Shared energy storage benefit evaluation method based on improved TOPSIS-ANP-CRITIC method

Abstract

The invention discloses a shared energy storage benefit evaluation method based on an improved TOPSIS-ANP-CRITIC method, and the method comprises the steps: obtaining a shared energy storage data set, and building a shared energy storage evaluation index system; an ANP method network structure diagram is established based on the shared energy storage evaluation index system, and experts are invited to score according to the structure diagram to obtain the subjective weight of each index; establishing a judgment matrix of a CRITIC method based on each index data of the shared energy storage evaluation index system, and obtaining an objective weight of each index; combining the objective weight with the subjective weight by adopting a combined weighting method to obtain a comprehensive weight of each index; and determining an expected target of the energy storage project as a reference scheme, constructing a standard matrix, calculating the closeness between each scheme and the reference scheme through the standard matrix and the comprehensive weight, and carrying out sorting. According to the method, an evaluation system taking economy, environment, market and social benefits as basic indexes is established, the TOPSIS method is improved by introducing an expected target scheme, the defects of a traditional TOPSIS method in the aspect of result processing are overcome, and longitudinal and transverse evaluation among all the schemes is achieved.

Description

Technical Field

[0001] The invention belongs to the field of energy storage benefit evaluation, and specifically relates to a shared energy storage benefit evaluation method based on an improved TOPSIS-ANP-CRITIC method. Background Art

[0002] As energy storage technology continues to upgrade, building matching energy storage power stations for new energy power stations has brought huge economic benefits. However, with the increasing number of new energy power stations, it is very expensive to equip each new energy power station with independent energy storage, and it may also cause a waste of energy storage capacity. Therefore, shared energy storage can provide a new solution to the above problem through a new model that combines "sharing economy" and energy storage power stations.

[0003] Although shared energy storage can solve the problem of resource waste, for decision makers, if they want to configure shared energy storage, they need to comprehensively measure the economic feasibility of the shared energy storage system from the aspects of economic benefits, environmental benefits, market benefits and social benefits. By establishing a shared energy storage evaluation index system, it can provide guidance for decision makers who are not related professionals.

[0004] The establishment of an evaluation system is of great significance for the construction of energy storage power stations. At present, there are many shared energy storage evaluation systems at home and abroad, but most of them have studied the economic benefits and market benefits of energy storage, and there are few studies on environmental benefits and social benefits. Summary of the invention

[0005] In view of the above-mentioned shortcomings of the prior art, the present invention provides a method for evaluating the benefits of shared energy storage.

[0006] The technical solution of the present invention is as follows:

[0007] A shared energy storage benefit evaluation method based on an improved TOPSIS-ANP-CRITIC method, the method comprising:

[0008] Obtain shared energy storage data sets and establish a shared energy storage evaluation index system;

[0009] An ANP method network structure diagram is established based on the shared energy storage evaluation index system, and experts are invited to score the structure diagram to obtain the subjective weight of each index;

[0010] A judgment matrix of the CRITIC method is established based on the data of each indicator of the shared energy storage evaluation index system to obtain the objective weight of each indicator;

[0011] The combined weighting method is used to combine the objective weight calculated by the CRITIC method with the subjective weight calculated by the ANP method to obtain the comprehensive weight of each indicator;

[0012] The expected goal of the energy storage project is determined as a benchmark solution, a standard matrix is ​​constructed, and the closeness of each solution to the benchmark solution is calculated and ranked using the standard matrix and the comprehensive weight.

[0013] Furthermore, the ANP method network structure diagram is established based on the shared energy storage evaluation index system, and experts are invited to score according to the structure diagram to obtain the subjective weight of each index as follows:

[0014] Construct the ANP network structure and determine the hierarchy and interrelationships among the factors;

[0015] An unweighted supermatrix is ​​established based on the expert evaluation;

[0016] Experts score the relationships between the criterion layers to form a weighted supermatrix;

[0017] The limit supermatrix is ​​obtained through the weighted supermatrix, and the subjective weight of each indicator is obtained by solving it.

[0018] Furthermore, the shared energy storage evaluation index system includes a three-layer structure, specifically:

[0019] The first layer is the target layer, which maximizes the benefits of shared energy storage power stations;

[0020] The second layer is the criteria layer, including economic benefits, environmental benefits, market benefits and social benefits;

[0021] The third layer is the indicators under each criterion layer.

[0022] Furthermore, the third layer is specifically:

[0023] Economic benefits include: investment cost, operation and maintenance cost, labor cost, residual value input and capacity income;

[0024] Environmental benefits include: reduced carbon dioxide emissions;

[0025] Market benefits include: supply market activity, demand market activity and energy storage utilization;

[0026] Social benefits include: reducing peak-to-valley differences and increasing the consumption of new energy power generation.

[0027] Furthermore, the judgment matrix of the CRITIC method is established based on the index data of each index of the shared energy storage evaluation index system, and the objective weight of each index is obtained as follows:

[0028] Establish the judgment matrix of CRITIC method;

[0029] Performing forward normalization processing on the judgment matrix to obtain a normalized matrix;

[0030] Calculating contrast strength and conflict based on the normalized matrix;

[0031] Calculating information carrying capacity based on the comparison strength and conflict;

[0032] Finally, the information carrying capacity is normalized to obtain the objective weight of each indicator.

[0033] Furthermore, the expected goals of the energy storage project are determined as a benchmark solution, and the standard matrix is ​​constructed as follows:

[0034] Invite experts to determine the expected goals of energy storage projects based on the development of shared energy storage projects and use them as benchmark plans;

[0035] Constructing a scheme matrix according to the numerical values ​​of each indicator of the benchmark scheme and other schemes;

[0036] The solution matrix is ​​forward normalized to obtain the standard matrix of the TOPSIS method.

[0037] Furthermore, the closeness of each solution to the benchmark solution is calculated and ranked by using the standard matrix and the comprehensive weights as follows:

[0038] Multiply the standard matrix and the comprehensive weight to obtain a weighted standard matrix;

[0039] The degree of closeness between each solution and the ideal solution is calculated based on the weighted standard matrix, and finally the degree of closeness between each solution and the benchmark solution is calculated and ranked.

[0040] Furthermore, the method for calculating the degree of closeness between each solution and the ideal solution is the KL divergence method.

[0041] Compared with the prior art, the present invention has the following advantages:

[0042] The present invention analyzes the operation of shared energy storage and establishes an evaluation system based on economic, environmental, market and social benefits. The subjective and objective weights of each indicator under economic, environmental, market and social benefits are calculated using the ANP method and the CRITIC method, and the combined weights of each indicator are obtained by combining the two through the combined weighting method, ensuring that more important factors play a greater role in the decision-making process and further improving data utilization.

[0043] By introducing the expected target solution to improve the TOPSIS method, the single ranking selection is transformed into a method that can intuitively see the development trend of the project, overcoming the shortcomings of the traditional TOPSIS method in result processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings generally illustrate various embodiments by way of example and not limitation, and together with the description and claims, serve to illustrate the embodiments of the invention. Where appropriate, the same reference numerals are used throughout the drawings to refer to the same or similar parts. Such embodiments are illustrative and are not intended to be exhaustive or exclusive embodiments of the present apparatus or method.

[0045] Figure 1 A schematic diagram of the method flow of the present invention is shown;

[0046] Figure 2 A schematic diagram of the ANP network structure of the present invention is shown;

[0047] Figure 3 A schematic diagram of a shared energy storage evaluation system of the present invention is shown. DETAILED DESCRIPTION

[0048] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0049] The embodiment of the present invention provides a shared energy storage benefit evaluation method based on an improved TOPSIS-ANP-CRITIC method, which specifically includes:

[0050] The specific steps of the shared energy storage benefit evaluation method based on the improved TOPSIS-ANP-CRITIC method are as follows:

[0051] 1) The shared energy storage evaluation index system is divided into a three-layer structure. The first layer is the target layer (i.e. the shared energy storage power station has the greatest benefit), the second layer is the criterion layer (i.e. economic benefits, environmental benefits, market benefits and social benefits), and the third layer is the indicators under each criterion layer (i.e. investment costs and operation and maintenance costs, etc.). In the second layer, economic and environmental protection, market and social benefits influence each other, and market and social benefits are interrelated. The market environment has a greater impact on environmental benefits; in the third layer, the indicators interact with each other. According to the influence relationship between the indicators, the ANP method network structure diagram is established, as shown in the figure below: Figure 2 As shown;

[0052] 2) Invite 3-4 experts to score each indicator of the third layer according to the 1-9 gradient table to form an unweighted super matrix. First, the criterion layer elements (A, B, C and D) are established as criterion layer elements, and each indicator (A 1 —D 2 ) as the basic object for comparison. Figure 2 The mutual influence relationship of each indicator network structure is compared, and then the results of each level are normalized. The above process is repeated until all indicators are compared to obtain the unweighted super matrix S.

[0053]

[0054] In the formula, m is the evaluation object, n is the evaluation index:

[0055] 3) Experts score the influence of each criterion layer according to the gradient table to form a weighted matrix. Similar to the establishment of an unweighted super matrix, each criterion is used as a basic object for comparison. Figure 2 The weighting matrix W can be obtained by comparing the relationships between the quasi-side layers shown one by one.

[0056]

[0057] 4) According to Figure 2 The mutual influence relationship between each level is established, and the weighted super matrix W is established J .

[0058] W J =W×S

[0059] 5) Perform limit operations on the obtained weighted supermatrix When the values ​​of each row are made to be the same, the limit supermatrix can be obtained. All are corresponding ANP method weights.

[0060] 6) Establish the judgment matrix X of the CRITIC method m×n .

[0061]

[0062] 7) Forward the data in the matrix.

[0063] a. Very small:

[0064]

[0065] In the formula, max(X j )——the maximum value of the j-th index.

[0066] b. Intermediate type:

[0067]

[0068] In the formula, X j,b ——The best value of the jth indicator, which depends on the specific indicator.

[0069] c. Interval type:

[0070]

[0071] H = max{u-min(x ij ),max(xij )-p}

[0072] In the formula, u is the lower limit of the interval; p is the upper limit of the interval.

[0073] 8) Standardize the matrix X data to obtain the standardized matrix B.

[0074]

[0075] 9) Calculate the comparison strength. The comparison strength refers to the difference between the values ​​of the same indicator among the various evaluation schemes, expressed in the form of standard deviation. The larger the standard deviation, the greater the fluctuation, that is, the greater the difference between the values ​​of the schemes, the higher the weight. The relevant calculation formula is as follows:

[0076]

[0077] In the formula, σ j ——the comparison strength of the jth index; B ij ——The value of the jth indicator corresponding to the i-th evaluation object; j ——The average value of the j-th indicator.

[0078] 10) Calculate the conflict. The conflict between indicators is expressed by the correlation coefficient. If there is a strong positive correlation between two indicators, the smaller the conflict, the lower the weight. The relevant calculation formula is as follows:

[0079]

[0080] In the formula, f j ——Conflict coefficient of the jth indicator; r ab ——Correlation coefficient between the a-th index and the b-th index; cov(a,b)——Covariance between the a-th index and the b-th index; σ a ——Standard deviation of the index a; σ b ——The standard deviation of the b-th indicator.

[0081] 11) Calculate the information carrying capacity. Let the information carrying capacity be C j , the formula is:

[0082] C j =σ j f j

[0083] 12) Calculate the CRITIC weight. Here, the information carrying capacity C j Normalized, it is the calculated weight w. It can be seen that the greater the information carrying capacity, the greater the weight.

[0084]

[0085] 13) The two weights calculated by the ANP method and the CRITIC method are combined by the combined weighting method to obtain the combined weight.

[0086]

[0087] In the formula, w j ——Combined weight of the jth indicator; ——The weight of the jth indicator in the ANP weighting method; ——The weight of the jth indicator in the CRITIC weighting method.

[0088] 14) Invite experts to determine the expected goals of energy storage projects based on the development of shared energy storage projects in recent years, and use them as the benchmark plan. Construct the plan matrix S based on the indicator values ​​of the benchmark plan and other plans. C

[0089] 15) Considering that the decision of shared energy storage project is based on economic considerations, all index values ​​are normalized for comparison. C The normalization matrix C of the TOPSIS method is obtained by the forward normalization method of the CRITIC method, and the combination weight w j Multiplying with the normalization matrix C yields the weighted normalization matrix Z.

[0090] Z ij =w j C ij

[0091] 16) Calculate the distance to the maximum value and the distance to the minimum value. In order to solve the problem that the projection points on the perpendicular median line of the TOPSIS method have the same closeness value, which makes it impossible to calculate, KL divergence is introduced, and KL distance is used instead of Euclidean distance to calculate the closeness of each solution to the ideal solution (i.e., ideal solution). The smaller the KL divergence between the selected solution and the ideal solution, the smaller the gap between the two, and the greater the closeness. Because KL divergence is not the actual distance, mapping the projection points on the perpendicular median line in space to the divergence space has a good effect on Euclidean distance sorting anomalies. The KL distance formula is as follows:

[0092]

[0093] In the formula, ——The minimum value of the j-th index of the matrix Z; Z + ——The maximum value of the jth index of the matrix Z. In the specific calculation, due to the limitations of the formula, infinitesimal should be replaced by a relatively small number to avoid program errors.

[0094] 17) Use TOPSIS method to calculate the closeness S of each solution j .

[0095]

[0096] 18) By determining the closeness relationship between the evaluation object and the expected goal, the development prospects and feasibility of the project can be determined. Therefore, the closeness of all plans is proportional to the benchmark value based on the closeness of the expected goal.

[0097]

[0098] In the formula, S eg ——closeness to the expected target; S j,nor ——The closeness of the jth index after scaling.

[0099] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A shared energy storage benefit evaluation method based on the improved TOPSIS-ANP-CRITIC method, characterized in that: The method comprises: Obtain shared energy storage data sets and establish a shared energy storage evaluation index system; An ANP method network structure diagram is established based on the shared energy storage evaluation index system, and experts are invited to score the structure diagram to obtain the subjective weight of each index; A judgment matrix of the CRITIC method is established based on the data of each indicator in the shared energy storage evaluation indicator system to obtain the objective weight of each indicator; The combined weighting method is used to combine the objective weight calculated by the CRITIC method with the subjective weight calculated by the ANP method to obtain the comprehensive weight of each indicator; The expected goal of the energy storage project is determined as a benchmark solution, a standard matrix is ​​constructed, and the closeness of each solution to the benchmark solution is calculated and ranked using the standard matrix and the comprehensive weight.

2. The shared energy storage benefit evaluation method based on the improved TOPSIS-ANP-CRITIC method according to claim 1 is characterized in that: The ANP method network structure diagram is established based on the shared energy storage evaluation index system, and experts are invited to score according to the structure diagram to obtain the subjective weight of each index as follows: Construct the ANP network structure and determine the hierarchy and interrelationships among the factors; An unweighted supermatrix is ​​established based on the expert evaluation; Experts score the relationships between the criterion layers to form a weighted supermatrix; The limit supermatrix is ​​obtained through the weighted supermatrix, and the subjective weight of each indicator is obtained by solving it.

3. The shared energy storage benefit evaluation method based on the improved TOPSIS-ANP-CRITIC method according to claim 2 is characterized in that: The shared energy storage evaluation index system includes a three-layer structure, specifically: The first layer is the target layer, which maximizes the benefits of shared energy storage power stations; The second layer is the criteria layer, including economic benefits, environmental benefits, market benefits and social benefits; The third layer is the indicators under each criterion layer.

4. The shared energy storage benefit evaluation method based on the improved TOPSIS-ANP-CRITIC method according to claim 3 is characterized in that: The third layer is specifically: Economic benefits include: investment cost, operation and maintenance cost, labor cost, residual value input and capacity income; Environmental benefits include: reduced carbon dioxide emissions; Market benefits include: supply market activity, demand market activity and energy storage utilization; Social benefits include: reducing peak-to-valley differences and increasing the consumption of new energy power generation.

5. The shared energy storage benefit evaluation method based on the improved TOPSIS-ANP-CRITIC method according to claim 1 is characterized in that: The judgment matrix of the CRITIC method is established based on the index data of each index in the shared energy storage evaluation index system, and the objective weight of each index is obtained as follows: Establish the judgment matrix of CRITIC method; Performing forward normalization processing on the judgment matrix to obtain a normalized matrix; Calculating contrast strength and conflict based on the normalized matrix; Calculating information carrying capacity based on the comparison strength and conflict; Finally, the information carrying capacity is normalized to obtain the objective weight of each indicator.

6. The shared energy storage benefit evaluation method based on the improved TOPSIS-ANP-CRITIC method according to claim 1 is characterized in that: The expected goals of the energy storage project are determined as the benchmark solution, and the standard matrix is ​​constructed as follows: Invite experts to determine the expected goals of energy storage projects based on the development of shared energy storage projects and use them as benchmark plans; Constructing a scheme matrix according to the numerical values ​​of each indicator of the benchmark scheme and other schemes; The solution matrix is ​​forward normalized to obtain the standard matrix of the TOPSIS method.

7. The shared energy storage benefit evaluation method based on the improved TOPSIS-ANP-CRITIC method according to claim 1 is characterized in that: The closeness of each solution to the benchmark solution is calculated and ranked by using the standard matrix and the comprehensive weights as follows: Multiply the standard matrix and the comprehensive weight to obtain a weighted standard matrix; The degree of closeness between each solution and the ideal solution is calculated based on the weighted standard matrix, and finally the degree of closeness between each solution and the benchmark solution is calculated and ranked.

8. The shared energy storage benefit evaluation method based on the improved TOPSIS-ANP-CRITIC method according to claim 1 is characterized in that: The method for calculating the degree of closeness between each solution and the ideal solution is the KL divergence method.

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