Method for analyzing waveform in power system

Abstract

The invention relates to the technical field of electric power system analysis, and discloses a method for analyzing waveforms in an electric power system.The method comprises the steps of data collection, data preprocessing, feature extraction, comparative analysis and result display.The waveform data of multiple data points are collected in real time through a voltage transformer and a current transformer, the data accuracy is ensured, and the analysis accuracy is improved. Voltage and current waveform characteristics are comprehensively analyzed through feature extraction, and the monitoring accuracy is improved; comparing and analyzing, judging abnormity according to a preset threshold value and determining an accurate abnormity level, and clearly dividing normal and different risk levels by calculating a deviation rate and an analysis factor in combination with a preset abnormity factor threshold value set, so that related personnel can quickly know the risk degree to take measures; results are displayed visually and clearly, key data and risk levels are presented to related personnel, problems can be found in time, maintenance and repair are carried out, and the stability and reliability of the system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system analysis, and in particular to a method for analyzing waveforms in a power system. Background Art

[0002] As power systems continue to develop and become more complex, accurate monitoring and analysis of their operating status has become crucial. The voltage and current waveforms in power systems contain rich information that can reflect system operating conditions, fault conditions, and power quality issues.

[0003] Traditional power system monitoring methods often provide only limited information, making it difficult to comprehensively and deeply analyze waveform characteristics. For example, some methods may focus solely on the amplitude of voltage or current, while ignoring other important waveform characteristics such as crest factor and effective value. Furthermore, traditional methods may be unable to promptly and accurately identify and classify abnormal conditions in the power system, resulting in delayed fault handling and impacting system reliability and stability.

[0004] In order to meet the needs of modern power systems for high-precision, high-efficiency monitoring and analysis, there is an urgent need for a method that can comprehensively and accurately analyze the power system waveform to achieve real-time monitoring of the power system operating status and rapid judgment of abnormal situations. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for analyzing waveforms in an electric power system, which solves the technical problems raised in the background technology.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A method for analyzing waveforms in an electric power system, comprising the steps of:

[0008] Step 1: Data Collection

[0009] Using voltage transformers and current transformers, waveform data corresponding to voltage and current waveforms at multiple data collection time points in the power system are collected in real time;

[0010] Step 2: Feature Extraction

[0011] Extract specified data features from preprocessed waveform data;

[0012] Step 3: Comparative Analysis

[0013] Based on the voltage waveform and current waveform corresponding to the preset peak factor threshold and effective value threshold, it is judged whether there is an abnormality in the power system and the abnormality level is determined;

[0014] Step 4: Results display

[0015] Present the results of the third step to relevant personnel.

[0016] As a further solution of the present invention: the feature extraction method is as follows:

[0017] SA.1. Mark the voltage waveform at all data collection points as V t , t=1, 2, ... n; n represents the number of data collection time points;

[0018] Then, the maximum absolute value of the voltage values at all different data acquisition time points is found as the peak feature and marked as FV;

[0019] Then find all V t The average value will be marked as V p ;

[0020] Then divide FV by Y p Calculate the voltage crest factor of the voltage waveform within the standard cycle and mark it as FV e ;

[0021] SA.2. Divide a specified period into m standard time periods;

[0022] Divide the length of the specified period by the number of standard time periods to get the length of the standard time period and mark it as B t ;

[0023] Then obtain the voltage value at a data collection time point selected in each standard time period, and calculate its square value, and record it as V 1j 2 ;

[0024] Then through Calculate the effective value XV of the voltage waveform;

[0025] SA.3. Mark the current waveform at all data collection points as L t , t=1, 2, ... n;

[0026] Find the maximum absolute value of the current value at all different data acquisition time points as the peak feature and mark it as FL;

[0027] Then find all L t The average value is marked as L p ;

[0028] Then divide FL by L p Calculate the current crest factor of the current waveform within the standard cycle and mark it as FL e ;

[0029] SA.4. Obtain the current value at a data collection time point selected within each standard time period and calculate its square value, which will be recorded as L 1j 2 ;

[0030] Then through Calculate the effective value XL of the current waveform.

[0031] As a further solution of the present invention: the method of comparative analysis is as follows:

[0032] SK.1. Mark the voltage waveform corresponding to the preset peak factor threshold and effective value threshold as FV y and XV y ;

[0033] At the same time, the current waveform corresponding to the preset peak factor threshold and effective value threshold are marked as FL y and XL y ;

[0034] SK.2, then FV e With FV y Compare and e and FL y Compare and contrast XV and XV y Compare and contrast XL and XL y Comparing and, based on the comparison results, determining the deviation rates of the voltage waveform and the current waveform corresponding to the peak factor, and determining the deviation rates of the voltage waveform and the current waveform corresponding to the effective value;

[0035] SK.3. Then, extract the deviation rate of the voltage waveform and the current waveform corresponding to the peak factor, and determine the deviation rate of the voltage waveform and the current waveform corresponding to the effective value;

[0036] The power system analysis factor C is calculated by C = VP × α1 + LP × α2 + VU × α3 + LU × α4;

[0037] Where VP is the deviation rate of the voltage waveform corresponding to the peak factor;

[0038] LP is the deviation rate of the current waveform corresponding to the peak factor;

[0039] VU is the deviation rate of the voltage waveform corresponding to the effective value;

[0040] LU is the deviation rate of the current waveform corresponding to the effective value;

[0041] α1, α2, α3, and α4 are corresponding preset weight coefficients, and α1+α2+α3+α4=1;

[0042] SK.4. Then, the analysis factor C is compared with the preset abnormal factor threshold set [C1, C2, C3], and the abnormality level of the power system is determined based on the comparison result.

[0043] As a further embodiment of the present invention: In SK.2,

[0044] If FV e >FV y , then through Calculate the deviation rate VP of the voltage waveform corresponding to the peak factor;

[0045] If FV e ≤FV y , then let the value of VP be 0;

[0046] If FL e >FL y , then through Calculate the deviation rate LP of the current waveform corresponding to the peak factor;

[0047] If FL e ≤FL y , then let the value of LP be 0;

[0048] If XV>XV y , then through Calculate the deviation rate VU of the voltage waveform corresponding to the effective value;

[0049] If XV≤XV y , then let the value of VU be 0;

[0050] If XL>XL y , then through Calculate the deviation rate LU of the current waveform corresponding to the effective value;

[0051] If XL≤XL y , then let the value of LU be 0.

[0052] As a further embodiment of the present invention: In SK.4,

[0053] If C≤C1, it is determined that the waveform of the power system is relatively stable and is at a normal level;

[0054] If C1<C≤C2, it means that there is a small deviation in the waveform and it is at a low risk level;

[0055] If C2<C≤C3, it means that the waveform has a large deviation and is at a medium risk level;

[0056] If C3<C, it means that there is a serious deviation in the waveform and it is at a high risk level.

[0057] As a further solution of the present invention: wherein, the normal level indicates that there is no abnormality in the power system, and the low risk level, medium risk level and high risk level indicate that there is an abnormality in the power system.

[0058] As a further solution of the present invention: the result of the result display is to display the values of VP, LP, VU, LU and C, and the corresponding risk level obtained based on C to relevant personnel.

[0059] As a further solution of the present invention: the method further comprises the steps of: data preprocessing

[0060] It pre-processes the waveform data collected at multiple data collection time points, removes abnormal waveform data at the corresponding data collection time points based on the processing results, and then inserts normal waveform data at the corresponding data collection time points;

[0061] As a further solution of the present invention, the preprocessing method for the waveform data corresponding to the voltage waveform is as follows:

[0062] SS.1. Mark the voltage waveform at all data collection points as V t , t=1, 2, ... n; n represents the number of data collection time points;

[0063] Then find all V t The mean and standard deviation of p and V c ;

[0064] SS.2, let the value of t be 1, 2, ..., n;

[0065] Then (|V t -V p |) / V c The obtained result value is compared with the preset abnormality determination factor K; and the value range of K is 2 to 4;

[0066] If (|V t -V p |) / V c ≤K, then the Vt corresponding to the t-th data collection time point is determined to be a normal value;

[0067] If (|V t -V p |) / V c >K, then the Vt corresponding to the t-th data collection time point is determined to be an abnormal value;

[0068] SS.3, from all V t Extract normal values and calculate the average of all normal values;

[0069] SS.4, from all Vt Extract outliers and replace them in the following way:

[0070] Get the value of V t Adjacent V t+1 and V t-1 ,At the same time, according to the comparison results of SS.2;

[0071] If V t+1 and V t-1 If both are normal values, then find V t+1 and V t-1 The average value between the two values is then used as the abnormal value V corresponding to the t-th data collection time point. t substituted value for ;

[0072] If V t+1 and V t-1 If at least one of the values is an outlier, the average value of all normal values obtained by SS.3 is taken as the corresponding outlier value V t The replacement value of .

[0073] As a further solution of the present invention: wherein, the pre-processing method of the waveform data corresponding to the voltage waveform and the waveform data corresponding to the current waveform are consistent.

[0074] Beneficial effects of the present invention:

[0075] The present invention collects voltage waveform and current waveform data at multiple data collection time points in real time, utilizes voltage transformers and current transformers to ensure the accuracy and reliability of the data, and provides a solid foundation for subsequent analysis.

[0076] In the feature extraction process of the present invention, detailed analysis is performed on the voltage and current waveforms respectively, including calculation of peak characteristics, average value, crest factor and effective value, etc., which comprehensively describes the characteristics of the waveforms and can more accurately judge the operating status of the power system.

[0077] In the comparative analysis of the present invention, the voltage and current waveforms are judged respectively according to the preset peak factor threshold and effective value threshold to determine whether there are abnormalities. By calculating the deviation rate and the analysis factor C, the abnormality level of the power system can be accurately determined, including the normal level, low risk level, medium risk level and high risk level.

[0078] The present invention clarifies the classification standards of different levels by comparing with a preset abnormal factor threshold set, so that relevant personnel can quickly understand the risk level of the power system and take corresponding measures.

[0079] The present invention displays the deviation rate of the peak factor corresponding to the voltage waveform and the current waveform, the deviation rate of the effective value, the value of the analysis factor and the corresponding risk level to relevant personnel in an intuitive and clear manner, which facilitates relevant personnel to quickly understand the operation status of the power system; helps relevant personnel to promptly discover problems and take targeted measures for maintenance and repair, thereby improving the stability and reliability of the power system.

[0080] The present invention and the method of the present invention are applicable to various power systems, can perform waveform analysis on power systems of different sizes and types, and have wide applicability; can provide strong support for the design, operation and maintenance of power systems, and improve the overall performance and safety of power systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] The present invention will be further described below with reference to the accompanying drawings.

[0082] Figure 1 It is a flow chart of a method for analyzing waveforms in a power system according to the present invention.

[0083] Figure 2 It is a flow chart of the comparison and analysis steps in a method for analyzing the waveform of an electric power system according to the present invention. DETAILED DESCRIPTION

[0084] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making any creative efforts shall fall within the scope of protection of the present invention.

[0085] Example 1

[0086] See also Figure 1 and Figure 2 As shown, the present invention is a method for analyzing waveforms in a power system, comprising the following steps:

[0087] Step 1: Data Collection

[0088] Using voltage transformers and current transformers, waveform data corresponding to voltage and current waveforms at multiple data collection time points in the power system are collected in real time;

[0089] Step 2: Feature Extraction

[0090] Extract specified data features from preprocessed waveform data;

[0091] The specific extraction method is as follows:

[0092] SA.1. Mark the voltage waveform at all data collection points as V t , t=1, 2, ... n; n represents the number of data collection time points;

[0093] Then through FV=max(|V t |), calculate the peak characteristic FV of the voltage waveform;

[0094] Then find all V t The average value will be marked as V p ;

[0095] Then divide FV by Y p Calculate the voltage crest factor of the voltage waveform within the standard cycle and mark it as FV e ;

[0096] SA.2. Divide a specified period into m standard time periods;

[0097] In this embodiment, the designated period is determined by relevant calculation personnel through monitoring and analysis of the actual power system, observing the changes in waveform characteristics under different period lengths, and starting with a shorter period and gradually increasing the period length until a stable and representative result is obtained;

[0098] By B t =T / m, calculate the length of the standard time period B t , where T is the length of the specified period;

[0099] Then obtain the voltage value at a data collection time point selected in each standard time period, and calculate its square value, and record it as V 1j 2 ;

[0100] Then through Calculate the effective value XV of the voltage waveform;

[0101] SA.3. Mark the current waveform at all data collection points as L t , t=1, 2, ... n;

[0102] Then through FL=max(|L t |), calculate the peak characteristic FL of the current waveform;

[0103] Then find all L t The average value is marked as L p ;

[0104] Then divide FL by L pCalculate the current crest factor of the current waveform within the standard cycle and mark it as FL e ;

[0105] SA.4. Obtain the current value at a data collection time point selected within each standard time period and calculate its square value, which will be recorded as L 1j 2 ;

[0106] Then through Calculate the effective value XL of the current waveform;

[0107] This embodiment can comprehensively describe the characteristics of the voltage and current waveforms by calculating the peak characteristics, average values, and crest factors. It accurately reflects the extreme conditions of the waveforms by finding the maximum absolute value at different data collection time points as the peak characteristic. Dividing a specified period into standard time periods, obtaining and calculating the voltage and current values within each time period, facilitates a more detailed analysis of waveform changes in different time periods, thereby improving the accuracy of feature extraction.

[0108] Step 3: Comparative Analysis

[0109] Based on the voltage waveform and current waveform corresponding to the preset peak factor threshold and effective value threshold, it is judged whether there is an abnormality in the power system and the abnormality level is determined;

[0110] The specific method is as follows:

[0111] SK.1. Setting thresholds

[0112] The voltage waveform corresponding to the preset peak factor threshold and effective value threshold are marked as FV y and XV y ;

[0113] At the same time, the current waveform corresponding to the preset peak factor threshold and effective value threshold are marked as FL y and XL y ;

[0114] SK.2. Calculate the deviation rate

[0115] Then FV e With FV y Compare and e and FL y Compare and contrast XV and XV y Compare and contrast XL and XL y Compare:

[0116] If FV e >FV y , then through Calculate the deviation rate VP of the voltage waveform corresponding to the peak factor;

[0117] If FV e ≤FV y , then let the value of VP be 0;

[0118] If FL e >FL y , then through Calculate the deviation rate LP of the current waveform corresponding to the peak factor;

[0119] If FL e ≤FL y , then let the value of LP be 0;

[0120] If XV>XV y , then through Calculate the deviation rate VU of the voltage waveform corresponding to the effective value;

[0121] If XV≤XV y , then let the value of VU be 0;

[0122] If XL>XL y , then through Calculate the deviation rate LU of the current waveform corresponding to the effective value;

[0123] If XL≤XL y , then let the value of LU be 0;

[0124] SK.3. Calculation and Analysis Factors

[0125] Then extract VP, LP, VU and LU;

[0126] The power system analysis factor C is calculated by C = VP × α1 + LP × α2 + VU × α3 + LU × α4;

[0127] Where α1, α2, α3, and α4 are corresponding preset weight coefficients, and α1+α2+α3+α4=1;

[0128] SK.4. Determine the risk level

[0129] Then the analysis factor C is compared with the preset abnormal factor threshold set [C1, C2, C3];

[0130] If C≤C1, it is determined that the waveform of the power system is relatively stable and is at a normal level;

[0131] If C1<C≤C2, it means that there is a small deviation in the waveform and it is at a low risk level;

[0132] If C2<C≤C3, it means that the waveform has a large deviation and is at a medium risk level;

[0133] If C3 < C, it means that the waveform has serious deviations and is at a high risk level;

[0134] Among them, the normal level indicates that there is no abnormality in the power system, and the low risk level, medium risk level and high risk level indicate that there is an abnormality in the power system;

[0135] This embodiment uses preset peak factor thresholds and effective value thresholds to determine whether the power system is abnormal and to determine the abnormality level. This approach has clear judgment criteria, making abnormality judgment more scientific and reasonable. By comparing and analyzing multiple parameters, such as the peak factor deviation rate, and combining them with preset weight coefficients to calculate the analysis factor, it can comprehensively consider the impact of different factors on the power system, thereby improving the accuracy and reliability of abnormality judgment.

[0136] Step 4: Results display

[0137] Present the results of step 3 to relevant personnel;

[0138] The specific results displayed are the values of VP, LP, VU, LU and C, as well as the corresponding risk level obtained based on the analysis factor C;

[0139] This embodiment displays the analysis results to relevant personnel in the form of specific numerical values and corresponding risk levels, which is intuitive and easy to understand, allowing relevant personnel to quickly understand the operating status of the power system and take appropriate measures for maintenance and management in a timely manner;

[0140] This embodiment covers every step from data acquisition to result presentation, demonstrating its strong systematic nature. This makes the method easy to understand and apply, providing a comprehensive solution for waveform analysis in power systems. First, during data acquisition, waveform data is collected in real time using voltage and current transformers, ensuring data accuracy and timeliness, providing a reliable foundation for subsequent analysis. During feature extraction, the characteristics of the voltage and current waveforms are comprehensively and accurately characterized by calculating multi-dimensional indicators such as peak characteristics, average values, and crest factors. Flexible division of specified periods further enhances the precision of analysis. Regarding anomaly determination, the anomaly level is determined based on preset thresholds and scientific calculation methods, comprehensively considering multiple factors to improve the reliability of the determination. The result presentation is intuitive and clear, allowing relevant personnel to quickly understand the operating status of the power system. Overall, this method provides a strong guarantee for the stable operation of the power system, helping to promptly identify problems and take appropriate measures, reducing risks and improving the safety and reliability of the power system.

[0141] Example 2

[0142] As the second embodiment of the present invention, when the present application is specifically implemented, compared with the first embodiment, the technical solution of this embodiment is different from that of the first embodiment only in that,

[0143] The method also includes the steps of: data preprocessing, which is used before feature extraction;

[0144] This step is used to preprocess the waveform data collected at multiple data collection time points in the following way:

[0145] The pre-processing methods of the waveform data corresponding to the voltage waveform and the waveform data corresponding to the current waveform are the same, and the waveform data corresponding to the voltage waveform is taken as an example;

[0146] SS.1. Mark the voltage waveform at all data collection points as V t , t=1, 2, ... n; n represents the number of data collection time points;

[0147] Then find all V t The mean and standard deviation of p and V c ;

[0148] SS.2, let the value of t be 1, 2, ..., n;

[0149] Then (|V t -V p |) / V c The obtained result value is compared with the preset abnormality determination factor K;

[0150] In this embodiment, the value of K ranges from 2 to 4;

[0151] If (|V t -V p |) / V c ≤K, then the Vt corresponding to the t-th data collection time point is determined to be a normal value;

[0152] If (|V t -V p |) / V c >K, then the Vt corresponding to the t-th data collection time point is determined to be an abnormal value;

[0153] SS.3, from all V t Extract normal values and calculate the average of all normal values;

[0154] SS.4, from all V t Extract outliers and replace them in the following way:

[0155] Get the value of V tAdjacent V t+1 and V t-1 ,At the same time, according to the comparison results of SS.2;

[0156] If V t+1 and V t-1 If both are normal values, then find V t+1 and V t-1 The average value between the two values is then used as the abnormal value V corresponding to the t-th data collection time point. t substituted value for ;

[0157] If V t+1 and V t-1 If at least one of the values is an outlier, the average of all normal values obtained in SS.3 is used as the replacement value for the corresponding outlier value Vt;

[0158] SS.5. Mark the current waveform at all data collection points as L t , t=1, 2, ... n,

[0159] Then find all L t The mean and standard deviation of p and L c ;

[0160] SS.6. Let the value of t be 1, 2, ..., n.

[0161] Then (|L t -L p |) / Lc and compare the result value obtained with the preset abnormality judgment factor K;

[0162] In this embodiment, the value of K is consistent with the value of K in SS.2;

[0163] If (|L t -L p |) / L c ≤K, then determine the L corresponding to the tth data collection time point t is the normal value;

[0164] If (|L t -L p |) / L c >K, then determine the L corresponding to the tth data collection time point t is an outlier;

[0165] SS.7, from all L t Extract normal values and calculate the average of all normal values;

[0166] SS.8, from all L tExtract outliers and replace them in the following way:

[0167] Get the outlier L t Adjacent L t+1 and L t-1 ,At the same time, according to the comparison results of SS.6;

[0168] If L t+1 and L t-1 If they are all normal values, then find L t+1 and L t-1 The average value between the two values is then used as the abnormal value L corresponding to the t-th data collection time point. t substituted value for ;

[0169] If L t+1 and L t-1 If at least one of the items is an outlier, the average value of all normal values obtained by SS.7 is taken as the corresponding outlier value L t The replacement value of .

[0170] This embodiment can effectively identify and eliminate outliers by preprocessing the voltage and current waveform data, thereby improving the accuracy of subsequent feature extraction and analysis. The average value and standard deviation are used to determine outliers, making the determination of outliers more scientific and reasonable, and avoiding the misleading of the overall analysis results by individual abnormal data. The preset abnormality determination factor K ranges from 2 to 4 and can be adjusted according to actual conditions, enhancing the adaptability of the method to different power systems and data characteristics. For the replacement of outliers, the situation of adjacent data points is taken into account. When the adjacent data points are all normal values, the average value of the adjacent data points is used for replacement, ensuring the continuity of the data. When at least one of the adjacent data points is an outlier, the average value of all normal values is used for replacement, avoiding the problem of inaccurate replacement due to multiple consecutive outliers, and restoring the integrity of the data to the greatest extent. The data corresponding to the voltage waveform and the current waveform are preprocessed in a consistent manner, ensuring that the two different types of data can be processed fairly and uniformly in the subsequent analysis, improving the reliability of the overall analysis.

[0171] Example 3

[0172] As the third embodiment of the present invention, when this application is specifically implemented, compared with the first and second embodiments, the technical solution of this embodiment is to combine the solutions of the first and second embodiments.

[0173] This embodiment combines the solutions of embodiment one and embodiment two, integrating the systematicness and comprehensiveness of embodiment one with the data preprocessing advantages of embodiment two. It not only provides a comprehensive solution in the aspects of data collection, feature extraction, comparative analysis and result presentation, but also improves the data quality and accuracy of analysis through data preprocessing, providing a stronger guarantee for the stable operation of the power system. It ensures the accuracy and timeliness of data in the data collection stage, eliminates outliers and restores data continuity through the preprocessing stage, comprehensively characterizes the waveform characteristics in the feature extraction stage, comprehensively considers multiple factors to determine the abnormality level in the abnormality judgment stage, and finally facilitates relevant personnel to take timely measures through intuitive result presentation, thereby reducing risks and improving the safety and reliability of the power system.

[0174] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters and thresholds in the formulas are set by technicians in this field according to actual conditions.

[0175] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A method for analyzing waveforms in an electric power system, characterized in that The following steps are involved: Step 1: Data Collection Using voltage transformers and current transformers, waveform data corresponding to voltage and current waveforms at multiple data collection time points in the power system are collected in real time; Step 2: Data preprocessing Preprocessing the waveform data collected at multiple data collection time points, eliminating abnormal waveform data at the corresponding data collection time points based on the processing results, and then replacing the abnormal waveform data to insert normal waveform data at the corresponding data collection time points; Step 3: Feature extraction Extract specified data features from preprocessed waveform data; Step 4: Comparative Analysis Based on the voltage waveform and current waveform corresponding to the preset peak factor threshold and effective value threshold, it is judged whether there is an abnormality in the power system and the abnormality level is determined; Step 5: Results display Show the results of step 4 to relevant personnel.

2. A method for analyzing waveforms in a power system according to claim 1, characterized in that: The feature extraction method is as follows: SA.

1. Mark the voltage waveform at all data collection points as V t , t=1, 2, ... n; n represents the number of data collection time points; Then, find the maximum absolute value of the voltage values at all different data acquisition time points as the peak feature and mark it as FV; Then find all V t The average value will be marked as V p ; Then divide FV by Y p Calculate the voltage crest factor of the voltage waveform within the standard cycle and mark it as FV e ; SA.

2. Divide a specified period into m standard time periods; Divide the length of the specified period by the number of standard time periods to get the length of the standard time period and mark it as B t ; Then obtain the voltage value at a data collection time point selected in each standard time period, and calculate its square value, and record it as V 1j 2 ; Then through Calculate the effective value XV of the voltage waveform; SA.

3. Mark the current waveform at all data collection points as L t , t=1, 2, ... n; Find the maximum absolute value of the current value at all different data acquisition time points as the peak feature and mark it as FL; Then find all L t The average value is marked as L p ; Then divide FL by L p Calculate the current crest factor of the current waveform within the standard cycle and mark it as FL e ; SA.

4. Obtain the current value at a data collection time point selected within each standard time period and calculate its square value, which will be recorded as L 1j 2 ; Then through Calculate the effective value XL of the current waveform.

3. A method for analyzing waveforms in a power system according to claim 2, characterized in that: The comparative analysis is as follows: SK.

1. Mark the voltage waveform corresponding to the preset peak factor threshold and effective value threshold as FV y and XV y ; At the same time, the current waveform corresponding to the preset peak factor threshold and effective value threshold are marked as FL y and XL y ; SK.2, then FV e With FV y Compare and e and FL y Compare and contrast XV and XV y Compare and contrast XL and XL y Comparing and, based on the comparison results, determining the deviation rates of the voltage waveform and the current waveform corresponding to the peak factor, and determining the deviation rates of the voltage waveform and the current waveform corresponding to the effective value; SK.

3. Then, extract the deviation rate of the voltage waveform and the current waveform corresponding to the peak factor, and determine the deviation rate of the voltage waveform and the current waveform corresponding to the effective value; The power system analysis factor C is calculated by C = VP × α1 + LP × α2 + VU × α3 + LU × α4; Where VP is the deviation rate of the voltage waveform corresponding to the peak factor; LP is the deviation rate of the current waveform corresponding to the peak factor; VU is the deviation rate of the voltage waveform corresponding to the effective value; LU is the deviation rate of the current waveform corresponding to the effective value; α1, α2, α3, and α4 are corresponding preset weight coefficients, and α1+α2+α3+α4=1; SK.

4. Then, the analysis factor C is compared with the preset abnormal factor threshold set [C1, C2, C3], and the abnormality level of the power system is determined based on the comparison result.

4. A method for analyzing waveforms in a power system according to claim 3, characterized in that: In SK.2, If FV e >FV y , calculate the absolute value of the difference between FVe and FVy, and then divide the absolute value of the difference by FV y , get the deviation rate of the voltage waveform corresponding to the crest factor, and then mark it as VP; If FV e ≤FV y , then let the value of VP be 0; If FL e >FL y , then calculate FL e With FL y The absolute value of the difference between the two, and then divide the absolute value of the difference by FL y , get the deviation rate of the voltage waveform corresponding to the crest factor, and then mark it as LP; If FL e ≤FL y , then let the value of LP be 0; If XV>XV y , then calculate XV and XV y The absolute value of the difference between them is then divided by XV y , get the deviation rate of the voltage waveform corresponding to the crest factor, and then mark it as VU; If XV≤XV y , then let the value of VU be 0; If XL>XL y , then calculate XL and XL y The absolute value of the difference between the two, and then divide the absolute value of the difference by XL y , get the deviation rate of the voltage waveform corresponding to the crest factor, and then mark it as LU; If XL≤XL y , then let the value of LU be 0.

5. A method for analyzing waveforms in a power system according to claim 3, characterized in that: In SK.4, If C≤C1, it is determined that the waveform of the power system is relatively stable and is at a normal level; If C1<C≤C2, it means that there is a small deviation in the waveform and it is at a low risk level; If C2<C≤ C3 , it means that there is a large deviation in the waveform and it is at a medium risk level; If C3<C, it means that there is a serious deviation in the waveform and it is at a high risk level.

6. A method for analyzing waveforms in a power system according to claim 5, characterized in that: in, The normal level indicates that there is no abnormality in the power system, and the low risk level, medium risk level and high risk level indicate that there is an abnormality in the power system.

7. A method for analyzing waveforms in a power system according to claim 5, characterized in that: The display result is to display the values of VP, LP, VU, LU and C, as well as the corresponding risk level obtained based on C to relevant personnel.

8. A method for analyzing waveforms in a power system according to claim 1, characterized in that: The preprocessing method for the waveform data corresponding to the voltage waveform is as follows: SS.

1. Mark the voltage waveform at all data collection points as V t , t=1, 2, ... n; n represents the number of data collection time points; Then find all V t The mean and standard deviation of p and V c ; SS.2, let the value of t be 1, 2, ..., n; Then (|V t -V p |) / V c The obtained result value is compared with the preset abnormality determination factor K, where the value range of K is 2 to 4; If (|V t -V p |) / V c ≤K, then the Vt corresponding to the t-th data collection time point is determined to be a normal value; If (|V t -V p |) / V c >K, then the Vt corresponding to the t-th data collection time point is determined to be an abnormal value; SS.3, from all V t The abnormal values are extracted and replaced, and the replacement values are determined as the normal waveform data inserted at the corresponding data acquisition time point.

9. A method for analyzing waveforms in a power system according to claim 8, characterized in that: The replacement is handled as follows: From all V t Extract normal values and calculate the average of all normal values; Get the outlier value V t Adjacent V t+1 and V t-1 ,At the same time, according to the comparison results of SS.2; If V t+1 and V t-1 If both are normal values, then find V t+1 and V t-1 The average value between , and then the average value is used as the replacement value of the abnormal value Vt corresponding to the t-th data collection time point; If V t+1 and V t-1 If at least one of the values is an outlier, the average value of all normal values obtained by SS.3 is taken as the corresponding outlier value V t The replacement value of .

10. A method for analyzing waveforms in a power system according to claim 9, characterized in that: in, The preprocessing method of the waveform data corresponding to the voltage waveform and the waveform data corresponding to the current waveform is the same.

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