A comprehensive analysis method and system for terminal operation and maintenance quality based on intelligent inspection

Abstract

The present invention discloses a terminal operation and maintenance quality comprehensive analysis method and system based on intelligent inspection, including: obtaining historical power quality monitoring data of each terminal in the distribution network from the power quality monitoring system; calculating the terminal data quality, terminal communication reliability, terminal failure frequency and terminal maintenance time corresponding to each terminal according to the historical power quality monitoring data of each terminal, as the operation and maintenance quality evaluation index of each terminal; obtaining the first weight value of each terminal by the hierarchical analysis method according to the operation and maintenance quality evaluation index of each terminal, and obtaining the second weight value of each terminal by the entropy weight method; obtaining the comprehensive score of the operation and maintenance quality of each terminal by the superior and inferior solution distance method according to the first weight value and the second weight value, in combination with the operation and maintenance quality evaluation index of each terminal; regulating the operation and maintenance strategy of each terminal in the distribution network according to the comprehensive score of the operation and maintenance quality of each terminal. The present invention realizes a more efficient analysis of the operation and maintenance quality of each terminal in the power quality monitoring system.

Description

Technical Field

[0001] The present invention relates to the field of power quality monitoring, and in particular to a method and system for comprehensive analysis of terminal operation and maintenance quality based on intelligent inspection. Background Art

[0002] The increasing number of power quality problems has led to the vigorous development of power quality monitoring systems in power grid companies in various provinces. However, as the scale of power quality monitoring terminals connected to power quality monitoring systems in various provinces continues to expand, terminal device failures, terminal device communication problems, and data quality problems are rapidly increasing.

[0003] At present, a large number of monitoring terminals are connected to the power quality monitoring system, and terminal fault troubleshooting and operation and maintenance work rely on manual intervention. In other words, managers need to spend a lot of time and energy on the maintenance and management of power quality monitoring terminals, which affects the actual monitoring effect of the power quality monitoring system. Therefore, a more efficient terminal operation and maintenance quality comprehensive analysis method and system is urgently needed. Summary of the invention

[0004] The present invention provides a method and system for comprehensive analysis of terminal operation and maintenance quality based on intelligent inspection, which realizes more efficient analysis of the operation and maintenance quality of each terminal in a power quality monitoring system.

[0005] In order to solve the above technical problems, an embodiment of the present invention provides a terminal operation and maintenance quality comprehensive analysis method based on intelligent inspection, including:

[0006] Obtain historical power quality monitoring data of each terminal in the distribution network from the power quality monitoring system;

[0007] According to the historical power quality monitoring data of each terminal, the terminal data quality, terminal communication reliability, terminal failure frequency and terminal maintenance time corresponding to each terminal are calculated as operation and maintenance quality evaluation indicators of each terminal;

[0008] According to the operation and maintenance quality evaluation index of each terminal, a first weight value of each terminal is obtained by using a hierarchical analysis method, and a second weight value of each terminal is obtained by using an entropy weight method;

[0009] According to the first weight value and the second weight value, in combination with the operation and maintenance quality evaluation index of each terminal, a comprehensive operation and maintenance quality score of each terminal is obtained by using a good-bad solution distance method;

[0010] According to the comprehensive operation and maintenance quality scores of the terminals, the operation and maintenance strategies of the terminals in the distribution network are adjusted.

[0011] It can be understood that, compared with the prior art, the method provided by the present invention obtains and stores the historical power quality monitoring data of the power quality monitoring system for a period of time, and calculates the weight value of the terminal operation and maintenance quality evaluation through the hierarchical analysis method and the entropy weight method based on four indicators such as terminal data quality, terminal communication reliability, terminal fault frequency, and terminal maintenance time, and combines the superior and inferior solution distance method to calculate the comprehensive weight, which can make full use of the information of the original data, avoid the subjectivity of the data, and reasonably realize the comprehensive evaluation of the terminal operation and maintenance quality, and provide theoretical support for the establishment of the operation and maintenance evaluation system of the power quality monitoring terminal in operation. At the same time, the operation and maintenance quality evaluation results of the power quality monitoring terminal are updated regularly, which can realize the online intelligent judgment of the actual operation of the power quality monitoring terminal, which is conducive to reducing the terminal fault detection and operation and maintenance work, and provides an objective and scientific basis for the power grid company to carry out technical supervision of power quality.

[0012] Further, the terminal data quality, terminal communication reliability, terminal failure frequency and terminal maintenance duration corresponding to each terminal are calculated based on the historical power quality monitoring data of each terminal, specifically including:

[0013] According to the historical power quality monitoring data, the terminal data accuracy, terminal data completeness and terminal data efficiency of each terminal are calculated to obtain the terminal data quality corresponding to each terminal;

[0014] Obtaining a terminal communication reliability rate according to the communication interruption time of each terminal in the historical power quality monitoring data, the expected number of power quality monitoring data to be obtained, and the time interval for statistical data;

[0015] Calculating the sum of the number of failures of each terminal in the historical power quality monitoring data respectively to obtain the terminal failure frequency corresponding to each terminal;

[0016] The sum of the maintenance time of each terminal in the historical power quality monitoring data is calculated respectively to obtain the terminal maintenance time corresponding to each terminal.

[0017] It can be understood that the method provided by the present invention calculates the terminal data quality, terminal communication reliability, terminal failure frequency and terminal maintenance time corresponding to each terminal, and comprehensively evaluates the operation quality and maintenance status of the terminals that have been connected to the power quality monitoring system, thereby helping system operation and maintenance personnel to quickly discover and identify problem terminals, improve the efficiency and personnel input of terminal operation and maintenance, and also improve the online monitoring quality of the State Grid power quality monitoring system.

[0018] Further, the terminal data accuracy, terminal data completeness and terminal data efficiency are calculated according to the historical power quality monitoring data to obtain the terminal data quality corresponding to each terminal, specifically including:

[0019] Obtaining data accuracy based on the total data quantity and the data quantity with abnormal change rate in the historical power quality monitoring data;

[0020] Obtaining a data integrity rate according to the total amount of data in the historical power quality monitoring data and the amount of missing data caused by device failure;

[0021] The data efficiency is obtained according to the total data quantity and the data quantity with disordered timestamp in the historical power quality monitoring data.

[0022] It can be understood that the method provided by the present invention counts the number of data with abnormal change rate, the number of missing data caused by device failure, and the number of data with disordered timestamps, which can describe the terminal data quality in multiple dimensions and more accurately evaluate the terminal operation and maintenance quality.

[0023] Further, the first weight value of each terminal is obtained by using a hierarchical analysis method according to the operation and maintenance quality evaluation index of each terminal, specifically including:

[0024] According to the operation and maintenance quality evaluation indicators of each terminal, a judgment matrix is ​​obtained by a consistent matrix method; wherein the number of rows of the judgment matrix corresponds to the number of operation and maintenance quality evaluation indicators, the number of columns of the judgment matrix corresponds to the number of terminals, and the elements of the judgment matrix are comparison weights of the rows and columns corresponding to the current elements;

[0025] Calculate the eigenvalues ​​in the judgment matrix by the eigenvector method to obtain the maximum eigenvalue and the eigenvector corresponding to the maximum eigenvalue;

[0026] Normalizing the feature vector to obtain a normalized feature vector;

[0027] Calculate the consistency index of the maximum eigenvalue, combine it with the random consistency index, calculate the consistency ratio, and determine whether the consistency test is passed according to the consistency ratio;

[0028] If the consistency check fails, the judgment matrix is ​​iteratively updated; if the consistency check passes, the normalized feature vector is used as a first weight coefficient vector to obtain a first weight value of each terminal.

[0029] It can be understood that the method provided by the present invention uses a hierarchical analysis method to hierarchically divide the importance of different operation and maintenance quality evaluation indicators to operation and maintenance and management personnel, which helps to optimize the resource allocation of power quality monitoring terminals and improve operation and maintenance efficiency and quality.

[0030] Furthermore, obtaining the second weight value of each terminal by the entropy weight method specifically includes:

[0031] According to the operation and maintenance quality evaluation indicators of each terminal, an evaluation matrix is ​​constructed; wherein the number of rows of the evaluation matrix corresponds to the number of operation and maintenance quality evaluation indicators, the number of columns of the evaluation matrix corresponds to the number of terminals, and the elements of the evaluation matrix are the proportion of the terminal corresponding to the current element under the operation and maintenance quality evaluation indicator corresponding to the current element to all operation and maintenance quality evaluation indicators;

[0032] According to the evaluation matrix and in combination with the entropy value calculation formula, the weight of each operation and maintenance quality evaluation indicator is calculated to obtain a second weight value of each terminal.

[0033] It can be understood that the method provided by the present invention obtains the second weight value of each terminal through the entropy weight method, and calculates the weight of each operation and maintenance quality evaluation index through information entropy, which can objectively describe the operation and maintenance quality evaluation index of each terminal and lay the foundation for efficient comprehensive score calculation.

[0034] Further, the first weight value and the second weight value are combined with the operation and maintenance quality evaluation index of each terminal, and the comprehensive operation and maintenance quality score of each terminal is obtained by the superior and inferior solution distance method, specifically including:

[0035] The terminal data quality and the terminal communication reliability are used as the maximum large-scale indicators, and the terminal failure frequency and the terminal maintenance duration are used as the minimum small-scale indicators;

[0036] Performing positive processing on the extremely small index, and constructing a positive matrix according to the extremely large index and the extremely small index after the positive processing;

[0037] Dividing each element in the forward matrix by the Euclidean norm of the forward matrix to obtain a standardized matrix;

[0038] Calculating a weighted sum of the first weight value and the second weight value to obtain a comprehensive weight value;

[0039] Obtaining a weighted normalized matrix according to the comprehensive weight value and the normalized matrix;

[0040] According to the weighted normalization matrix, the maximum value and the minimum value of each operation and maintenance quality evaluation indicator are calculated, and according to the maximum value and the minimum value of each operation and maintenance quality evaluation indicator, the positive ideal solution distance and the negative ideal solution distance are calculated;

[0041] According to the positive ideal solution distance and the negative ideal solution distance, a comprehensive score of the operation and maintenance quality of each terminal is obtained.

[0042] It can be understood that the method provided by the present invention divides each element by the Euclidean norm of the normalized matrix, so that all elements of the normalized matrix are positive numbers. Combined with the superior and inferior solution distance method to calculate the comprehensive weight, it is possible to make full use of the information of historical power quality monitoring and realize online intelligent determination of the actual operation of the power quality monitoring terminal.

[0043] Accordingly, an embodiment of the present invention provides a terminal operation and maintenance quality comprehensive analysis system based on intelligent inspection, comprising:

[0044] A data acquisition module is used to obtain historical power quality monitoring data of each terminal in the distribution network from the power quality monitoring system;

[0045] An evaluation index calculation module is used to calculate the terminal data quality, terminal communication reliability, terminal failure frequency and terminal maintenance time corresponding to each terminal according to the historical power quality monitoring data of each terminal, as the operation and maintenance quality evaluation index of each terminal;

[0046] A weight determination module, used to obtain a first weight value of each terminal through a hierarchical analysis method according to the operation and maintenance quality evaluation index of each terminal, and obtain a second weight value of each terminal through an entropy weight method;

[0047] A comprehensive score determination module, configured to obtain a comprehensive score of the operation and maintenance quality of each terminal by using a good-bad solution distance method according to the first weight value and the second weight value and in combination with the operation and maintenance quality evaluation index of each terminal;

[0048] The control module is used to control the operation and maintenance strategy of each terminal in the distribution network according to the comprehensive operation and maintenance quality score of each terminal.

[0049] It can be understood that, compared with the prior art, the system provided by the present invention obtains and stores the historical power quality monitoring data of the power quality monitoring system for a period of time, and calculates the weight value of the terminal operation and maintenance quality evaluation through the hierarchical analysis method and the entropy weight method based on four indicators such as terminal data quality, terminal communication reliability, terminal fault frequency, and terminal maintenance time, and combines the superior and inferior solution distance method to calculate the comprehensive weight, which can make full use of the information of the original data, avoid the subjectivity of the data, and reasonably realize the comprehensive evaluation of the terminal operation and maintenance quality, and provide theoretical support for the establishment of the operation and maintenance evaluation system of the power quality monitoring terminal in operation. At the same time, the operation and maintenance quality evaluation results of the power quality monitoring terminal are updated regularly, which can realize the online intelligent judgment of the actual operation of the power quality monitoring terminal, which is conducive to reducing the terminal fault detection and operation and maintenance work, and provides an objective and scientific basis for the power grid company to carry out technical supervision of power quality.

[0050] Furthermore, the evaluation index calculation module specifically includes:

[0051] The terminal data quality calculation submodule is used to calculate the terminal data accuracy, terminal data completeness and terminal data efficiency of each terminal according to the historical power quality monitoring data, and obtain the terminal data quality corresponding to each terminal;

[0052] The terminal communication reliability calculation submodule is used to obtain the terminal communication reliability according to the communication interruption time of each terminal in the historical power quality monitoring data, the expected number of power quality monitoring data to be obtained and the time interval for statistical data;

[0053] The terminal fault frequency calculation submodule is used to calculate the sum of the number of faults of each terminal in the historical power quality monitoring data to obtain the terminal fault frequency corresponding to each terminal;

[0054] The terminal maintenance duration calculation submodule is used to respectively calculate the sum of the maintenance time of each terminal in the historical power quality monitoring data to obtain the terminal maintenance duration corresponding to each terminal.

[0055] It can be understood that the system provided by the present invention calculates the terminal data quality, terminal communication reliability, terminal failure frequency and terminal maintenance time corresponding to each terminal, and comprehensively evaluates the operation quality and maintenance status of the terminals that have been connected to the power quality monitoring system, thereby helping system operation and maintenance personnel to quickly discover and identify problem terminals, improve the efficiency and personnel input of terminal operation and maintenance, and also improve the online monitoring quality of the State Grid power quality monitoring system.

[0056] Furthermore, the terminal data quality calculation submodule specifically includes:

[0057] A data accuracy calculation unit, used to obtain the data accuracy according to the total data quantity and the abnormal change rate data quantity in the historical power quality monitoring data;

[0058] A data integrity rate calculation unit, used to obtain a data integrity rate according to the total amount of data in the historical power quality monitoring data and the amount of missing data caused by device failure;

[0059] The data effectiveness calculation unit is used to obtain the data effectiveness according to the total data quantity and the time stamp disorder data quantity in the historical power quality monitoring data.

[0060] It can be understood that the system provided by the present invention records the number of abnormal change rate data, the number of missing data caused by device failures, and the number of data with disordered timestamps, which can describe the terminal data quality in multiple dimensions and more accurately evaluate the terminal operation and maintenance quality.

[0061] Furthermore, the weight determination module specifically includes: a first weight determination submodule, the first weight determination submodule including:

[0062] A judgment matrix construction unit, used to obtain a judgment matrix by a consistent matrix method according to the operation and maintenance quality evaluation indicators of each terminal; wherein the number of rows of the judgment matrix corresponds to the number of operation and maintenance quality evaluation indicators, the number of columns of the judgment matrix corresponds to the number of terminals, and the elements of the judgment matrix are comparison weights of the rows and columns corresponding to the current elements;

[0063] An eigenvalue determination unit, used to calculate the eigenvalues ​​in the judgment matrix by an eigenvector method to obtain a maximum eigenvalue and an eigenvector corresponding to the maximum eigenvalue;

[0064] A normalization unit, used for normalizing the feature vector to obtain a normalized feature vector;

[0065] A consistency check unit is used to calculate the consistency index of the maximum eigenvalue, and calculate the consistency ratio in combination with the random consistency index, and judge whether the consistency check is passed according to the consistency ratio; if the consistency check is not passed, the judgment matrix is ​​iteratively updated; if the consistency check is passed, the normalized eigenvector is used as the first weight coefficient vector to obtain the first weight value of each terminal.

[0066] It can be understood that the system provided by the present invention uses a hierarchical analysis method to hierarchically divide the importance of different operation and maintenance quality evaluation indicators to operation and maintenance and management personnel, which helps to optimize the resource allocation of power quality monitoring terminals and improve operation and maintenance efficiency and quality.

[0067] Furthermore, the weight determination module specifically includes: a second weight determination submodule, and the second weight determination submodule includes:

[0068] An evaluation matrix construction unit is used to construct an evaluation matrix according to the operation and maintenance quality evaluation indicators of each terminal; wherein the number of rows of the evaluation matrix corresponds to the number of operation and maintenance quality evaluation indicators, the number of columns of the evaluation matrix corresponds to the number of terminals, and the elements of the evaluation matrix are the proportion of the terminal corresponding to the current element under the operation and maintenance quality evaluation indicator corresponding to the current element to all operation and maintenance quality evaluation indicators;

[0069] The entropy weight calculation unit is used to calculate the weight of each operation and maintenance quality evaluation indicator according to the evaluation matrix and the entropy value calculation formula to obtain the second weight value of each terminal.

[0070] It can be understood that the system provided by the present invention obtains the second weight value of each terminal through the entropy weight method, and calculates the weight of each operation and maintenance quality evaluation index through information entropy, which can objectively describe the operation and maintenance quality evaluation indicators of each terminal and lay the foundation for efficient comprehensive score calculation.

[0071] Furthermore, the comprehensive score determination module specifically includes:

[0072] A forward matrix construction submodule is used to take the terminal data quality and the terminal communication reliability rate as the extremely large index, and take the terminal failure frequency and the terminal maintenance duration as the extremely small index; perform forward processing on the extremely small index, and construct a forward matrix according to the extremely large index and the extremely small index after the forward processing;

[0073] A standardized matrix determination submodule, used for dividing each element in the forward matrix by the Euclidean norm of the forward matrix to obtain a standardized matrix;

[0074] A comprehensive weight value determination submodule, used to calculate a weighted sum of the first weight value and the second weight value to obtain a comprehensive weight value;

[0075] A weighted normalized matrix calculation submodule, used to obtain a weighted normalized matrix according to the comprehensive weight value and the normalized matrix;

[0076] A distance determination submodule, used to calculate the maximum and minimum values ​​of each operation and maintenance quality evaluation indicator according to the weighted normalization matrix, and calculate the positive ideal solution distance and the negative ideal solution distance according to the maximum and minimum values ​​of each operation and maintenance quality evaluation indicator;

[0077] The evaluation submodule is used to obtain the comprehensive score of the operation and maintenance quality of each terminal according to the positive ideal solution distance and the negative ideal solution distance.

[0078] It can be understood that the system provided by the present invention divides each element by the Euclidean norm of the normalized matrix, so that all elements of the normalized matrix are positive numbers. The combined use of the superior and inferior solution distance method to calculate the comprehensive weight can make full use of the information of historical power quality monitoring and realize online intelligent determination of the actual operation of the power quality monitoring terminal. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 : A flowchart of the steps of the comprehensive analysis method of terminal operation and maintenance quality based on intelligent inspection provided by an embodiment of the present invention;

[0080] Figure 2 : A schematic diagram of the operation and maintenance quality evaluation indexes of each terminal in the terminal operation and maintenance quality comprehensive analysis method based on intelligent inspection provided in an embodiment of the present invention;

[0081] Figure 3 : A structural diagram of the terminal operation and maintenance quality comprehensive analysis system based on intelligent inspection provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0082] 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.

[0083] In the description of this specification, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0084] Embodiment 1

[0085] Please refer to Figure 1 , which is a flow chart of the steps of the terminal operation and maintenance quality comprehensive analysis method based on intelligent inspection provided by an embodiment of the present invention, including steps S101-S105, and each step is specifically as follows.

[0086] S101: Acquire historical power quality monitoring data of each terminal in the distribution network from the power quality monitoring system.

[0087] S102: Calculate the terminal data quality, terminal communication reliability, terminal failure frequency and terminal maintenance duration corresponding to each terminal according to the historical power quality monitoring data of each terminal as operation and maintenance quality evaluation indicators of each terminal.

[0088] In this embodiment, Figure 2 The diagram is a schematic diagram of the operation and maintenance quality evaluation index of each terminal. According to the historical power quality monitoring data, the terminal data accuracy, terminal data completeness and terminal data efficiency of each terminal are calculated to obtain the terminal data quality corresponding to each terminal.

[0089] As a preferred solution, the data accuracy is obtained according to the total data quantity and the abnormal change rate data quantity in the historical power quality monitoring data. The specific formula is: Among them, λ1 is the data accuracy; M is the total data quantity; M1 is the number of data with abnormal change rate.

[0090] It should be noted that the principles for judging abnormal change rate data are as follows:

[0091]

[0092]

[0093]

[0094]

[0095] Among them, x k is the value of the kth data point; f1 is the previous change rate of the kth data point; f2 is the subsequent change rate of the kth data point. Set the judgment coefficient v. If f1>v and f2>v are satisfied, the data of the target point is abnormal data.

[0096] As a preferred solution, the data integrity rate is obtained according to the total amount of data in the historical power quality monitoring data and the amount of missing data caused by device failure. The specific formula is: Wherein, λ2 is the data integrity rate, M′2 is the amount of missing data caused by the device failure; and N is the total amount of data.

[0097] It should be noted that the power quality monitoring terminal collects statistical data at a fixed statistical interval, τ represents the time interval of statistical data, T represents the communication interruption time between the device and the system, N represents the number of power quality monitoring data expected to be obtained by the system, and M2 represents the number of power quality monitoring data actually obtained. Excluding the power-off time of the device and the network failure time, the number of missing data caused by the device failure is calculated as M′2:

[0098] As a preferred solution, the data efficiency is obtained according to the total data quantity and the number of data with disordered timestamps in the historical power quality monitoring data. The specific formula is: Wherein, λ3 is the data efficiency; M3 is the number of the timestamp disordered data; and N is the total number of data.

[0099] In this embodiment, the terminal communication reliability rate is obtained according to the communication interruption time of each terminal in the historical power quality monitoring data, the expected number of power quality monitoring data to be obtained, and the time interval for statistical data. The specific formula is: Among them, λ4 is the terminal communication reliability rate; T is the communication interruption time of each terminal; τ is the time interval of the statistical data; and N is the expected number of power quality monitoring data to be obtained.

[0100] In this embodiment, the sum of the number of terminal failures such as failure / shutdown / offline of the operating power quality monitoring terminal device caused by non-human and natural factors of each terminal in the historical power quality monitoring data is calculated respectively to obtain the terminal failure frequency corresponding to each terminal.

[0101] In this embodiment, the sum of the time required for operation and maintenance personnel to resolve the failure / shutdown / offline status of the operating terminal caused by non-human and natural factors of each terminal in the historical power quality monitoring data is calculated separately to obtain the terminal maintenance time corresponding to each terminal.

[0102] S103: According to the operation and maintenance quality evaluation index of each terminal, a first weight value of each terminal is obtained by using a hierarchy analysis method, and a second weight value of each terminal is obtained by using an entropy weight method.

[0103] In this embodiment, according to the operation and maintenance quality evaluation indicators of each terminal, a judgment matrix is ​​obtained by a consistent matrix method; wherein the number of rows of the judgment matrix corresponds to the number of operation and maintenance quality evaluation indicators, the number of columns of the judgment matrix corresponds to the number of terminals, and the elements of the judgment matrix are the comparison weights of the rows and columns corresponding to the current elements, specifically: In the formula, A mn is the judgment matrix, n is the number of terminals, m is the number of operation and maintenance quality evaluation indicators, a ij It represents the comparison weight of the i-th terminal in this layer relative to the j-th operation and maintenance quality evaluation index.

[0104] In this embodiment, after constructing the judgment matrix A, the eigenvalues ​​of the judgment matrix are obtained by the eigenvector method, and the maximum eigenvalue λ is found. max And its corresponding eigenvector W, that is: AW = λ max W. The feature vector is normalized to obtain a normalized feature vector, and the specific formula is: Where W i is the i-th element in the feature vector W.

[0105] It should be noted that to determine whether the subjective weight coefficient is reasonable, it is also necessary to perform a consistency test on the judgment matrix. First, calculate the consistency index corresponding to the maximum eigenvalue, then calculate the consistency ratio in combination with the random consistency index, and finally determine whether the consistency test has passed based on the size. The specific calculation formula is: In the formula, C I is the consistency index; n is the order of the judgment matrix; R I is the random consistency index; R I See Table 1 for the values.

[0106] Table 1 Average random consistency index

[0107]

[0108]

[0109] As a preferred solution, when C R= 0, it means that the pairwise comparison matrix is ​​completely consistent and passes the consistency test; when C R When <0.1, it means that the pairwise comparison matrix has acceptable consistency and can pass the consistency test. After passing the test, its normalized eigenvector can be used as the first weight coefficient vector. Otherwise, it is necessary to reconstruct the judgment matrix and repeat the above steps until it passes the consistency test.

[0110] In this embodiment, an evaluation matrix is ​​constructed according to the operation and maintenance quality evaluation indicators of each terminal; wherein the number of rows of the evaluation matrix corresponds to the number of operation and maintenance quality evaluation indicators, the number of columns of the evaluation matrix corresponds to the number of terminals, and the elements of the evaluation matrix are the proportion of the terminal corresponding to the current element under the operation and maintenance quality evaluation indicator corresponding to the current element to all operation and maintenance quality evaluation indicators, specifically: Where, X mn is the evaluation matrix;

[0111] In this embodiment, the proportion of the i-th terminal in the j-th operation and maintenance quality evaluation indicator is calculated as: Among them, x ij is the value of the jth operation and maintenance quality evaluation index of the i-th terminal. The entropy value of the j-th index is e j The calculation formula is: Where k = 1 / ln(n)>0, satisfying e j >0. Calculate the weight w of each operation and maintenance quality evaluation indicator j : Finally, the second weight vector μ2 of n operation and maintenance quality evaluation indicators is obtained as follows: μ2=(w1,w2,...,w n ) T .

[0112] As a preferred solution, combining the entropy weight method and the hierarchical analysis method, the comprehensive weight calculation formula for the operation and maintenance quality evaluation index is: β=k1μ1+k2μ2; where: k1 and k2 are the first weight coefficient and the second weight coefficient respectively, and the weight coefficients of both are equally important, that is, k1=k2=0.5.

[0113] S104: According to the first weight value and the second weight value, combined with the operation and maintenance quality evaluation index of each terminal, a comprehensive operation and maintenance quality score of each terminal is obtained by using a superior and inferior solution distance method.

[0114] In this embodiment, the terminal data quality and the terminal communication reliability are used as the extremely large indicators, and the terminal failure frequency and the terminal maintenance duration are used as the extremely small indicators.

[0115] It should be noted that the larger the value of the extremely large index is, the better, and the smaller the value of the extremely small index is, the better.

[0116] In this embodiment, the extremely small indicator is forward-processed, and the formula for converting the extremely small indicator into the extremely large indicator is max-x, where max represents the maximum value in the extremely small indicator sample, and x represents a value in the extremely small indicator sample. A forward-processed matrix is ​​constructed based on the extremely large indicator and the extremely small indicator after the forward processing.

[0117] In this embodiment, each element x in the forward matrix ij Divide the Euclidean norm of the normalized matrix to obtain the standardized matrix Z ij , specifically:

[0118] In this embodiment, the weighted sum of the first weight value and the second weight value is calculated to obtain a comprehensive weight value, specifically: β=k1μ1+k2μ2; wherein μ1 and μ2 are the first weight vector and the second weight vector, respectively; k1 and k2 are the first weight coefficient and the second weight coefficient, respectively, and both weight coefficients are equally important, that is, equivalent to k1=k2=0.5.

[0119] In this embodiment, according to the comprehensive weight value β and the standardized matrix Z ij , get the weighted normalized matrix Y ij =βZ ij .

[0120] In this embodiment, the maximum value X of each operation and maintenance quality evaluation index is calculated according to the weighted normalization matrix. + and minimum value X - , specifically:

[0121]

[0122]

[0123] In the formula, r ij is the element in the i-th row and j-th column of the weighted normalization matrix, is the maximum value of the jth column, is the minimum value of the jth column; according to the maximum and minimum values ​​of each operation and maintenance quality evaluation indicator, calculate the positive ideal solution distance D i + and negative ideal solution distance The specific formula is:

[0124] In this embodiment, according to the positive ideal solution distance D i + and negative ideal solution distance Get the comprehensive score C of the operation and maintenance quality of each terminal i , the specific formula is:

[0125] S105: According to the comprehensive operation and maintenance quality scores of the terminals, the operation and maintenance strategies of the terminals in the distribution network are adjusted.

[0126] In this embodiment, the comprehensive operation and maintenance quality scores of the terminals are sorted, so that the terminal with the lowest comprehensive operation and maintenance quality score can be quickly located, and the corresponding operation and maintenance strategy can be adjusted according to the operation and maintenance quality assessment indicators corresponding to the terminal with the lowest comprehensive operation and maintenance quality score that do not meet the preset standards.

[0127] The method provided by the present invention obtains and stores the historical power quality monitoring data of a period of time of the power quality monitoring system, and calculates the weight value of the terminal operation and maintenance quality evaluation through the hierarchical analysis method and the entropy weight method based on four indicators such as terminal data quality, terminal communication reliability, terminal fault frequency, and terminal maintenance time, and combines the superior and inferior solution distance method to calculate the comprehensive weight, which can make full use of the information of the original data, avoid the subjectivity of the data, and reasonably realize the comprehensive evaluation of the terminal operation and maintenance quality, and provide theoretical support for the establishment of the operation and maintenance evaluation system of the power quality monitoring terminal in operation. At the same time, the operation and maintenance quality evaluation results of the power quality monitoring terminal are updated regularly, which can realize the online intelligent judgment of the actual operation of the power quality monitoring terminal, which is conducive to reducing the terminal fault investigation and operation and maintenance work, and provides an objective and scientific basis for the power grid company to carry out technical supervision of power quality.

[0128] Embodiment 2

[0129] Please refer to Figure 3 , which is a structural diagram of a terminal operation and maintenance quality comprehensive analysis system based on intelligent inspection provided in an embodiment of the present invention, wherein the system includes a data acquisition module 201, an evaluation index calculation module 202, a weight determination module 203, a comprehensive score determination module 204 and a control module 205.

[0130] The data acquisition module is used to acquire historical power quality monitoring data of each terminal in the distribution network from the power quality monitoring system.

[0131] The evaluation index calculation module is used to calculate the terminal data quality, terminal communication reliability, terminal failure frequency and terminal maintenance time corresponding to each terminal according to the historical power quality monitoring data of each terminal, as the operation and maintenance quality evaluation index of each terminal.

[0132] The weight determination module is used to obtain the first weight value of each terminal through the hierarchical analysis method according to the operation and maintenance quality evaluation index of each terminal, and to obtain the second weight value of each terminal through the entropy weight method.

[0133] The comprehensive score determination module is used to obtain the comprehensive score of the operation and maintenance quality of each terminal through the superior and inferior solution distance method according to the first weight value and the second weight value in combination with the operation and maintenance quality evaluation index of each terminal.

[0134] The control module is used to control the operation and maintenance strategy of each terminal in the distribution network according to the comprehensive operation and maintenance quality score of each terminal.

[0135] In this embodiment, the evaluation index calculation module specifically includes: a terminal data quality calculation submodule, a terminal communication reliability calculation submodule, a terminal fault frequency calculation submodule and a terminal maintenance time calculation submodule. The terminal data quality calculation submodule is used to calculate the terminal data accuracy, terminal data integrity rate and terminal data efficiency of each terminal according to the historical power quality monitoring data, and obtain the terminal data quality corresponding to each terminal; the terminal communication reliability calculation submodule is used to obtain the terminal communication reliability according to the communication interruption time of each terminal in the historical power quality monitoring data, the expected number of power quality monitoring data and the time interval for statistical data; the terminal fault frequency calculation submodule is used to calculate the sum of the number of faults of each terminal in the historical power quality monitoring data, and obtain the terminal fault frequency corresponding to each terminal; the terminal maintenance time calculation submodule is used to calculate the sum of the maintenance time of each terminal in the historical power quality monitoring data, and obtain the terminal maintenance time corresponding to each terminal.

[0136] In this embodiment, the terminal data quality calculation submodule specifically includes: a data accuracy calculation unit, a data integrity calculation unit and a data efficiency calculation unit. The data accuracy calculation unit is used to obtain the data accuracy according to the total data quantity and the number of abnormal change rate data in the historical power quality monitoring data; the data integrity calculation unit is used to obtain the data integrity rate according to the total data quantity and the number of missing data caused by device failure in the historical power quality monitoring data; the data efficiency calculation unit is used to obtain the data efficiency according to the total data quantity and the number of data with disordered timestamps in the historical power quality monitoring data.

[0137] In this embodiment, the weight determination module specifically includes: a first weight determination submodule, which includes: a judgment matrix construction unit, an eigenvalue determination unit, a normalization unit and a consistency check unit. The judgment matrix construction unit is used to obtain a judgment matrix by a consistent matrix method according to the operation and maintenance quality evaluation indicators of each terminal; wherein the number of rows of the judgment matrix corresponds to the number of operation and maintenance quality evaluation indicators, the number of columns of the judgment matrix corresponds to the number of terminals, and the elements of the judgment matrix are the comparison weights of the rows and columns corresponding to the current elements; the eigenvalue determination unit is used to calculate the eigenvalues ​​in the judgment matrix by an eigenvector method to obtain the maximum eigenvalue and the eigenvector corresponding to the maximum eigenvalue; the normalization unit is used to normalize the eigenvector to obtain a normalized eigenvector; the consistency check unit is used to calculate the consistency index of the maximum eigenvalue, combine the random consistency index, calculate the consistency ratio, and judge whether the consistency check is passed according to the consistency ratio; if the consistency check is not passed, the judgment matrix is ​​iteratively updated, and if the consistency check is passed, the normalized eigenvector is used as the first weight coefficient vector to obtain the first weight value of each terminal.

[0138] In this embodiment, the weight determination module specifically includes: a second weight determination submodule, and the second weight determination submodule includes: an evaluation matrix construction unit and an entropy weight calculation unit. The evaluation matrix construction unit is used to construct an evaluation matrix according to the operation and maintenance quality evaluation indicators of each terminal; wherein the number of rows of the evaluation matrix corresponds to the number of operation and maintenance quality evaluation indicators, the number of columns of the evaluation matrix corresponds to the number of terminals, and the elements of the evaluation matrix are the proportion of the terminal corresponding to the current element under the operation and maintenance quality evaluation indicator corresponding to the current element to all operation and maintenance quality evaluation indicators; the entropy weight calculation unit is used to calculate the weight of each operation and maintenance quality evaluation indicator according to the evaluation matrix and the entropy value calculation formula to obtain the second weight value of each terminal.

[0139] In this embodiment, the comprehensive score determination module specifically includes: a forward matrix construction submodule, a standardized matrix determination submodule, a comprehensive weight value determination submodule, a weighted normalized matrix calculation submodule, a distance determination submodule and an evaluation submodule. The forward matrix construction submodule is used to take the terminal data quality and the terminal communication reliability rate as extremely large indicators, and the terminal failure frequency and the terminal maintenance time as extremely small indicators; forward process the extremely small indicators, and construct a forward matrix based on the extremely large indicators and the extremely small indicators after forward processing; the standardized matrix determination submodule is used to divide each element in the forward matrix by the Euclidean norm of the forward matrix to obtain a standardized matrix; the comprehensive weight value determination submodule is used to calculate the first weight value and the weighted sum of the first and second weight values ​​to obtain a comprehensive weight value; the weighted normalization matrix calculation submodule is used to obtain a weighted normalization matrix according to the comprehensive weight value and the standardized matrix; the distance determination submodule is used to calculate the maximum and minimum values ​​of each operation and maintenance quality evaluation indicator according to the weighted normalization matrix, and calculate the positive ideal solution distance and the negative ideal solution distance according to the maximum and minimum values ​​of each operation and maintenance quality evaluation indicator; the evaluation submodule is used to obtain the comprehensive operation and maintenance quality score of each terminal according to the positive ideal solution distance and the negative ideal solution distance.

[0140] The system provided by the present invention acquires and stores the historical power quality monitoring data of a period of time of the power quality monitoring system, and calculates the weight value of the terminal operation and maintenance quality evaluation through the hierarchical analysis method and the entropy weight method based on four indicators such as terminal data quality, terminal communication reliability, terminal fault frequency, and terminal maintenance time, and combines the superior and inferior solution distance method to calculate the comprehensive weight, which can make full use of the information of the original data, avoid the subjectivity of the data, and reasonably realize the comprehensive evaluation of the terminal operation and maintenance quality, and provide theoretical support for the establishment of the operation and maintenance evaluation system of the power quality monitoring terminal in operation. At the same time, the operation and maintenance quality evaluation results of the power quality monitoring terminal are updated regularly, which can realize the online intelligent judgment of the actual operation of the power quality monitoring terminal, which is conducive to reducing the terminal fault detection and operation and maintenance work, and provides an objective and scientific basis for the power grid company to carry out technical supervision of power quality.

[0141] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A comprehensive analysis method for terminal operation and maintenance quality based on intelligent inspection, characterized in that: include: Obtain historical power quality monitoring data of each terminal in the distribution network from the power quality monitoring system; According to the historical power quality monitoring data of each terminal, the terminal data quality, terminal communication reliability, terminal failure frequency and terminal maintenance time corresponding to each terminal are calculated as operation and maintenance quality evaluation indicators of each terminal; According to the operation and maintenance quality evaluation index of each terminal, a first weight value of each terminal is obtained by using a hierarchical analysis method, and a second weight value of each terminal is obtained by using an entropy weight method; According to the first weight value and the second weight value, in combination with the operation and maintenance quality evaluation index of each terminal, a comprehensive operation and maintenance quality score of each terminal is obtained by using a good-bad solution distance method; According to the comprehensive operation and maintenance quality scores of the terminals, the operation and maintenance strategies of the terminals in the distribution network are adjusted; Among them, the operation and maintenance quality comprehensive score of each terminal is obtained by the superior and inferior solution distance method according to the first weight value and the second weight value, in combination with the operation and maintenance quality evaluation index of each terminal, specifically including: The terminal data quality and the terminal communication reliability are used as the maximum large-scale indicators, and the terminal failure frequency and the terminal maintenance duration are used as the minimum small-scale indicators; Performing positive processing on the extremely small index, and constructing a positive matrix according to the extremely large index and the extremely small index after the positive processing; Dividing each element in the forward matrix by the Euclidean norm of the forward matrix to obtain a standardized matrix; Calculating a weighted sum of the first weight value and the second weight value to obtain a comprehensive weight value; Obtaining a weighted normalized matrix according to the comprehensive weight value and the normalized matrix; According to the weighted normalization matrix, the maximum value and the minimum value of each operation and maintenance quality evaluation indicator are calculated, and according to the maximum value and the minimum value of each operation and maintenance quality evaluation indicator, the positive ideal solution distance and the negative ideal solution distance are calculated; According to the positive ideal solution distance and the negative ideal solution distance, a comprehensive score of the operation and maintenance quality of each terminal is obtained.

2. The terminal operation and maintenance quality comprehensive analysis method based on intelligent inspection according to claim 1 is characterized in that: The calculating of the terminal data quality, terminal communication reliability, terminal failure frequency and terminal maintenance duration corresponding to each terminal according to the historical power quality monitoring data of each terminal specifically includes: According to the historical power quality monitoring data, the terminal data accuracy, terminal data completeness and terminal data efficiency of each terminal are calculated to obtain the terminal data quality corresponding to each terminal; Obtaining a terminal communication reliability rate according to the communication interruption time of each terminal in the historical power quality monitoring data, the expected number of power quality monitoring data to be obtained, and the time interval for statistical data; Calculating the sum of the number of failures of each terminal in the historical power quality monitoring data respectively to obtain the terminal failure frequency corresponding to each terminal; The sum of the maintenance time of each terminal in the historical power quality monitoring data is calculated respectively to obtain the terminal maintenance time corresponding to each terminal.

3. The terminal operation and maintenance quality comprehensive analysis method based on intelligent inspection according to claim 2 is characterized in that: The calculating of the terminal data accuracy, terminal data integrity and terminal data efficiency according to the historical power quality monitoring data to obtain the terminal data quality corresponding to each terminal specifically includes: Obtaining data accuracy based on the total data quantity and the data quantity with abnormal change rate in the historical power quality monitoring data; Obtaining a data integrity rate according to the total amount of data in the historical power quality monitoring data and the amount of missing data caused by device failure; The data efficiency is obtained according to the total data quantity and the data quantity with disordered timestamp in the historical power quality monitoring data.

4. The terminal operation and maintenance quality comprehensive analysis method based on intelligent inspection according to claim 1 is characterized in that: The step of obtaining a first weight value of each terminal by using a hierarchical analysis method according to the operation and maintenance quality evaluation index of each terminal specifically includes: According to the operation and maintenance quality evaluation indicators of each terminal, a judgment matrix is ​​obtained by a consistent matrix method; wherein the number of rows of the judgment matrix corresponds to the number of operation and maintenance quality evaluation indicators, the number of columns of the judgment matrix corresponds to the number of terminals, and the elements of the judgment matrix are comparison weights of the rows and columns corresponding to the current elements; Calculate the eigenvalues ​​in the judgment matrix by the eigenvector method to obtain the maximum eigenvalue and the eigenvector corresponding to the maximum eigenvalue; Normalizing the feature vector to obtain a normalized feature vector; Calculate the consistency index of the maximum eigenvalue, combine it with the random consistency index, calculate the consistency ratio, and determine whether the consistency test is passed according to the consistency ratio; If the consistency check fails, the judgment matrix is ​​iteratively updated; if the consistency check passes, the normalized feature vector is used as a first weight coefficient vector to obtain a first weight value of each terminal.

5. The terminal operation and maintenance quality comprehensive analysis method based on intelligent inspection according to claim 1 is characterized in that: The obtaining of the second weight value of each terminal by the entropy weight method specifically includes: According to the operation and maintenance quality evaluation indicators of each terminal, an evaluation matrix is ​​constructed; wherein the number of rows of the evaluation matrix corresponds to the number of operation and maintenance quality evaluation indicators, the number of columns of the evaluation matrix corresponds to the number of terminals, and the elements of the evaluation matrix are the proportion of the terminal corresponding to the current element under the operation and maintenance quality evaluation indicator corresponding to the current element to all operation and maintenance quality evaluation indicators; According to the evaluation matrix and in combination with the entropy value calculation formula, the weight of each operation and maintenance quality evaluation indicator is calculated to obtain a second weight value of each terminal.

6. A terminal operation and maintenance quality comprehensive analysis system based on intelligent inspection, characterized in that: include: A data acquisition module is used to obtain historical power quality monitoring data of each terminal in the distribution network from the power quality monitoring system; An evaluation index calculation module is used to calculate the terminal data quality, terminal communication reliability, terminal failure frequency and terminal maintenance time corresponding to each terminal according to the historical power quality monitoring data of each terminal, as the operation and maintenance quality evaluation index of each terminal; A weight determination module, used to obtain a first weight value of each terminal through a hierarchical analysis method according to the operation and maintenance quality evaluation index of each terminal, and obtain a second weight value of each terminal through an entropy weight method; A comprehensive score determination module, configured to obtain a comprehensive score of the operation and maintenance quality of each terminal by using a good-bad solution distance method according to the first weight value and the second weight value and in combination with the operation and maintenance quality evaluation index of each terminal; A control module, used to control the operation and maintenance strategy of each terminal in the distribution network according to the comprehensive operation and maintenance quality score of each terminal; Among them, the operation and maintenance quality comprehensive score of each terminal is obtained by the superior and inferior solution distance method according to the first weight value and the second weight value, in combination with the operation and maintenance quality evaluation index of each terminal, specifically including: The terminal data quality and the terminal communication reliability are used as the maximum large-scale indicators, and the terminal failure frequency and the terminal maintenance duration are used as the minimum small-scale indicators; Performing positive processing on the extremely small index, and constructing a positive matrix according to the extremely large index and the extremely small index after the positive processing; Dividing each element in the forward matrix by the Euclidean norm of the forward matrix to obtain a standardized matrix; Calculating a weighted sum of the first weight value and the second weight value to obtain a comprehensive weight value; Obtaining a weighted normalized matrix according to the comprehensive weight value and the normalized matrix; According to the weighted normalization matrix, the maximum value and the minimum value of each operation and maintenance quality evaluation indicator are calculated, and according to the maximum value and the minimum value of each operation and maintenance quality evaluation indicator, the positive ideal solution distance and the negative ideal solution distance are calculated; According to the positive ideal solution distance and the negative ideal solution distance, a comprehensive score of the operation and maintenance quality of each terminal is obtained.

7. The terminal operation and maintenance quality comprehensive analysis system based on intelligent inspection according to claim 6, characterized in that: The evaluation index calculation module specifically includes: The terminal data quality calculation submodule is used to calculate the terminal data accuracy, terminal data completeness and terminal data efficiency of each terminal according to the historical power quality monitoring data, and obtain the terminal data quality corresponding to each terminal; The terminal communication reliability calculation submodule is used to obtain the terminal communication reliability according to the communication interruption time of each terminal in the historical power quality monitoring data, the expected number of power quality monitoring data to be obtained and the time interval for statistical data; The terminal fault frequency calculation submodule is used to calculate the sum of the number of faults of each terminal in the historical power quality monitoring data to obtain the terminal fault frequency corresponding to each terminal; The terminal maintenance duration calculation submodule is used to respectively calculate the sum of the maintenance time of each terminal in the historical power quality monitoring data to obtain the terminal maintenance duration corresponding to each terminal.

8. The terminal operation and maintenance quality comprehensive analysis system based on intelligent inspection according to claim 7, characterized in that: The terminal data quality calculation submodule specifically includes: A data accuracy calculation unit, used to obtain the data accuracy according to the total data quantity and the abnormal change rate data quantity in the historical power quality monitoring data; A data integrity rate calculation unit, used to obtain a data integrity rate according to the total amount of data in the historical power quality monitoring data and the amount of missing data caused by device failure; The data effectiveness calculation unit is used to obtain the data effectiveness according to the total data quantity and the time stamp disorder data quantity in the historical power quality monitoring data.

9. The terminal operation and maintenance quality comprehensive analysis system based on intelligent inspection according to claim 6, characterized in that: The weight determination module specifically includes: a first weight determination submodule, the first weight determination submodule including: A judgment matrix construction unit, used to obtain a judgment matrix by a consistent matrix method according to the operation and maintenance quality evaluation indicators of each terminal; wherein the number of rows of the judgment matrix corresponds to the number of operation and maintenance quality evaluation indicators, the number of columns of the judgment matrix corresponds to the number of terminals, and the elements of the judgment matrix are comparison weights of the rows and columns corresponding to the current elements; An eigenvalue determination unit, used to calculate the eigenvalues ​​in the judgment matrix by an eigenvector method to obtain a maximum eigenvalue and an eigenvector corresponding to the maximum eigenvalue; A normalization unit, used for normalizing the feature vector to obtain a normalized feature vector; A consistency check unit is used to calculate the consistency index of the maximum eigenvalue, and calculate the consistency ratio in combination with the random consistency index, and judge whether the consistency check is passed according to the consistency ratio; if the consistency check is not passed, the judgment matrix is ​​iteratively updated; if the consistency check is passed, the normalized eigenvector is used as the first weight coefficient vector to obtain the first weight value of each terminal.

10. The terminal operation and maintenance quality comprehensive analysis system based on intelligent inspection according to claim 6, characterized in that: The weight determination module specifically includes: a second weight determination submodule, and the second weight determination submodule includes: An evaluation matrix construction unit is used to construct an evaluation matrix according to the operation and maintenance quality evaluation indicators of each terminal; wherein the number of rows of the evaluation matrix corresponds to the number of operation and maintenance quality evaluation indicators, the number of columns of the evaluation matrix corresponds to the number of terminals, and the elements of the evaluation matrix are the proportion of the terminal corresponding to the current element under the operation and maintenance quality evaluation indicator corresponding to the current element to all operation and maintenance quality evaluation indicators; The entropy weight calculation unit is used to calculate the weight of each operation and maintenance quality evaluation indicator according to the evaluation matrix and the entropy value calculation formula to obtain the second weight value of each terminal.

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