Compressed air energy storage system multi-target evaluation method and device

Abstract

The invention relates to the technical field of compressed air energy storage, in particular to a multi-target evaluation method and device for a compressed air energy storage system. According to the compressed air energy storage technology route and application scene analysis content, compressed air energy storage technology evaluation indexes covering economical efficiency, environmental performance, technicality and reliability are established; an objective weight coefficient is determined by adopting an improved entropy weight method, the influence of extreme index numerical values on a weight evaluation result is weakened, a subjective weight coefficient is determined by adopting an analytic hierarchy process, and weight deviation generated by the entropy weight method due to the fact that the number of evaluation objects is too small is corrected; the established model evaluation result is simple and visual, and the problem that the route selection index of the current compressed air energy storage technology cannot be quantified is solved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of compressed air energy storage, and in particular to a multi-objective evaluation method and device for a compressed air energy storage system. Background Art

[0002] The installed capacity of new energy power generation represented by wind power generation and photovoltaic power generation has gradually increased. According to statistics, by the end of 2023, the installed capacity of wind power will reach 440 million kilowatts, and the installed capacity of photovoltaic power generation will be about 610 million kilowatts, accounting for 15.12% and 20.88% of the total installed capacity in the country, respectively. However, new energy is intermittent and uncertain, and its large-scale grid connection will have an adverse impact on the operation of the power system. Compressed air energy storage technology has the advantages of long energy storage time, large energy storage scale, and long service life. It is suitable for the problem of new energy consumption and is of great significance to the development and utilization of new energy.

[0003] With the deepening of research on compressed air energy storage technology, its equipment and operation process are constantly innovating, and a variety of technical routes with their own characteristics have emerged. Considering the different impacts of different technical routes on the environment, economy, and power system operation, it is necessary to select the appropriate technical route for specific application scenarios and needs.

[0004] In the existing technology, the methods for evaluating the technical routes of compressed air energy storage systems are mostly qualitative evaluations, lacking intuitive and effective quantitative evaluation results, and the evaluation index system is still imperfect.

[0005] In summary, there is an urgent need for a quantitative evaluation method for compressed air energy storage systems that covers multiple indicators such as efficiency, cost, and environment. Summary of the invention

[0006] In response to the above problems, the present disclosure provides a multi-objective evaluation method and device for a compressed air energy storage system, which is used to establish a quantitative evaluation model covering economic, environmental, technical, reliability and other objectives.

[0007] In a first aspect, a multi-objective evaluation method for a compressed air energy storage system is provided, the method comprising:

[0008] Establish a multi-objective evaluation index system, which includes: total index, primary index, and secondary index; the primary index includes: economic index A1, environmental index A2, technical index A3, and reliability index A4; the secondary index under economic index A1 includes: investment cost B1, rate of return B2, and service life B3; the secondary index under environmental index A2 includes: carbon emission B4; the secondary index under technical index A3 includes: efficiency B5, capacity B6, and power B7; the secondary index under reliability index A4 includes: technology maturity B8;

[0009] Standardize the indicators in the multi-objective evaluation indicator system and establish an evaluation matrix;

[0010] The weights of each indicator in the multi-objective evaluation index system are determined. The process of determining the weights includes: hierarchical analysis method and entropy weight method, specifically: the weights of the first-level indicators are determined by the hierarchical analysis method, and the subjective weights of the subordinate second-level indicators are the same as the upper-level indicators; the objective weights of the second-level indicators are evaluated by the entropy weight method; the final weights of each second-level indicator are determined by combined weighting according to the objective results evaluated by the entropy weight method and the subjective results evaluated by the hierarchical analysis method;

[0011] According to the multi-objective evaluation index system and weight results of compressed air energy storage, a comprehensive evaluation of the compressed air energy storage technical route is carried out to obtain the evaluation results.

[0012] Furthermore, the indicators in the multi-objective evaluation index system are standardized, including:

[0013] Use the mean method to make the indicator dimensionless, the formula is as follows:

[0014]

[0015] where x ij is the original data of the jth indicator of the ith evaluation object, m is the number of evaluation objects, x′ ij It is the dimensionless data of the jth indicator of the i-th evaluation object.

[0016] Furthermore, the indicators in the multi-objective evaluation indicator system are standardized, including:

[0017] The indicators are operated in the same direction. The same direction data of the positive indicator is the original data. For the reverse indicator, there are:

[0018] p ij = -x′ ij

[0019] Among them, p ij is the standardized data of the jth indicator of the i-th evaluation object, x′ ij It is the dimensionless data of the jth indicator of the i-th evaluation object.

[0020] Furthermore, an evaluation matrix was established, including:

[0021] Establish a standardized evaluation matrix P, the formula is as follows:

[0022]

[0023] Among them, n represents the total number of secondary indicators, m is the number of evaluation objects, and p ijis the standardized data of the j-th index of the i-th evaluation object. The indexes involved in the standardized evaluation matrix should be the bottom-level indexes of the entire index system, that is, the secondary indexes.

[0024] Furthermore, the weights of the first-level indexes are determined by the analytic hierarchy process, including:

[0025] Compare the first-level indexes pairwise to determine their importance, and construct a judgment matrix A; conduct a consistency test on the judgment matrix; after the consistency test passes, use the eigenvalue method to determine the weights.

[0026] Furthermore, the judgment matrix A is expressed as where a ij is the scale value of the importance degree between index i and index j, and there are r first-level indexes in total;

[0027] The steps of the consistency check are as follows:

[0028] Calculate the maximum eigenvalue λ max of matrix A, and calculate the consistency index CI of matrix A from λ max :

[0029]

[0030] The random consistency ratio CR of the judgment matrix A = CI / RI. If CR < CR threshold, the judgment matrix A passes the consistency test; otherwise, it fails. Re-compare the importance between the first-level indexes and construct matrix A, and re-conduct the consistency test on the modified judgment matrix;

[0031] where RI is obtained by looking up the table according to the relationship table between the average random consistency index RI and r.

[0032] Furthermore, the steps of the eigenvalue method are as follows:

[0033] Calculate the eigenvector V′ corresponding to the maximum eigenvalue of the judgment matrix A, and normalize the eigenvector to obtain the first-level weight vector V1:

[0034]

[0035] where r indicates that the eigenvector is an r-dimensional vector, and the dimension of the first-level weight vector established according to the first-level indexes is the same as the number of first-level indexes; V′ i represents the i-th component of the eigenvector V′.

[0036] Furthermore, the weights of the secondary indexes under the first-level indexes are the same as those of the upper-level indexes. After normalizing all the secondary indexes, the subjective weights of the secondary indexes determined by the analytic hierarchy process are obtained. The formula is as follows:

[0037] V2 = F(V1)

[0038]

[0039] Where V1 represents the first-level weight vector, V2 represents the second-level subjective weight vector, F represents the mapping from the first-level indicator to the corresponding second-level indicator, n is the number of second-level indicators, subscript j represents the jth component of the weight vector, V represents the subjective weight of the second-level indicator after homogenization, V j represents the jth component of the subjective weight of the secondary indicator after homogenization, V 2j Represents the j-th component of the secondary subjective weight vector V2.

[0040] Furthermore, the objective weights of the secondary indicators are assessed using the entropy weight method, including:

[0041] Calculate the index contribution y through the standardized matrix ij and information entropy value E j ;

[0042]

[0043]

[0044] The objective weight W of the indicator is calculated by the information entropy value of the jth indicator. j :

[0045]

[0046] p ij Represents the standardized matrix elements, m means that the matrix has m rows; n means that there are n secondary indices, subscript j represents the jth index; subscript k represents the kth index, which is used to represent the traversal summation calculation when the jth index is fixed.

[0047] Furthermore, the final weights of each secondary indicator are determined by combining the objective results of the entropy weight method and the subjective results of the analytic hierarchy process, including:

[0048]

[0049] V j and W j Respectively represent the subjective weight and objective weight of the j-th indicator, q j Represents the final combined weight of the secondary indicators of the j-th indicator.

[0050] Furthermore, a comprehensive evaluation of the compressed air energy storage technology route is conducted based on the compressed air energy storage multi-objective evaluation index system and weight results to obtain the evaluation results, including:

[0051] Multiply the standardized evaluation matrix P by the combined weight vector q to obtain the evaluation result R, as shown in the following formula:

[0052] R=P·q

[0053] The combined weight vector q is formed by the final weights of each secondary indicator.

[0054] In a second aspect, a multi-objective evaluation device for a compressed air energy storage system includes: an index system establishment unit, an index standardization unit, a weight determination unit, and an evaluation unit;

[0055] The index system establishment unit is used to establish a multi-objective evaluation index system. The index system includes: total index, primary index, and secondary index. The primary index includes: economic index A1, environmental index A2, technical index A3, and reliability index A4. The secondary index under economic index A1 includes: investment cost B1, rate of return B2, and service life B3. The secondary index under environmental index A2 includes: carbon emission B4. The secondary index under technical index A3 includes: efficiency B5, capacity B6, and power B7. The secondary index under reliability index A4 includes: technology maturity B8.

[0056] The indicator standardization unit is used to standardize the indicators in the multi-objective evaluation indicator system and establish an evaluation matrix;

[0057] The weight determination unit is used to determine the weight of each indicator in the multi-objective evaluation indicator system. The process of determining the weight includes: hierarchical analysis method and entropy weight method, specifically including: the weight of the first-level indicator is determined by the hierarchical analysis method, and the subjective weight of the subordinate second-level indicator is the same as the upper-level indicator; the objective weight of the second-level indicator is evaluated by the entropy weight method; the final weight of each second-level indicator is determined by combined weighting according to the objective results evaluated by the entropy weight method and the subjective results evaluated by the hierarchical analysis method;

[0058] The evaluation unit is used to conduct a comprehensive evaluation on the compressed air energy storage technology route according to the compressed air energy storage multi-objective evaluation index system and weight results to obtain the evaluation results.

[0059] In a third aspect, an electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus;

[0060] a memory storing a computer program;

[0061] The processor is used to implement the above-mentioned multi-objective evaluation method for a compressed air energy storage system when executing the computer program stored in the memory.

[0062] In a fourth aspect, a computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned multi-objective evaluation method for a compressed air energy storage system.

[0063] The present disclosure includes at least the following beneficial effects:

[0064] Based on the analysis of compressed air energy storage technology routes and application scenarios, this paper establishes compressed air energy storage technology evaluation indicators covering economy, environment, technology and reliability; uses the improved entropy weight method to determine the objective weight coefficient, weakens the influence of extreme indicator values ​​on the weight assessment results, and uses the hierarchical analysis method to determine the subjective weight coefficient, corrects the weight deviation caused by the entropy weight method due to the small number of evaluation objects; the evaluation results of the constructed model are concise and intuitive, which solves the problem that the current compressed air energy storage technology route selection indicators cannot be quantified.

[0065] Other features and advantages of the present disclosure will be described in the following description, and partly become apparent from the description, or be understood by implementing the present disclosure. The purpose and other advantages of the present disclosure can be realized and obtained by the structures indicated in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0067] Figure 1 This is a flow chart of the evaluation method according to the embodiment of the present disclosure;

[0068] Figure 2 This is a schematic diagram of the structure of the evaluation device according to the embodiment of the present disclosure;

[0069] Figure 3 It is a schematic diagram of the structure of an electronic device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0070] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0071] like Figure 1As shown, a multi-objective evaluation method for a compressed air energy storage system comprises:

[0072] S101, establish a multi-objective evaluation index system, the index system includes: total index, first-level index, and second-level index; the first-level index includes: economic index A1, environmental index A2, technical index A3, and reliability index A4; the economic index A1 has second-level indicators, including: investment cost B1, rate of return B2, and service life B3; the environmental index A2 has second-level indicators, including: carbon emissions B4; the technical index A3 has second-level indicators, including: efficiency B5, capacity B6, and power B7; the reliability index A4 has second-level indicators, including: technology maturity B8;

[0073] S102, standardizing the indicators in the multi-objective evaluation indicator system and establishing an evaluation matrix;

[0074] S103, determining the weight of each indicator in the multi-objective evaluation indicator system, the process of determining the weight includes: hierarchical analysis method and entropy weight method, specifically including: the weight of the first-level indicator is determined by the hierarchical analysis method, and the subjective weight of the subordinate second-level indicator is the same as the upper-level indicator; the objective weight of the second-level indicator is evaluated by the entropy weight method; the final weight of each second-level indicator is determined by combined weighting according to the objective result evaluated by the entropy weight method and the subjective result evaluated by the hierarchical analysis method;

[0075] S104, comprehensively evaluate the compressed air energy storage technology route according to the compressed air energy storage multi-objective evaluation index system and weight results to obtain an evaluation result.

[0076] The specific implementation is as follows:

[0077] First, a multi-objective evaluation index system for compressed air energy storage is established, which consists of total indicators, primary indicators, and secondary indicators. The primary indicators include economic indicators A1, environmental indicators A2, technical indicators A3, and reliability indicators A4; the secondary indicators under economic indicators A1 include investment cost B1, rate of return B2, and service life B3; the secondary indicators under environmental indicators A2 are carbon emissions B4; the secondary indicators under technical indicators include efficiency B5, capacity B6, and power B7; the secondary indicators under reliability indicators A4 are technology maturity B8.

[0078] Then, the indicators in the multi-objective comprehensive evaluation system are standardized to construct an evaluation matrix. The standardization operation includes dimensionless and isotropic.

[0079] Use the mean method to perform dimensionless operations on the indicators, namely:

[0080]

[0081] where x ij is the original data of the jth indicator of the ith evaluation object, and m is the number of evaluation objects. In the same-direction operation, the same-direction data of the positive indicator is the original data, and for the reverse indicator:

[0082] p i j = -x′ ij

[0083] The standardized evaluation matrix is ​​as follows:

[0084]

[0085] Where n represents the total number of secondary indicators.

[0086] Afterwards, the weights of the indicators in the multi-objective comprehensive evaluation system are determined. The process of determining the weights adopts the hierarchical analysis method and the entropy weight method for comprehensive evaluation. The steps are as follows:

[0087] The weight of the first-level indicators is determined by the hierarchical analysis method, and the determination process is as follows:

[0088] For a specific application scenario, the first-level indicators are compared pairwise to determine their importance and a judgment matrix is ​​constructed: In the formula, a ij is the scale value of the importance of index i and index j, and there are r first-level indicators in total.

[0089] The consistency test of the judgment matrix is ​​as follows:

[0090] Calculate the largest eigenvalue λ of matrix A max , and by λ max Calculate the consistency index of the judgment matrix A:

[0091]

[0092] The relationship between the average random consistency index RI and n is shown in Table 1:

[0093] Table 1

[0094] r 1 2 3 4 5 6 7 8 9 10 RI 0 0 0.58 0.9 1.12 1.24 1.32 1.41 1.45 1.49

[0095] The random consistency ratio CR of the judgment matrix A is CI / RI. If CR < 0.1, it can be considered that the matrix A passes the consistency test; otherwise, it fails and the matrix A needs to be modified and the consistency test of the modified judgment matrix is ​​re-performed.

[0096] When the consistency check passes, the eigenvalue method can be used to determine the weight. The steps of the eigenvalue method are as follows:

[0097] Calculate the eigenvector V′ corresponding to the maximum eigenvalue of matrix A, normalize the eigenvector, and obtain the weight vector:

[0098]

[0099] The weights of the secondary indicators under the primary indicator are the same as those of the upper indicator. After homogenizing all secondary indicators, the subjective weights of the secondary indicators determined by the hierarchical analysis method are obtained, namely:

[0100] V2=F(V1)

[0101]

[0102] F represents the mapping from the first-level indicators to their corresponding second-level indicators.

[0103] The objective weight of the secondary indicators is assessed by the entropy weight method. The determination process of the entropy weight method specifically includes the following two steps:

[0104] First, the index contribution y is calculated from the standardized matrix ij and information entropy value E j .

[0105]

[0106]

[0107] Then, the objective weight W of the indicator can be calculated from the information entropy value of the jth indicator. j :

[0108]

[0109] According to the results of the entropy weight method and the hierarchical analysis method, the weights of the secondary indicator parameters are determined by using the combined weighting. The calculation process of the combined weighting is as follows:

[0110]

[0111] Finally, the compressed air energy storage technology route is comprehensively evaluated according to the compressed air energy storage comprehensive evaluation index system and weight results, and the standardized evaluation matrix is ​​multiplied by the combined weight vector to obtain the evaluation result:

[0112] R=P·q

[0113] Based on the evaluation results, the most suitable compressed air energy storage technology route for a specific application scenario can be selected.

[0114] This embodiment establishes a compressed air energy storage multi-objective evaluation model for the four indicators of economy, environment, technology and reliability. It can analyze the compressed air energy storage technology route and application scenarios according to the compressed air energy storage technology route and application scenario, and establish a compressed air energy storage technology evaluation index covering economy, environment, technology and reliability; and adopts a combined weighting method combining the analytic hierarchy process and the entropy weight method to avoid the extreme objective evaluation results caused by too few evaluation objects and the lack of data objectivity caused by the focus preference. The improved entropy weight method is used to determine the objective weight coefficient, which weakens the influence of extreme indicator values ​​on the weight assessment results; the evaluation results of the constructed model are concise and intuitive, which solves the problem that the current compressed air energy storage technology route selection indicators cannot be quantified.

[0115] like Figure 2 As shown, a multi-objective evaluation device for a compressed air energy storage system includes: an index system establishment unit 201, an index standardization unit 202, a weight determination unit 203 and an evaluation unit 204;

[0116] The index system establishment unit 201 is used to establish a multi-objective evaluation index system, and the index system includes: a total index, a primary index, and a secondary index; the primary index includes: an economic index A1, an environmental index A2, a technical index A3, and a reliability index A4; the secondary indexes under the economic index A1 include: investment cost B1, rate of return B2, and service life B3; the secondary indexes under the environmental index A2 include: carbon emissions B4; the secondary indexes under the technical index A3 include: efficiency B5, capacity B6, and power B7; the secondary indexes under the reliability index A4 include: technology maturity B8;

[0117] The indicator standardization unit 202 is used to standardize the indicators in the multi-objective evaluation indicator system and establish an evaluation matrix;

[0118] The weight determination unit 203 is used to determine the weight of each indicator in the multi-objective evaluation indicator system. The process of determining the weight includes: the hierarchical analysis method and the entropy weight method, specifically including: the weight of the first-level indicator is determined by the hierarchical analysis method, and the subjective weight of the subordinate second-level indicator is the same as the upper-level indicator; the objective weight of the second-level indicator is evaluated by the entropy weight method; the final weight of each second-level indicator is determined by combined weighting according to the objective result evaluated by the entropy weight method and the subjective result evaluated by the hierarchical analysis method;

[0119] The evaluation unit 204 is used to comprehensively evaluate the compressed air energy storage technical route according to the compressed air energy storage multi-objective evaluation index system and weight results to obtain an evaluation result.

[0120] like Figure 3As shown, the present disclosure provides an electronic device, including a processor 301, a communication interface 302, a memory 303 and a communication bus 304, wherein the processor 301, the communication interface 302 and the memory 303 communicate with each other through the communication bus 304;

[0121] Memory 303, storing computer programs;

[0122] The processor 301 is configured to implement the above method when executing the computer program stored in the memory 303 .

[0123] The present disclosure provides a computer-readable storage medium storing a computer program, wherein the computer program implements the above method when executed by a processor.

[0124] The computer-readable storage medium may be included in the device / apparatus described in the above embodiment; or it may exist independently without being assembled into the device / apparatus. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0125] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: 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), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0126] Although the present disclosure has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure.

Claims

1. A multi-objective evaluation method for a compressed air energy storage system, characterized in that: The method includes: Establishing a multi-objective evaluation index system, which consists of a general index, first-level indexes, and second-level indexes; the first-level indexes include: economic index A1, environmental index A2, technical index A3, and reliability index A4; the second-level indexes subordinate to the economic index A1 include: investment cost B1, rate of return B2, and service life B3; the second-level indexes subordinate to the environmental index A2 include: carbon emission B4; the second-level indexes subordinate to the technical index A3 include: efficiency B5, capacity B6, and power B7; the second-level indexes subordinate to the reliability index A4 include: technology maturity B8; Standardizing the indexes in the multi-objective evaluation index system to establish an evaluation matrix; Determining the weights of the indexes in the multi-objective evaluation index system. The process of determining the weights includes: the analytic hierarchy process and the entropy weight method. Specifically, the weights of the first-level indexes are determined by the analytic hierarchy process, and the subjective weights of their subordinate second-level indexes are the same as those of the superior indexes; the objective weights of the second-level indexes are evaluated by the entropy weight method; the final weights of each second-level index are determined by combining the objective results evaluated by the entropy weight method and the subjective results evaluated by the analytic hierarchy process; Comprehensively evaluating the compressed air energy storage technology route according to the multi-objective evaluation index system of compressed air energy storage and the weight results to obtain the evaluation results.

2. The multi-objective evaluation method for a compressed air energy storage system according to claim 1, characterized in that Standardizing the indexes in the multi-objective evaluation index system includes: Using the mean method to perform a dimensionless operation on the indexes, and the formula is as follows: where x ij is the original data of the jth indicator of the ith evaluation object, m is the number of evaluation objects, x′ ij It is the dimensionless data of the jth indicator of the i-th evaluation object.

3. The multi-objective evaluation method for a compressed air energy storage system according to claim 1, characterized in that Standardizing the indexes in the multi-objective evaluation index system also includes: Performing a homogeneization operation on the indexes. The homogeneized data of the positive indexes are the original data, and for the reverse indexes, there are: p i j =-x′ ij Among them, p ij is the standardized data of the jth indicator of the i-th evaluation object, x′ ij It is the dimensionless data of the jth indicator of the i-th evaluation object.

4. The multi-objective evaluation method for a compressed air energy storage system according to claim 1, characterized in that Establishing an evaluation matrix includes: Establishing a standardized evaluation matrix P, and the formula is as follows: Among them, n represents the total number of secondary indicators, m is the number of evaluation objects, and p ij is the standardized data of the jth indicator of the i-th evaluation object.

5. The multi-objective evaluation method for a compressed air energy storage system according to claim 1, characterized in that The weights of the first-level indexes are determined by the analytic hierarchy process, including: Comparing the first-level indexes pairwise to determine their importance, and constructing a judgment matrix A; performing a consistency test on the judgment matrix; after the consistency test passes, using the eigenvalue method to determine the weights.

6. The multi-objective evaluation method for a compressed air energy storage system according to claim 5, characterized in that The judgment matrix A is expressed as In the formula, a ij is the scale value of the importance of index i and index j, and there are r first-level indicators in total; The steps of the consistency check are as follows: Calculating the maximum eigenvalue λ of matrix A, and calculating the consistency index CI of matrix A from λ: maxmax Judging that the random consistency ratio CR of matrix A = CI / RI. If CR < CR threshold, matrix A passes the consistency test; otherwise, it fails. Re-compare the importance between the first-level indexes and construct matrix A, and perform the consistency test on the modified judgment matrix again; Among them, RI is obtained by looking up the table according to the relationship table between the average random consistency index RI and r.

7. A multi-objective evaluation method for a compressed air energy storage system according to claim 5, characterized in that: The steps of the eigenvalue method are as follows: Calculate the eigenvector V′ corresponding to the maximum eigenvalue of the judgment matrix A, normalize the eigenvector, and obtain the first-level weight vector V1: Among them, r means that the feature vector is an r-dimensional vector, and the dimension of the first-level weight vector established according to the first-level index is the same as the number of first-level indexes; V i ′ represents the i-th component of the eigenvector V′.

8. A multi-objective evaluation method for a compressed air energy storage system according to claim 7, characterized in that: The weights of the secondary indicators under the primary indicator are the same as those of the upper indicator. After homogenizing all secondary indicators, the subjective weights of the secondary indicators determined by the hierarchical analysis method are obtained. The formula is as follows: V2=F(V1) Where V1 represents the first-level weight vector, V2 represents the second-level subjective weight vector, F represents the mapping from the first-level indicator to the corresponding second-level indicator, n is the number of second-level indicators, subscript j represents the jth component of the weight vector, V represents the subjective weight of the second-level indicator after homogenization, V j represents the jth component of the subjective weight of the secondary indicator after homogenization, V 2j Represents the j-th component of the secondary subjective weight vector V2.

9. A multi-objective evaluation method for a compressed air energy storage system according to claim 1, characterized in that: The objective weight of the secondary indicators is assessed by the entropy weight method, including: Calculate the index contribution y through the standardized matrix ij and information entropy value E j ; The objective weight W of the indicator is calculated by the information entropy value of the jth indicator. j : p ij Represents the standardized matrix elements, m means that the matrix has m rows; n means that there are n secondary indices, subscript j represents the jth index; subscript k represents the kth index, which is used to represent the traversal summation calculation when the jth index is fixed.

10. A multi-objective evaluation method for a compressed air energy storage system according to claim 1, characterized in that: The final weight of each secondary indicator is determined by combining the objective results of the entropy weight method and the subjective results of the analytic hierarchy process, including: V j and W j Represent the subjective weight and objective weight of the jth indicator, q j Represents the final combined weight of the secondary indicators of the j-th indicator.

11. A multi-objective evaluation method for a compressed air energy storage system according to claim 1, characterized in that: Based on the multi-objective evaluation index system and weight results of compressed air energy storage, a comprehensive evaluation of the compressed air energy storage technology route was conducted to obtain the evaluation results, including: Multiply the standardized evaluation matrix P by the combined weight vector q to obtain the evaluation result R, as shown in the following formula: R=P·q The combined weight vector q is formed by the final weights of each secondary indicator.

12. A multi-objective evaluation device for a compressed air energy storage system, characterized in that: include: Indicator system establishment unit, indicator standardization unit, weight determination unit and evaluation unit; The index system establishment unit is used to establish a multi-objective evaluation index system. The index system includes: total index, primary index, and secondary index. The primary index includes: economic index A1, environmental index A2, technical index A3, and reliability index A4. The secondary index under economic index A1 includes: investment cost B1, rate of return B2, and service life B3. The secondary index under environmental index A2 includes: carbon emission B4. The secondary index under technical index A3 includes: efficiency B5, capacity B6, and power B7. The secondary index under reliability index A4 includes: technology maturity B8. The indicator standardization unit is used to standardize the indicators in the multi-objective evaluation indicator system and establish an evaluation matrix; The weight determination unit is used to determine the weight of each indicator in the multi-objective evaluation indicator system. The process of determining the weight includes: hierarchical analysis method and entropy weight method, specifically including: the weight of the first-level indicator is determined by the hierarchical analysis method, and the subjective weight of the subordinate second-level indicator is the same as the upper-level indicator; the objective weight of the second-level indicator is evaluated by the entropy weight method; the final weight of each second-level indicator is determined by combined weighting according to the objective results evaluated by the entropy weight method and the subjective results evaluated by the hierarchical analysis method; The evaluation unit is used to conduct a comprehensive evaluation on the compressed air energy storage technology route according to the compressed air energy storage multi-objective evaluation index system and weight results to obtain the evaluation results.

13. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; a memory storing a computer program; A processor, for implementing a multi-objective evaluation method for a compressed air energy storage system according to any one of claims 1 to 11 when executing a computer program stored in a memory.

14. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, a multi-objective evaluation method for a compressed air energy storage system according to any one of claims 1 to 11 is implemented.

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