Method and system for evaluating lean management effect of power distribution area

Abstract

The invention discloses a lean management effect evaluation method and system for a power distribution area, and belongs to the technical field of data processing. The subjective preference of an evaluation subject and the objective authenticity of an evaluation object are fully analyzed through a Delphi analysis method and a principal analytic hierarchy process for internal indexes to obtain a subjective weight and an objective weight, and then the subjective weight and the objective weight are comprehensively considered through a comprehensive weighting method to obtain a comprehensive weight; according to the comprehensive weight, overall analysis is carried out on the power distribution area management data corresponding to the corresponding indexes in the index evaluation system to obtain a management effect evaluation result, so that accurate and comprehensive evaluation of the lean management condition of the power distribution area is realized, and reference is provided for power distribution network and marketing management operation of the power distribution area. Therefore, the management effect of the power distribution area is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and more specifically, to a method and system for evaluating the lean management effect of a distribution transformer area. Background Art

[0002] The operation status of the distribution transformer area directly affects whether power customers can use electricity normally. Conducting real-time monitoring and lean management of the operation status of the distribution transformer area and taking precise measures for substation area management are of great significance for ensuring the stability and reliability of power supply. With the development of the power industry and the intensification of market competition, how to improve the efficiency and service quality of substation area management has gradually become the focus of attention of scholars and industry experts. Research shows that by implementing Value Stream Mapping, it can help identify and eliminate non-value-added activities in substation area management, thereby optimizing resource allocation and improving operation and maintenance efficiency, and can reduce human subjectivity to a certain extent. However, by using data envelopment analysis, fuzzy comprehensive evaluation method, principal component analysis method, etc. for the comprehensive evaluation of medium-voltage distribution networks, although human subjectivity is avoided, it is impossible to judge and evaluate the importance of various operation indicators of low-voltage distribution transformer areas, and it is difficult to provide reference for marketing management operation.

[0003] Chinese Patent, Publication No.: CN117910723A, Publication Date: April 19, 2024, discloses a method and system for managing a distribution transformer area based on big data. By obtaining historical distribution transformer area management operation data and distribution transformer area management monitoring data based on big data technology; identifying equipment nodes for the distribution transformer area management monitoring data to generate distribution facility nodes; performing node coupling analysis on the distribution facility nodes to generate node coupling data; performing dynamic performance calculation on the distribution facility nodes to generate node dynamic performance data; performing optimal topology network analysis on the node dynamic performance data based on the node coupling data to generate optimal topology network data; performing network topology association fitting on the distribution facility nodes through the optimal topology network data to construct a distribution node topology network; using the distribution node topology network to perform edge state detection on the distribution facility nodes to generate edge state data, so as to realize the distribution management of the distribution transformer area. However, it is impossible to judge and evaluate the importance of various operation indicators of low-voltage distribution transformer areas, and it is difficult to provide reference for marketing management operation, and it is not flexible enough in actual implementation. Summary of the Invention

[0004] In view of the problem of low evaluation accuracy caused by the difficulty in taking into account the subjective preferences of evaluation subjects and the objective authenticity of evaluation objects when evaluating the management effect of the existing distribution transformer area management method, the present invention provides a method and system for evaluating the lean management effect of a distribution transformer area. By constructing an index evaluation system, the subjective weight and objective weight are obtained through the Delphi analysis method and the analytic hierarchy process for the subjective preferences of the evaluation subject and the objective authenticity of the evaluation object respectively for the internal indicators of the system. Then, the subjective weight and objective weight are comprehensively considered through the comprehensive weighting method to obtain the comprehensive weight. According to the comprehensive weight, the management data of the distribution transformer area corresponding to the corresponding indicators in the index evaluation system is analyzed as a whole to obtain the management effect evaluation result, realizing an accurate and comprehensive evaluation of the lean management status of the transformer area, and at the same time providing a reference for the operation of the distribution network and marketing management of the transformer area, thereby improving the management effect of the distribution transformer area.

[0005] In a first aspect, a technical solution provided in an embodiment of the present invention is: a method for evaluating the lean management effect of a distribution transformer area, comprising the following steps: S1. Collect the management data of the distribution transformer area based on the data collection principle; S2. Extract the evaluation indicators of the management effect of the distribution transformer area by analyzing the characteristics of the management data of the distribution transformer area based on the operation conditions of the transformer area; construct an index evaluation system based on the management directions to which the evaluation indicators of the management effect of the transformer area belong; S3. Analyze the weights of the indicators in the index evaluation system based on the Delphi analysis method to obtain the subjective weight; analyze the weights of the indicators in the index evaluation system based on the principal component analysis method to obtain the objective weight; the comprehensive weighting method responds to the subjective weight and the objective weight to obtain the comprehensive weight; S4. The index index calculation principle responds to the management data of the distribution transformer area corresponding to the indicators in the index evaluation system to obtain the index index, and performs weighted summation on the index index based on the comprehensive weight to obtain the management effect score.

[0006] In this solution, by analyzing the characteristics of the management data of the distribution transformer area, various indicators reflecting the management effect of the distribution transformer area are extracted, thereby simplifying the analysis and evaluation difficulty of the complex data of the distribution transformer area and improving the evaluation efficiency; by adopting the combination of the Delphi analysis method and the analytic hierarchy process, the interference of human subjective factors on the evaluation result is effectively avoided, and the subjective preferences of the evaluation subject and the objective authenticity of the evaluation object are taken into account, thereby greatly improving the evaluation accuracy; By performing weighted summation on each indicator in the index evaluation system respectively, the management operation status of the distribution transformer area is comprehensively analyzed, and the complex management operation status is quantified into a management effect score that is convenient to understand, thereby reducing the evaluation understanding difficulty, providing a scientific reference basis for the management of the transformer area, and also indicating the direction for the future management development of the transformer area.

[0007] Preferably, in S2, the evaluation indicators for the management effect of the substation area at least include the overload rate, negative loss rate, high loss rate during the operation of substation area equipment, the acquisition success rate during the operation of substation area acquisition equipment, the three-phase current imbalance rate of the substation area, the over-compensation rate of the power factor, and the under-compensation rate of the power factor.

[0008] In this solution, since the management of the distribution substation area is relatively complex, in order to simplify the evaluation process, several aspects that mainly affect the management effect of the distribution substation area are used as the evaluation indicators for the management effect. Among them, the overload rate is calculated from the heavy load rate and the overload rate. The heavy load rate is the number of days when the monthly load rate is greater than 80% and less than 100% / the total number of days in the current month, and the overload rate is the number of days when the monthly load rate is greater than 100% / the total number of days in the current month. The negative loss rate is the number of days when the monthly line loss rate is less than -1 / the total number of days in the current month, and the high loss rate is the number of days when the "statistical line loss rate" in the current month is higher than the theoretical line loss rate + 2 / the total number of days in the current month.

[0009] Preferably, in S2, an index evaluation system is constructed based on the management directions to which the evaluation indicators for the management effect of the substation area belong, including the following steps: The overload rate, negative loss rate, and high loss rate during the operation of substation area equipment are used as the operation criticism index set for the operation status of the substation area in the management direction of the substation area; the acquisition success rate during the operation of substation area acquisition equipment is used as the acquisition criticism index set for the operation status of substation area acquisition equipment in the management direction of the substation area; the three-phase current imbalance rate of the substation area, the over-compensation rate of the power factor, and the under-compensation rate of the power factor are used as the power supply criticism index set for the power supply guarantee index of the substation area in the management direction of the substation area; The operation status of the substation area, the operation status of substation area acquisition equipment, and the power supply guarantee index of the substation area are used as the first-level indicators, and the indicators in the operation criticism index set, the acquisition criticism index set, and the power supply criticism index set are used as the second-level indicators to construct the index evaluation system.

[0010] In this solution, by dividing the indicators into first-level indicators and second-level indicators, a hierarchical evaluation system is constructed, making the evaluation structure clearer and facilitating understanding and management; by dividing the management of the substation area into three directions: operation status, operation status of acquisition equipment, and power supply guarantee index, it is ensured that the evaluation system covers the key areas of substation area management and avoids omitting important content; through the hierarchical index design, it is possible to quickly locate the management direction and specific indicators where the problem lies, thereby supporting targeted improvement measures. For example, if the score of the operation status of the substation area is low, it can be further analyzed whether the problem is caused by the overload rate, negative loss rate, or high loss rate. If the score of the power supply guarantee index of the substation area is low, it can be analyzed whether the problem is the three-phase current imbalance rate, the over-compensation rate of the power factor, or the under-compensation rate. This targeted analysis can help managers formulate precise improvement strategies, thereby improving management efficiency.

[0011] Preferably, in S3, the Delphi method is used to analyze the weights of the indicators in the indicator evaluation system to obtain the subjective weights, including the following steps: Based on the management decisions and the degree of decision-making influence in the distribution substation area management data, score the indicators in the indicator evaluation system to obtain the indicator values, and obtain the original weights based on the proportion of the indicator values corresponding to each indicator in the sum of the indicator values of all indicators; calculate the mean and standard deviation of the original weights, and obtain the mean deviation based on the difference between the original weights of each indicator and the mean. If the mean deviation is less than or equal to the standard deviation, take the original weight as the subjective weight; if the mean deviation is greater than the standard value, re-score the indicators in the indicator evaluation system until the mean deviation is less than or equal to the standard deviation.

[0012] In this solution, the Delphi method is combined with experts' understanding of distribution substation area management decisions and their influence degrees to score, ensuring that the weight distribution meets the actual management requirements, avoiding the "mechanized" weight distribution of pure mathematical models, and making the weights closer to the actual management priorities; when there are significant differences in experts' opinions (the mean deviation exceeds the standard deviation), the re-scoring mechanism can guide experts to re-examine the importance of indicators, allowing experts to adjust their views according to the feedback during the iteration process, gradually approaching consensus, and the calculation process of subjective weights is transparent and traceable, facilitating managers to understand the source of weights, thereby enhancing the interpretability of decisions.

[0013] Preferably, in S3, the principal component analysis method is used to analyze the weights of the indicators in the indicator evaluation system to obtain the objective weights, including the following steps: Construct a sample matrix based on the number of first-level and second-level indicators in the indicator evaluation system, and perform standardization processing on the sample matrix to obtain a standardized matrix; Calculate the covariance of the standardized matrix to obtain the sample correlation coefficient matrix, and perform eigenvalue decomposition on the sample correlation coefficient matrix to obtain eigenvalues and corresponding eigenvectors; Sort by the eigenvalue size, select the eigenvectors corresponding to the first m largest eigenvalues as the principal components to obtain the weight model; calculate the contribution rate of each principal component in the weight model to obtain the contribution rate of each component, and perform weighted summation on the load of each indicator on all principal components with the contribution rate of each component as the weight to obtain the comprehensive load; Normalize the comprehensive load to obtain the objective weights of the indicators in the indicator evaluation system.

[0014] In this solution, by adopting the principal component analysis method, an objective weighting method based on data characteristics, it avoids the biases and uncertainties that may be brought about by subjective weighting. By calculating the contribution rates of each principal component and using these contribution rates as weights to perform weighted summation on the indicators, a more objective and reasonable weight distribution can be obtained. Moreover, it can simplify the indicator system and eliminate redundant information. When conducting comprehensive evaluation, the scores of each indicator and the total score can be calculated more quickly, which not only improves the evaluation efficiency but also helps to make decisions more rapidly.

[0015] Preferably, in S3, the comprehensive weighting method obtains the comprehensive weight in response to the subjective weight and the objective weight, including the following steps: Integrate the subjective weight and the objective weight to obtain a comprehensive indicator matrix; Calculate the average value of each integrated weight in the comprehensive indicator matrix to obtain the average weight; Compare the average weight with the integrated weight of the corresponding indicator to obtain the absolute deviation; Multiply each integrated weight in the comprehensive indicator matrix by the corresponding absolute deviation and sum them to obtain the integrated weight vector, and divide the integrated weight vector by the sum of the absolute deviations to obtain the comprehensive weight.

[0016] In this solution, by combining the subjective weight and the objective weight, it takes into account the subjective preferences of the evaluation subject and the objective authenticity of the evaluation object, avoids the biases that may exist in the subjective weight, and also makes up for the actual management requirements that may be ignored by the objective weight. It can more accurately reflect the overall effect of substation area management, avoid the biases caused by a single indicator or weight distribution method, and thus significantly improve the authenticity and reliability of the evaluation results.

[0017] Preferably, in S4, the indicator index calculation principle obtains the indicator index in response to the distribution substation area management data corresponding to each indicator in the indicator evaluation system, including the following steps: Perform weighted summation on the distribution substation area management data corresponding to the indicators in the operation criticism index set based on the corresponding comprehensive weight to obtain the operation index; Perform weighted summation on the distribution substation area management data corresponding to the indicators in the acquisition criticism index set based on the corresponding comprehensive weight to obtain the acquisition index; Perform weighted summation on the distribution substation area management data corresponding to the indicators in the power supply criticism index set based on the corresponding comprehensive weight to obtain the power supply index.

[0018] In this solution, by further calculating the distribution substation area management data to obtain the indicator index, it not only reduces the amount of data to be processed when evaluating the management effect subsequently, but also quantifies the abstract management effect into a data structure that is easy to understand, thereby reducing the computing power requirements during evaluation and improving the evaluation efficiency.

[0019] Preferably, in S4, the management effect score is obtained by weighted summation of the index indices based on the comprehensive weight, including the following steps: The operation index, the acquisition index, and the power supply index are weighted and summed based on the comprehensive weight of the first-level indicators to obtain the management effect score; the management effect score is fuzzily evaluated to obtain the evaluation result of the substation area management.

[0020] In this solution, the operation index, the acquisition index, and the power supply index are integrated into a management effect score through weighted summation, which can comprehensively reflect the overall effect of the substation area management; the management effect score is transformed into the evaluation result of the substation area management (such as excellent, good, medium, poor) through fuzzy evaluation, which enhances the interpretability and practicability of the result; by analyzing the management effect score and its components (operation index, acquisition index, power supply index), the management direction where the problem lies can be quickly located, so as to support targeted improvement measures.

[0021] Preferably, the management effect score is fuzzily evaluated to obtain the evaluation result of the substation area management, including the following steps: constructing a comment set, and the evaluation levels of the comment set include "excellent", "good", "general", "poor", and "very poor"; taking the operation index, the acquisition index, and the power supply index as fuzzy membership degrees to construct a fuzzy evaluation matrix, and taking the comprehensive weight of the first-level indicators as the weight vector; The fuzzy evaluation matrix and the weight vector are combined and calculated to obtain an evaluation result matrix, the evaluation result matrix is normalized to obtain the membership degrees of each evaluation level in the comment set, and the evaluation result of the substation area management is obtained based on the maximum membership degree principle.

[0022] In this solution, by using the fuzzy state evaluation method, in-depth and detailed analysis is carried out on each index index of the operation state of the distribution substation area obtained, the lean management effect of the substation area is comprehensively evaluated, the actual operation state of the distribution substation area is truly and objectively reflected, a scientific reference basis is provided for the substation area management, and the direction for the future management development of the substation area is pointed out, reducing the management workload of the substation area management personnel, thereby improving the work efficiency.

[0023] In the second aspect, a technical solution provided in an embodiment of the present invention is: a lean management effect evaluation system for a distribution substation area, including a data acquisition module, an index generation module, a calculation module, and an evaluation module; The data acquisition module acquires the management data of the distribution substation area; The index generation module extracts the characteristics of the management data of the distribution substation area based on the operation situation of the substation area to obtain the evaluation indicators of the management effect of the substation area, and constructs an index evaluation system based on the management direction to which the evaluation indicators of the management effect of the substation area belong; The calculation module respectively performs weight analysis on each index in the index evaluation system based on the Delphi analysis method and the principal component analysis method to obtain the subjective weight and the objective weight, and analyzes the subjective weight and the objective weight based on the comprehensive weighting method to obtain the comprehensive weight; The evaluation module evaluates the distribution substation area management data corresponding to each index in the index evaluation system based on the index index calculation principle to obtain the index index, performs weighted summation on the index index based on the comprehensive weight to obtain the management effect score, and obtains the management effect evaluation based on the management effect score.

[0024] In this solution, the distribution substation area management data is collected by the data collection module, and at the same time, the big data analysis technology is integrated to converge and integrate rich information from multiple data sources, realizing real-time monitoring and all-round evaluation of the operation status of the substation area, improving the management efficiency of the substation area by the substation area management personnel, reducing the burden and increasing the efficiency of grass-roots employees, and promoting the improvement of the operation and service level of the distribution network in the substation area.

[0025] Advantages of the present invention: (1) By performing feature analysis on the distribution substation area management data, the present invention extracts various indexes reflecting the management effect of the distribution substation area, thereby simplifying the analysis and evaluation difficulty of the complex data of the distribution substation area and improving the evaluation efficiency; (2) By adopting the combination of the Delphi analysis method and the main hierarchy analysis method, the present invention effectively avoids the interference of human subjective factors on the evaluation result, takes into account the subjective preference of the evaluation subject and the objective authenticity of the evaluation object, thereby greatly improving the evaluation accuracy; (3) By using the fuzzy state evaluation method to deeply and carefully analyze the operation status model of the distribution substation area, the present invention comprehensively analyzes the management operation status of the distribution substation area, quantifies the complex management operation status into a management effect score that is convenient to understand, thereby reducing the evaluation understanding difficulty, providing a scientific reference basis for the substation area management, and also pointing out the direction for the future management development of the substation area.

[0026] The above-mentioned invention content is only an overview of the technical solution of the present invention. In order to be able to understand the technical means of the present invention more clearly, it can be implemented according to the content of the specification. And in order to make the above-mentioned and other purposes, features and advantages of the present invention more obvious and understandable, the specific embodiments of the present invention are specifically given below. Description of the Drawings

[0027] By reading the detailed description of the non-limiting embodiments made with reference to the following drawings, other features, purposes and advantages of the present invention will become more obvious. The drawings are only used for the purpose of showing the preferred embodiments, and are not considered to be a limitation of the present invention. Moreover, throughout the drawings, the same reference numerals are used to represent the same components.

[0028] Figure 1It is a flowchart of a method for evaluating the lean management effect of a distribution substation area in the present invention; Figure 2 It is a schematic structural diagram of the index evaluation system in the present invention; Figure 3 It is a block diagram of a system for evaluating the lean management effect of a distribution substation area in the present invention. Specific implementation manners

[0029] To make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific implementation manners described herein are only the best embodiments of the present invention, which are only used to explain the present invention and do not limit the protection scope of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the protection scope of the present invention.

[0030] Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the operations (or steps) as sequential processes, many of the operations (or steps) can be implemented in parallel, concurrently or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operations are completed, but it can also have additional steps not included in the drawings; the process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0031] Embodiment 1: As Figure 1 shown, in order to solve the problem of low evaluation accuracy caused by the difficulty in taking into account the subjective preferences of the evaluation subject and the objective authenticity of the evaluation object when evaluating the management effect of the existing distribution substation area management method, this embodiment provides a method for evaluating the lean management effect of a distribution substation area, including the following steps: S1: Collect the management data of the distribution substation area based on the data collection principle.

[0032] S2: Extract the characteristics of the management data of the distribution substation area based on the operation conditions of the substation area to obtain the evaluation indicators of the management effect of the substation area; construct an index evaluation system based on the management directions to which the evaluation indicators of the management effect of the substation area belong.

[0033] In this embodiment, the evaluation indicators of the management effect of the substation area at least include the overload rate, negative loss rate, high loss rate when the substation area equipment is operating, the acquisition success rate when the substation area acquisition equipment is operating, the three-phase current imbalance rate of the substation area, the over-compensation rate of the power factor, and the under-compensation rate of the power factor.

[0034] In this embodiment, since the management of the distribution transformer area is relatively complex, in order to simplify the evaluation process, several aspects that mainly affect the management effect of the distribution transformer area are used as the evaluation indicators for the management effect. Among them, the heavy overload rate is calculated from the heavy load rate and the overload rate. The heavy load rate is the number of days when the monthly load rate is greater than 80% and less than 100% / the total number of days in the current month. The overload rate is the number of days when the monthly load rate is greater than 100% / the total number of days in the current month. The negative loss rate is the number of days when the monthly line loss rate is less than -1 / the total number of days in the current month. The high loss rate is the number of days when the "statistical line loss rate" in the current month is higher than the theoretical line loss rate + 2 / the total number of days in the current month.

[0035] In this embodiment, as Figure 2 shown, an index evaluation system is constructed based on the management directions to which the evaluation indicators of the transformer area management belong, including the following steps: The heavy overload rate, negative loss rate, and high loss rate during the operation of the transformer area equipment are used as the operation criticism index set for the operation status of the transformer area in the management direction of the transformer area; the acquisition success rate during the operation of the acquisition equipment in the transformer area is used as the acquisition criticism index set for the operation status of the acquisition equipment in the transformer area in the management direction of the transformer area; the three-way current imbalance rate, power factor over-compensation rate, and power factor under-compensation rate in the transformer area are used as the power supply criticism index set for the power supply guarantee index in the management direction of the transformer area. The operation status of the transformer area, the operation status of the acquisition equipment in the transformer area, and the power supply guarantee index in the transformer area are used as the first-level indicators, and the indicators in the operation criticism index set, acquisition criticism index set, and power supply criticism index set are used as the second-level indicators to construct the index evaluation system.

[0036] In this embodiment, by dividing the indicators into first-level indicators and second-level indicators, a hierarchical evaluation system is constructed, making the evaluation structure clearer and facilitating understanding and management; by dividing the transformer area management into three directions: operation status, operation status of the acquisition equipment, and power supply guarantee index, it is ensured that the evaluation system covers the key areas of the transformer area management and avoids omitting important content; through the hierarchical index design, it is possible to quickly locate the management direction and specific indicators where the problem lies, thereby supporting targeted improvement measures. For example, if the score of the operation status of the transformer area is low, it can be further analyzed whether the problem is caused by the heavy overload rate, negative loss rate, or high loss rate. If the score of the power supply guarantee index in the transformer area is low, it can be analyzed whether the problem is the three-way current imbalance rate, power factor over-compensation rate, or under-compensation rate. This targeted analysis can help managers formulate precise improvement strategies, thereby improving management efficiency.

[0037] S3: Based on the Delphi analysis method, the subjective weights are obtained by analyzing the weights of the indicators in the index evaluation system; based on the principal component analysis method, the objective weights are obtained by analyzing the weights of the indicators in the index evaluation system; the comprehensive weight is obtained by the comprehensive weighting method in response to the subjective weight and the objective weight.

[0038] In this embodiment, the subjective weights are obtained by analyzing the weights of each index in the index evaluation system based on the Delphi method, including the following steps: Based on the management decisions and decision-making influence degrees in the distribution substation area management data, each index in the index evaluation system is scored to obtain the index values. Based on the proportion of the index value corresponding to each index in the sum of the index values of all indexes, the original weights are obtained; the mean value and standard deviation of the original weights are calculated, and the mean deviation is obtained based on the difference between the original weight of each index and the mean value. If the mean deviation is less than or equal to the standard deviation, the original weight is used as the subjective weight. If the mean deviation is greater than the standard value, each index in the index evaluation system is re-scored until the mean deviation is less than or equal to the standard deviation.

[0039] Specifically, in this embodiment, 10 experts in substation area management and 20 substation area manager workers are selected for interviews. They determine the ranking of the weights of each attribute according to the actual decision-making problems and their own knowledge and experience, avoiding the situation where the attribute weight is inconsistent with the actual importance of the attribute. The specific formula is as follows: Where a j represents the subjective weight of the jth index, and s j is the full score value of the jth index, and n is equal to the number of scoring indexes.

[0040] In this embodiment, the Delphi method is combined with the experts' understanding of the distribution substation area management decision-making and its influence degree for scoring, ensuring that the weight distribution meets the actual management requirements, avoiding the "mechanized" weight distribution of the pure mathematical model, making the weight closer to the actual management priority; when there are large differences in the experts' opinions (the mean deviation exceeds the standard deviation), the re-scoring mechanism can guide the experts to re-examine the importance of the indexes. In the iterative process, the experts are allowed to adjust their views according to the feedback, gradually approaching the consensus, and the calculation process of the subjective weight is transparent and traceable, which is convenient for managers to understand the weight source, thereby enhancing the interpretability of the decision-making.

[0041] In this embodiment, the objective weights are obtained by analyzing the weights of each index in the index evaluation system based on the principal component analysis method, including the following steps: Based on the number of first-level indexes and second-level indexes in the index evaluation system, a sample matrix X(n×m) is constructed. The sample matrix X(n×m) is transformed to obtain Y = [y ij , and then Y is standardized. The formula is as follows: The standardized matrix is obtained where X(n×m) represents that there are n samples, and each sample has m indexes; The covariance of the standardized matrix is calculated to obtain the sample correlation coefficient matrix, and the formula is expressed as follows: The eigenvalue decomposition of the sample correlation coefficient matrix is performed to obtain eigenvalues and corresponding eigenvectors, and the formula is expressed as follows: |R - λI m | = 0 Solving gives p eigenvalues λ 1 ≥ λ 2 ≥ … ≥ λ p ≥ 0 The eigenvector of the i-th variable: Sorted by eigenvalue size, select the eigenvectors corresponding to the top m largest eigenvalues as the principal components to obtain the weight model, and the formula is expressed as follows: In the formula, F 1 , F 2 , …, F m are the m principal components obtained after analysis and are uncorrelated with each other; among them u i = (u 1i , u 2i ,... u ni ) is exactly the eigenvector corresponding to the eigenvalue of the R covariance matrix The contribution of each principal component in the weight model is calculated to obtain the contribution rate of each component, and the formula is expressed as follows: k = λ 1 + λ 2 + … + λ m The comprehensive load is obtained by weighted summation of the load of each index on all principal components with the contribution rate of each component as the weight; The comprehensive load is normalized to obtain the objective weight W′(n) of each index in the index evaluation system, and the formula is expressed as follows: In the formula, t is the number of principal components.

[0042] In this embodiment, by adopting the principal component analysis method, an objective weighting method based on data characteristics is used to avoid the biases and uncertainties that may be brought by subjective weighting. By calculating the contribution rates of each principal component and using these contribution rates as weights to perform weighted summation on the indexes, a more objective and reasonable weight distribution can be obtained, and it can also simplify the index system and eliminate redundant information. When performing comprehensive evaluation, the scores of each index and the total score can be calculated more quickly, which not only improves the efficiency of evaluation but also helps to make decisions more quickly.

[0043] In this embodiment, the comprehensive weighting method obtains a comprehensive weight in response to the subjective weight and the objective weight, including the following steps: Integrate the subjective weight and the objective weight to obtain a comprehensive index matrix w(m×n), where: w ij represents the weight of index j under the i-th model, Calculate the average value of each integrated weight in the comprehensive index matrix to obtain the average weight. The formula is expressed as follows: Compare the average weight with the integrated weight of the corresponding index to obtain the absolute deviation. The formula is expressed as follows: When is satisfied, s ij is uniformly replaced by 1; Multiply each integrated weight in the comprehensive index matrix by the corresponding absolute deviation and sum them to obtain the integrated weight vector. Divide the integrated weight vector by the sum of the absolute deviations to obtain the comprehensive weight. The formula is expressed as follows: And w j satisfies

[0044] In this embodiment, by combining the subjective weight and the objective weight, it takes into account the subjective preferences of the evaluation subject and the objective authenticity of the evaluation object, avoids the possible biases of the subjective weight, and also makes up for the actual management needs that may be ignored by the objective weight. It can more accurately reflect the overall effect of the substation area management, avoid the deviation caused by a single index or weight allocation method, and thus significantly improve the authenticity and reliability of the evaluation results.

[0045] S4: The index calculation principle obtains the index number in response to the distribution substation area management data corresponding to each index in the index evaluation system, and performs weighted summation on the index number based on the comprehensive weight to obtain the management effect score.

[0046] In this embodiment, the index calculation principle obtains the index number in response to the distribution substation area management data corresponding to each index in the index evaluation system, including the following steps: Perform weighted summation on the distribution substation area management data corresponding to the indexes in the operation critical index set based on the corresponding comprehensive weight to obtain the operation index; Perform weighted summation on the distribution substation area management data corresponding to the indexes in the acquisition critical index set based on the corresponding comprehensive weight to obtain the acquisition index; Perform weighted summation on the distribution substation area management data corresponding to the indexes in the power supply critical index set based on the corresponding comprehensive weight to obtain the power supply index.

[0047] Specifically, for example, the comprehensive weights corresponding to the indicators in the obtained operation criticism index set are: the weight of the heavy overload rate is 0.30, the weight of the negative loss rate is 0.30, and the weight of the high loss rate is 0.4. Then the operation index = 0.3 * heavy overload rate + 0.3 * negative loss rate + 0.4 * high loss rate.

[0048] In this embodiment, by further calculating the distribution transformer area management data to obtain the index, not only the amount of data to be processed in subsequent evaluation of the management effect is reduced, but also the abstract management effect is quantified into a data structure that is easy to understand, thereby reducing the computing power requirement during evaluation and improving the evaluation efficiency.

[0049] In this embodiment, the management effect score is obtained by weighted summation of the index based on the comprehensive weight, including the following steps: The management effect score is obtained by weighted summation of the operation index, the acquisition index, and the power supply index based on the comprehensive weight of the primary indicators; the management effect score is subjected to fuzzy evaluation to obtain the distribution transformer area management evaluation result.

[0050] In this embodiment, the operation index, the acquisition index, and the power supply index are synthesized into a management effect score through weighted summation, which can comprehensively reflect the overall effect of the distribution transformer area management; the management effect score is transformed into the distribution transformer area management evaluation result (such as excellent, good, medium, poor) through fuzzy evaluation, enhancing the interpretability and practicality of the result; by analyzing the management effect score and its components (operation index, acquisition index, power supply index), the management direction where the problem lies can be quickly located, thereby supporting targeted improvement measures.

[0051] In this embodiment, the management effect score is subjected to fuzzy evaluation to obtain the distribution transformer area management evaluation result, including the following steps: constructing a comment set, and the evaluation levels of the comment set include "excellent", "good", "general", "poor", and "very poor"; constructing a fuzzy evaluation matrix with the operation index, the acquisition index, and the power supply index as fuzzy membership degrees, and the formula is expressed as follows: In the formula: R(i = 1, 2,..., m; j = 1, 2,..., n) is the membership degree of the i-th evaluation index for the j-th evaluation level, reflecting the fuzzy relationship between the evaluation index and the evaluation level; Taking the comprehensive weight of the primary indicators as the weight vector; The fuzzy evaluation matrix and the weight vector are combined and calculated to obtain an evaluation result matrix. The evaluation result matrix is normalized, and according to the principle of maximum membership degree, the membership degrees of each evaluation level in the comment set are queried to obtain the evaluation result of the substation area management. For example, if the evaluation result matrix is BA = [0.2261 0.7370 0.0369 0 0], according to the principle of maximum membership degree, the membership degree of "excellent" is 0.2261, the membership degree of "good" is 0.7370, the membership degree of "general" is 0.0369, the membership degree of "poor" is 0, and the membership degree of "very poor" is 0. The maximum value of the evaluation result is 0.7370. Querying the comment set, the corresponding evaluation level is good, so the evaluation result of the distribution substation area management in this place is good.

[0052] In this embodiment, by using the fuzzy state evaluation method, in-depth and detailed analysis is carried out on the various index numbers of the operating state of the obtained distribution substation area, the lean management effect of the substation area is comprehensively evaluated, the actual operating state of the distribution substation area is truly and objectively reflected, a scientific reference basis is provided for the substation area management, and the direction for the future management development of the substation area is also pointed out, reducing the management workload of the substation area management personnel, thereby improving the work efficiency.

[0053] Embodiment 2: As Figure 3 shown, this embodiment provides a lean management effect evaluation system for a distribution substation area, including a data acquisition module, an index generation module, a calculation module, and an evaluation module; The data acquisition module acquires the distribution substation area management data; The index generation module extracts the characteristics of the distribution substation area management data based on the operation situation of the substation area to obtain the evaluation indexes of the substation area management effect, and constructs an index evaluation system based on the management directions to which the substation area management effect evaluation indexes belong; The calculation module respectively conducts weight analysis on the various indexes in the index evaluation system based on the Delphi analysis method and the principal component analysis method to obtain the subjective weight and the objective weight, and conducts analysis on the subjective weight and the objective weight based on the comprehensive weighting method to obtain the comprehensive weight; The evaluation module evaluates the distribution substation area management data corresponding to the various indexes in the index evaluation system based on the index number calculation principle to obtain the index numbers, performs weighted summation on the index numbers based on the comprehensive weight to obtain the management effect score, and obtains the management effect evaluation based on the management effect score.

[0054] In this embodiment, the data acquisition module acquires the distribution substation area management data, and at the same time integrates the big data analysis technology to converge and integrate rich information from multiple data sources, realizes the real-time monitoring and comprehensive evaluation of the operating state of the substation area, improves the efficiency of the substation area management personnel in managing the substation area, reduces the burden on grass-roots employees and increases efficiency, and promotes the improvement of the operation and service level of the substation area distribution network.

[0055] As can be seen from the above embodiments, there are at least the following substantial effects: (1) By analyzing the characteristics of the management data of the distribution transformer area, the present invention extracts various indicators reflecting the management effect of the distribution transformer area, thereby simplifying the analysis and evaluation difficulty of the complex data of the distribution transformer area and improving the evaluation efficiency; (2) By adopting the combination of the Delphi analysis method and the analytic hierarchy process, the present invention effectively avoids the interference of human subjective factors on the evaluation results, takes into account the subjective preferences of the evaluation subject and the objective authenticity of the evaluation object, and thus greatly improves the evaluation accuracy; (3) By using the fuzzy state evaluation method to deeply and carefully analyze the operation state model of the distribution transformer area, the present invention comprehensively analyzes the management operation status of the distribution transformer area, quantifies the complex management operation status into a management effect score that is convenient to understand, thereby reducing the evaluation understanding difficulty, providing a scientific reference basis for the transformer area management, and also pointing out the direction for the future management development of the transformer area.

[0056] The above specific implementation manners are the preferred implementation manners of a method and system for evaluating the lean management effect of a distribution transformer area of the present invention, and do not limit the specific implementation scope of the present invention. The scope of the present invention includes but is not limited to the present specific implementation manners. Any equivalent changes made according to the shape and structure of the present invention are within the protection scope of the present invention.

Claims

1. A method for evaluating the effect of lean management of a distribution station area, characterized by: The following steps are involved: S1. Collect distribution substation area management data based on data collection principles; S2. Extract features from the distribution station area management data based on the station area operation situation to obtain the station area management effect evaluation index; construct an index evaluation system based on the management direction to which the station area management effect evaluation index belongs; S3. Based on the Delphi analysis method, the weight analysis of each indicator in the indicator evaluation system is carried out to obtain the subjective weight; Based on the principal component analysis method, the weight analysis of each indicator in the indicator evaluation system is carried out to obtain the objective weight; The comprehensive weighting method obtains the comprehensive weight in response to the subjective weight and the objective weight; S4. Principles of indicator index calculation: In response to the distribution station area management data corresponding to each indicator in the indicator evaluation system, the indicator index is obtained, and the indicator index is weighted and summed based on the comprehensive weight to obtain the management effect score.

2. A method for evaluating the effect of lean management of a distribution station area according to claim 1, characterized in that: In S2, the substation management effect evaluation index includes at least the heavy overload rate, negative loss rate, high loss rate of the substation equipment during operation, the collection success rate of the substation collection equipment during operation, the three-way imbalance rate of the substation current, the power factor overcompensation rate and the power factor undercompensation rate.

3. A method for evaluating the effect of lean management of a distribution station area according to claim 2, characterized in that: In S2, an indicator evaluation system is constructed based on the management direction to which the area management effect evaluation indicator belongs, including the following steps: The heavy overload rate, negative loss rate and high loss rate of the substation equipment during operation are used as the operation critical index set of the substation operation status in the substation management direction; the collection success rate of the substation collection equipment during operation is used as the collection critical index set of the substation collection equipment operation status in the substation management direction; the three-way imbalance rate of the substation current, the power factor over-compensation rate and the power factor under-compensation rate are used as the power supply critical index set of the substation power supply guarantee index in the substation management direction; The operating status of the substation, the operating status of the substation collection equipment and the substation power supply guarantee index are taken as the first-level indicators, and the indicators in the operation critical indicator set, collection critical indicator set and power supply critical indicator set are taken as the second-level indicators to construct an indicator evaluation system.

4. A method for evaluating the effect of lean management of a distribution station area according to claim 1, characterized in that: In S3, the weight analysis of each indicator in the indicator evaluation system is performed based on the Delphi analysis method to obtain the subjective weight, including the following steps: Based on the management decisions and decision-making influence in the distribution station area management data, each indicator in the indicator evaluation system is scored to obtain the indicator value, and the original weight is obtained based on the proportion of the indicator value corresponding to each indicator to the sum of the indicator values ​​of all indicators; The original weights are calculated for mean and standard deviation, and the mean deviation is obtained based on the difference between the original weights and the mean of each indicator; If the mean deviation is less than or equal to the standard deviation, the original weight will be used as the subjective weight. If the mean spread is greater than the standard value, the indicators in the indicator evaluation system will be re-scored until the mean deviation is less than or equal to the standard deviation.

5. A method for evaluating the effect of lean management of a distribution station area according to claim 3, characterized in that: In S3, the weight analysis of each indicator in the indicator evaluation system is performed based on the principal component analysis method to obtain the objective weight, including the following steps: A sample matrix is ​​constructed based on the number of primary and secondary indicators in the indicator evaluation system, and the sample matrix is ​​standardized to obtain a standardized matrix; The covariance of the standardized matrix is ​​calculated to obtain the sample correlation coefficient matrix, and the sample correlation coefficient matrix is ​​decomposed by eigenvalue to obtain the eigenvalue and the corresponding eigenvector; Sort by eigenvalues, select the eigenvectors corresponding to the first m largest eigenvalues ​​as the principal components to obtain the weight model; calculate the contribution of each principal component in the weight model to obtain the contribution rate of each component, and use the contribution rate of each component as the weight to perform the weighted summation of the loads of each indicator on all principal components to obtain the comprehensive load; The comprehensive load is normalized to obtain the objective weights of each indicator in the indicator evaluation system.

6. A method for evaluating the effect of lean management of a distribution station area according to claim 1, characterized in that: In S3, the comprehensive weighting method obtains the comprehensive weight in response to the subjective weight and the objective weight, including the following steps: Integrate the subjective weights and objective weights to obtain a comprehensive indicator matrix; Calculate the average of each integrated weight in the comprehensive indicator matrix to obtain the average weight; The average weight is compared with the integrated weight of the corresponding indicator to obtain the absolute deviation; The integrated weights in the comprehensive indicator matrix are multiplied by the corresponding absolute deviations and the sum is calculated to obtain the integrated weight vector. The integrated weight vector is divided by the sum of the absolute deviations to obtain the comprehensive weight.

7. A method for evaluating the effect of lean management of a distribution station area according to claim 3, characterized in that: In S4, the indicator index calculation principle obtains the indicator index in response to the distribution station area management data corresponding to each indicator in the indicator evaluation system, including the following steps: The distribution station area management data corresponding to the indicators in the operation critical indicator set are weighted and summed based on the corresponding comprehensive weights to obtain the operation index; The distribution station area management data corresponding to the indicators in the collection critical indicator set are weighted and summed based on the corresponding comprehensive weights to obtain the collection index; The distribution station area management data corresponding to the indicators in the power supply critical index set are weighted and summed based on the corresponding comprehensive weights to obtain the power supply index.

8. A method for evaluating the effect of lean management of a distribution station area according to claim 7, characterized in that: In S4, the indicator index is weighted and summed based on the comprehensive weight to obtain the management effect score, including the following steps: The operation index, collection index and power supply index are weighted and summed based on the comprehensive weight of the first-level indicators to obtain the management effect score; the management effect score is fuzzy evaluated to obtain the substation management evaluation result.

9. A method for evaluating the effect of lean management of a distribution station area according to claim 8, characterized in that: The fuzzy evaluation of the management effect score is performed to obtain the substation management evaluation result, which includes the following steps: Constructing a comment set, wherein the evaluation levels of the comment set include "excellent", "good", "average", "poor" and "very poor"; constructing a fuzzy evaluation matrix with the operation index, the collection index and the power supply index as the fuzzy membership, and taking the comprehensive weight of the primary index as the weight vector; The fuzzy evaluation matrix and the weight vector are combined to obtain the evaluation result matrix, which is normalized to obtain the membership of each evaluation level in the comment set, and the substation management evaluation result is obtained based on the maximum membership principle.

10. A distribution substation area lean management effect evaluation system, applicable to a distribution substation area lean management effect evaluation method according to any one of claims 1 to 9, characterized in that: It includes data collection module, indicator generation module, calculation module and evaluation module; The data acquisition module collects distribution station area management data; The indicator generation module extracts features from the distribution station area management data based on the station area operation situation to obtain the station area management effect evaluation index, and constructs an indicator evaluation system based on the management direction to which the station area management effect evaluation index belongs; The calculation module performs weight analysis on each indicator in the indicator evaluation system based on the Delphi analysis method and the principal component analysis method to obtain subjective weight and objective weight, and analyzes the subjective weight and objective weight based on the comprehensive weighting method to obtain the comprehensive weight; The evaluation module evaluates the distribution station area management data corresponding to each indicator in the indicator evaluation system based on the indicator index calculation principle to obtain the indicator index, performs weighted summation of the indicator index based on the comprehensive weight to obtain the management effect score, and obtains the management effect evaluation based on the management effect score.

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