Multi-dimensional evaluation method and system for load-adjustable participation in market transaction

Abstract

The invention discloses a multi-dimensional evaluation method and system for an adjustable load to participate in a market transaction, and the method comprises the steps: constructing a multi-dimensional evaluation index system, and obtaining the corresponding index data of the adjustable load to participate in the transaction; an AHP-EWM evaluation model is established, the subjective weight is calculated through AHP based on the index data, the objective weight is calculated through EWM, the AHP is an analytic hierarchy process, and the EWM is an entropy weight method; according to the AHP-EWM evaluation model, combined with the subjective weight and the objective weight, calculating to obtain a comprehensive weight of each index; and evaluating the transaction result according to the comprehensive weight. According to the method, a three-level index system covering multiple dimensions and an evaluation model combining subjectivity and objectivity are established, so that the accuracy and reliability of evaluation are improved, and diversified requirements are met.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of power economy of power systems, and particularly relates to a multi-dimensional evaluation method and system for adjustable load participating in market transaction. BACKGROUND

[0002] The marketization reform process of China's power system continues to deepen, and the demand side load resource participating in market transaction gradually evolves towards a normal operation mode. As the core carrier of demand side response, adjustable load adjusts its power consumption behavior according to system demand, supports the flexible adjustment of supply and demand balance on both sides of the power grid through the power market price signal transmission mechanism, and realizes the two-way dynamic coupling of load curve and generation side output.

[0003] The participation of load side adjustable resources in market transaction has different degrees of influence on power grid operation, user use and cost benefit, and has multiple values. At present, many scholars have carried out research on the value of adjustable load participating in market, including establishing characteristic indexes and static indexes under different actual businesses, and value evaluation indexes for participating in spot market. However, the current achievements mostly focus on the emission reduction and economy generated by demand side load participating in adjustment, and less consider the multi-dimensional influence effect. The indexes are not fully combined with the development of multi-market transaction environment, and the index design needs to be further improved. In addition, the evaluation process of transaction results has not been visually displayed, and the evaluation results of different dimensions need to be further quantitatively represented. SUMMARY

[0004] (I) Invention purpose

[0005] The purpose of the present application is to provide a multi-dimensional evaluation method and system for adjustable load participating in market transaction, which establishes a three-level index system covering multiple dimensions and an evaluation model combining subjective and objective factors to improve the accuracy and reliability of evaluation and meet diversified needs.

[0006] (II) Technical solution

[0007] To solve the above problems, the first aspect of the present application provides a multi-dimensional evaluation method for adjustable load participating in market transaction, comprising:

[0008] Constructing a multi-dimensional evaluation index system to obtain corresponding index data of adjustable load participating in transaction;

[0009] Establishing an AHP-EWM evaluation model, calculating subjective weights based on the index data by AHP, and calculating objective weights by EWM, wherein AHP is an analytic hierarchy process, and EWM is an entropy weight method;

[0010] According to the AHP-EWM evaluation model, the comprehensive weights of each index are calculated by combining the subjective weights and the objective weights.

[0011] evaluate the transaction result according to the comprehensive weight;

[0012] The evaluation index system comprises three first-level indexes, each first-level index comprises at least one second-level index, and each second-level index comprises a plurality of third-level indexes.

[0013] Further, the AHP is used to calculate the subjective weight based on the transaction index data, and the AHP comprises:

[0014] According to the AHP, a target layer, a criterion layer and a scheme layer are established, the evaluation of the transaction result is taken as the target layer, a plurality of third-level indexes are taken as the criterion layer, and transaction index data are taken as the scheme layer;

[0015] The 1-9 scale method is used to compare the third-level indexes in the criterion layer two by two, and a judgment matrix is constructed according to the comparison result;

[0016] It is judged whether the judgment matrix is a consistent matrix, and the subjective weight is calculated according to the judgment result;

[0017] According to the subjective weight, the consistency of the judgment matrix is verified.

[0018] Further, the EWM is used to calculate the objective weight, and the EWM comprises:

[0019] The information entropy of each index data is calculated;

[0020] The occurrence probability of the corresponding index data under each index is calculated in combination with the information entropy;

[0021] The entropy value of each index is calculated based on the occurrence probability, and the objective weight is calculated based on the entropy value.

[0022] Further, the calculation formula of the occurrence probability of the corresponding index data under each index is as follows:

[0023]

[0024] wherein p ij represents the probability of the occurrence of the i th transaction result under the j th index, x ij represents the i th transaction result under the j th index, and n is the number of transaction results.

[0025] Further, the calculation formula of the entropy value is as follows:

[0026]

[0027] wherein e j represents the entropy value of the j th index.

[0028] Further, the calculation formula of the objective weight is as follows:

[0029]

[0030] d j =1-e j ;

[0031] Wherein, d j is the information utility value, beta j is the objective weight of the index determined by EWM, and m is the number of evaluation indexes.

[0032] Further, the calculation formula of the comprehensive weight is as follows:

[0033]

[0034] Wherein, w j is the comprehensive weight of the index j, and alpha j is the subjective weight of the index determined by AHP.

[0035] Further, judging whether the judgment matrix is a consistent matrix, and calculating the subjective weight according to the judgment result comprises:

[0036] If the judgment matrix is a consistent matrix, the maximum characteristic vector thereof is the subjective weight;

[0037] If the judgment matrix is an inconsistent matrix, the subjective weight is calculated by using the geometric mean method, the arithmetic mean method or the eigenvalue method.

[0038] Further, the consistency formula of the judgment matrix is as follows:

[0039]

[0040] Wherein, CR is the consistency ratio, CI is the consistency index, and RI is the random consistency index.

[0041] The second aspect of the application provides a multi-dimensional evaluation system for adjustable load participating in market transaction, comprising:

[0042] An index system construction module is configured to construct a multi-dimensional evaluation index system, acquire corresponding index data of adjustable load participating in transaction, and visually display the index data.

[0043] An evaluation model establishment module is configured to establish an AHP-EWM evaluation model, calculate the subjective weight by using AHP based on the index data, calculate the objective weight by using EWM, wherein AHP is a hierarchical analysis method, EWM is an entropy weight method, and the calculation results are visually displayed.

[0044] A computing comprehensive weight module is configured to calculate and visually display the comprehensive weight of each index according to the AHP-EWM evaluation model, in combination with the subjective weight and the objective weight.

[0045] An evaluation module is configured to evaluate the transaction result according to the comprehensive weight and visually compare and display the evaluation result with the single-dimension index evaluation result.

[0046] The evaluation index system includes three first-level indexes, each first-level index includes at least one second-level index, and each second-level index includes a plurality of third-level indexes.

[0047] (Three) beneficial effects

[0048] The above technical solution of the present application has the following beneficial technical effects: the present application provides a multi-dimension evaluation method and system for adjustable load participating in market transaction, which establishes a three-level index system covering market transaction, market efficiency, economic benefit and other multi-dimensions, considers the objective connection between different index data, combines the subjectivity of the weight of each index, establishes an evaluation model combining subjectivity and objectivity, and evaluates different transaction results flexibly. Based on the model, considering the difference of the evaluation results of different dimension indexes, the present application further provides a design system based on the method, which visually displays the evaluation process of transaction data through a software interface design, displays the output of each evaluation process in multiple forms, finally compares and presents the evaluation results of the overall evaluation system and a single-dimension index, quantifies the transaction result, and provides a reference basis for subsequent market design. BRIEF DESCRIPTION OF DRAWINGS

[0049] Figure 1 is a multi-dimension evaluation method flow chart for adjustable load participating in market transaction of the present application;

[0050] Figure 2 is a multi-dimension evaluation system schematic diagram for adjustable load participating in market transaction of the present application;

[0051] Figure 3 is a hierarchical analysis evaluation model schematic diagram of a specific embodiment of the present application;

[0052] Figure 4 is an entropy weight method weight determination flow chart of a specific embodiment of the present application;

[0053] Figure 5 is a software interface platform of a multi-dimension evaluation system specific embodiment for adjustable load participating in market transaction of the present application. DETAILED DESCRIPTION

[0054] To make the objects, technical solutions and advantages of the present application clearer, further detailed description will be made to the present application with reference to the specific embodiments and the accompanying drawings. It should be understood that the description is only exemplary and is not intended to limit the scope of the present application. In addition, in the following description, the description of the known structures and technologies is omitted to avoid unnecessary confusion of the concept of the present application.

[0055] As shown in Figure 1 , the first aspect of the present application provides a multi-dimensional evaluation method for adjustable load participating in market transaction, comprising:

[0056] S1, constructing a multi-dimensional evaluation index system to obtain corresponding index data (transaction results) of adjustable load participating in transaction; the adjustable load refers to the load that can be flexibly adjusted in the use of electricity within a certain time range, including demand elastic industrial and commercial load, residential load, electric vehicles with two-way regulation capacity, energy storage, distributed power and virtual power plant, etc. The evaluation index system includes 3 first-level indexes, each first-level index includes at least one second-level index, and each second-level index includes a plurality of third-level indexes, as shown in Table 1. Table 1 is to sort out the different levels of value brought by the adjustable load participating in the operation of the power grid, and a three-level index system is established, which is more detailed, for example, there are 3 first-level indexes, including market transaction, market efficiency and market transaction. There are 5 second-level indexes and 8 third-level indexes. The index data of each transaction result can be obtained according to the three-level evaluation indexes in Table 1, which is used as the input of the transaction result evaluation.

[0057] Table 1 Multi-dimensional evaluation index

[0058]

[0059] S2, establishing an AHP-EWM evaluation model, calculating the subjective weight based on the index data by AHP and calculating the objective weight by EWM, wherein AHP is the analytic hierarchy process and EWM is the entropy weight method; in this step, the calculation of the subjective weight and the objective weight is as follows:

[0060] I) calculating the subjective weight based on the transaction index data by AHP, comprising:

[0061] (1) establishing the target layer, the criterion layer and the scheme layer according to the AHP analytic hierarchy process, as shown in Figure 3As shown, the evaluation of the trading result is taken as a target layer, a plurality of third-level indexes are taken as a criterion layer, and trading index data is taken as a scheme layer; the evaluation of the adjustable load trading result needs to consider the influence of a plurality of third-level indexes and belongs to a multi-index comprehensive evaluation problem. Compared with other common comprehensive evaluation methods, the model of the analytic hierarchy process is simpler and has high evaluation efficiency, which matches the comprehensive evaluation demand of the application. AHP establishes a hierarchical model by analyzing and researching a target, and completes the advantage and disadvantage ordering comparison of the target problem according to the correlation degree and importance ordering of each evaluation index. In addition, the application involves both objective analysis of the weight relationship configuration between each evaluation index and subjective analysis of the influence of different power market construction on the index, wherein the subjective weighting part needs to be discussed according to the market construction environment and expert experience, which perfectly matches the subjective characteristics of the analytic hierarchy process. The AHP model takes the evaluation problem of the adjustable load trading result as a target layer, and evaluates the trading result in different scenarios in the scheme layer, wherein the criterion layer is the third-level evaluation index established in table 1, the weight of each third-level index is calculated, and finally the advantages and disadvantages of the trading result are judged.

[0062] (2) The 1-9 scale method is used to compare the third-level indexes in the criterion layer two by two, and a judgment matrix is constructed according to the comparison result; in order to compare the influence of the evaluation index weight on the result of different trading results x={x1,x2,…,x m},a comparison judgment matrix B=(b ij ) m×m is established by comparison, m is the number of evaluation indexes, b ij is the influence ratio of x i and x j on a certain evaluation index, and b ji =1 / b ij . The construction of the judgment matrix depends on the analysis of subjective influence factors such as external policy situation and the given experience of experts. If the matrix B satisfies b ij >0 and b ji =1 / b ij (i,j=1,2,…,m), the matrix B is called a positive reciprocal matrix. In the comparison judgment matrix, 1-9 and its reciprocal are used as scales, wherein 1 represents that two indexes have equal importance, and 9 represents that the index is extremely important than another index.

[0063] (3) Determine whether the judgment matrix is a consistent matrix, and calculate the subjective weight according to the judgment result, which specifically includes:

[0064] A、If the judgment matrix is a consistent matrix, its maximum eigenvector is the subjective weight. In determining the weight, firstly judge whether the comparison matrix B is a consistent matrix. If the matrix B is a consistent matrix, each row and column is proportional, and a maximum eigenvector can be obtained by selecting a column. If the positive reciprocal matrix satisfying formula (1) is a consistent matrix, as follows:

[0065]

[0066] B、If the judgment matrix is an inconsistent matrix, the subjective weight is calculated by using the geometric mean method, the arithmetic mean method or the eigenvalue method. For the inconsistent matrix, the weight can be obtained by using the geometric mean method, the arithmetic mean method and the eigenvalue method. The eigenvalue method is used in the determination of the weight in the application, the eigenvector corresponding to the maximum eigenvalue of the judgment matrix B is obtained, and the normalized eigenvector is the ranking weight.

[0067] (4) According to the subjective weight, the consistency of the judgment matrix is verified. Considering that there may be an unreasonable or non-existent relationship between the rows and columns of the judgment matrix, it is necessary to verify whether the constructed judgment matrix B is reasonable or whether there is a serious inconsistency. If the m-order positive reciprocal matrix B is a consistent matrix, its maximum eigenvalue λ max =m, when the positive reciprocal matrix B is inconsistent, there must be λ max >m. Therefore, the consistency index CI=(λ max -m) / (m-1) is defined, and the more λ max is greater than m, the more serious the inconsistency of the matrix B is. In order to measure the size of CI, the random consistency index RI is introduced, and the consistency ratio CR=CI / RI is defined. When CR<0.1, it is considered that the inconsistency of the matrix B is within the tolerable range and passes the consistency test. Otherwise, the value of the elements of the judgment matrix B will be adjusted. The formula for verifying the consistency of the judgment matrix is as follows:

[0068]

[0069] Wherein, CR is the consistency ratio, CI is the consistency index, and α i is the subjective weight of the index i determined by AHP.

[0070] II) The objective weight is calculated by using EWM, including:

[0071] (1) Calculate the information entropy of each indicator data; although there is a certain objective connection between different evaluation indicators, if the weight configuration is based solely on the empirical inference of the AHP method, there may be strong subjectivity, resulting in weight deviation. Therefore, it is necessary to analyze the objective weighting method based on entropy weight calculation to calculate the objective weight of each evaluation indicator. Among them, the EWM method determines the indicator weight by introducing information entropy. Assuming that x represents a certain situation in which event X may occur, and p(x) represents the probability of this situation occurring, then the relationship between the amount of information I and the probability p can be fitted by a logarithmic function:

[0072] I(x)=-ln(p(x)); (3)

[0073] The possible occurrences of event X are x1, x2, ..., x n , then define the information entropy of event X:

[0074]

[0075] (2) Combined with the information entropy, the probability of occurrence of the corresponding indicator data under each indicator is calculated. The calculation process of determining the weight of each indicator based on information entropy includes data preprocessing and calculating the probability of occurrence of the corresponding indicator data under each indicator. The calculation formula is as follows:

[0076]

[0077] Among them, p ij represents the probability of the i-th transaction result occurring under the j-th indicator, x ij It represents the i-th transaction result under the j-th indicator, and n is the number of transaction results.

[0078] (3) Calculate the entropy value of each indicator based on the occurrence probability, and calculate the objective weight based on the entropy value. The calculation formula of the entropy value is as follows:

[0079]

[0080] Among them, e j The information entropy of each indicator is in the range of [0,1], and the larger the information entropy, the more stable the data under the indicator. Therefore, the concept of information utility value d is introduced. j , d j =1-e j , normalizing the information utility value, we can get the entropy weight of each indicator. The calculation formula of the objective weight is as follows:

[0081]

[0082] d j =1-e j ; (8)

[0083] Among them, d j is the information utility value, β j is the objective weight of the indicator determined by EWM, m

[0084] is the number of evaluation indicators.

[0085] S3. Based on the AHP-EWM evaluation model, the subjective weights and the objective weights are combined to calculate the comprehensive weights of each indicator. Based on the principle analysis in the previous article, the transaction results to be evaluated in this application involve both the objective connection between the indicator weights and the subjective analysis of the overall market construction. Therefore, it will be considered to establish an AHP-EWM evaluation model that combines subjective and objective weighting. First, the subjective indicator weights of the AHP model are determined through subjective analysis. Then, the objective weights of each evaluation indicator are calculated using EWM. After that, the final comprehensive weight is obtained by combining the subjective and objective weights. The overall process of determining the comprehensive weight is shown in the attached figure. Figure 4 As shown, the consistency of the constructed evaluation model is then verified to be reasonable. The final evaluation scenario and rating settings are subjectively adjusted according to the actual business situation to optimize the overall model design. The calculation formula for the comprehensive weight is as follows;

[0086]

[0087] where w j is the comprehensive weight of index j, α j It is the subjective weight of the indicator determined by AHP.

[0088] The weight of each indicator is obtained according to the entropy weight method. It is necessary to test whether the consistency of the judgment matrix of the evaluation model is reasonable. The test formula tests the consistency of the total ranking:

[0089]

[0090] Among them, CR is the consistency ratio, CI is the consistency index, RI is the random consistency index, CI=(λ max -m) / (m-1). λ max is the maximum eigenvalue of the judgment matrix.

[0091] S4, evaluating the transaction results according to the comprehensive weight, and visually displaying the evaluation results;

[0092] In addition, if Figure 2 As shown, the second aspect of the present invention provides a multi-dimensional evaluation system for adjustable loads participating in market transactions. The system is based on the constructed AHP-EWM evaluation model, designs an evaluation software platform, simulates the overall evaluation process, and intuitively visualizes the output of the evaluation process and evaluation results. The system includes:

[0093] The index system construction module 21 is configured to construct a multi-dimensional evaluation index system, acquire corresponding index data of the load-adjustable participants in the transaction, and visually display the index data, as shown in Figure 5

[0094] The evaluation model establishment module 22 is configured to establish an AHP-EWM evaluation model, calculate subjective weights based on the index data by using AHP, calculate objective weights by using EWM, wherein AHP is a hierarchical analysis method, EWM is an entropy weight method, and the calculation results are visually displayed.

[0095] The comprehensive weight calculation module 23 is configured to calculate comprehensive weights of each index according to the AHP-EWM evaluation model and the subjective weights and the objective weights, and visually display the comprehensive weights.

[0096] The evaluation module 24 is configured to evaluate the transaction results according to the comprehensive weights, and visually compare and display the evaluation results with the single-dimensional index evaluation results. In the system, each module realizes visual display through a selection interface. The module 24 can perform two parts of single-dimensional and overall evaluation of the three-level indexes. The results in different transaction rounds can be compared according to the index weights, or the evaluation level under a certain transaction condition can be given by giving a reference value. The evaluation results of the overall evaluation system and the single-dimensional index are compared and presented in a radar chart, the transaction results are quantified, and a reference basis is provided for subsequent market design. The evaluation index system includes three first-level indexes, each first-level index includes at least one second-level index, and each second-level index includes a plurality of third-level indexes.

[0097] ​It should be understood that the foregoing detailed description of the application, rather than limiting the application, is intended to explain and describe the current implementation of the application. Any modification, equivalent replacement, improvement, etc. made without departing from the spirit and scope of the application shall be included in the protection scope of the application. In addition, the appended claims of the application are intended to cover all changes and modifications falling within the scope and boundary of the appended claims or the equivalent forms of such scope and boundary. In the description of the application, it should be noted that the terms "first", "second", "third" are only for the purpose of description and cannot be understood as indicating or implying relative importance. Those skilled in the art should understand that the embodiments of the application can be provided as a method, a system, or a computer program product. Therefore, the application can be in the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the application can be in the form of a computer program product implemented on one or more computer usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer usable program code. The application is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as a combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the computer or other programmable data processing apparatus produce a device that implements the functions specified in the flowcharts and / or block diagrams. Those skilled in the art can understand that all or part of the steps in the above-described embodiment methods can be completed by programs instructing relevant hardware. The programs can be stored in a computer readable storage medium, and when executed, include the flow of the above-described embodiment methods. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM), etc. The steps in the embodiment methods of the application can be adjusted, combined, and deleted according to actual needs. The units in the embodiment system of the application can be combined, divided, and deleted according to actual needs. Figure 1 one or more flows and / or blocks Figure 1 one or more flows and / or blocks The skilled in the art can understand that all or part of the steps in the above-described embodiment methods can be completed by programs instructing relevant hardware. The programs can be stored in a computer readable storage medium, and when executed, include the flow of the above-described embodiment methods. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM), etc. The steps in the embodiment methods of the application can be adjusted, combined, and deleted according to actual needs. The units in the embodiment system of the application can be combined, divided, and deleted according to actual needs.

Claims

1. A multi-dimensional evaluation method for adjustable loads participating in market transactions, characterized in that: include: Build a multi-dimensional evaluation index system to obtain the corresponding index data for adjustable load participation in transactions; Establish an AHP-EWM evaluation model, and use AHP to calculate subjective weights based on the indicator data, and use EWM to calculate objective weights, where AHP is the analytic hierarchy process and EWM is the entropy weight method; According to the AHP-EWM evaluation model, the comprehensive weight of each indicator is calculated by combining the subjective weight and the objective weight; Evaluate the transaction results based on the comprehensive weights; The evaluation index system includes three first-level indicators, each first-level indicator includes at least one second-level indicator, and each second-level indicator includes multiple third-level indicators.

2. The multi-dimensional evaluation method for adjustable loads participating in market transactions according to claim 1 is characterized in that: The calculation of subjective weights based on the transaction index data using AHP includes: According to the AHP analytic hierarchy process, the target layer, criterion layer and solution layer are established, including the evaluation of transaction results as the target layer, multiple third-level indicators as the criterion layer, and transaction indicator data as the solution layer; Using the 1-9 scaling method, the three-level indicators in the criterion layer are compared in pairs, and a judgment matrix is ​​constructed based on the comparison results; Determine whether the judgment matrix is ​​a consistent matrix, and calculate the subjective weight according to the judgment result; The consistency of the judgment matrix is ​​verified according to the subjective weights.

3. The multi-dimensional evaluation method for adjustable loads participating in market transactions according to claim 1 is characterized in that: The objective weight calculation using EWM includes: Calculate the information entropy of each indicator data; Combined with the information entropy, the probability of occurrence of the corresponding indicator data under each indicator is calculated; The entropy value of each indicator is calculated based on the occurrence probability, and the objective weight is calculated based on the entropy value.

4. The multi-dimensional evaluation method for adjustable loads participating in market transactions according to claim 3 is characterized in that: The calculation formula for the occurrence probability of the corresponding indicator data under each indicator is as follows: Among them, p ij represents the probability of the i-th transaction result occurring under the j-th indicator, x ij It represents the i-th transaction result under the j-th indicator, and n is the number of transaction results.

5. The multi-dimensional evaluation method for adjustable loads participating in market transactions according to claim 3 is characterized in that: The calculation formula of the entropy value is as follows: Among them, e j Represents the entropy value of the j-th indicator.

6. The multi-dimensional evaluation method for adjustable loads participating in market transactions according to claim 5 is characterized in that: The calculation formula of the objective weight is as follows: d j =1-e j ; Among them, d j is the information utility value, β j is the objective weight of the indicator determined by EWM, and m is the number of evaluation indicators.

7. The multi-dimensional evaluation method for adjustable loads participating in market transactions according to claim 6 is characterized in that: The calculation formula of the comprehensive weight is as follows: where w j is the comprehensive weight of index j, α j It is the subjective weight of the indicator determined by AHP.

8. The multi-dimensional evaluation method for adjustable loads participating in market transactions according to claim 2 is characterized in that: Determining whether the judgment matrix is ​​a consistent matrix and calculating the subjective weight according to the judgment result include: If the judgment matrix is ​​a consistent matrix, then its maximum eigenvector is the subjective weight; If the judgment matrix is ​​an inconsistent matrix, the subjective weight is calculated using the geometric mean method, the arithmetic mean method or the eigenvalue method.

9. The multi-dimensional evaluation method for adjustable loads participating in market transactions according to claim 7 is characterized in that: The consistency formula for checking the judgment matrix is ​​as follows: Among them, CR is the consistency ratio, CI is the consistency index, and RI is the random consistency index.

10. A multi-dimensional evaluation system for adjustable loads participating in market transactions, characterized in that: include: The indicator system construction module is used to build a multi-dimensional evaluation indicator system, obtain the corresponding indicator data of adjustable load participating in the transaction, and visualize the indicator data; Establish an evaluation model module for establishing an AHP-EWM evaluation model, calculate subjective weights based on the indicator data using AHP and calculate objective weights using EWM, where AHP is the analytic hierarchy process and EWM is the entropy weight method, and visualize the calculation results; A comprehensive weight calculation module is used to calculate the comprehensive weight of each indicator based on the AHP-EWM evaluation model and combine the subjective weight and the objective weight, and to perform a visual display; An evaluation module, configured to evaluate the transaction results based on the comprehensive weights, and visually compare the evaluation results with the evaluation results of the single-dimensional indicators; The evaluation index system includes three first-level indicators, each first-level indicator includes at least one second-level indicator, and each second-level indicator includes multiple third-level indicators.

Images