Intelligent management system of voltage monitoring operation and maintenance platform

Abstract

The invention discloses an intelligent management system of a voltage monitoring operation and maintenance platform, relates to the technical field of voltage monitoring management, and is used for solving the problems that the influence of an event on voltage cannot be quickly responded, and the monitoring risk and the maintenance time are increased. Acquiring a phase deviation and a voltage amplitude unbalance degree; setting a phase deviation threshold value; detecting an actual phase deviation and comparing the actual phase deviation with the threshold value; analyzing a voltage unbalance state coefficient; and substituting logistic regression to determine a voltage fluctuation result, merging a voltage unbalance state coefficient into a voltage fluctuation data set, taking a ratio of a current voltage fluctuation value to an average value as an adjustment coefficient, taking a product of the adjustment coefficient and an initial threshold value as an initial threshold value of next system operation, supporting long-time operation and continuous optimization, and reducing excessive sensitivity of monitoring.

Description

Technical Field

[0001] The present invention relates to the technical field of voltage monitoring management, and more specifically, to an intelligent management system for a voltage monitoring operation and maintenance platform. Background Art

[0002] With the expansion of the scale of power systems and the improvement of their intelligence levels, there is an increasing demand for real-time monitoring of voltage quality and operation and maintenance efficiency. Voltage monitoring involves many aspects, such as high voltage, low voltage, voltage fluctuation, instantaneous voltage fluctuation, instantaneous voltage rise, voltage imbalance, voltage harmonic distortion, and voltage interruption. Therefore, when designing a management system, it is necessary to determine in which direction to monitor. The existing technology already has relatively mature monitoring methods for monitoring high and low voltages and instantaneous voltage rises and falls.

[0003] The prior art has the following deficiencies:

[0004] At present, regarding monitoring whether there is voltage fluctuation, when an emergency occurs, the existing judgment of fluctuation is still based on voltage parameters and the length of time introduced to determine the possibility of fluctuation and the impact of the emergency on the voltage. However, this cannot quickly respond to the impact of the event on the voltage, reduces the probability of accurately distinguishing the voltage state, and increases the monitoring risk and maintenance time. Therefore, an intelligent management system for the voltage monitoring operation and maintenance platform is proposed.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an intelligent management system for a voltage monitoring and operation and maintenance platform, which solves the problems raised in the above-mentioned background technology by using different product inspection methods.

[0007] To achieve the above object, the present invention provides the following technical solution: an intelligent management system for a voltage monitoring and operation and maintenance platform, comprising an event collection module, an imbalance analysis module, a determination monitoring module and a cyclic update module; signal connections between the modules;

[0008] The event collection module is used to collect characteristic information of user equipment, obtain the user equipment strobe and user equipment operation delay through data processing, and perform weighted calculation to obtain the event burst coefficient, and compare it with the preset initial threshold to determine the impact degree of the event, send the event impact degree to the determination monitoring module, and send the initial threshold to the cyclic update module;

[0009] The imbalance analysis module is used to collect phase deviation and voltage amplitude imbalance, determine the phase deviation threshold, detect the actual phase deviation amplitude, compare it with the phase deviation threshold, analyze the voltage imbalance state coefficient, and send it to the determination monitoring module;

[0010] Determine the monitoring module for obtaining the event impact degree and the voltage imbalance state coefficient, perform normalization processing, and substitute it into the logistic regression model to obtain the voltage monitoring coefficient, compare it with the monitoring threshold, determine the voltage fluctuation result, and send it to the cyclic update module;

[0011] The cyclic update module is used to obtain the voltage fluctuation results and the initial threshold, determine the voltage monitoring coefficients corresponding to different tags and their assignments, mark the voltage monitoring coefficients as voltage fluctuation values, and put them into a preset voltage fluctuation data set, calculate the average value of the voltage fluctuation data set, calculate the ratio of the current voltage fluctuation value to the average value of the voltage fluctuation data set, and obtain the adjustment coefficient. The product of the adjustment coefficient and the obtained initial threshold is used as the initial threshold for the next system operation and is sent to the event acquisition module.

[0012] In a preferred embodiment, the user equipment characteristic information includes the user equipment flicker and the user equipment operation delay; the user equipment flicker is calculated by a standard measuring device to quantify the flicker degree, and the user equipment flicker is obtained. ; Where i is the i-th sampling number;

[0013] The precise time when the trigger signal is sent is recorded through a high-precision timing tool. The signal change after the device performs the action is detected through the sensor or device output interface, and the time when the response signal is detected is recorded. The user device operation delay is obtained by subtracting the trigger signal sending time from the response signal receiving time. .

[0014] In a preferred embodiment, the user equipment flash and the user equipment operation delay are weighted to obtain the event burst coefficient. ;

[0015] Compare the event suddenness coefficient with the preset initial threshold to obtain the comparison result, and determine the impact of the event based on the comparison result; specifically:

[0016] If the event suddenness coefficient is greater than or equal to the initial threshold, it indicates that the current event is a sudden event, and the current event suddenness coefficient is marked as the event impact degree; if the event suddenness coefficient is less than the initial threshold, it indicates that the current event is a common event, and the current event suddenness coefficient is screened out.

[0017] In a preferred embodiment, corresponding phase information is extracted from the frequency domain representation of adjacent signals by Fourier transform, and the phases of adjacent signals are subtracted to obtain phase deviation;

[0018] The voltage amplitude imbalance is obtained by obtaining the maximum amplitude of the three-phase voltage and the minimum amplitude of the three-phase voltage, calculating the subtraction value of the maximum and minimum voltage amplitudes, and performing ratio calculation with the average amplitude of the three-phase voltage.

[0019] In a preferred embodiment, the phase deviation threshold is calculated by the maximum value of the phase deviation and the voltage amplitude imbalance, and the actual phase deviation amplitude is detected. ;

[0020] The actual phase deviation amplitude is compared with the calculated phase deviation threshold, specifically:

[0021] If the actual phase deviation amplitude is greater than or equal to the phase deviation threshold, it means that the current voltage is in an unbalanced state, and the actual phase deviation amplitude is marked as the voltage unbalanced state coefficient. If the actual phase deviation amplitude is less than the phase deviation threshold, it means that the current voltage is in a balanced state, and the actual phase deviation amplitude is screened out.

[0022] In a preferred embodiment, the event impact degree and the voltage imbalance state coefficient are normalized, and the event impact degree and the voltage imbalance state coefficient are substituted into the logistic regression calculation specific formula as follows: ;

[0023] In the formula, is the result of logistic regression calculation, that is, the voltage monitoring coefficient, e is the natural base, and y is the linear combination term of the logistic regression model. Specifically, y can be set as: ;

[0024] In the formula, is the bias term, is the impact degree of the event sampled at the i-th time, is the voltage imbalance coefficient of the i-th sampling, and are the regression coefficients of the event impact degree and the voltage unbalance state coefficient respectively.

[0025] In a preferred embodiment, after the voltage monitoring coefficient is obtained, the voltage monitoring coefficient is compared and analyzed with the continuously iterated monitoring threshold value;

[0026] If the voltage monitoring coefficient is greater than or equal to the monitoring threshold, the current voltage is marked as a fluctuating voltage and a fluctuation signal is generated;

[0027] If the voltage monitoring coefficient is less than the monitoring threshold, the current voltage is marked as a stable voltage and an end signal is generated; based on the marking result, the voltage fluctuation result is determined.

[0028] In a preferred embodiment, the voltage fluctuation result includes the current voltage marked as the fluctuating voltage and the stable voltage, and the voltage monitoring coefficient is obtained and calibrated as the voltage fluctuation value; the voltage marked as the fluctuating voltage is substituted as a positive value into the preset voltage fluctuation data set, and the voltage marked as the stable voltage is substituted as a negative value into the preset voltage fluctuation data set; the voltage fluctuation value is obtained and substituted into the preset voltage fluctuation data set to obtain the voltage fluctuation data set.

[0029] In a preferred embodiment, the current voltage fluctuation value is calculated by ratio with the average value of the voltage fluctuation data set to obtain the adjustment coefficient;

[0030] The adjustment coefficient is multiplied by the initial threshold, and the product is used as the initial threshold for the next system operation. When the voltage fluctuation value is substituted into the preset voltage fluctuation data set during the next system operation, the ratio calculation of the current voltage fluctuation value and the average value of the voltage fluctuation data set is repeated to obtain a new adjustment coefficient.

[0031] Technical effects and advantages of the present invention:

[0032] 1. The present invention obtains user equipment flicker and user equipment operation delay by collecting user equipment characteristic information, and performs weighted calculation to obtain event burst coefficient, and compares it with a preset initial threshold to determine the degree of event impact, and collects phase deviation and voltage amplitude imbalance to determine the phase deviation threshold, detects the actual phase deviation amplitude, and compares it with the phase deviation threshold, analyzes the voltage imbalance state coefficient, and determines the voltage fluctuation result according to the event impact degree and the voltage imbalance state coefficient, thereby improving the monitoring accuracy and response capability of the power system, thereby improving the reliability of the power system, accelerating the efficiency of the system in monitoring emergencies, and reducing the maintenance time of the power system.

[0033] 2. The present invention obtains voltage fluctuation results and initial thresholds, determines voltage monitoring coefficients corresponding to different tags and their assignments, incorporates voltage fluctuation values ​​into a preset voltage fluctuation data set, calculates the average value of the voltage fluctuation data set, and obtains an adjustment coefficient by the ratio of the current voltage fluctuation value to the average value of the voltage fluctuation data set. The product of the adjustment coefficient and the obtained initial threshold is used as the initial threshold for the next system operation, and the system is maintained in a continuous loop calculation, supporting long-term operation and continuous optimization, reducing excessive sensitivity, and improving the system's adaptability and monitoring accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a module flow chart of an intelligent management system for a voltage monitoring and operation and maintenance platform of the present invention. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] Example 1

[0037] The present invention discloses an intelligent management system for a voltage monitoring and operation and maintenance platform, such as Figure 1 As shown, it includes an event acquisition module, an imbalance analysis module, a determination monitoring module and a cyclic update module; and signal connections between the modules;

[0038] The event collection module is used to collect characteristic information of user equipment, obtain the user equipment strobe and user equipment operation delay through data processing, and perform weighted calculation to obtain the event burst coefficient, and compare it with the preset initial threshold to determine the impact degree of the event, send the event impact degree to the determination monitoring module, and send the initial threshold to the cyclic update module;

[0039] Specifically, the user equipment characteristic information includes the user equipment flicker and the user equipment operation delay;

[0040] Among them, user device flicker refers to the rapid fluctuation of the brightness of user-side lighting equipment, which is usually manifested as periodic changes in light output. Its acquisition logic is to calculate the user device flicker through standard measurement equipment, thereby quantifying the degree of flicker and obtaining the user device flicker. ;

[0041] Specifically, the specific formula for calculating the flicker of the user equipment is expressed as follows: ;

[0042] In the formula, is the brightness change, is the average brightness, is the flicker perception coefficient, i.e., the flicker of the user equipment, where i is the i-th sampling sequence number and N is the total number of sampling points;

[0043] It should be noted that the numerical settings for the sampling interval and the total number of sampling points are set by the experimenter based on the historical user's strobe frequency and number of times, and will not be repeated here;

[0044] Specifically, the light intensity data of the user device in time series is obtained through a high-frequency sensor, the brightness change is calculated for each sampling point, and then the brightness of the entire sampling interval is averaged. According to the flicker perception coefficient formula, the ratio of the brightness change to the average brightness is combined to obtain the flicker of the user device;

[0045] The user equipment operation delay refers to the time difference between the user equipment receiving the external trigger signal and completing the response action. Its acquisition logic is to use a high-precision timing tool to record the precise time when the trigger signal is sent, detect the signal change after the device executes the action through the sensor or device output interface, and record the time when the response signal is detected. The user equipment operation delay is obtained by subtracting the trigger signal sending time from the response signal receiving time. ;

[0046] Specifically, the trigger signal includes but is not limited to a control instruction and a physical action request, wherein the selection of the trigger signal is not limited, but is set by the experimenter according to the user equipment requirements, and will not be elaborated here;

[0047] Among them, the high-precision timing tool refers to the tool used to record timestamps at the microsecond or nanosecond level to ensure accurate measurement of the time interval of events, especially for the application of parameters such as user equipment operation delay, which requires precise timing. The specific type of high-precision timing tool used is not limited, but is set by the experimenter based on the built-in tools of the specific system, and is not limited here;

[0048] The user equipment strobe and the user equipment operation delay are weighted to obtain the event burst coefficient. The specific formula is: ;

[0049] In the formula, is the event burst coefficient, as well as are preset proportional coefficients for the user equipment strobe and the user equipment operation delay, respectively, and, as well as All are greater than 0;

[0050] Compare the event suddenness coefficient with the preset initial threshold to obtain the comparison result, and determine the impact of the event based on the comparison result; specifically:

[0051] If the event suddenness coefficient is greater than or equal to the initial threshold, it indicates that the current event is a sudden event, and the current event suddenness coefficient is marked as the event impact degree; if the event suddenness coefficient is less than the initial threshold, it indicates that the current event is a common event, and the current event suddenness coefficient is screened out;

[0052] Specifically, screening refers to forgetting the sudden coefficient of the current event to clean the system database and avoid interference and pollution from invalid data;

[0053] Among them, the setting of the initial threshold is generally set by the experimenter based on the experimental results at the beginning of this round of calculation, that is, the initialization calculation (when running for the first time). In the subsequent verification, the initial threshold is continuously adjusted by multiplying the determined adjustment coefficient with the initial threshold, so that it has dynamic changes and adapts to the binary classification of the long-term event burst coefficient.

[0054] The imbalance analysis module is used to collect phase deviation and voltage amplitude imbalance, determine the phase deviation threshold, detect the actual phase deviation amplitude, compare it with the phase deviation threshold, analyze the voltage imbalance state coefficient, and send it to the determination monitoring module;

[0055] Phase deviation refers to the phase offset between two adjacent signals. It determines whether the phase is within a predetermined range. The acquisition logic is to extract the corresponding phase information from the frequency domain representation of adjacent signals through Fourier transform, and subtract the phases of adjacent signals to obtain the phase deviation.

[0056] Specifically, suppose that adjacent signals are A and B, and perform fast Fourier transform on signal A and signal B respectively to convert the signals from the time domain to the frequency domain. Perform Fourier transform on signal A and signal B to obtain their frequency domain representation. The specific formula is expressed as follows: ;

[0057] In the formula, is the frequency domain representation of the signal, is the amplitude spectrum of the signal, is the phase spectrum of the signal, is an imaginary unit;

[0058] Extract the phase information of the signal from the Fourier transform result. For each frequency component f, the phase of the signal and They can be obtained from and Extract, the specific extraction expression is: as well as ;

[0059] Calculate the phase difference between two signals at the same frequency to get the phase deviation. The specific formula is as follows: ;

[0060] Where R is the phase deviation;

[0061] Specifically, the present invention uses a three-phase voltage system as the voltage system monitored in the embodiment, wherein the three-phase voltage system is the most commonly used power distribution method in the power system, and is composed of three AC voltages with a phase difference of 120 degrees, usually represented as a three-phase power supply, that is, three phases A, B, and C. It can be seen that the above phase deviation includes the phase deviation between B and C;

[0062] Furthermore, in a typical three-phase system, the three voltage waveforms are 120 degrees out of phase with each other, corresponding to different current paths, and the amplitude (voltage magnitude) of each voltage waveform is usually equal, but their phases are different, allowing the system to provide continuous power flow at the same time;

[0063] It should be noted that this embodiment uses a three-phase voltage system as an application scenario. In fact, different voltage systems can be selected as the actual subject of voltage monitoring, which will not be described in detail here.

[0064] Voltage amplitude imbalance refers to the difference in the amplitude of the three-phase voltage. The acquisition logic is to obtain the maximum amplitude of the three-phase voltage and the minimum amplitude of the three-phase voltage, calculate the subtraction value of the maximum and minimum voltage amplitudes, and calculate the ratio with the average amplitude of the three-phase voltage to obtain the voltage amplitude imbalance;

[0065] Specifically, the calculation formula for voltage amplitude imbalance is: ;

[0066] In the formula, is the maximum amplitude of the three-phase voltage, is the minimum amplitude of the three-phase voltage, is the average amplitude of the three-phase voltage;

[0067] Furthermore, the phase deviation threshold is calculated by the maximum value of the phase deviation and the voltage amplitude imbalance, that is: ;

[0068] In the formula, is the phase deviation threshold;

[0069] Specifically, the specific calculation formula for detecting the actual phase deviation amplitude is: ;

[0070] In the formula, is the actual phase deviation amplitude, , , are the amplitudes of the three-phase voltages A, B, and C respectively;

[0071] The actual phase deviation amplitude is compared with the calculated phase deviation threshold, specifically:

[0072] If the actual phase deviation amplitude is greater than or equal to the phase deviation threshold, it means that the current voltage is in an unbalanced state, and the actual phase deviation amplitude is marked as the voltage unbalanced state coefficient. If the actual phase deviation amplitude is less than the phase deviation threshold, it means that the current voltage is in a balanced state, and the actual phase deviation amplitude is screened out;

[0073] The screening operation has been described above in relation to the sudden coefficient of the current event, and will not be described in detail here.

[0074] Determine the monitoring module for obtaining the event impact degree and the voltage imbalance state coefficient, perform normalization processing, and substitute it into the logistic regression model to obtain the voltage monitoring coefficient, compare it with the monitoring threshold, determine the voltage fluctuation result, and send it to the cyclic update module;

[0075] Specifically, according to the binary classification results of the above event acquisition module and imbalance analysis module, there are four results. One is that the comparison results are all greater than or equal to, and the event impact degree and the voltage imbalance state coefficient are obtained. The second is that any one of the comparison results is greater than or equal to, and the event impact degree or the voltage imbalance state coefficient is obtained, that is, there are two cases. In this case, only one parameter of the event impact degree or the voltage imbalance state coefficient is substituted as the voltage monitoring coefficient. The third is that the comparison results are all less than, then the system operation ends, returns to the start instruction state, and waits for the next system self-start;

[0076] It should be noted that when the comparison results are all less than , it means that the voltage remains stable and the equipment is running stably, so there is no need to perform subsequent operations and wait for the next system to start automatically. The specific frequency and start interval of the automatic start are set by the experimenter according to the specific voltage operation conditions and are not limited here;

[0077] The event impact degree and voltage imbalance state coefficient are normalized, and all input variables are converted to the same range to ensure that the contribution of each input to the model is balanced. Specifically, the normalization method is to normalize the [0,1] interval. The specific formula is: ;

[0078] In the formula, is the impact of the event, is the normalized impact of the event, is the minimum value of the event impact, is the maximum value of the impact of the event;

[0079] The voltage unbalance state coefficient is also normalized using the above formula, which will not be described in detail here.

[0080] After normalization, the values ​​of the event impact degree and the voltage unbalance state coefficient are both within the range of [0, 1]. The system can make comparisons and decisions on a unified scale, thereby improving the accuracy and efficiency of the logistic regression model.

[0081] Substituting the event impact degree and voltage imbalance state coefficient into the logistic regression calculation, the specific formula is expressed as follows: ;

[0082] In the formula, is the result of logistic regression calculation, that is, the voltage monitoring coefficient, e is the natural base, and y is the linear combination term of the logistic regression model. Specifically, y can be set as: ;

[0083] In the formula, is the bias term, is the impact degree of the event sampled at the i-th time, is the voltage imbalance coefficient of the i-th sampling, and are the regression coefficients of the event impact degree and the voltage unbalance state coefficient respectively;

[0084] The logic of obtaining the monitoring threshold is to collect a set of voltage fluctuation samples obtained by the experimenters in the laboratory, divide the data set into a training set and a test set, set the evaluation index and clustering algorithm, and in each round of cross-validation, train the model on the training set and evaluate the model performance on the test set. Then, adjust the monitoring threshold according to the performance of the validation set. Therefore, the monitoring threshold is constantly updated.

[0085] In the present invention, clustering algorithm is a kind of unsupervised learning algorithm, which is used to divide the voltage fluctuation samples in the data set into groups or clusters with similarities; the common one is K-means clustering, which divides the voltage fluctuation samples in the data set into K clusters, so that the distance between each voltage fluctuation sample and the center point (center of mass) of the cluster to which it belongs is minimized, and finally the similarity between the voltage fluctuation samples is measured by the Euclidean distance, so as to set the monitoring threshold;

[0086] Get voltage monitoring coefficient Finally, the voltage monitoring coefficient is compared and analyzed with the continuously iterated monitoring threshold;

[0087] If the voltage monitoring coefficient is greater than or equal to the monitoring threshold, the current voltage is marked as a fluctuating voltage and a fluctuation signal is generated;

[0088] If the voltage monitoring coefficient is less than the monitoring threshold, the current voltage is marked as a stable voltage and an end signal is generated;

[0089] Specifically, according to the marking result, the voltage fluctuation result is determined;

[0090] The present invention obtains user equipment strobe and user equipment operation delay by collecting user equipment characteristic information, performs weighted calculation, obtains event burst coefficient, compares with a preset initial threshold, determines the event impact degree, collects phase deviation and voltage amplitude imbalance, determines the phase deviation threshold, detects the actual phase deviation amplitude, and compares it with the phase deviation threshold, analyzes the voltage imbalance state coefficient, determines the voltage fluctuation result according to the event impact degree and the voltage imbalance state coefficient, improves the monitoring accuracy and response capability of the power system, improves the reliability of the power system, speeds up the system's efficiency in monitoring sudden events, and reduces the maintenance time of the power system.

[0091] Example 2

[0092] In the first embodiment of the present invention, an example is given of collecting characteristic information of user equipment, obtaining the stroboscopic information of user equipment and the operation delay of user equipment, performing weighted calculation, obtaining the event burst coefficient, and comparing it with the preset initial threshold value to determine the degree of event impact, and collecting the phase deviation and the voltage amplitude imbalance degree to determine the phase deviation threshold, detecting the actual phase deviation amplitude, and comparing it with the phase deviation threshold value, analyzing the voltage imbalance state coefficient, and determining the operation strategy of the voltage fluctuation result according to the degree of event impact and the voltage imbalance state coefficient; however, in the first embodiment, only the voltage fluctuation result is determined, and no analysis is made for the subsequent detection process, especially the setting of the initial threshold value. Obviously, this will cause the monitoring of emergencies to always remain at the same standard, and for long-term monitoring, the monitoring accuracy is reduced and the emergency monitoring error is caused; in view of the above problems, the second embodiment of the present invention is further refined;

[0093] The cyclic update module is used to obtain the voltage fluctuation results and the initial threshold, determine the voltage monitoring coefficients corresponding to different tags and their values, mark the voltage monitoring coefficients as voltage fluctuation values, and put them into a preset voltage fluctuation data set, calculate the average value of the voltage fluctuation data set, calculate the ratio of the current voltage fluctuation value to the average value of the voltage fluctuation data set, obtain the adjustment coefficient, and use the product of the adjustment coefficient and the obtained initial threshold as the initial threshold for the next system operation, and send it to the event acquisition module;

[0094] The voltage fluctuation result includes the current voltage marked as the fluctuating voltage and the stable voltage, and the voltage monitoring coefficient is obtained and calibrated as the voltage fluctuation value;

[0095] Specifically, the voltage marked as fluctuating is substituted as a positive value into a preset voltage fluctuation data set, and the voltage marked as stable is substituted as a negative value into a preset voltage fluctuation data set;

[0096] Get the voltage fluctuation value and substitute it into the preset voltage fluctuation data set to get the voltage fluctuation data set: ;

[0097] It should be noted that when the mark is stable voltage, it means that the current voltage is in a stable state. In order to ensure that the data set in the voltage fluctuation data set does not continue to increase or decrease, for the voltage fluctuation results in the above embodiment, according to different marks, the voltage monitoring coefficients corresponding to different marks are assigned positive or negative values ​​(positive or negative numbers), etc., which will not be elaborated here;

[0098] It should be noted that the preset voltage fluctuation data set refers to the voltage fluctuation value calibrated according to the voltage monitoring coefficient after the voltage fluctuation is determined and substituted into a preset set to further adjust the initial threshold so that the system can be closed-loop and realize dynamic monitoring;

[0099] The current voltage fluctuation value is calculated by ratio with the average value of the voltage fluctuation data set to obtain the adjustment coefficient;

[0100] The adjustment coefficient is multiplied by the initial threshold value, and the product result is used as the initial threshold value for the next system operation. When the voltage fluctuation value is substituted into the preset voltage fluctuation data set during the next system operation, the ratio calculation of the current voltage fluctuation value and the average value of the voltage fluctuation data set is repeated to obtain a new adjustment coefficient;

[0101] Since this embodiment takes the first round of system operation as an example, the adjustment coefficient calculated in this embodiment is 1. Therefore, when the second round of system operation is performed, the initial threshold value preset in the event collection module is still the initial threshold value preset in the event collection module in the first round of system operation;

[0102] This embodiment demonstrates how the system runs for a long time by example, and the specific examples are as follows:

[0103] Specifically, when determining the voltage fluctuation this time, a product of an adjustment coefficient and an initial threshold is calculated as the threshold of the next monitoring point, that is, at least two cycles are required to obtain a new monitoring point threshold;

[0104] Since there is only one value in the voltage fluctuation data set during initialization, the ratio of the current voltage fluctuation value to the average value of the voltage fluctuation data set is 1. After being substituted into the second cycle, the initial threshold for monitoring emergencies in the event acquisition module is: Initial threshold 1, it is still the initial threshold;

[0105] However, when the second loop reaches the loop update module, since there are two values ​​in the voltage fluctuation data set, the voltage fluctuation data set is , then the average value of the voltage fluctuation data set is: , then the ratio of the current voltage fluctuation value to the average value of the voltage fluctuation data set is , when substituted into the event acquisition module of the third cycle, the initial threshold , as the threshold of the emergency monitoring point, used to assess the impact of the incident;

[0106] So, in summary, the threshold of the emergency monitoring point in the fourth cycle is: initial threshold , the threshold of the emergency monitoring point in the fifth cycle is: initial threshold , then it can be seen that the threshold for emergency event monitoring in the i-th cycle is: initial threshold … ;

[0107] This forms a closed loop, completes dynamic monitoring and rapid response to the impact of emergencies on voltage, and accurately identifies the current voltage status;

[0108] Furthermore, a discrimination coefficient of the initial threshold of the next system operation is set. Specifically, twice the initial threshold can be set as the discrimination coefficient. If the initial threshold of the next system operation is greater than the discrimination coefficient, the voltage fluctuation values ​​in the voltage fluctuation data set are arranged in descending order, and the maximum and minimum values ​​are screened out to ensure that the initial threshold of the next system operation is within a normal range.

[0109] It should be noted that the setting of the discrimination coefficient can be based on the multiple of the initial threshold or the number of system cycles. The experimenter determined the discrimination coefficient based on the specific implementation and comprehensive analysis of the system operation status, which will not be elaborated here;

[0110] The present invention obtains voltage fluctuation results and initial thresholds, determines voltage monitoring coefficients corresponding to different tags and their assignments, incorporates voltage fluctuation values ​​into a preset voltage fluctuation data set, calculates the average value of the voltage fluctuation data set, and obtains an adjustment coefficient by the ratio of the current voltage fluctuation value to the average value of the voltage fluctuation data set. The product of the adjustment coefficient and the obtained initial threshold is used as the initial threshold for the next system operation, and the system is maintained in a continuous loop calculation, thereby supporting long-term operation and continuous optimization, reducing excessive sensitivity, and improving the system's adaptability and monitoring accuracy.

[0111] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0112] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center containing one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD) or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0113] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean 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 application.

[0114] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0115] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0116] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0117] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0118] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0119] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0120] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An intelligent management system for a voltage monitoring and operation and maintenance platform, characterized in that: It includes event acquisition module, imbalance analysis module, determination monitoring module and cyclic update module; signal connection between each module; The event collection module is used to collect characteristic information of user equipment, obtain the user equipment strobe and user equipment operation delay through data processing, and perform weighted calculation to obtain the event burst coefficient, and compare it with the preset initial threshold to determine the impact degree of the event, send the event impact degree to the determination monitoring module, and send the initial threshold to the cyclic update module; The imbalance analysis module is used to collect phase deviation and voltage amplitude imbalance, determine the phase deviation threshold, detect the actual phase deviation amplitude, compare it with the phase deviation threshold, analyze the voltage imbalance state coefficient, and send it to the determination monitoring module; Determine the monitoring module for obtaining the event impact degree and the voltage imbalance state coefficient, perform normalization processing, and substitute it into the logistic regression model to obtain the voltage monitoring coefficient, and compare it with the preset monitoring threshold to determine the voltage fluctuation result, and send it to the cyclic update module; The cyclic update module is used to obtain the voltage fluctuation results and the initial threshold, determine the voltage monitoring coefficients corresponding to different tags and their assignments, mark the voltage monitoring coefficients as voltage fluctuation values, and put them into a preset voltage fluctuation data set, calculate the average value of the voltage fluctuation data set, calculate the ratio of the current voltage fluctuation value to the average value of the voltage fluctuation data set, and obtain the adjustment coefficient. The product of the adjustment coefficient and the obtained initial threshold is used as the initial threshold for the next system operation and is sent to the event acquisition module.

2. The intelligent management system of a voltage monitoring and operation and maintenance platform according to claim 1 is characterized in that: User equipment characteristic information includes user equipment flicker and user equipment operation delay; the user equipment flicker is calculated by standard measuring equipment to quantify the flicker degree and obtain the user equipment flicker ; Where i is the i-th sampling number; The precise time when the trigger signal is sent is recorded through a high-precision timing tool. The signal change after the device performs the action is detected through the sensor or device output interface, and the time when the response signal is detected is recorded. The user device operation delay is obtained by subtracting the trigger signal sending time from the response signal receiving time. .

3. The intelligent management system of a voltage monitoring and operation and maintenance platform according to claim 2 is characterized in that: The user equipment flash frequency and the user equipment operation delay are weighted and calculated to obtain the event burst coefficient ; Compare the event suddenness coefficient with the preset initial threshold to obtain the comparison result, and determine the impact of the event based on the comparison result; specifically: If the event suddenness coefficient is greater than or equal to the initial threshold, it indicates that the current event is a sudden event, and the current event suddenness coefficient is marked as the event impact degree; If the event burst coefficient is less than the initial threshold, it indicates that the current event is a common event, and the current event burst coefficient is screened out.

4. The intelligent management system of a voltage monitoring and operation and maintenance platform according to claim 2 is characterized in that: The corresponding phase information is extracted from the frequency domain representation of adjacent signals through Fourier transform, and the phases of adjacent signals are subtracted to obtain the phase deviation; The voltage amplitude imbalance is obtained by obtaining the maximum amplitude of the three-phase voltage and the minimum amplitude of the three-phase voltage, calculating the subtraction value of the maximum and minimum voltage amplitudes, and performing ratio calculation with the average amplitude of the three-phase voltage.

5. The intelligent management system of a voltage monitoring and operation and maintenance platform according to claim 4 is characterized in that: The phase deviation threshold is calculated by the maximum value of the phase deviation and the voltage amplitude imbalance, and the actual phase deviation amplitude is detected. ; The actual phase deviation amplitude is compared with the calculated phase deviation threshold, specifically: If the actual phase deviation amplitude is greater than or equal to the phase deviation threshold, it means that the current voltage is in an unbalanced state, and the actual phase deviation amplitude is marked as the voltage unbalanced state coefficient. If the actual phase deviation amplitude is less than the phase deviation threshold, it means that the current voltage is in a balanced state, and the actual phase deviation amplitude is screened out.

6. The intelligent management system of a voltage monitoring and operation and maintenance platform according to claim 1, characterized in that: The event impact degree and the voltage unbalance state coefficient are normalized, and the event impact degree and the voltage unbalance state coefficient are substituted into the logistic regression calculation specific formula as follows: ； In the formula, is the result of logistic regression calculation, that is, the voltage monitoring coefficient, e is the natural base, and y is the linear combination term of the logistic regression model. Specifically, y can be set as: ； In the formula, is the bias term, is the impact degree of the event sampled at the i-th time, is the voltage imbalance coefficient of the i-th sampling, and are the regression coefficients of the event impact degree and the voltage unbalance state coefficient respectively.

7. The intelligent management system of a voltage monitoring and operation and maintenance platform according to claim 6 is characterized by: After obtaining the voltage monitoring coefficient, the voltage monitoring coefficient is compared and analyzed with the continuously iterated monitoring threshold; If the voltage monitoring coefficient is greater than or equal to the monitoring threshold, the current voltage is marked as a fluctuating voltage and a fluctuation signal is generated; If the voltage monitoring coefficient is less than the monitoring threshold, the current voltage is marked as a stable voltage and an end signal is generated; Based on the marked results, determine the voltage fluctuation results.

8. The intelligent management system of a voltage monitoring and operation and maintenance platform according to claim 7, characterized in that: The voltage fluctuation result includes the current voltage marked as the fluctuating voltage and the stable voltage, and the voltage monitoring coefficient is obtained and calibrated as the voltage fluctuation value; the voltage marked as the fluctuating voltage is substituted as a positive value into the preset voltage fluctuation data set, and the voltage marked as the stable voltage is substituted as a negative value into the preset voltage fluctuation data set; The voltage fluctuation value is obtained and substituted into a preset voltage fluctuation data set to obtain a voltage fluctuation data set.

9. The intelligent management system of a voltage monitoring and operation and maintenance platform according to claim 8, characterized in that: The current voltage fluctuation value is calculated by ratio with the average value of the voltage fluctuation data set to obtain the adjustment coefficient; The adjustment coefficient is multiplied by the initial threshold, and the product is used as the initial threshold for the next system operation. When the voltage fluctuation value is substituted into the preset voltage fluctuation data set during the next system operation, the ratio calculation of the current voltage fluctuation value and the average value of the voltage fluctuation data set is repeated to obtain a new adjustment coefficient.

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