Electric energy quality treatment method, device, equipment and medium

Abstract

The invention discloses an electric energy quality treatment method, device and equipment and a medium. The method comprises the following steps: acquiring voltage and current data of a power grid in real time, monitoring electric energy quality, comparing the data with values required in actual operation, judging whether the electric energy quality of a region needs to be treated or not, and if only one electric energy index does not meet requirements, according to the index needing to be treated, controlling the electric energy quality according to the index needing to be treated. The method comprises the following steps: starting electric energy quality adjusting equipment to perform cooperative treatment with equipment installed in a power grid, if two or more electric energy indexes do not meet requirements, starting the electric energy quality adjusting equipment to perform comprehensive treatment, and during comprehensive treatment, sequencing the conditions of different electric energy indexes by comparing the deviation degree of each electric energy index. The method comprises the steps of determining the type and priority of an electric energy index needing to be treated, and finally, according to the comprehensiveness of electric energy quality adjusting equipment needing to be treated and the characteristics of the equipment, researching a comprehensive treatment means for the electric energy quality under the condition that multiple electric energy quality problems coexist.

Description

Technical Field

[0001] This invention relates to the field of power quality management technology, and in particular to a power quality management method, apparatus, equipment and medium. Background Technology

[0002] With the widespread application of power electronics technology and nonlinear loads, power quality problems in power systems are becoming increasingly prominent. Power quality problems mainly manifest in various forms such as harmonic distortion, voltage deviation, three-phase imbalance, and reduced power factor. These problems seriously affect the safe and stable operation of power systems and the normal operation of electrical equipment.

[0003] Traditional governance methods often target single power quality issues, such as harmonics or reactive power compensation, lacking comprehensive consideration of multiple power quality problems. This results in limited governance effectiveness. Existing governance equipment mostly operates with preset parameters, making it difficult to adaptively adjust according to the grid's operating status and disturbance characteristics, thus failing to achieve optimal control. Various power quality governance devices often operate independently, lacking a unified coordination mechanism, which can easily lead to control conflicts or resource waste. The accuracy of identifying the type and location of power quality disturbance sources is not high, making it difficult to implement targeted governance measures. With the expansion of the power grid and the diversification of electricity demand, power quality problems are becoming more complex, diverse, and dynamic. Traditional single governance methods are no longer sufficient to meet the demands of modern power systems for high-quality power.

[0004] Therefore, how to conduct a comprehensive analysis of power quality issues and achieve coordinated control of power quality management equipment to complete comprehensive power quality management has become an urgent problem to be solved. Summary of the Invention

[0005] In view of this, embodiments of the present invention provide a power quality management method, apparatus, computer equipment, and storage medium to address how to comprehensively analyze power quality problems, thereby achieving coordinated control of management equipment to complete comprehensive power quality management.

[0006] In a first aspect, embodiments of the present invention provide a power quality management method, comprising:

[0007] Acquire the power index data of the target index items collected in the power system and a standard database containing any of the target index items;

[0008] Extract reference data corresponding to the electrical energy index data from the standard database, and calculate the deviation value between the electrical energy index data and the reference data;

[0009] Based on the deviation value, abnormal indicators are determined, and based on the number of abnormal indicators, the equipment management method for handling the abnormal indicators is determined, wherein the equipment management method is collaborative management or comprehensive management.

[0010] Extract the abnormal data changes corresponding to the abnormal indicators from the power index data, determine the abnormal type based on the abnormal data changes, and determine the power quality management plan for the power system based on the abnormal type and the equipment management method.

[0011] Secondly, embodiments of the present invention provide a power quality management device and a data acquisition module for acquiring power index data of target index items collected in a power system and a standard database containing any of the target index items.

[0012] The deviation calculation module is used to extract reference data corresponding to the electrical energy index data in the standard database and calculate the deviation value between the electrical energy index data and the reference data.

[0013] An anomaly handling module is used to determine anomaly indicators based on the deviation value, and to determine the equipment management method for handling the anomaly indicators based on the number of anomaly indicators, wherein the equipment management method is collaborative management or comprehensive management.

[0014] The scheme determination module is used to extract abnormal data changes corresponding to the abnormal indicators in the power index data, determine the abnormal type based on the abnormal data changes, and determine the power quality management scheme of the power system based on the abnormal type and the equipment management method.

[0015] Thirdly, embodiments of the present invention provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described power quality management method.

[0016] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-described power quality management method.

[0017] The beneficial effects of this invention compared to existing technologies are as follows: It acquires power index data of target indicators collected in the power system and a standard database containing any target indicator; extracts reference data for the corresponding power index data from the standard database; calculates the deviation between the power index data and the reference data; identifies abnormal indicators based on the deviation; determines the equipment management method for handling abnormal indicators based on the number of abnormal indicators (either collaborative management or comprehensive management); extracts abnormal data changes corresponding to the abnormal indicators from the power index data; determines the anomaly type based on the abnormal data changes; and determines the power system's power quality management plan based on the anomaly type. This allows for a comprehensive analysis of power quality problems, thereby achieving collaborative control of management equipment to complete comprehensive power quality management. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the application environment of a power quality management method provided in Embodiment 1 of the present invention;

[0020] Figure 2 This is a schematic flowchart of a power quality management method provided in Embodiment 2 of the present invention;

[0021] Figure 3 This is a schematic flowchart of a power quality management method provided in Embodiment 3 of the present invention;

[0022] Figure 4 This is a schematic flowchart of a power quality management method provided in Embodiment 4 of the present invention;

[0023] Figure 5 This is a schematic flowchart of a power quality management method provided in Embodiment 5 of the present invention;

[0024] Figure 6 This is a schematic diagram of the structure of a power quality management device provided in Embodiment Six of the present invention;

[0025] Figure 7 This is a schematic diagram of the structure of a computer device provided in Embodiment 7 of the present invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] The first embodiment of this application provides a discrimination method for adversarial training of acoustic models, which can be applied to, for example... Figure 1 In this application environment, the client and server connect and communicate. Users can provide the conditions, requirements and operation instructions for power quality management through the client, and the server is used to control the power quality management methods according to the instructions sent by the client.

[0028] The client side includes, but is not limited to, PDAs, desktop computers, laptops, ultra-mobile personal computers (UMPCs), netbooks, cloud terminal devices, and personal digital assistants (PDAs). The server side can be a standalone server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0029] like Figure 2 The diagram shown is a flowchart illustrating a power quality management method according to Embodiment 2 of the present invention.

[0030] This power quality management method may include the following steps:

[0031] Step S201: Obtain the power index data of the target index items collected in the power system and a standard database containing any of the target index items.

[0032] In power system monitoring scenarios, target indicators include voltage deviation, harmonic distortion rate, three-phase imbalance, voltage variation rate, and power factor. These indicators reflect the quality of power from different perspectives.

[0033] Voltage deviation refers to the difference between the actual voltage and the rated voltage, reflecting the stability of the voltage. Excessive or insufficient voltage deviation can affect the normal operation of electrical equipment and even damage it. Harmonic distortion rate measures the harmonic content in a power system. Harmonics are generated by nonlinear loads and can lead to increased power loss, equipment overheating, and malfunctions of protection devices. Three-phase imbalance describes the degree of imbalance between the three-phase voltage or current in a three-phase system. Three-phase imbalance can cause additional losses and vibrations in motors, reducing equipment lifespan. Voltage change rate represents the rate of change of voltage over time, reflecting the dynamic characteristics of voltage. Rapid voltage changes can affect some voltage-sensitive equipment. Power factor measures the efficiency of electrical equipment in utilizing electrical energy. A low power factor means that equipment needs to absorb more reactive power from the grid, increasing grid losses.

[0034] To obtain the electrical energy performance data for these target indicators, relevant monitoring equipment needs to be installed at key nodes in the power system. This equipment can collect basic parameters such as voltage and current in real time and calculate the aforementioned electrical energy indicators using specific algorithms. For example, voltage deviation and voltage change rate can be calculated by measuring voltage values ​​at different times; harmonic components can be analyzed by performing Fourier transforms on voltage and current signals to calculate harmonic distortion rate; three-phase imbalance can be calculated by comparing the amplitude and phase of three-phase voltage or current; and power factor can be calculated by measuring active and reactive power.

[0035] The standards database contains the standard values ​​or allowable ranges for each of the above-mentioned target indicators. These standards are formulated based on relevant national standards and the operational requirements of the power system, and are important bases for judging whether power quality is up to standard. For example, for voltage deviation, national standards specify the allowable deviation ranges for different voltage levels, and there are also corresponding limits for harmonic distortion rate.

[0036] The standard database can be stored on a local server or a cloud server. During power quality management, the system can retrieve the standard database containing any target indicator from the server via a network connection. This database is regularly updated as relevant national standards are revised and power system operation requirements change to ensure its accuracy and effectiveness.

[0037] Step S202: Extract reference data corresponding to the power index data from the standard database, and calculate the deviation value between the power index data and the reference data.

[0038] After acquiring electrical energy index data such as voltage deviation, harmonic distortion rate, three-phase unbalance, voltage change rate, and power factor from the power system, corresponding reference data needs to be extracted from a standard database. This is analogous to finding a benchmark value for each acquired electrical energy index data point. For example, if voltage deviation data at a certain moment is acquired, the corresponding standard range of voltage deviation for that voltage level is found in the standard database; if harmonic distortion rate data is acquired, the corresponding standard limit value of harmonic distortion rate for that system is extracted. Accurate extraction of this correspondence is the foundation for subsequent calculations of deviation values.

[0039] Calculating the deviation between power quality index data and reference data can intuitively reflect the gap between the current power quality of the power system and national standards. Through the deviation values, we can quickly determine which power quality indicators are abnormal and the degree of abnormality, providing an important basis for subsequent power quality improvement measures.

[0040] Step S203: Based on the deviation value, determine the abnormal indicators; based on the number of abnormal indicators, determine the equipment management method for handling the abnormal indicators; the equipment management method is collaborative management or comprehensive management.

[0041] Optionally, step S203 may include the following steps:

[0042] If the deviation value is not within the preset standard range, the target indicator item corresponding to the deviation value is determined to be an abnormal indicator.

[0043] If the number of abnormal indicators is only one, then the equipment management method is determined to be collaborative management, which involves calling preset power quality conditioning equipment and voltage regulation equipment to complete power quality management.

[0044] Optionally, step S203 may include the following steps:

[0045] If the number of abnormal indicators is at least two, then the abnormal indicators are sorted in descending order according to the deviation value to obtain the sorting result, and the treatment items for the abnormal indicators are determined according to the sorting result.

[0046] The comprehensive management equipment management method is invoked to complete the power quality management of the management item. The comprehensive management refers to invoking the power quality conditioning equipment to complete the power quality management.

[0047] After step S203, it may also include:

[0048] Based on the abnormal data changes, the comprehensive problem type is determined. For any comprehensive problem type, the corresponding problem management solution of the power quality conditioning equipment is invoked to complete the power quality management solution.

[0049] The criteria for identifying abnormal indicators involve analyzing the calculated deviations of various electrical energy indicators and comparing them with preset standard ranges. These preset standard ranges are similar to the national standards for voltage deviation, harmonic distortion rate, and other indicators mentioned earlier. When a deviation value falls outside the preset standard range, it indicates that the corresponding electrical energy indicator has deviated from its normal state, and the corresponding target indicator is identified as an abnormal indicator. For example, if the preset standard range for voltage deviation is ±5%, but the actual calculated voltage deviation is -8%, this means the voltage indicator is not within the preset standard range, so it is identified as an abnormal indicator. Collaborative management (only one abnormal indicator): When only one abnormal indicator is identified, a collaborative management approach is adopted. If the calculation results show that only the voltage indicator does not meet the national standard, a collaborative control method using UPQC (Power Quality Control) and voltage regulation equipment can be used. UPQC is an advanced power quality control device that can simultaneously compensate for multiple power quality problems such as voltage deviation, harmonics, and reactive power. Adjusting the transformer tap changer adjusts the output voltage by changing the transformer's turns ratio. In this situation, UPQC can quickly and accurately regulate the voltage, while adjusting the transformer tap can achieve coarse voltage adjustment. The two work together to more effectively adjust the voltage to the normal range.

[0050] Comprehensive management (at least two abnormal indicators): When there are two or more abnormal indicators, they should first be sorted in descending order based on their deviation values. The larger the deviation value, the more serious the impact of the indicator on power quality, and the more priority it needs to be addressed. This sorting method yields the ranking results, which then determines the abnormal indicators that require priority management, i.e., the management items.

[0051] After identifying the issues to be addressed, the comprehensive governance equipment is activated. This primarily involves using power quality control equipment, such as UPQC (Upgraded Power Quality Control), to perform the governance. In scenarios where multiple power quality issues coexist, UPQC possesses strong comprehensive regulation capabilities, enabling it to address multiple abnormal indicators simultaneously. For example, when multiple indicators such as harmonic distortion rate, voltage deviation, three-phase imbalance, and voltage change rate fail to meet requirements, UPQC can utilize its internal control strategies to simultaneously suppress harmonics, adjust voltage, and compensate for three-phase imbalance, thereby achieving comprehensive power quality governance.

[0052] After identifying the abnormal indicators and selecting the mitigation methods, it is necessary to further determine the comprehensive problem type based on the changes in the abnormal data. Comprehensive problem types include complex issues such as voltage fluctuations and flicker, and harmonic pollution. For each comprehensive problem type, the corresponding mitigation solution from the power quality conditioning equipment is invoked. For example, for harmonic pollution problems, a specific harmonic mitigation algorithm might be used, where the UPQC outputs a reverse harmonic current to cancel harmonics in the system. For voltage fluctuations and flicker problems, a dynamic voltage compensation strategy is used to quickly adjust the voltage. Through these targeted mitigation solutions, power quality management can be completed more efficiently, ensuring the stable operation of the power system and the normal use of electrical equipment.

[0053] Step S204: Extract abnormal data changes corresponding to the abnormal indicators from the power index data, determine the abnormal type based on the abnormal data changes, and determine the power quality management plan for the power system based on the abnormal type and the equipment management method.

[0054] In step S204, the specific type of anomaly is determined by extracting changes in abnormal indicator data, and then a targeted power quality management plan is formulated based on the type of anomaly to achieve more precise and efficient power quality control.

[0055] Having identified the abnormal indicators in the previous steps, we now need to extract data specifically related to these abnormal indicators from the collected electrical energy data and analyze their changes. If the identified abnormal indicators are voltage deviation and harmonic distortion rate, then we need to precisely filter out the data related to voltage deviation and harmonic distortion rate from all the collected voltage, current, and other electrical energy data. This data may contain measurements from different time points, forming a data sequence.

[0056] The extracted data is analyzed to observe its trends over time. For example, for voltage deviation data, it is analyzed whether it continuously increases, fluctuates, or gradually decreases. For harmonic distortion rate data, it is examined whether the harmonic content suddenly increases within a certain period or whether there are periodic changes. By analyzing these changes, a deeper understanding of the dynamic characteristics of abnormal indicators can be obtained. Based on the changing characteristics of abnormal data, different types of abnormal situations can be classified. This allows for the development of appropriate equipment management methods and power quality management solutions, which can more effectively solve power quality problems in the power system and improve the stability and reliability of the power system.

[0057] Optionally, when using power quality conditioning equipment for pollution control, a dynamic priority coefficient can be introduced. Achieve precise governance. For binary variables (0 or 1), when The condition indicates that the indicator needs to be addressed; otherwise, it is skipped. The indicators with the largest weights can be selected for addressing by ranking the weighted results of the poorer regions in the evaluation. ωi represents the weight of each indicator. If the weight ωi of an unaddressed indicator is automatically reset to 0, the weights of the electricity indicators requiring addressing are renormalized proportionally. To improve the operating efficiency of the UPQC and prevent excessive losses, a dynamic control module matrix is ​​constructed based on a topological division of labor: series-side voltage control and parallel-side current control. If harmonic issues require mitigation, γ1=1. For voltage-level harmonics, a PR controller is used to set a resonant peak at a fixed subharmonic frequency. Weighted current feedback via an LCL filter achieves THD_u≤3%, solving the static error problem of traditional PI controllers. For current-level harmonics, harmonic current commands are obtained based on pq transformation. The FCS-MPC algorithm selects the optimal switching state, reducing THDi from 6% to 4.8% within 8ms, and stabilizing the switching frequency at 10kHz.

[0058] If a voltage flicker problem exists and needs to be addressed, then γ2=1 is set, and after detecting the voltage fluctuation frequency, an inverse fluctuation signal is injected to reduce Pst from the detected value to below 0.8.

[0059] If voltage fluctuations exist, let γ3 = 1. Calculate the required compensation value based on the data collected within the system to compensate for the voltage fluctuations. Utilizing the fast response of the series side, a phase-locked loop (PLL) locks the fundamental phase of the power grid. A compensation voltage command Us = ΔU is generated through feedforward control. Finite set model predictive control (FCS-MPC) is used to restore the voltage to within the specified range within 5ms, while limiting the compensation amount to ≤20%UN to prevent further problems and provide a margin.

[0060] If the voltage over-limit problem in the system is severe and this indicator has a large weight in the evaluation, then γ4=1. Similar to the method used to manage voltage fluctuations, the phase-locked loop (PLL) locks the fundamental phase of the power grid. Whether the over-limit is in the forward or reverse direction, a compensation voltage command Us=ΔU is generated through feedforward control. Finite set model predictive control (FCS-MPC) is used to restore the voltage to above 90%UN within 5ms, while limiting the compensation amount to ≤20%UN to prevent the over-limit from recurring.

[0061] If a three-phase imbalance problem exists and needs to be addressed, then γ5=1. If the three-phase imbalance is at the voltage level, the negative sequence voltage component is extracted as the setpoint for the PR controller, and a reverse negative sequence voltage is injected to reduce εU to ≤2%, forming a superimposed control with the sag compensation module. If the three-phase imbalance is at the current level, the negative sequence component of the load current is decomposed, and the parallel converter is controlled to inject an equal amount of reverse current, reducing ε_I from the unbalanced state within the system to within 1%.

[0062] If power supply reliability needs to be improved, the reactive power compensation module, when γ6=1, calculates the reactive power deficit Q=P(tanφ_load-tan0.99), and outputs the reactive current command through the current loop PI controller, dynamically responding to the load power factor increase from 0.85 to 0.99.

[0063] The beneficial effects of this invention compared to existing technologies are as follows: It acquires power index data of target indicators collected in the power system and a standard database containing any target indicator; extracts reference data for the corresponding power index data from the standard database; calculates the deviation between the power index data and the reference data; identifies abnormal indicators based on the deviation; determines the equipment management method for handling abnormal indicators based on the number of abnormal indicators (either collaborative management or comprehensive management); extracts abnormal data changes corresponding to the abnormal indicators from the power index data; determines the anomaly type based on the abnormal data changes; and determines the power system's power quality management plan based on the anomaly type. This allows for a comprehensive analysis of power quality problems, thereby achieving collaborative control of management equipment to complete comprehensive power quality management.

[0064] like Figure 3 The diagram shown is a flowchart of a power quality management method according to Embodiment 3 of the present invention. Step S204, which involves extracting abnormal data changes corresponding to the abnormal indicators from the power index data, determining the abnormality type based on the abnormal data changes, and determining a power quality management scheme for the power system based on the abnormality type and the equipment management method, may include the following steps:

[0065] Step S301: If the number of abnormal indicators is one, then extract the abnormal time corresponding to the abnormal indicator and the voltage change data corresponding to the abnormal time from the power index data.

[0066] Step S302: Obtain preset voltage change rate threshold, voltage change amount threshold, first time scale threshold, second time scale threshold, and third time scale threshold.

[0067] Step S303: If the voltage change data is greater than the voltage change rate threshold and greater than the voltage change amount threshold, then determine whether the abnormal time is less than the first time scale threshold.

[0068] Step S304: If the abnormal time is less than the first time scale threshold, then the abnormal type is a transient mutation type, and the power quality regulation equipment is invoked to complete the treatment.

[0069] Optionally, if the voltage change data is less than the voltage change rate threshold and greater than the voltage change amount threshold, then it is determined whether the abnormal time is greater than the first time scale and less than the second time scale threshold.

[0070] If the abnormal time is greater than the first time scale and less than the second time scale threshold, then the abnormal type is a transient slow change type, and the power quality conditioning equipment is invoked in conjunction with the voltage regulation equipment to complete power quality management.

[0071] The number of abnormal indicators is only one, which means that the current approach only addresses abnormal situations of a single power indicator.

[0072] From all collected electrical energy index data, the abnormal time corresponding to the abnormal index, as well as the voltage change data within that abnormal time, are precisely extracted. The abnormal time can be understood as the period from the start to the end of the abnormal index occurrence, while the voltage change data reflects the specific changes in voltage during this abnormal time, such as whether the voltage increased or decreased, and the magnitude of the change.

[0073] A series of preset thresholds are obtained, including a voltage change rate threshold, a voltage change amount threshold, a first time scale threshold, a second time scale threshold, and a third time scale threshold. These thresholds are pre-set based on the characteristics and operational requirements of the power system and are used as standards for subsequent anomaly type determination. Assuming the voltage change rate threshold is set to 0.5%, the voltage change amount threshold to 5%, and the first time scale threshold to 10ms, the extracted voltage change data is compared with both the voltage change rate threshold and the voltage change amount threshold. If the voltage change data is greater than both the voltage change rate threshold and the voltage change amount threshold, it indicates that the voltage not only changes significantly (change amount greater than 5%) within the abnormal time period but also changes rapidly (change rate greater than 0.5%). After meeting the above conditions, it is further determined whether the abnormal time is less than the first time scale threshold.

[0074] If the anomaly time is less than the first time scale threshold (e.g., less than 10ms), combined with the previous cases where both the voltage change rate and the amount of change are large, the anomaly type can be identified as a transient change. A transient change means that the voltage changes drastically within a very short period of time, which can cause serious impacts on electrical equipment.

[0075] For anomalies involving transient changes, power quality control equipment (such as UPQC) is invoked to mitigate the problem. In such cases, the equipment must be able to respond quickly and compensate for voltage fluctuations promptly. Simultaneously, to prevent malfunctions of voltage regulators (such as OLTC) under such rapidly changing conditions, the OLTC is locked in place to ensure system stability.

[0076] If the voltage change data is less than the voltage change rate threshold but greater than the voltage change amount threshold, it indicates that although the voltage change amplitude is large (change amount greater than 5%), the change rate is relatively slow (change rate less than 0.5%). In this case, it is further determined whether the abnormal time is greater than the first time scale but less than the second time scale threshold.

[0077] If the abnormal time meets this condition, the anomaly type can be identified as a transient, gradually changing anomaly. A transient, gradually changing anomaly indicates that the voltage has gradually changed significantly over a period of time. Although this change is not as drastic as a transient abrupt change, it can still affect the stability of the power system and the normal operation of equipment. For transient, gradually changing anomalies, power quality control equipment (such as UPQC) is invoked for fine-tuning to gradually restore the voltage to the normal range. Voltage regulation equipment (such as OLTC) observes the changes; if the UPQC's adjustment effect is unsatisfactory, the OLTC can intervene at any time to collaboratively improve power quality.

[0078] In this embodiment, by accurately determining the type of anomaly based on factors such as the amplitude, speed, and time of voltage changes, and by selecting appropriate equipment management methods accordingly, the efficiency and accuracy of power quality regulation are improved.

[0079] like Figure 4 The diagram shown is a flowchart of a power quality management method according to Embodiment 4 of the present invention. Step S204, which involves extracting abnormal data changes corresponding to the abnormal indicators from the power index data, determining the abnormality type based on the abnormal data changes, and determining the power quality management scheme for the power system based on the abnormality type and the equipment management method, may include the following steps:

[0080] Step S401: Based on the voltage regulating device, determine the device action signal. If the voltage change data and the device action signal meet the preset index conditions, determine whether the abnormal time is between the first time scale threshold and the second time scale threshold.

[0081] Step S402: If the abnormal time is between the first time scale threshold and the second time scale threshold, then the abnormal type is the transitional fluctuation type, and the power quality conditioning equipment is invoked in conjunction with the voltage regulation equipment to complete the power quality management.

[0082] In power systems, voltage regulating devices such as OLTCs (On-Load Tap Changers) play a role in regulating voltage. When a deviation occurs in the system voltage, the voltage regulating device will issue an action signal according to a preset control strategy to adjust the tap position of the transformer, thereby changing the output voltage. Whether the voltage regulating device has issued an action signal is determined based on its operating status and control logic. For example, its action command information can be obtained by monitoring the control circuit or communication interface of the voltage regulating device.

[0083] The preset indicator conditions here are set according to the operating requirements of the power system and power quality standards, including conditions such as voltage jumps and OLTC issuing action signals. The previously extracted voltage change data is analyzed to determine whether voltage jumps have occurred, such as a sudden increase or decrease in voltage within a short period. The voltage change data and equipment action signals are comprehensively considered to determine whether the preset indicator conditions are simultaneously met. The first and second time scale thresholds are pre-set time limits, corresponding to the time range of transitional fluctuations (e.g., 10ms - 2s).

[0084] Under the condition that the preset index is met, it is further determined whether the abnormal time falls between these two time thresholds. If the abnormal time is within this range, it indicates that the voltage change and equipment operation conform to the time characteristics of transitional fluctuations. When the abnormal time is between the first and second time scale thresholds and meets the preset index conditions, the abnormality type can be identified as a transitional fluctuation type. Transitional fluctuations mean that the voltage jumps within a certain period of time, and the voltage regulating equipment also begins to adjust the voltage. For anomalies of the transitional fluctuation type, power quality conditioning equipment (such as UPQC) is called in conjunction with voltage regulating equipment (such as OLTC) to complete power quality management. When OLTC operates, its regulation process may cause further voltage fluctuations or jumps. At this time, UPQC needs to play a role in real-time monitoring and compensation of the voltage to prevent voltage jumps from damaging power equipment. UPQC can quickly respond to voltage changes and stabilize the system voltage by injecting appropriate voltage or current. OLTC then adjusts the taps according to its control strategy to achieve long-term stable voltage regulation. The two work together to achieve better power quality management results.

[0085] This application can accurately identify anomalies of transitional fluctuation types and take effective collaborative governance measures to ensure the stable operation of the power system and power quality.

[0086] like Figure 5The diagram shown is a flowchart of a power quality management method according to Embodiment 5 of this application. Step S204, which involves extracting abnormal data changes corresponding to the abnormal indicators from the power index data, determining the abnormality type based on the abnormal data changes, and determining the power quality management scheme of the power system based on the abnormality type and the equipment management method, may include the following steps:

[0087] Step S501: If the voltage change data meets the preset change index conditions, then determine whether the abnormal time is between the second time scale threshold and the third time scale threshold.

[0088] Step S502: If the abnormal time is between the second time scale threshold and the third time scale threshold, then the abnormal type is a steady-state offset type, and the power quality conditioning equipment is invoked in conjunction with the voltage regulation equipment to complete the power quality management.

[0089] The preset change index condition refers to a relatively large voltage change amplitude, while the voltage change rate is less than 0.5%. Here, "relatively large change" corresponds to the previously mentioned amplitude requirement of a change amount greater than 5%, and the specific value will be set according to the actual situation and standards of the power system.

[0090] A detailed analysis was performed on the previously extracted voltage change data, calculating its rate of change and magnitude of change. The results were then compared with preset change index conditions. If the voltage change data met the condition of a large magnitude of change and a rate of change of less than 0.5%,

[0091] The second and third time scale thresholds are pre-defined time intervals; the second time scale threshold is 2 seconds, and the third time scale threshold is 10 seconds. When voltage change data meets the change index conditions, it is determined whether the abnormal time falls between these two thresholds. If the abnormal time is within this interval, it is likely a steady-state offset anomaly.

[0092] When the abnormal time falls between the second and third time scale thresholds, and the voltage change data meets the preset change index conditions, the anomaly type can be identified as a steady-state offset. A steady-state offset indicates that the voltage remains deviated from the normal level for a relatively long period. Although the rate of change is slow, long-term offsets may adversely affect the operating efficiency and lifespan of power equipment.

[0093] For anomalies of steady-state deviation type, power quality conditioning equipment (such as UPQC) combined with voltage regulating equipment (such as OLTC) is used to manage power quality. OLTC (On-Load Tap Changer) can change the voltage ratio by adjusting the transformer taps, thereby achieving long-term stable voltage regulation. Since steady-state deviation is a long-term process, OLTC can gradually adjust the voltage to restore it to the normal range, thus playing a leading role in the management process. UPQC (Unified Power Quality Conditioner) has the ability to respond quickly and compensate precisely. During OLTC voltage regulation, UPQC can monitor voltage changes in real time and quickly compensate for any small fluctuations or instantaneous deviations, assisting OLTC in better achieving stable voltage regulation and ensuring that power quality meets requirements.

[0094] In this embodiment, by judging voltage change data and abnormal time, anomalies of steady-state deviation type are accurately identified, and a reasonable equipment collaborative management scheme is formulated, which helps to ensure the stable operation of the power system and good power quality.

[0095] Optionally, based on the type of disturbance, the most suitable equipment can be matched. When a transient change occurs, UPQC uses millisecond-level response speed to quickly compensate the voltage. When the transient change is gradual, UPQC is used for fine-tuning compensation to avoid excessive action. When a tap change causes a transitional fluctuation, UPQC is activated to suppress voltage jumps caused by switching.

[0096] When a steady-state deviation occurs in the system, the OLTC will activate to gradually eliminate the long-term deviation. In addition, if the steady-state deviation in the system exceeds the UPQC capacity, the OLTC will activate directly to avoid UPQC overload.

[0097] In actual power grid operation, voltage transient fluctuations pose a greater threat to the normal operation of the grid than steady-state fluctuations, and it is essential to prevent damage to sensitive loads. Furthermore, frequent operation of OLTCs (Optical Voltage Control Units) during voltage regulation can damage transformer structures, leading to increased costs. Therefore, the operational costs of OLTCs must be considered when building the model, and the number of mechanical operations must be limited. Finally, considering the installed UPQC (Upload Power Control Unit) capacity, prolonged heavy overload should be avoided during regulation to extend the equipment's lifespan.

[0098] The mathematical model of the objective function is

[0099]

[0100] in,

[0101]

[0102] For transient scenarios, k is the number of transient sampling steps, used to distinguish different transient stages. One step is equal to 1ms. UL(k) is the instantaneous voltage on the load side in step k, in pu. Uref is the rated value of the target voltage, denoted as 1pu. Wk is the emergency weight of step k, which is 3.0 when K is less than or equal to 10 and 1.5 when K is greater than 10.

[0103]

[0104] For steady-state scenarios, i is the steady-state sampling step number, used to distinguish different stages of steady-state, one step equals 10s; UL(k) is the average voltage on the load side in the kth step (10s), in pu; Uref is the rated value of the target voltage, the same as the transient target, denoted as 1pu.

[0105]

[0106] Whether a penalty is imposed depends on whether the voltage change rate exceeds a threshold. Tf is the fluctuation time, t is the instantaneous time of the fluctuation time, U(t) is the voltage change rate at time t, and Umax is the maximum allowable change rate. Exceeding this value will cause the equipment in the power supply area to exceed its tolerance limit. U(t) is the voltage change rate at time t. Finally, there is an index function. If it exceeds the threshold, it takes a value of 1, triggering a penalty. If it does not exceed the threshold, it takes a value of 0, and no penalty is triggered.

[0107] Regarding the operational costs of OLTC, there are

[0108]

[0109] is the action indication for the i-th step OLTC, 1 when there is an action and 0 when there is no action. CO is the cost of a single action, usually 200. T(i) is the time interval between the last action and the previous action. If the specified interval between two actions is not met, a penalty is triggered. The output value of max is the calculated value. If the action interval is met, no penalty is imposed and the output value of max is 0. Ci is the penalty cost for each 1 second reduction.

[0110] Regarding the capacity constraints of the installed UPQC, there are

[0111]

[0112] Uupqc(k) is the transient compensation capacity of UPQC at step k, Uupqc,max is the maximum compensation capacity of UPQC, and Uupqc(i) is the steady-state average compensation capacity of UPQC at step i.

[0113] Based on the output of the objective function, when the standard value of a certain system and the maximum allowable deviation of the national standard are substituted into the system to obtain the value JN, and compared with the adjusted output value J, if J>JN, the magnitude of various indicators is considered to carry out further precise control.

[0114] when If the transient voltage is too high, it indicates that the transient voltage management is insufficient. In this case, the transient compensation coefficient of UPQC can be increased to enhance the compensation capability of UPQC; the priority of transient compensation should be strengthened by increasing the weight when k is less than 10.

[0115] when If the voltage fluctuation suppression is insufficient, the OLTC warning time should be increased and the UPQC non-compensation time extended.

[0116] when If this indicates that the OLTC is acting frequently, the trigger threshold of the OLTC should be increased, and the penalty coefficient for the action interval should be increased.

[0117] when When this occurs, it indicates that the UPQC is in steady-state overload, and the steady-state compensation penalty factor will be increased.

[0118] The execution logic of UPQC and OLTC coordinated control is to use the voltage change rate to classify 'fast / slow' disturbances, use the voltage change quantity to quantify 'large / small' deviations, then let 'fast equipment control fast, slow equipment control slow, and the two cooperate to control the transition', and finally use feedback closed loop to ensure accuracy. All links are based on two core indicators to achieve a synergistic effect of "clear division of labor, orderly cooperation, safety and efficiency".

[0119] In actual operation, the specific values ​​were 0.877 pu before voltage compensation and 0.980 pu after compensation; the unbalance was 3.675% before compensation and 0.018% after compensation; and the THD was 17.43% before compensation and 2.839% after compensation.

[0120] After compensation, the voltage deviation, three-phase imbalance, and harmonic distortion rate all decreased significantly from very high values ​​(17~18%) to about 3~4%, indicating that the compensation effect was significant.

[0121] In practice, the performance indicators for the pollution control included imbalance (three-phase voltage or current imbalance), stability (stability of system voltage or frequency), harmonic distortion, voltage quality, and power factor. All indicators were normalized to a range of 0 to 1, with higher values ​​indicating better performance. Before the pollution control, the harmonic distortion indicators were poor (close to 0). After the pollution control, all five indicators showed significant improvement compared to before, with the harmonic distortion indicators increasing by nearly 60%.

[0122] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0123] Corresponding to the methods in the above embodiments, such as Figure 6 The diagram shown is a schematic of a power quality management device provided in Embodiment 6 of the present invention. The power quality management and authentication device is applied to a quantum communication system. The quantum communication system includes a digital certificate authentication center, a quantum key distribution device, and a quantum key management device. The digital certificate authentication center is connected to the quantum key distribution device and the quantum key management device.

[0124] The power quality management device includes:

[0125] Data acquisition module 61 is used to acquire power index data of target index items collected in the power system and a standard database containing any of the target index items;

[0126] Deviation calculation module 62 is used to extract reference data corresponding to the power index data in the standard database and calculate the deviation value between the power index data and the reference data.

[0127] Anomaly handling module 63 is used to determine anomaly indicators based on the deviation value, and to determine the equipment management method for handling the anomaly indicators based on the number of anomaly indicators, wherein the equipment management method is collaborative management or comprehensive management.

[0128] The scheme determination module 64 is used to extract abnormal data changes corresponding to the abnormal indicators in the power index data, determine the abnormal type based on the abnormal data changes, and determine the power quality management scheme of the power system based on the abnormal type and the equipment management method.

[0129] Optionally, the exception handling module 63 includes:

[0130] The deviation analysis unit is used to analyze the deviation value. If the deviation value is not within the preset standard range, the target indicator item corresponding to the deviation value is determined to be an abnormal indicator.

[0131] The collaborative governance unit is used to determine that the equipment governance method is collaborative governance if the number of abnormal indicators is one. The collaborative governance is to call preset power quality conditioning equipment and voltage regulation equipment to complete power quality governance.

[0132] Optionally, the scheme determination module 64 includes:

[0133] If the number of abnormal indicators is one, then extract the abnormal time corresponding to the abnormal indicator and the voltage change data corresponding to the abnormal time from the power index data.

[0134] The threshold acquisition unit is used to acquire preset voltage change rate threshold, voltage change amount threshold, first time scale threshold, second time scale threshold and third time scale threshold;

[0135] The first judgment unit is used to determine whether the abnormal time is less than the first time scale threshold if the voltage change data is greater than the voltage change rate threshold and greater than the voltage change amount threshold.

[0136] The transient mutation unit is used to invoke the power quality regulation equipment to complete the treatment if the abnormal time is less than the first time scale threshold, and the abnormal type is a transient mutation type.

[0137] Optionally, the scheme determination module 64 includes:

[0138] The second judgment unit is used to determine whether the abnormal time is greater than the first time scale and less than the second time scale threshold if the voltage change data is less than the voltage change rate threshold and greater than the voltage change amount threshold.

[0139] The transient slow change unit is used to call the power quality conditioning equipment in conjunction with the voltage regulation equipment to complete power quality management if the abnormal time is greater than the first time scale and less than the second time scale threshold, and the abnormal type is a transient slow change type.

[0140] Optionally, the scheme determination module 64 includes:

[0141] The third judgment unit is used to determine the device action signal based on the voltage regulating device. If the voltage change data and the device action signal meet the preset index conditions, then it is determined whether the abnormal time is between the first time scale threshold and the second time scale threshold.

[0142] The transition fluctuation unit is used to call the power quality conditioning equipment in conjunction with the voltage regulation equipment to complete power quality management if the abnormal time is between the first time scale threshold and the second time scale threshold, and the abnormal type is the transition fluctuation type.

[0143] Optionally, the scheme determination module 64 includes:

[0144] The fourth judgment unit is used to determine whether the abnormal time is between the second time scale threshold and the third time scale threshold if the voltage change data meets the preset change index conditions.

[0145] The steady-state offset unit is used to call the power quality conditioning equipment in conjunction with the voltage regulating equipment to complete power quality management if the abnormal time is between the second time scale threshold and the third time scale threshold, and the abnormal type is the steady-state offset type.

[0146] Optionally, the exception handling module 63 includes:

[0147] The sorting unit is used to sort the abnormal indicators in descending order according to the deviation value if the number of abnormal indicators is at least two, and to obtain the sorting result. Based on the sorting result, the treatment items for the abnormal indicators are determined.

[0148] The governance unit is used to invoke the equipment governance mode of the comprehensive governance to complete the power quality governance of the governance item. The comprehensive governance is to invoke the power quality regulating equipment to complete the power quality governance.

[0149] The classification and management unit is used to determine the comprehensive problem type based on the abnormal data changes, and for any comprehensive problem type, to call the corresponding problem management solution of the power quality conditioning equipment to complete the power quality management solution.

[0150] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of the present invention. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0151] like Figure 7 This is a schematic diagram of the structure of a computer device provided in Embodiment 7 of the present invention. The computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the power quality management method described in the above embodiments.

[0152] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the power quality management method described above.

[0153] The computer-readable storage medium may be non-volatile or volatile. 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. This computer program may be stored in a non-volatile computer-readable storage medium, and when executed, it may include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0154] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0155] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for improving power quality, characterized in that, include: Acquire the power index data of the target index items collected in the power system and a standard database containing any of the target index items; Extract reference data corresponding to the electrical energy index data from the standard database, and calculate the deviation value between the electrical energy index data and the reference data; Based on the deviation value, abnormal indicators are determined, and based on the number of abnormal indicators, the equipment management method for handling the abnormal indicators is determined, wherein the equipment management method is collaborative management or comprehensive management. Extract the abnormal data changes corresponding to the abnormal indicators from the power index data, determine the abnormal type based on the abnormal data changes, and determine the power quality management plan for the power system based on the abnormal type and the equipment management method.

2. The power quality management method according to claim 1, characterized in that, The step of determining abnormal indicators based on the deviation value and determining the equipment management method for handling the abnormal indicators based on the number of abnormal indicators includes: If the deviation value is not within the preset standard range, the target indicator item corresponding to the deviation value is determined to be an abnormal indicator. If the number of abnormal indicators is only one, then the equipment management method is determined to be collaborative management, which involves calling preset power quality conditioning equipment and voltage regulation equipment to complete power quality management.

3. The power quality management method according to claim 2, characterized in that, The process of extracting abnormal data changes corresponding to the abnormal indicators from the power index data, determining the anomaly type based on the abnormal data changes, and determining a power quality management plan for the power system based on the anomaly type and the equipment management method includes: If the number of abnormal indicators is one, then extract the abnormal time corresponding to the abnormal indicator and the voltage change data corresponding to the abnormal time from the power index data. Obtain the preset voltage change rate threshold, voltage change amount threshold, first time scale threshold, second time scale threshold, and third time scale threshold; If the voltage change data is greater than the voltage change rate threshold and greater than the voltage change amount threshold, then it is determined whether the abnormal time is less than the first time scale threshold. If the abnormal time is less than the first time scale threshold, then the abnormal type is a transient mutation type, and the power quality regulation equipment is invoked to complete the treatment.

4. The power quality management method according to claim 3, characterized in that, The process of extracting abnormal data changes corresponding to the abnormal indicators from the power index data, determining the anomaly type based on the abnormal data changes, and determining a power quality management plan for the power system based on the anomaly type and the equipment management method includes: If the voltage change data is less than the voltage change rate threshold and greater than the voltage change amount threshold, then it is determined whether the abnormal time is greater than the first time scale and less than the second time scale threshold. If the abnormal time is greater than the first time scale and less than the second time scale threshold, then the abnormal type is a transient slow change type, and the power quality conditioning equipment is invoked in conjunction with the voltage regulation equipment to complete power quality management.

5. The power quality management method according to claim 3, characterized in that, The process of extracting abnormal data changes corresponding to the abnormal indicators from the power index data, determining the anomaly type based on the abnormal data changes, and determining a power quality management plan for the power system based on the anomaly type and the equipment management method includes: Based on the voltage regulating device, determine the device action signal. If the voltage change data and the device action signal meet the preset index conditions, determine whether the abnormal time is between the first time scale threshold and the second time scale threshold. If the abnormal time is between the first time scale threshold and the second time scale threshold, then the abnormal type is a transitional fluctuation type, and the power quality conditioning equipment is invoked in conjunction with the voltage regulation equipment to complete power quality management.

6. The power quality management method according to claim 3, characterized in that, The process of extracting abnormal data changes corresponding to the abnormal indicators from the power index data, determining the anomaly type based on the abnormal data changes, and determining a power quality management plan for the power system based on the anomaly type and the equipment management method includes: If the voltage change data meets the preset change index conditions, then it is determined whether the abnormal time is between the second time scale threshold and the third time scale threshold. If the abnormal time is between the second time scale threshold and the third time scale threshold, then the abnormal type is a steady-state offset type, and the power quality conditioning equipment is invoked in conjunction with the voltage regulation equipment to complete power quality management.

7. The power quality management method according to claim 2, characterized in that, The step of determining abnormal indicators based on the deviation value and determining the equipment management method for handling the abnormal indicators based on the number of abnormal indicators includes: If the number of abnormal indicators is at least two, then the abnormal indicators are sorted in descending order according to the deviation value to obtain the sorting result, and the treatment items for the abnormal indicators are determined according to the sorting result. The comprehensive management equipment management method is invoked to complete the power quality management of the management item. The comprehensive management refers to invoking the power quality conditioning equipment to complete the power quality management. The process of extracting abnormal data changes corresponding to the abnormal indicators from the power index data, determining the anomaly type based on the abnormal data changes, and determining a power quality management plan for the power system based on the anomaly type and the equipment management method includes: Based on the abnormal data changes, the comprehensive problem type is determined. For any comprehensive problem type, the corresponding problem management solution of the power quality conditioning equipment is invoked to complete the power quality management solution.

8. A power quality management device, characterized in that, include: The data acquisition module is used to acquire the power index data of the target index items collected in the power system and a standard database containing any of the target index items. The deviation calculation module is used to extract reference data corresponding to the electrical energy index data in the standard database and calculate the deviation value between the electrical energy index data and the reference data. An anomaly handling module is used to determine anomaly indicators based on the deviation value, and to determine the equipment management method for handling the anomaly indicators based on the number of anomaly indicators, wherein the equipment management method is collaborative management or comprehensive management. The scheme determination module is used to extract abnormal data changes corresponding to the abnormal indicators in the power index data, determine the abnormal type based on the abnormal data changes, and determine the power quality management scheme of the power system based on the abnormal type and the equipment management method.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the power quality management method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the power quality management method according to any one of claims 1 to 7.

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