Comprehensive evaluation method and device for low-voltage transformer area of power distribution network, electronic equipment and medium

Abstract

The embodiment of the invention discloses a comprehensive evaluation method and device for a low-voltage transformer area of a power distribution network, electronic equipment and a medium. The method comprises the following steps: determining candidate evaluation indexes influencing the operation state of the low-voltage transformer area of the power distribution network, obtaining first index data of the candidate evaluation indexes, and preprocessing the first index data to obtain second index data; constructing a decision table according to the second index data, and reducing the decision table by adopting a rough set theory to obtain a target evaluation index; and performing comprehensive weighting on the target evaluation index by adopting a Delphi subjective weighting method and a rough set objective weighting method, and performing comprehensive evaluation on the low-voltage transformer area of the power distribution network by adopting the target evaluation index after comprehensive weighting. By adopting the scheme, a set of index system capable of efficiently, scientifically and comprehensively evaluating the running state of the low-voltage transformer areas of the power distribution network is established, the problems that the number of the low-voltage transformer areas of the power distribution network is large and the evaluation index system is disordered are solved, and auxiliary decision making is provided for operation and maintenance personnel and planning personnel.

Description

Technical Field

[0001] Embodiments of the present invention relate to the technical field of distribution network, and in particular to a method, device, electronic equipment and medium for comprehensively evaluating a low-voltage area of ​​a distribution network. Background Art

[0002] With the rapid development of the economy, the electricity consumption of low-voltage users has continued to increase, and the requirements for power supply quality have been improved. The power supply capacity of low-voltage distribution networks in some areas can no longer fully meet the needs of users. Low-voltage distribution networks have the characteristics of large scale, flexible and complex structure, much uncertain information, and low intelligence, which has brought certain difficulties and challenges to the planning, construction, and management of low-voltage distribution networks.

[0003] The low-voltage area of ​​the distribution network is a large and complex system with multiple attributes and indicators, different levels of development, and affected by multiple factors. The low-voltage area of ​​the intelligent distribution network is an important factor in the construction and operation level of the comprehensive intelligent low-voltage distribution network. An evaluation index model and evaluation method for the low-voltage area of ​​the intelligent distribution network is established to evaluate the operation, management, development and construction level and weak links of the intelligent low-voltage distribution network, providing a basis for further scientific planning, construction and management of the distribution network.

[0004] Therefore, how to comprehensively evaluate the low-voltage substations in the distribution network is a technical problem that needs to be solved urgently by technical personnel in this field. Summary of the invention

[0005] The embodiments of the present invention provide a method, device, electronic device and storage medium for comprehensively evaluating low-voltage areas in a distribution network, so as to realize an index system for comprehensively evaluating the operating status of low-voltage areas in a distribution network in an efficient and scientific manner, solve the problems of a large number of low-voltage areas in the distribution network and a chaotic evaluation index system, and provide auxiliary decision-making for operation and maintenance personnel and planners.

[0006] In a first aspect, an embodiment of the present invention provides a method for comprehensively evaluating a low-voltage area in a distribution network, comprising:

[0007] Determine candidate evaluation indicators that affect the operating state of the low-voltage area of ​​the distribution network, obtain first indicator data of the candidate evaluation indicators, and pre-process the first indicator data to obtain second indicator data;

[0008] A decision table is constructed according to the second indicator data, and the decision table is simplified by using rough set theory to obtain a target evaluation indicator;

[0009] The Delphi subjective weighting method and the rough set objective weighting method are used to comprehensively weight the target evaluation indicators, and the target evaluation indicators after comprehensive weighting are used to comprehensively evaluate the low-voltage substations of the distribution network.

[0010] In a second aspect, an embodiment of the present invention further provides a comprehensive evaluation device for low-voltage distribution network areas, including:

[0011] An indicator data processing module is used to determine candidate evaluation indicators that affect the operating state of the low-voltage substation of the distribution network, obtain first indicator data of the candidate evaluation indicators, and pre-process the first indicator data to obtain second indicator data;

[0012] A decision table processing module, used for constructing a decision table according to the second indicator data, and simplifying the decision table by using rough set theory to obtain a target evaluation indicator;

[0013] The low-voltage substation comprehensive evaluation module is used to use the Delphi subjective weighting method and the rough set objective weighting method to comprehensively weight the target evaluation indicators, and use the target evaluation indicators after comprehensive weighting to comprehensively evaluate the low-voltage substation of the distribution network.

[0014] In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:

[0015] one or more processors;

[0016] A storage device for storing one or more programs;

[0017] When the one or more programs are executed by the one or more processors, the one or more processors implement the comprehensive evaluation method for low-voltage substations in a distribution network as described in any embodiment of the present invention.

[0018] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the comprehensive evaluation method for low-voltage substations in a distribution network as described in any embodiment of the present invention.

[0019] In a fifth aspect, an embodiment of the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the comprehensive evaluation method for low-voltage substations in a distribution network as described in any embodiment of the present invention.

[0020] The embodiment of the present invention provides a method, device, electronic device and storage medium for comprehensive evaluation of low-voltage areas in a distribution network. By determining candidate evaluation indicators that affect the operating status of low-voltage areas in the distribution network, obtaining the first indicator data of the candidate evaluation indicators and preprocessing the first indicator data to obtain the second indicator data; constructing a decision table based on the second indicator data, and simplifying the decision table using rough set theory to obtain the target evaluation indicator; using the Delphi subjective weighting method and the rough set objective weighting method to comprehensively weight the target evaluation indicator, and using the comprehensively weighted target evaluation indicator to comprehensively evaluate the low-voltage areas in the distribution network. Using the technical solution of the embodiment of the present invention, a set of indicator systems that can realize efficient and scientific comprehensive evaluation of the operating status of low-voltage areas in the distribution network is built based on six three-level evaluation indicators, solving the problem of a large number of low-voltage areas in the distribution network and a chaotic evaluation indicator system, and providing auxiliary decision-making for operation and maintenance personnel and planners. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Other features, objects and advantages of the present invention will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings. The drawings are only for the purpose of illustrating preferred embodiments and are not to be considered as limiting the present invention. Also, the same reference symbols are used throughout the drawings to represent the same parts. In the drawings:

[0022] Figure 1 It is a flow chart of a comprehensive evaluation method for low-voltage areas of a distribution network provided in an embodiment of the present invention;

[0023] Figure 2 is a schematic diagram of a three-level rating indicator system provided in an embodiment of the present invention;

[0024] Figure 3 is a flow chart of another comprehensive evaluation method for low-voltage areas of a distribution network provided in an embodiment of the present invention;

[0025] Figure 4 It is a flow chart of another comprehensive evaluation method for low-voltage areas of a distribution network provided in an embodiment of the present invention;

[0026] Figure 5 It is a structural schematic diagram of a comprehensive evaluation device for low-voltage areas of a distribution network provided in an embodiment of the present invention;

[0027] Figure 6 It is a structural schematic diagram of an electronic device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0029] Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the operations (or steps) as sequential processes, many of the operations (or steps) therein 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 operation is completed, but can also have additional steps not included in the accompanying drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0030] Among them, the acquisition, storage, use and processing of data in the technical solution of this application are in compliance with the relevant provisions of national laws and regulations. It should be noted that in the embodiments of this application, some existing solutions in the industry such as certain software, components or models may be mentioned, which should be considered as exemplary, and their purpose is only to illustrate the feasibility of the implementation of the technical solution of this application, but it does not mean that the applicant has or will necessarily use the solution.

[0031] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein.

[0032] Embodiment 1

[0033] Figure 1 This is a flow chart of a method for comprehensive evaluation of low-voltage areas in a distribution network provided in an embodiment of the present invention. This embodiment can be applied to the case where rough set theory is used to comprehensively evaluate low-voltage areas in a distribution network. The method of this embodiment can be executed by a comprehensive evaluation device for low-voltage areas in a distribution network, and the device can be implemented in hardware and / or software. The device can be configured in a server for comprehensive evaluation of low-voltage areas in a distribution network. The method specifically includes the following steps:

[0034] S110, determining candidate evaluation indicators that affect the operating state of the low-voltage substation of the distribution network, obtaining first indicator data of the candidate evaluation indicators and preprocessing the first indicator data to obtain second indicator data.

[0035] Among them, in the embodiment of the present invention, a comprehensive evaluation is performed on the low-voltage substation of the distribution network based on the operating status of the low-voltage substation of the distribution network. The operating status of the low-voltage substation of the distribution network is information that the distribution operation and maintenance and distribution planning personnel urgently need to know. In the embodiment of the present invention, based on the comprehensive information of the low-voltage substation of the distribution network, a status evaluation is performed on the low-voltage substation operating in the distribution network, so as to obtain the operating status of the low-voltage substation of the distribution network, and provide auxiliary decision-making for the operation and maintenance personnel and planners.

[0036] Among them, see Figure 2 The evaluation indicators for comprehensive evaluation of the low-voltage area of ​​the distribution network include first-level evaluation indicators, second-level rating indicators and third-level rating indicators. Among them, the first-level evaluation indicators refer to the operating status of the low-voltage area of ​​the distribution network; the first-level evaluation indicators refer to the candidate evaluation indicators that affect the operating status of the low-voltage area of ​​the distribution network, and the candidate evaluation indicators include the grid structure and the operating level; the first-level evaluation indicators refer to the indicators included in the candidate evaluation indicators, including the qualified rate of the conductor cross-section, the power supply radius, the transformer load rate, the three-phase load imbalance, the node voltage qualified rate and the proportion of qualified voltage users.

[0037] The first indicator data of the candidate evaluation indicator is obtained and the first indicator data is preprocessed to obtain the second indicator data; wherein the preprocessing includes but is not limited to normalization and discretization processing.

[0038] Optionally, the wire cross-section qualified rate may refer to the proportion of the number of wire cross-sections with qualified wires in the low-voltage area to the total number of wires. The amount of current and power allowed to be transmitted by the wire is closely related to the wire material and cross-sectional area. Under the premise of not increasing the economic cost, a wire cross-sectional area that is too small will affect the transmission effect of electric energy. Therefore, the more qualified wires there are in the low-voltage area, the more reasonable the operation state of the low-voltage area of ​​the distribution network. The formula for calculating the wire cross-section qualified rate is:

[0039]

[0040] In the formula, Indicates the qualified rate of wire cross section, l q Refers to the number of conductors in this area whose conductor cross-section is within the allowable qualified range, l t Refers to the number of all conductors in this area.

[0041] Optional, the power supply radius refers to the line distance between the transformer and the farthest load point. As an important indicator for evaluating the operating status of the low-voltage area of ​​the distribution network, this value should not be too large, otherwise it will cause voltage problems at the end of the network. Generally speaking, the power supply radius is related to the voltage level. At the same time, the power supply radius distance allowed by cities, suburbs, and farms increases in turn under the same voltage level.

[0042] Optionally, the transformer load rate refers to the ratio of the average apparent power output of the transformer within a certain period of time to the rated capacity of the transformer, which is used to reflect the load-bearing capacity of the transformer. The optimal range of its operating curve is 30%-70%. When the transformer operates in a range closer to the upper limit of the curve, as the actual load increases, the transformer is prone to overload; the closer to the lower limit of the curve, the transformer has too much margin, resulting in a waste of resources; when it is near the optimal range, the transformer can better exert its effectiveness. When processing the index data, the embodiment of the present invention sets the transformer load rate value to 50% as the best. The calculation formula is:

[0043]

[0044] In the formula, Indicates transformer load factor, W t is the total power supply load borne by the area during period t (Kw·h), W T is the total capacity of the transformer.

[0045] Optionally, the three-phase load imbalance refers to the ratio of the difference between the maximum load of each phase in the three-phase low-voltage side of the distribution network transformer and the average value of the three-phase load to the average value of the three-phase load; it reflects the rationality of the load distribution in the three phases. The operating status of the substation increases as the imbalance decreases. The calculation formula is:

[0046]

[0047] In the formula, Indicates the three-phase load imbalance, P A , P B , P C They respectively refer to the three-phase loads at terminals A, B, and C on the low-voltage side of the transformer in this area.

[0048] Optionally, the node voltage qualification rate refers to the proportion of qualified nodes in the substation to the total number of nodes in the substation. This value reflects the qualified level of power in the substation and is proportional to the operating status of the substation. The formula is as follows:

[0049]

[0050] Where: γ refers to the node voltage qualification rate, v q is the number of qualified nodes in the area; v t is the total number of nodes.

[0051] Optionally, the proportion of users with qualified voltage refers to the proportion of all users in the area whose voltage is within the qualified range to all users in the area. This value explains the power supply level of the area from the user's perspective. The larger the value, the better the status of the area. The formula is as follows:

[0052]

[0053] Where: ρ is the proportion of users with qualified voltage, x q For all users in the area whose voltage is within the qualified range, q t The total number of users in the area.

[0054] S120. Construct a decision table based on the second indicator data, and simplify the decision table using rough set theory to obtain a target evaluation indicator.

[0055] Among them, the decision table is a graphical tool in the form of a table, which is particularly suitable for describing the situation where there are many processing judgment conditions, the conditions are combined with each other, and there are multiple decision-making schemes. In the embodiment of the present invention, the decision table is used to describe the dependency relationship between the candidate evaluation indicators and the low-voltage station area, and the operating status of the low-voltage station area is graded based on the decision table.

[0056] Rough set theory refers to a mathematical method for processing imprecise, uncertain and incomplete data, which is widely used in machine learning, data mining and decision support. In the embodiment of the present invention, the rough set theory is used to simplify the decision table, and the candidate evaluation indicators with little influence on the comprehensive evaluation of the low-voltage area of ​​the distribution network are eliminated in the decision table to obtain the target evaluation indicators.

[0057] S130, using the Delphi subjective weighting method and the rough set objective weighting method to comprehensively weight the target evaluation indicators, and using the target evaluation indicators after comprehensive weighting to comprehensively evaluate the low-voltage substation of the distribution network.

[0058] Among them, the Delphi method is a decision-making method that uses communication to send the problems to be solved to each expert separately, solicit opinions, and then collect and summarize the opinions of all experts and compile comprehensive opinions, and finally gradually obtain relatively consistent prediction results through repeated operations. The Delphi method is a subjective method. In the embodiment of the present invention, the Delphi method is used to weight the target evaluation indicators.

[0059] In the embodiment of the present invention, the Delphi subjective weighting method and the rough set objective weighting method are used to assign corresponding weights to the target evaluation indicators respectively, and perform comprehensive weighting; the target evaluation indicators after comprehensive weighting are used to comprehensively evaluate the low-voltage substation of the distribution network.

[0060] The embodiment of the present invention provides a comprehensive evaluation method for low-voltage areas of a distribution network. By determining candidate evaluation indicators that affect the operating status of low-voltage areas of the distribution network, obtaining first indicator data of the candidate evaluation indicators and preprocessing the first indicator data to obtain second indicator data; constructing a decision table based on the second indicator data, and simplifying the decision table using rough set theory to obtain target evaluation indicators; using Delphi subjective weighting method and rough set objective weighting method to comprehensively weight the target evaluation indicators, and using the comprehensively weighted target evaluation indicators to comprehensively evaluate the low-voltage areas of the distribution network. Using the technical solution of the embodiment of the present invention, a set of indicator systems that can realize efficient and scientific comprehensive evaluation of the operating status of low-voltage areas of the distribution network is built based on six three-level evaluation indicators, solving the problem of a large number of low-voltage areas of the distribution network and a chaotic evaluation indicator system, and providing auxiliary decision-making for operation and maintenance personnel and planners.

[0061] Embodiment 2

[0062] Figure 3 The flowchart of a comprehensive evaluation method for low-voltage distribution network areas provided in an embodiment of the present invention. The embodiment of the present invention further optimizes the above embodiment on the basis of the above embodiment, and the embodiment of the present invention can be combined with various optional solutions in one or more of the above embodiments. Figure 3 As shown, the comprehensive evaluation method for low-voltage distribution network areas provided in the embodiment of the present invention may include the following steps:

[0063] S310, determining candidate evaluation indicators that affect the operating state of the low-voltage substation of the distribution network, obtaining first indicator data of the candidate evaluation indicators and preprocessing the first indicator data to obtain second indicator data.

[0064] Among them, there are many candidate evaluation indicators that reflect the operation status of the low-voltage area of ​​the distribution network, but the dimensions cannot be uniformly compared at different levels, and it is difficult to draw the relationship between the indicators; at the same time, the rough set data analysis is based on discrete data, so before using the rough set theory to conduct a comprehensive evaluation of the operation status of the low-voltage area of ​​the distribution network, it is necessary to first pre-process the indicator data of the low-voltage area of ​​the distribution network to make it meet the scope of use of the rough set theory. The embodiment of the present invention will process the first indicator data of the candidate evaluation indicator from the two aspects of data normalization and data discretization.

[0065] As an optional but non-limiting implementation, the determining of candidate evaluation indicators that affect the operating state of the low-voltage substation of the distribution network, obtaining first indicator data of the candidate evaluation indicators and preprocessing the first indicator data to obtain second indicator data includes but is not limited to steps A1-A2:

[0066] Step A1: Determine candidate evaluation indicators that affect the operating status of the low-voltage substation in the distribution network, and obtain first indicator data of the candidate evaluation indicators; wherein the candidate evaluation indicators include grid structure and operating level, and the first indicator data includes conductor cross-section qualification rate, power supply radius, transformer load rate, three-phase load imbalance, node voltage qualification rate and proportion of voltage qualified users.

[0067] Step A2: normalizing and discretizing the first indicator data of the candidate evaluation indicator to obtain second indicator data; wherein the preprocessing includes normalization and discretization.

[0068] Among them, the evaluation index of the distribution network substation interprets the substation status from different angles. Although the embodiment of the present invention focuses on proportional data in the selection of candidate evaluation indicators, it still cannot ensure that each evaluation indicator is at the same dimensional level, resulting in the evaluation indicator data cannot be compared and analyzed at the same level, so normalization processing is required. The embodiment of the present invention puts each candidate evaluation indicator in the same dimensionless interval, even if it is in the [0, 1] interval. The processing formula is as follows:

[0069]

[0070] In the formula, represents the normalized data of the first indicator, C i Indicates the first indicator data, C m , C max , C min They are respectively the average value, maximum value and minimum value of the first indicator data; i=1, 2, 3...n.

[0071] Optionally, the normalization processing of candidate evaluation indicators should identify the indicator types, usually divided according to the indicator effects. For example, the closer the indicator value is to the midpoint of the interval within a specified interval, the better the indicator effect is called an interval indicator; the closer the indicator value is to the maximum value, the better the indicator effect is called a positive indicator; the closer the indicator value is to the minimum value, the better the indicator effect is called a reverse indicator. For different types of candidate evaluation indicators, the processing formulas have the following subtle differences. The embodiments of the present invention uniformly stipulate that the candidate evaluation indicators are converted into positive indicators. Among them, the interval indicator formula is a reverse algorithm and needs to be positively indexed again.

[0072] For positive indicators, the dimensionless preprocessing formula is:

[0073]

[0074] For the reverse indicator, the dimensionless preprocessing formula is:

[0075]

[0076] For interval indicators, the dimensionless preprocessing formula is:

[0077]

[0078] Among them C mid is the best value in the interval.

[0079] The discretization processing in the embodiment of the present invention adopts equal-frequency discretization, and there are n samples. The embodiment of the present invention defines the frequency k as 2 or 3, and the discrete value is {excellent, good} or {excellent, suboptimal, good}, and discretizes according to this rule; and the intervals after discretization are defined as positive indicator intervals, that is, the larger the value represented by the interval, the more it can represent the normal status of the substation.

[0080] The embodiment of the present invention takes the first indicator data of 8 low-pressure areas in region A as an example to perform normalization and discretization processing. The first indicator data is shown in Table 1, the normalized data is shown in Table 2, and the discretized data is shown in Table 3. C1, C2, C3, C4, C5, and C6 are candidate evaluation indicators for 6 different low-pressure areas.

[0081] Table 1A: The first indicator data of 8 low-pressure areas in region

[0082]

[0083] Table 2 Normalized data of the first indicator of 8 low-pressure areas in Region A

[0084]

[0085] Table 3 Discretization of the first indicator data of the eight low-pressure areas in Region A

[0086]

[0087]

[0088] S320: Analyze the second indicator data using the Delphi method and the analytic hierarchy process to construct a decision table based on candidate evaluation indicators.

[0089] Among them, the simplification and weighting of indicator data in rough set theory are all based on decision tables. Therefore, before comprehensively evaluating the operating status of low-voltage substations, the corresponding low-voltage substation system information should be converted into the form of decision tables for subsequent processing. The decision attributes of the decision table correspond to the domain samples one by one, which is the final evaluation of the sample; in other words, in the low-voltage substation evaluation system, the decision conditions of the decision table constructed using the low-voltage substation information are the final basis for judging the operating status of the low-voltage substation. The level of the decision attribute in the decision table is determined by all the conditional attributes. The influence of different attributes on the final judgment may not be the same, which involves the problem of attribute weighting.

[0090] The rough set weighting method is a method based only on data, which will inevitably bring limitations. This limitation requires that the sample data used must be representative and universal, otherwise the weights obtained through data mining will hardly objectively reflect the actual effect of the indicator. Moreover, the rough set weighting method only mines weights based on the importance of attributes, and often draws conclusions that are contrary to the facts based on quantitative analysis alone, so qualitative analysis needs to be integrated. In order to incorporate the experience of predecessors into the subsequent rough set weighting and avoid the weighting results being inconsistent with objective facts, the embodiment of the present invention decides to introduce the idea of ​​subjective weighting in the problem of constructing the decision attributes of the decision table, so as to achieve the purpose of integrating prior knowledge. In this way, the solution to the entire problem evolves into using the predecessors' leading experience to find weights. Then according to the formula Convert the rating to a numerical value; where C i (X m ) is the value of the low-voltage area sample m on the i-th evaluation index, w i is the weight of condition attribute i. Note that the decision attribute obtained by this idea is still discrete. To facilitate subsequent processing, according to the above data preprocessing method, the embodiment of the present invention divides the decision attribute into three levels: {excellent, suboptimal, good}, and the corresponding scores are {3, 2, 1}, and the condition attribute is divided into two levels {excellent, good}, and the corresponding values ​​are {2, 1}.

[0091] As an optional but non-limiting implementation, the step of constructing a decision table based on the second indicator data includes but is not limited to steps B1-B3:

[0092] Step B1: Analyze the second indicator data according to the Delphi method and the analytic hierarchy process, and construct a judgment matrix based on the candidate evaluation indicators; wherein the element values ​​in the judgment matrix are used to represent the levels of the candidate evaluation indicators.

[0093] Step B2: Performing a prior weighting and normalization process on the element values ​​in the judgment matrix to obtain the decision attribute value of each candidate evaluation index.

[0094] Step B3: Discretize the decision attribute values ​​to obtain decision attribute vectors to construct a decision table based on candidate evaluation indicators.

[0095] The embodiment of the present invention relies on the Delphi method and the analytic hierarchy process to solve the problem of lack of leading experience in rough set weighting. The Delphi method and the analytic hierarchy process are systematic, simple and practical. When combined with rough sets, they can make up for the contradiction between the latter's weighting and reality to a certain extent. When specifically applied to the problem of weighting conditional attributes, each conditional attribute can be regarded as a different component factor for evaluating the operating status of a low-voltage station. These factors are used as the criterion layer, and the decision-making attributes are used as the target layer. By comparing the conditional attributes horizontally, the importance between the two is determined. In order to make the comparison more accurate, the comparison levels of all elements use the same scale to reduce the difficulty of comparing factors of different natures. The entire process of obtaining decision attributes can be carried out according to the following steps:

[0096] The first step is to judge the matrix S ij The construction of is the premise of finding the decision attribute. In the judgment matrix, any element a ij The meaning of is the comparison result of its corresponding i element and j element, and In order to improve the rationality of this algorithm, the Delphi method is used to classify the important relationship between elements i and j, and the rating is based on expert opinions. The overall idea is to divide the important relationship between factors i and j into 9 levels, that is, the [1, 9] scaling method is adopted. The specific importance of the 9 levels is shown in Table 4.

[0097] Table 4 Judgment matrix element definition

[0098]

[0099] The second step is to find the weight. Multiply the matrix indexes corresponding to each column element, and then take the nth power, where n is the total number of evaluation elements. The formula is as follows:

[0100]

[0101] Among them, q i It is the weighted value of each column element of the judgment matrix.

[0102] The third step is to normalize the weights obtained in the second step to obtain a weight vector B = {b1, b2, b3...b n}, by the formula d(X i )=C i (X)·B T Get the decision attribute value of each sample in the domain, where d(X i ) is the decision attribute value of the i-th sample; C i (X) is the conditional attribute vector of the i-th sample.

[0103] The fourth step is to discretize the decision attribute values ​​calculated in the third step to facilitate rough set data analysis and obtain a decision attribute vector. The embodiment of the present invention discretizes the decision attribute as a positive indicator to obtain three levels of {excellent, suboptimal, good}.

[0104] The embodiment of the present invention takes the construction of a decision table for the second indicator data in Table 3 as an example, and establishes a judgment matrix based on the rating opinions of experts. The judgment matrix can be expressed as:

[0105]

[0106] After weighting the elements of each column in the judgment matrix, we get q = {0.69, 1.48, 1.24, 1.00, 1.33, 0.74}; the weight vector after normalization is B = {0.11, 0.23, 0.19, 0.15, 0.21, 0.11}; the decision attribute value is expressed as d(X) T ={1.34, 1.37, 1.79, 2.24, 1.4, 1.81, 2.78, 2.27}; finally, the decision table is obtained, as shown in Table 5.

[0107] Table 5 Decision table

[0108]

[0109] S330, simplifying the decision table using rough set theory to obtain a target decision table.

[0110] Among them, for a single decision table, a single case is a decision rule, that is, according to the conditional attributes given by a certain sample, there is only one corresponding decision attribute. If all decision rules are listed, a collection of decision rules can be obtained, corresponding to the complete selection criteria of the decision table. However, such a decision table is useless. It only mechanically records the sample situation of the decision table. If a new sample is added to the domain, the decision rule cannot adapt to the new sample, lacks rationality, and has low adaptability. Therefore, it is necessary to simplify the decision table, otherwise the scattered decision rules are not only huge in number but also have no adaptability. By examining the internal connection between the conditional attributes, making the samples of the decision table regular is the simplification of evaluation indicators.

[0111] As an optional but non-limiting implementation, the use of rough set theory to simplify the decision table includes but is not limited to steps C1-C4:

[0112] Step C1: Determine the first dependency between the decision table and the candidate evaluation index.

[0113] Step C2: arbitrarily eliminate a first candidate evaluation indicator from the candidate evaluation indicators to obtain a second candidate evaluation indicator and a first decision table, and determine a second dependency between the second candidate evaluation indicator and the first decision table.

[0114] Step C3: If the difference between the second dependency and the first dependency is greater than a preset difference threshold, the first candidate evaluation indicator needs to be retained; otherwise, the first candidate evaluation indicator is eliminated.

[0115] Step C4: Eliminate any first candidate evaluation index from the candidate evaluation indexes in turn, and determine the second dependency, so as to simplify the decision table.

[0116] Among them, after obtaining the decision table, the decision table is simplified to determine the target decision table. The embodiment of the present invention simplifies the decision table by the dependency between the decision table and the candidate evaluation indicators; first determine the first dependency between the decision table and the candidate evaluation indicators; then eliminate any candidate evaluation indicator to determine the dependency between the decision table after eliminating the candidate evaluation indicator and the remaining candidate evaluation indicators; compare the dependency to determine whether the eliminated candidate evaluation indicator affects the decision table. If the impact is small, it means that the eliminated candidate evaluation indicator has a small impact on the comprehensive evaluation of the low-voltage substation of the distribution network, then the current candidate evaluation can be eliminated to obtain the target decision table; if the impact is large, the current candidate evaluation needs to be retained. Eliminate the candidate evaluation indicators once to obtain the corresponding dependency, and compare the corresponding dependency with the first dependency between the decision table and the candidate evaluation indicators to determine whether the current candidate evaluation indicator needs to be retained, and finally obtain the target decision table. Optionally, the simplification method of the decision table is not specifically limited in the implementation of the present invention.

[0117] S340, determine the target evaluation indicators that constitute the target decision table.

[0118] Among them, after determining the target decision table, the target evaluation index constituting the target decision table is determined; the target evaluation index is used to evaluate the operating status of the low-voltage substation of the distribution network.

[0119] S350, using the Delphi subjective weighting method and the rough set objective weighting method to comprehensively weight the target evaluation indicators, and using the target evaluation indicators after comprehensive weighting to comprehensively evaluate the low-voltage substation of the distribution network.

[0120] Among them, see Figure 4 After constructing the decision table and determining the target evaluation indicators, the Delphi subjective weighting method and the rough set objective weighting method are used to comprehensively weight the target evaluation indicators, and the target evaluation indicators after comprehensive weighting are used to comprehensively evaluate the low-voltage substation of the distribution network.

[0121] As an optional but non-limiting implementation method, the Delphi subjective weighting method and the rough set objective weighting method are used to comprehensively weight the target evaluation indicators, and the target evaluation indicators after comprehensive weighting are used to comprehensively evaluate the low-voltage substation of the distribution network, including but not limited to steps D1-D4:

[0122] Step D1: Use the Delphi subjective weighting method to determine the first weight of the target evaluation index.

[0123] Step D2: According to the dependency of each target evaluation indicator, the second weight of the target evaluation indicator is determined by using the rough set objective weighting method.

[0124] Step D3: Comprehensively weighting the target evaluation indicator according to the first weight and the second weight of the target evaluation indicator to obtain a target weight of the target evaluation indicator.

[0125] Step D4: Comprehensively evaluate the low-voltage substation of the distribution network based on the target evaluation indicators and the target weights corresponding to the target evaluation indicators.

[0126] Among them, after determining the target evaluation index, the Delphi subjective weighting method and the rough set objective weighting method are used to assign weights to the target evaluation index, and the assigned weights are comprehensively weighted to obtain the target weight of the target evaluation index. Based on the target evaluation index and the target weight, the low-voltage substation of the distribution network is comprehensively evaluated.

[0127] The embodiment of the present invention provides a comprehensive evaluation method for low-voltage substations in a distribution network. The method determines the candidate evaluation indexes that affect the operating state of the low-voltage substations in the distribution network, obtains the first index data of the candidate evaluation indexes and pre-processes the first index data to obtain the second index data; the second index data is analyzed by using the Delphi method and the analytic hierarchy process to construct a decision table based on the candidate evaluation indexes; the decision table is simplified by using the rough set theory to obtain the target decision table; the target evaluation indexes constituting the target decision table are determined; the Delphi subjective weighting method and the rough set objective weighting method are used to comprehensively weight the target evaluation indexes, and the target evaluation indexes after comprehensive weighting are used to comprehensively evaluate the low-voltage substations in the distribution network. The technical scheme of the embodiment of the present invention is adopted, the low-voltage substations in the distribution network are taken as the evaluation objects, the operating states of multiple substations are longitudinally evaluated as the evaluation purpose, the evaluation index system is qualitatively selected, and the evaluation index system is established under the premise of the systematic, scientific and feasible principles. Through the six third-level indicators of the low-voltage area of ​​the distribution network, the grid structure and operation level of the low-voltage area of ​​the distribution network are evaluated, and the Delphi subjective weighting method and the rough set objective weighting method are used to comprehensively evaluate the operation status of the low-voltage area, providing auxiliary decision-making for operation and maintenance personnel and planners.

[0128] Embodiment 3

[0129] Figure 5 This is a schematic diagram of the structure of a comprehensive evaluation device for low-voltage distribution network areas provided in an embodiment of the present invention. The technical solution of this embodiment can be applied to the situation where the rough set theory is used to comprehensively evaluate the low-voltage distribution network areas. The device can be implemented by software and / or hardware and is generally integrated on any electronic device with network communication function, including but not limited to: servers, computers, personal digital assistants and other devices. Figure 5 As shown, the comprehensive evaluation device for low-voltage distribution network areas provided in this embodiment may include:

[0130] The index data processing module 510 is used to determine the candidate evaluation index that affects the operation state of the low-voltage substation of the distribution network, obtain the first index data of the candidate evaluation index and pre-process the first index data to obtain the second index data;

[0131] A decision table processing module 520 is used to construct a decision table according to the second indicator data, and simplify the decision table using rough set theory to obtain a target evaluation indicator;

[0132] The low voltage substation comprehensive evaluation module 530 is used to use the Delphi subjective weighting method and the rough set objective weighting method to comprehensively weight the target evaluation indicators, and use the comprehensively weighted target evaluation indicators to comprehensively evaluate the low voltage substation of the distribution network.

[0133] Based on the above embodiment, optionally, the indicator data processing module is specifically used to:

[0134] Determine candidate evaluation indicators that affect the operating status of the low-voltage area of ​​the distribution network, and obtain first indicator data of the candidate evaluation indicators; wherein the candidate evaluation indicators include the grid structure and the operating level, and the first indicator data includes the qualified rate of the conductor cross section, the power supply radius, the transformer load rate, the three-phase load imbalance, the node voltage qualified rate, and the proportion of voltage qualified users;

[0135] The first indicator data of the candidate evaluation indicator is normalized and discretized to obtain second indicator data; wherein the preprocessing includes normalization and discretization.

[0136] Based on the above embodiment, optionally, the decision table processing module is specifically used to:

[0137] The second indicator data is analyzed by using the Delphi method and the analytic hierarchy process to construct a decision table based on candidate evaluation indicators;

[0138] The decision table is simplified by using rough set theory to obtain a target decision table;

[0139] Determine target evaluation indicators that constitute a target decision table; wherein the target evaluation indicators are used to evaluate the operating status of a low-voltage area in a distribution network.

[0140] Based on the above embodiment, optionally, the decision table processing module is further specifically used for:

[0141] Analyze the second indicator data according to the Delphi method and the hierarchical analysis method, and construct a judgment matrix based on the candidate evaluation indicators; wherein the element values ​​in the judgment matrix are used to represent the levels of the candidate evaluation indicators;

[0142] The element values ​​in the judgment matrix are weighted and normalized to obtain the decision attribute value of each candidate evaluation index;

[0143] The decision attribute values ​​are discretized to obtain a decision attribute vector to construct a decision table based on candidate evaluation indicators.

[0144] Based on the above embodiment, optionally, the decision table processing module is further specifically used for:

[0145] Determining a first dependency between the decision table and the candidate evaluation index;

[0146] Eliminate any first candidate evaluation indicator from the candidate evaluation indicators to obtain a second candidate evaluation indicator and a first decision table, and determine a second dependency between the second candidate evaluation indicator and the first decision table;

[0147] If the difference between the second dependency and the first dependency is greater than the preset difference threshold, the first candidate evaluation indicator needs to be retained; otherwise, the first candidate evaluation indicator is eliminated;

[0148] Any first candidate evaluation index is eliminated from the candidate evaluation indexes in turn, and a second dependency is determined to simplify the decision table.

[0149] On the basis of the above embodiment, optionally, the low voltage area comprehensive evaluation module is specifically used for:

[0150] The Delphi subjective weighting method is used to determine the first weight of the target evaluation index;

[0151] According to the dependency of each target evaluation index, the rough set objective weighting method is used to determine the second weight of the target evaluation index;

[0152] Comprehensively weighting the target evaluation indicator according to the first weight and the second weight of the target evaluation indicator to obtain a target weight value of the target evaluation indicator;

[0153] Based on the target evaluation indicators and the target weights corresponding to the target evaluation indicators, a comprehensive evaluation is performed on the low-voltage substation of the distribution network.

[0154] The comprehensive evaluation device for the low-voltage substation of the distribution network provided in the embodiment of the present invention can execute the comprehensive evaluation method for the low-voltage substation of the distribution network provided in any of the above-mentioned embodiments of the present invention, and has the corresponding functions and beneficial effects of executing the comprehensive evaluation method for the low-voltage substation of the distribution network. For detailed process, please refer to the relevant operations of the comprehensive evaluation method for the low-voltage substation of the distribution network in the above-mentioned embodiment.

[0155] Embodiment 4

[0156] Figure 6 1 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0157] like Figure 6 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0158] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0159] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 11 executes the various methods and processes described above, such as a comprehensive evaluation method for low-voltage distribution network areas.

[0160] In some embodiments, the comprehensive evaluation method for the low-voltage area of ​​the distribution network may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the comprehensive evaluation method for the low-voltage area of ​​the distribution network described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the comprehensive evaluation method for the low-voltage area of ​​the distribution network by any other appropriate means (e.g., by means of firmware).

[0161] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0162] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0163] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0164] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0165] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0166] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0167] Embodiment 5

[0168] An embodiment of the present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements a comprehensive evaluation method for low-voltage substations in a distribution network as provided in any embodiment of the present application.

[0169] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0170] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0171] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A comprehensive evaluation method for low-voltage distribution network areas, characterized in that: The method comprises: Determine candidate evaluation indicators that affect the operating state of the low-voltage area of ​​the distribution network, obtain first indicator data of the candidate evaluation indicators, and pre-process the first indicator data to obtain second indicator data; A decision table is constructed according to the second indicator data, and the decision table is simplified by using rough set theory to obtain a target evaluation indicator; The Delphi subjective weighting method and the rough set objective weighting method are used to comprehensively weight the target evaluation indicators, and the target evaluation indicators after comprehensive weighting are used to comprehensively evaluate the low-voltage substations of the distribution network.

2. The method according to claim 1, characterized in that The step of determining candidate evaluation indicators that affect the operation state of the low-voltage area of ​​the distribution network, obtaining first indicator data of the candidate evaluation indicators and preprocessing the first indicator data to obtain second indicator data includes: Determine candidate evaluation indicators that affect the operating status of the low-voltage area of ​​the distribution network, and obtain first indicator data of the candidate evaluation indicators; wherein the candidate evaluation indicators include the grid structure and the operating level, and the first indicator data includes the qualified rate of the conductor cross section, the power supply radius, the transformer load rate, the three-phase load imbalance, the node voltage qualified rate, and the proportion of voltage qualified users; The first indicator data of the candidate evaluation indicator is normalized and discretized to obtain second indicator data; wherein the preprocessing includes normalization and discretization.

3. The method according to claim 1, characterized in that: The decision table is constructed based on the second indicator data, and the decision table is simplified by using rough set theory to obtain the target evaluation index, including: The second indicator data is analyzed by using the Delphi method and the analytic hierarchy process to construct a decision table based on candidate evaluation indicators; The decision table is simplified by using rough set theory to obtain a target decision table; Determine target evaluation indicators that constitute a target decision table; wherein the target evaluation indicators are used to evaluate the operating status of a low-voltage substation in a distribution network.

4. The method according to claim 1, characterized in that The step of constructing a decision table based on the second indicator data includes: Analyze the second indicator data according to the Delphi method and the hierarchical analysis method, and construct a judgment matrix based on the candidate evaluation indicators; wherein the element values ​​in the judgment matrix are used to represent the levels of the candidate evaluation indicators; The element values ​​in the judgment matrix are weighted and normalized to obtain the decision attribute value of each candidate evaluation index; The decision attribute values ​​are discretized to obtain a decision attribute vector to construct a decision table based on candidate evaluation indicators.

5. The method according to claim 1, characterized in that: The adopting rough set theory to simplify the decision table includes: Determining a first dependency between the decision table and the candidate evaluation index; Eliminate any first candidate evaluation indicator from the candidate evaluation indicators to obtain a second candidate evaluation indicator and a first decision table, and determine a second dependency between the second candidate evaluation indicator and the first decision table; If the difference between the second dependency and the first dependency is greater than the preset difference threshold, the first candidate evaluation indicator needs to be retained; otherwise, the first candidate evaluation indicator is eliminated; Any first candidate evaluation index is eliminated from the candidate evaluation indexes in turn, and a second dependency is determined to simplify the decision table.

6. The method according to claim 1, characterized in that The Delphi subjective weighting method and the rough set objective weighting method are used to comprehensively weight the target evaluation indicators, and the target evaluation indicators after comprehensive weighting are used to comprehensively evaluate the low-voltage substation of the distribution network, including: The Delphi subjective weighting method is used to determine the first weight of the target evaluation index; According to the dependency of each target evaluation index, the rough set objective weighting method is used to determine the second weight of the target evaluation index; Comprehensively weighting the target evaluation indicator according to the first weight and the second weight of the target evaluation indicator to obtain a target weight value of the target evaluation indicator; Based on the target evaluation indicators and the target weights corresponding to the target evaluation indicators, a comprehensive evaluation is performed on the low-voltage substation of the distribution network.

7. A comprehensive evaluation device for low-voltage distribution network, characterized in that: The device comprises: An indicator data processing module is used to determine candidate evaluation indicators that affect the operating state of the low-voltage substation of the distribution network, obtain first indicator data of the candidate evaluation indicators, and pre-process the first indicator data to obtain second indicator data; A decision table processing module, used for constructing a decision table according to the second indicator data, and simplifying the decision table by using rough set theory to obtain a target evaluation indicator; The low-voltage substation comprehensive evaluation module is used to use the Delphi subjective weighting method and the rough set objective weighting method to comprehensively weight the target evaluation indicators, and use the target evaluation indicators after comprehensive weighting to comprehensively evaluate the low-voltage substation of the distribution network.

8. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the comprehensive evaluation method for low-voltage substations in a distribution network as described in any one of claims 1-6.

9. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions, when executed by a computer processor, are used to execute the comprehensive evaluation method for low-voltage substations in a distribution network as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the comprehensive evaluation method for low-voltage substations in a distribution network according to any one of claims 1 to 6.

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