each first preliminary associated device based on the time difference between the candidate start-up time and the start-up time of the first disturbance; and determine the second target electrical device that has a causal relationship with the power quality anomaly based on the time interval of each first preliminary associated device.

[0450] In some embodiments, the causal association determination module 503 is further configured to: determine a second preliminary associated device that satisfies the time causality constraint based on a time interval less than or equal to the physical response time threshold required for the observable disturbance to be generated after the device starts up; determine the disturbance duration interval covered by the device startup behavior based on the candidate startup time corresponding to each second preliminary associated device and the duration of the current surge caused during startup; determine whether the device startup behavior can cover the starting point of the power quality anomaly event in the time dimension based on whether the disturbance duration interval of each second preliminary associated device includes the first disturbance start time; obtain a disturbance coverage result; take the second preliminary associated device that can cover the starting point of the power quality anomaly event as a candidate associated device based on the disturbance coverage result; determine the observed disturbance intensity capability of the device startup behavior to cause the power quality anomaly event based on the electrical disturbance amplitude of the candidate associated device during startup; and determine the candidate associated device whose disturbance intensity capability is greater than or equal to a preset intensity capability threshold as the second target electrical device that has a causal relationship with the power quality anomaly.

[0451] In some embodiments, the loop state sensing module 504 is further configured to: determine the main line segment in the power supply loop that is electrically connected to the second target electrical device based on the access point location of the second target electrical device in the power distribution topology and its feeder hierarchy; determine the electrical dynamic response characteristics of the main line segment during the disturbance response based on the voltage instantaneous value sequence and current instantaneous value sequence of the main line segment within a preset time window after the second disturbance initiation time; the second disturbance initiation time indicates the disturbance initiation time corresponding to the time when the power quality abnormal event occurs in the second target electrical device; identify whether there is a persistent voltage drop or a persistent current surge in the main line segment based on the electrical dynamic response characteristics, obtain the abnormal identification result, and determine the abnormal propagation path of the main line segment during the disturbance response based on the abnormal identification result; locate the downstream branch line segment to which the abnormal signal propagation direction in the main line segment points based on the abnormal propagation path, and determine the loop state sensing result based on the effective value of the zero-sequence current of each downstream branch line segment within the same preset time window after the second disturbance initiation time.

[0452] In some embodiments, the loop state sensing module 504 is further configured to: take the downstream branch line segment where the effective value of the zero-sequence current exceeds a preset current threshold as the first target branch line segment; obtain the three-phase load imbalance index of each first target branch line segment based on the change in the phase-to-phase voltage imbalance degree of each first target branch line segment before and after the second disturbance initiation time; determine whether there is a local voltage distortion phenomenon caused by load asymmetry based on the three-phase load imbalance index of each first target branch line segment, and obtain a voltage distortion judgment result; determine the harmonic accumulation effect characteristics based on the voltage distortion judgment result indicating the trend of the total harmonic voltage distortion rate of the second target branch line segment with local voltage distortion phenomenon after the second disturbance initiation time; and determine the loop state sensing result based on the harmonic accumulation effect characteristics of each second target branch line segment.

[0453] In some embodiments, the loop state sensing module 504 is further configured to determine whether each second target branch line segment is in a harmonic resonance critical state based on the harmonic accumulation effect characteristics of each second target branch line segment, and obtain a harmonic resonance judgment result; based on the harmonic resonance judgment result, indicate the temperature rise rate data of the end distribution node connected to the third target branch line segment in a harmonic resonance critical state after the second disturbance initiation time, and determine the degree of thermal stability degradation of the end distribution node; based on the degree of thermal stability degradation, determine whether there is an overheating risk of the end distribution node, and obtain an overheating risk judgment result; based on the overheating risk judgment result, indicate the end distribution node with overheating risk and the abnormal conduction path, and determine the loop state sensing result.

[0454] In some embodiments, the non-intrusive identification module 502 is further configured to: determine the time window corresponding to the power quality anomaly event based on the start and end times of the power quality anomaly event in the synchronous sampling sequence; extract current signal waveform data within the time window from the synchronous sampling sequence and calculate the instantaneous active power sequence based on the current signal waveform data; determine the active power step change point based on the position and direction of amplitude abrupt change in the instantaneous active power sequence; each active power step change point corresponds to a load state switching time; divide the time window into multiple continuous steady-state operating segments based on each active power step change point, and determine the first target electrical equipment and its start-stop timing information based on the average instantaneous active power and the average instantaneous reactive power within each steady-state operating segment.

[0455] In some embodiments, the non-intrusive identification module 502 is further configured to: determine a two-dimensional electrical feature vector based on the average instantaneous active power and the average instantaneous reactive power in each steady-state operating segment; and obtain candidate electrical equipment combinations that match the two-dimensional electrical feature vector of each steady-state operating segment based on the active power amplitude range and reactive power amplitude range of various types of electrical equipment in a pre-built electrical feature library of electrical equipment under steady-state operating conditions; identify the identity information of electrical equipment added or removed at the segment switching time based on the differences between the candidate electrical equipment combinations corresponding to adjacent steady-state operating segments; determine the electrical equipment category associated with each load state switching based on the electrical equipment identity information combined with the equipment category mapping relationship in the electrical feature library of electrical equipment; and determine the first target electrical equipment and its start-stop sequence information based on the multiple switching times of each electrical equipment category.

[0456] In some embodiments, the non-intrusive identification module 502 is further configured to arrange multiple switching times of each electrical equipment category in chronological order to obtain a start-stop event sequence for each electrical equipment category within a time window; the rising edge switching time in the start-stop event sequence is the start time, and the falling edge switching time is the stop time; based on the start time and the last stop time in the start-stop event sequence of each electrical equipment category, the effective operating range of each electrical equipment category within the time window is determined; based on the effective operating range of each electrical equipment category, it is determined whether each electrical equipment category is in a power consumption state during the occurrence of a power quality abnormality event, and a power consumption participation result is obtained; based on the power consumption participation result, the electrical equipment corresponding to the electrical equipment category in a power consumption state is identified as the first target electrical equipment, and the start-stop event sequence corresponding to the first target electrical equipment is identified as the start-stop timing information of the first target electrical equipment.

[0457] The modules in the aforementioned intelligent terminal collaborative multiplexing device based on dynamic sensing of power quality anomalies can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0458] In one exemplary embodiment, a computer device is provided, which may be a terminal or a terminal, and its internal structure diagram may be as follows. Figure 4 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores various data involved in the intelligent terminal collaborative multiplexing method based on dynamic sensing of power quality anomalies. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements an intelligent terminal collaborative multiplexing method based on dynamic sensing of power quality anomalies.

[0459] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0460] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0461] In one embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0462] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0463] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0464] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0465] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0466] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A collaborative reuse method for intelligent terminals based on dynamic sensing of power quality anomalies, characterized in that, The method includes: Power quality anomalies are detected and identified based on power quality indicators calculated from the synchronous sampling sequence output by smart IoT power meters. Based on the power quality anomaly event, the load operation status within the same time period is identified non-intrusively to obtain the first target electrical equipment and its start-stop sequence information; Based on each first target electrical device and its corresponding start-stop timing information, combined with the first disturbance start time and disturbance type corresponding to the power quality anomaly event, the second target electrical device with a causal relationship to the occurrence of the power quality anomaly is determined. The status of the power supply circuit associated with the second target electrical equipment is detected to obtain the circuit status perception result.

2. The method according to claim 1, characterized in that, The method for determining the second target electrical equipment with a causal relationship to the occurrence of power quality anomalies based on each first target electrical device and its corresponding start-stop timing information, combined with the first disturbance start time and disturbance type corresponding to the power quality anomaly event, includes: Based on the start-stop timing information of each first target electrical device, a set of start times within the time window corresponding to the power quality abnormal event is determined, and start times within a preset time threshold range before the start time of the first disturbance are selected based on the set of start times to obtain candidate start times; Using the electrical equipment corresponding to the candidate start time as the potential disturbance source equipment for the start-up behavior, based on the first electrical disturbance characteristics of each potential disturbance source equipment under operating conditions and the second electrical disturbance characteristics corresponding to the abnormal electrical quantity characteristics characterized by the disturbance type, the consistency judgment result of each potential disturbance source equipment and the disturbance type in disturbance performance is determined. The potential disturbance source devices with consistent disturbance behavior as determined by the consistency judgment result are designated as the first preliminary associated devices. The time interval of each first preliminary associated device is obtained based on the time difference between the candidate start time and the first disturbance start time of each first preliminary associated device. Based on the time interval of each first preliminary associated device, a second target electrical device with a causal relationship to the occurrence of power quality anomalies is identified.

3. The method according to claim 2, characterized in that, The second target electrical equipment, determined based on the time interval of each first preliminary associated device, to have a causal relationship with the occurrence of power quality anomalies, includes: Based on the time interval being less than or equal to the physical response time threshold required for the device to generate an observable disturbance after startup, a second preliminary associated device that satisfies the time causality constraint is identified. Based on the candidate start-up time corresponding to each second preliminary associated device and the duration of the current surge caused during the start-up process, the disturbance duration range covered by the device start-up behavior is determined, and based on whether the disturbance duration range of each second preliminary associated device includes the first disturbance start time, it is determined whether the device start-up behavior can cover the start point of the power quality abnormal event in the time dimension, and the disturbance coverage result is obtained. The second preliminary associated device, whose disturbance coverage result is able to cover the starting point of the power quality anomaly event, is selected as the candidate associated device. Based on the electrical disturbance amplitude of the candidate associated device during the startup process, the observed disturbance intensity capability of its device startup behavior to trigger the power quality anomaly event is determined. Candidate associated devices with disturbance strength capabilities greater than or equal to a preset strength capability threshold are identified as the second target electrical devices that are causally associated with power quality anomalies.

4. The method according to claim 1, characterized in that, The step of performing status detection on the power supply circuit associated with the second target electrical device to obtain the circuit status perception result includes: Based on the location of the access point of the second target electrical equipment in the power distribution topology and its feeder hierarchy, the main line segment in the power supply circuit that is electrically connected to the second target electrical equipment is determined. Based on the instantaneous voltage and current value sequences of the main line segment within a preset time window after the second disturbance initiation time, the electrical dynamic response characteristics of the main line segment during the disturbance response are determined; the second disturbance initiation time indicates the disturbance initiation time corresponding to the time when the power quality abnormality event occurs for the second target electrical equipment; Based on the electrical dynamic response characteristics, identify whether there is a persistent voltage drop or a persistent current surge in the main line segment, obtain the anomaly identification result, and determine the abnormal conduction path of the main line segment during the disturbance response based on the anomaly identification result. Based on the abnormal conduction path, locate the downstream branch line segment to which the abnormal signal propagation direction in the main line segment points, and determine the loop state sensing result based on the effective value of the zero-sequence current in each downstream branch line segment within the same preset time window after the second disturbance initiation time.

5. The method according to claim 4, characterized in that, The determination of the loop state sensing result based on the effective value of the zero-sequence current of each downstream branch line segment within the same preset time window after the second disturbance initiation time includes: The downstream branch line segment where the effective value of the zero-sequence current exceeds the preset current threshold is taken as the first target branch line segment. Based on the change in the phase-to-phase voltage imbalance of each first target branch line segment before and after the second disturbance start time, the three-phase load imbalance index of each first target branch line segment is obtained. Based on the three-phase load imbalance index of each first target branch line segment, determine whether there is a local voltage distortion phenomenon caused by load asymmetry, and obtain the voltage distortion judgment result. Based on the voltage distortion judgment results, the trend of the total harmonic voltage distortion rate of the second target branch line segment with local voltage distortion after the second disturbance start time is determined, and the characteristics of the harmonic accumulation effect are identified. Based on the harmonic accumulation effect characteristics of each second target branch line segment, the loop state perception result is determined.

6. The method according to claim 5, characterized in that, The determination of the loop state sensing result based on the harmonic accumulation effect characteristics of each second target branch line segment includes: Based on the characteristics of the harmonic accumulation effect of each second target branch line segment, determine whether each second target branch line segment is in the critical state of harmonic resonance, and obtain the harmonic resonance judgment result; Based on the harmonic resonance judgment result, the temperature rise rate data of the end distribution node connected to the third target branch line segment that is in the critical state of harmonic resonance after the second disturbance start time is used to determine the degree of thermal stability degradation of the end distribution node. Based on the degree of thermal stability degradation, it is determined whether there is an overheating risk at the end power distribution node, and the overheating risk assessment result is obtained. Based on the overheating risk assessment results, the terminal distribution nodes with overheating risk and the abnormal conduction paths are indicated, and the circuit status perception results are determined.

7. The method according to any one of claims 1 to 6, characterized in that, The non-intrusive identification of load operation status within the same time period based on the power quality anomaly event, to obtain the first target electrical equipment and its start-stop sequence information, includes: Based on the start and end times of the power quality anomaly event in the synchronous sampling sequence, the time window corresponding to the power quality anomaly event is determined. The current signal waveform data within the time window is extracted from the synchronous sampling sequence, and the instantaneous active power sequence is calculated based on the current signal waveform data. Based on the location and direction of amplitude abrupt change points in the instantaneous active power sequence, active power step change points are determined; each active power step change point corresponds to a load state switching moment. The time window is divided into multiple continuous steady-state operating segments based on each step change point of active power, and the first target electrical equipment and its start-stop timing information are determined based on the average instantaneous active power and the average instantaneous reactive power in each steady-state operating segment.

8. The method according to claim 7, characterized in that, The determination of the first target electrical equipment and its start-stop sequence information based on the average instantaneous active power and average instantaneous reactive power within each steady-state operating segment includes: Based on the average instantaneous active power and average instantaneous reactive power in each steady-state operating segment, a two-dimensional electrical feature vector is determined. Based on the active power amplitude range and reactive power amplitude range of various types of electrical equipment in the pre-constructed electrical feature library of electrical equipment under steady-state operating conditions, a candidate combination of electrical equipment matching the two-dimensional electrical feature vector of each steady-state operating segment is obtained. Based on the differences between candidate power equipment combinations corresponding to adjacent steady-state operation sections, the identity information of power equipment added or removed at the time of section switching is identified. Based on the electrical equipment identity information and the equipment category mapping relationship in the electrical feature database of the electrical equipment, the associated electrical equipment category is determined each time the load state is switched. Based on multiple switching times for each category of electrical equipment, the first target electrical equipment and its start-stop sequence information are determined.

9. The method according to claim 8, characterized in that, The determination of the first target electrical device and its start / stop sequence information based on multiple switching times for each type of electrical equipment includes: Arrange the multiple switching moments of each category of electrical equipment in chronological order to obtain the start-stop event sequence of each category within the time window; the rising edge switching moment in the start-stop event sequence is the start moment, and the falling edge switching moment is the stop moment; Based on the start time and last stop time in the start-stop event sequence of each electrical equipment category, the effective operating range of each electrical equipment category within the time window is determined; Based on the effective operating range of each category of electrical equipment, determine whether each category of electrical equipment is in a state of participating in power consumption during the occurrence of the power quality anomaly event, and obtain the power consumption participation result; Based on the electricity consumption participation results, the electrical equipment corresponding to the category of electrical equipment in the electricity consumption state is determined as the first target electrical equipment, and the start-stop event sequence corresponding to the first target electrical equipment is determined as the start-stop timing information of the first target electrical equipment.

10. A smart terminal collaborative multiplexing device based on dynamic sensing of power quality anomalies, characterized in that, The device includes: The power quality anomaly sensing module is used to sense power quality anomalies based on power quality indicators calculated from the synchronous sampling sequence output by the smart IoT power meter, and to identify power quality anomaly events. The non-intrusive identification module is used to non-intrusively identify the load operation status within the same time period based on the power quality abnormality event, and obtain the first target electrical equipment and its start-stop timing information. The causal correlation determination module is used to determine the second target electrical equipment that has a causal relationship with the occurrence of power quality abnormality based on each first target electrical equipment and its corresponding start-stop timing information, combined with the first disturbance start time and disturbance type corresponding to the power quality abnormality event; The loop status sensing module is used to detect the status of the power supply loop associated with the second target electrical device and obtain the loop status sensing result.

Images