Energy storage safety evaluation method and system based on game theory and fuzzy comprehensive evaluation

Abstract

The invention discloses an energy storage safety assessment method and system based on the game theory and fuzzy comprehensive evaluation, and belongs to the technical field of battery safety. Constructing a judgment matrix for the safety evaluation index of the energy storage power station by using a three-scale method of an optimal transfer matrix, and calculating a subjective weight; calculating objective weights of the safety evaluation indexes of the energy storage power station by utilizing a contrast intensity and conflict comprehensive index evaluation CRITIC method; calculating the comprehensive weight of the safety evaluation index of the energy storage power station based on the subjective weight and the objective weight by adopting a game theory method; and according to the energy storage power station safety evaluation index comprehensive weight, obtaining the energy storage power station safety evaluation grade by adopting a fuzzy comprehensive evaluation method. According to the safety assessment method, the assessment accuracy can be remarkably improved, the decision scientificity is enhanced, the safety assessment work of the energy storage power station can be rapidly and accurately completed, the assessment efficiency is improved, and the given assessment result is more visual and easy to understand.

Description

Technical Field

[0001] The present invention belongs to the technical field of battery safety, and particularly relates to a safety assessment method and system for energy storage based on game theory and fuzzy comprehensive evaluation. Background Art

[0002] New energy storage is of profound significance for building a new power system and promoting the green and low-carbon transformation of energy. In recent years, new energy storage technologies have made remarkable progress, with the installed capacity continuously expanding, showing a strong development momentum. However, behind its rapid development, safety issues have gradually emerged and become the key factor restricting the further improvement of industrial quality.

[0003] First, the phenomenon of "high growth and low utilization" has become increasingly prominent, which reflects that in the actual application of energy storage technologies, although the installed capacity has expanded rapidly, the effective utilization rate has not increased synchronously. This is mainly because there is a lack of unified standards and methods in the production, manufacturing, integration and other links of electrochemical energy storage batteries, resulting in uneven battery performance and difficulty in meeting the high requirements in actual applications. Second, the fire safety equipment and facilities of energy storage power stations have not received enough attention during the infrastructure construction stage. Since a large amount of electric energy is stored inside an energy storage power station, once a safety accident such as a fire occurs, the consequences will be unimaginable. However, at present, some energy storage power stations have insufficient investment in fire safety equipment and facilities during the construction process, posing a great potential safety hazard. Up to now, multiple energy storage power station fire accidents have occurred globally. These accidents have not only caused huge economic losses, but also posed a serious threat to people's lives and safety. Through in-depth analysis, these accidents are mostly related to battery thermal runaway, failure of core equipment, insufficient safety protection measures and lack of safety supervision. Battery thermal runaway is caused by internal short circuit, overcharging and other reasons in the battery, which leads to an increase in temperature and then causes a fire or explosion; the failure of core equipment will cause the energy storage power station to be unable to operate normally and even trigger a safety accident; the insufficiency of safety protection measures makes it impossible to effectively contain the expansion of the situation when an accident occurs; and the lack of safety supervision allows some energy storage power stations to have illegal operations during the construction and operation processes, further exacerbating the safety risks.

[0004] Therefore, accelerating the research on energy storage safety technologies, improving energy storage safety management measures and protection means, and strengthening the awareness of safety risk prevention have become the key research directions in the current energy storage industry. In order to effectively improve the safety of energy storage power stations and strengthen the safety management of energy storage power stations, it is necessary to regularly conduct safety assessments of energy storage power stations, timely discover the risks existing in the power stations and make corresponding rectifications. Summary of the Invention

[0005] The object of the present invention is to provide a method and system for energy storage safety assessment based on game theory and fuzzy comprehensive evaluation in view of the problems in the above-mentioned existing technologies, which can significantly improve the assessment accuracy, enhance the scientificity of decision-making, quickly and accurately complete the safety assessment work of energy storage power stations, improve the assessment efficiency, and the assessment results given are more intuitive and easy to understand.

[0006] To achieve the above object, the present invention has the following technical solutions:

[0007] In the first aspect, a method for energy storage safety assessment based on game theory and fuzzy comprehensive evaluation is provided, including:

[0008] Collect energy storage power station safety assessment indicators;

[0009] Construct a judgment matrix for the energy storage power station safety assessment indicators by using the three-scale method of the optimal transfer matrix and calculate the subjective weight;

[0010] Calculate the objective weight for the energy storage power station safety assessment indicators by using the CRITIC method of comprehensive evaluation of contrast intensity and conflict;

[0011] Calculate the comprehensive weight of the energy storage power station safety assessment indicators based on the subjective weight and the objective weight by using the game theory method;

[0012] Obtain the energy storage power station safety assessment grade by using the fuzzy comprehensive evaluation method according to the comprehensive weight of the energy storage power station safety assessment indicators.

[0013] As a preferred solution, the step of constructing a judgment matrix for the energy storage power station safety assessment indicators by using the three-scale method of the optimal transfer matrix and calculating the subjective weight includes:

[0014] Construct a judgment matrix A according to the importance degree of influencing factors:

[0015]

[0016] where a ij = 1 indicates that index i is more important than index j; a ij = 0 indicates that index i and index j are equally important; a ij = -1 indicates that index j is more important than index i;

[0017] Calculate the optimal transfer matrix R of the judgment matrix A according to the following formula:

[0018]

[0019] For any element in the optimal transfer matrix R, it satisfies:

[0020]

[0021] where \(n\) is the number of evaluation indicators;

[0022] Calculate the judgment matrix \(D\) of the optimal transfer matrix \(R\) according to the following formula:

[0023]

[0024] For any element in the judgment matrix \(D\), it satisfies:

[0025] d ij = exp(r ij )

[0026] Calculate the subjective weights of the safety evaluation indicators of each energy storage power station according to the following formula:

[0027]

[0028] As a preferred solution, the steps of calculating the objective weights of the safety evaluation indicators of the energy storage power station by using the CRITIC method based on the contrast intensity and conflict comprehensive index evaluation include:

[0029] Establish a decision matrix according to the following expression:

[0030]

[0031] where \(i = 1, 2, \cdots, m\), \(j = 1, 2, \cdots, n\), \(x ij is the preference of the \(i\)-th alternative with respect to the \(j\)-th criterion;

[0032] Calculate the correlation according to the following expression to measure the degree of correlation between criteria:

[0033]

[0034] Calculate the standard deviation of each indicator according to the following formula:

[0035]

[0036] Calculate the objective weights of the safety evaluation indicators of each energy storage power station according to the following formula:

[0037]

[0038] As a preferred solution, the steps of calculating the comprehensive weights of the safety evaluation indicators of the energy storage power station by using the game theory method based on the subjective weights and objective weights include:

[0039] Establish a basic weight vector set according to the following formula:

[0040] W q = {W 1 , W 2 , \cdots, W n}

[0041] where \(q = 1,2,\cdots,p\), \(W\) p is the weight set determined by the \(p\)th weighting method, \(n\) is the number of design indicators, and \(p\) is the number of methods for obtaining weights;

[0042] Let \(\alpha=\{\alpha\) 1 , \(\alpha\) 2}\) be the linear combination coefficients, and the linear combination of two weight vectors is determined by the following formula:

[0043]

[0044] where \(W\) 1 is the set of subjective weight vectors of the indicators; \(W\) 2 is the set of objective weight vectors of the indicators; \(\alpha\) 1 , \(\alpha\) 2 are the coefficients of the subjective weight and the objective weight of the indicators, respectively;

[0045] Based on the idea of the game aggregation model, with the goal of minimizing the deviation, optimize the linear combination coefficients of the two weight vectors to obtain the target weights in \(W\), and establish the following objective function:

[0046]

[0047] where \(\min\parallel\) 2 represents solving the \(L_2\) norm, represents the vector set of the summation of the comprehensive weights;

[0048] According to the properties of matrix differentiation, transform the above formula into the optimal first derivative condition, and obtain the following linear equations:

[0049]

[0050] Calculate the optimized combination coefficients \(\alpha\) 1 , \(\alpha\) 2 , and perform normalization according to the following formula:

[0051]

[0052] Calculate the comprehensive weight of the energy storage power station safety evaluation index according to the following formula:

[0053]

[0054] As a preferred solution, the steps of obtaining the safety evaluation grade of the energy storage power station by using the fuzzy comprehensive evaluation method according to the comprehensive weight of the energy storage power station safety evaluation index include:

[0055] Determine the factor set \(U\) and the evaluation set \(V\) of the evaluation object. The factor set \(U\) is the set of energy storage power station safety evaluation indicators;

[0056] Select the membership function according to the factor set U and construct the membership matrix;

[0057] Multiply the comprehensive weight of the energy storage power station safety evaluation index by the membership matrix to obtain the fuzzy comprehensive evaluation result;

[0058] Compare the fuzzy comprehensive evaluation result with the evaluation set V to obtain the safety evaluation level of the energy storage power station.

[0059] As a preferred solution, select the normal distribution type as the membership function, and the expression is as follows:

[0060]

[0061] In the formula, z i is the specific score of a certain evaluation index;

[0062] The average value Z mean is the midpoint of each grade interval, and the calculation expression is:

[0063] z mean =(z 1 +z 2 ) / 2

[0064] When z = Z mean , the membership degree is 1;

[0065] The standard deviation σ is calculated according to the following expression:

[0066]

[0067] Construct the membership matrix according to the following formula:

[0068]

[0069] In the formula, r ij is the membership degree of the j-th index of the i-th scheme relative to the evaluation set V = {v 1 , v 2 , v 3 , v 4}.

[0070] On the second aspect, a safety evaluation system for energy storage based on game theory and fuzzy comprehensive evaluation is provided, including:

[0071] An index acquisition module for acquiring safety evaluation indexes of the energy storage power station;

[0072] A subjective weight calculation module for constructing a judgment matrix for the safety evaluation indexes of the energy storage power station by using the three-scale method of the optimal transfer matrix and calculating the subjective weight;

[0073] The objective weight calculation module is used to calculate the objective weight of the energy storage power station safety evaluation index by using the comprehensive index evaluation CRITIC method of comparison intensity and conflict;

[0074] The comprehensive weight calculation module is used to calculate the comprehensive weight of the energy storage power station safety evaluation index based on the subjective weight and the objective weight by using the game theory method;

[0075] The safety evaluation level determination module is used to obtain the safety evaluation level of the energy storage power station by using the fuzzy comprehensive evaluation method according to the comprehensive weight of the energy storage power station safety evaluation index.

[0076] As a preferred solution, the subjective weight calculation module constructs a judgment matrix A according to the importance degree of the influencing factors:

[0077]

[0078] where a ij = 1 indicates that index i is more important than index j; a ij = 0 indicates that index i and index j are equally important; a ij = -1 indicates that index j is more important than index i;

[0079] Calculate the optimal transfer matrix R of the judgment matrix A according to the following formula:

[0080]

[0081] For any element in the optimal transfer matrix R, it satisfies:

[0082]

[0083] where n is the number of evaluation indexes;

[0084] Calculate the judgment matrix D of the optimal transfer matrix R according to the following formula:

[0085]

[0086] For any element in the judgment matrix D, it satisfies:

[0087] d ij = exp(r ij )

[0088] Calculate the subjective weight of each energy storage power station safety evaluation index according to the following formula:

[0089]

[0090] As a preferred solution, the objective weight calculation module establishes a decision matrix according to the following expression:

[0091]

[0092] where \(i = 1, 2, \ldots, m\), \(j = 1, 2, \ldots, n\), \(x\) ij is the preference of the \(i\)-th alternative with respect to the \(j\)-th criterion; the correlation is calculated according to the following expression to measure the degree of correlation between criteria:

[0093]

[0094] The standard deviation of each index is calculated according to the following formula:

[0095]

[0096] The objective weights of the safety assessment indexes of each energy storage power station are calculated according to the following formula:

[0097]

[0098] As a preferred solution, the comprehensive weight calculation module establishes a basic weight vector set according to the following formula:

[0099] W q = {W 1 , W 2 , \(\ldots\), W n}

[0100] where \(q = 1, 2, \ldots, p\), \(W\) p is the weight set determined by the \(p\)-th weighting method, \(n\) is the number of design indexes, and \(p\) is the number of methods for obtaining weights;

[0101] Let \(\alpha=\{\alpha\) 1 , \(\alpha\) 2 \} be the linear combination coefficients, and the linear combination of two weight vectors is determined according to the following formula:

[0102]

[0103] where \(W\) 1 is the subjective weight vector set of indexes; \(W\) 2 is the objective weight vector set of indexes; \(\alpha\) 1 , \(\alpha\) 2 are the coefficients of the subjective weight and the objective weight of indexes respectively;

[0104] Based on the idea of the game aggregation model, with the goal of minimizing the deviation, the linear combination coefficients of the two weight vectors are optimized to obtain the target weights in \(W\), and the following objective function is established:

[0105]

[0106] where \(\min\|\) 2 represents solving the L2 norm, A vector set representing the summation comprehensive weight;

[0107] According to the matrix differential property, the above formula is equivalently transformed into the first-order derivative condition of optimization, and the following linear equations are obtained:

[0108]

[0109] The optimized combination coefficient α is calculated 1 , α 2 , and the normalization process is carried out according to the following formula:

[0110]

[0111] The comprehensive weight of the energy storage power station safety assessment index is calculated according to the following formula:

[0112]

[0113] As a preferred solution, when the safety assessment level determination module adopts the fuzzy comprehensive evaluation method to obtain the safety assessment level of the energy storage power station, the factor set U and the evaluation set V of the evaluation object are determined. The factor set U is the set of energy storage power station safety assessment indicators;

[0114] According to the factor set U, the membership function is selected to construct the membership matrix;

[0115] Multiply the comprehensive weight of the energy storage power station safety assessment index by the membership matrix to obtain the fuzzy comprehensive evaluation result;

[0116] Compare the fuzzy comprehensive evaluation result with the evaluation set V to obtain the safety assessment level of the energy storage power station.

[0117] In the third aspect, an electronic device is provided, including a processor and a memory. The processor is used to execute the computer program stored in the memory to implement the energy storage safety assessment method based on game theory and fuzzy comprehensive evaluation.

[0118] In the fourth aspect, a computer-readable storage medium is provided. The computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by the processor, the energy storage safety assessment method based on game theory and fuzzy comprehensive evaluation is implemented.

[0119] Compared with the prior art, the first aspect of the present invention has at least the following beneficial effects:

[0120] The present invention calculates the subjective weight of the energy storage power station safety assessment index using an improved analytic hierarchy process (AHP), calculates the objective weight using the comprehensive index evaluation method of contrast intensity and conflictiveness CRITIC method, calculates the comprehensive weight of the energy storage power station safety assessment index based on the subjective weight and the objective weight using the game theory method, and obtains the energy storage power station safety assessment level using the fuzzy comprehensive evaluation method. In the improved AHP of the present invention, the judgment matrix is constructed and the subjective weight is calculated using the three-scale method of the optimal transfer matrix. Specifically, a scale of 1 indicates that the previous index is more important than the latter index, a scale of 0 indicates that the previous index is equally important as the latter index, and a scale of -1 indicates that the latter index is more important than the previous index. Compared with the traditional AHP, the method of the present invention can improve the accuracy of the judgment result and the objectivity of the evaluation and greatly enhance the operability. The improved AHP fully considers the experience and knowledge of experts, making the weight distribution more in line with the actual situation. By introducing improvement strategies, the subjective tendency of the traditional AHP can be reduced, and the rationality and accuracy of the weight assignment result can be improved. The CRITIC method determines the weight by analyzing the mutual relationship between indicators and the dispersion degree of indicators. This method assigns weights based on the characteristics of the data itself, reducing the interference of human subjective factors. At the same time, the CRITIC method considers the correlation and dispersion of indicators, making the weight assignment more reasonable. The game theory method constructs a game model to solve the optimal weight assignment scheme. This method can comprehensively consider the subjective weight and the objective weight, making the combined weight reflect both the expert's empirical judgment and the objective characteristics of the data. The combined weight calculated by the game theory method is more comprehensive and objective, which helps to improve the accuracy of the safety assessment. The fuzzy comprehensive evaluation method can handle the uncertain factors in the energy storage power station safety assessment. Since the safety state of the energy storage power station is affected by various factors, and there are complex interactions between these factors, it is difficult to represent them with accurate numerical values. The fuzzy comprehensive evaluation method can take these uncertain factors into account and express them in a fuzzy form, so as to better reflect the real situation. In addition, the fuzzy comprehensive evaluation method can also handle the situation of multiple indicators and incomplete information and give an intuitive evaluation result. By combining the improved AHP, the CRITIC method and the game theory method, subjective and objective factors can be comprehensively considered, making the weight assignment more reasonable and comprehensive, which helps to improve the accuracy of the energy storage power station safety assessment. The application of the game theory method makes the calculation of the combined weight more objective and scientific, which helps decision-makers make more informed decisions. The fuzzy comprehensive evaluation method can handle problems such as uncertainty, multiple indicators and incomplete information, and is applicable to various complex safety assessment scenarios. The method of the present invention combines qualitative and quantitative analysis, can quickly and accurately complete the safety assessment work of the energy storage power station, and improve the assessment efficiency.Meanwhile, to enhance the intuitiveness and acceptability of the evaluation results, the evaluation results given by the fuzzy comprehensive evaluation method are more intuitive and easier to understand, enabling non-professionals to intuitively understand the safety status of the energy storage power station and take corresponding measures.

[0121] It can be understood that the beneficial effects of the above second aspect to the fourth aspect can be referred to the relevant descriptions in the above first aspect, and will not be elaborated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0122] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0123] Figure 1 Flowchart of the energy storage safety assessment method based on game theory and fuzzy comprehensive evaluation in the embodiment of the present invention;

[0124] Figure 2 Block diagram of the energy storage safety assessment system based on game theory and fuzzy comprehensive evaluation in the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0125] In the following description, specific details such as specific system structures and technologies are proposed for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can also be implemented in other embodiments without these specific details. In other cases, the detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.

[0126] Please refer to Figure 1 , in order to effectively improve the safety of the energy storage power station and strengthen the safety management of the energy storage power station, the embodiment of the present invention proposes an energy storage safety assessment method based on game theory and fuzzy comprehensive evaluation, mainly including the following steps:

[0127] S101. Collect the safety assessment indicators of the energy storage power station;

[0128] S102. Construct a judgment matrix for the safety assessment indicators of the energy storage power station by using the three-scale method of the optimal transfer matrix and calculate the subjective weight;

[0129] S103. Calculate the objective weight for the safety assessment indicators of the energy storage power station by using the CRITIC method for evaluating the comprehensive index of comparison intensity and conflict;

[0130] S104. Calculate the comprehensive weight of the energy storage power station safety evaluation index based on subjective weight and objective weight using game theory method;

[0131] S105. Obtain the safety evaluation grade of the energy storage power station by using the fuzzy comprehensive evaluation method according to the comprehensive weight of the energy storage power station safety evaluation index.

[0132] In the embodiment of the present invention, the improved Analytic Hierarchy Process (AHP) method is used to calculate the subjective weight of the index. The basic principle of the AHP method is to decompose the decision-making problem into different hierarchical structures in the order of the overall goal, sub-goals at each layer, evaluation criteria, and specific alternative solutions. Then, by solving the eigenvector of the judgment matrix, the priority weight of each element at each layer with respect to an element at the previous layer is obtained. Finally, the weighted sum method is used to hierarchically merge the final weights of each alternative solution with respect to the overall goal, and this is used as the basis for decision-making. The calculation steps of the AHP method mainly include the following four aspects:

[0133] Establish a hierarchical structure model: Divide the decision-making goal, considered factors (decision criteria), and decision-making objects into the highest layer, middle layer, and lowest layer according to their mutual relationships, and draw a hierarchical structure diagram. The highest layer refers to the purpose of decision-making and the problem to be solved; the lowest layer refers to the alternative solutions during decision-making; the middle layer refers to the considered factors and decision-making criteria.

[0134] Construct a judgment matrix: For a certain criterion, compare each pair of the following solutions and evaluate their importance levels. Then, construct a judgment matrix according to the evaluation results.

[0135] Hierarchical single sorting and consistency test: According to the judgment matrix, solve the weights of each index and conduct a consistency test. The consistency test is to ensure the rationality of the judgment matrix, that is, to ensure that the relative importance relationships between elements are consistent.

[0136] Hierarchical total sorting: Calculate the weights of the relative importance of all factors at a certain layer with respect to the highest layer (overall goal), which is called hierarchical total sorting. This process is carried out sequentially from the highest layer to the lowest layer.

[0137] The improved AHP method of the present invention constructs a judgment matrix and calculates weights using the three-scale method of the optimal transfer matrix. Compared with the traditional AHP method, it can improve the accuracy of judgment results, the objectivity of evaluation, and greatly enhance the operability.

[0138] The construction principle of the judgment matrix is as follows:

[0139] Scale Meaning 1 The previous indicator is more important than the next one 0 The previous indicator is equally important as the next one -1 The next indicator is more important than the previous one

[0140] Based on this, in a possible implementation manner, when constructing a judgment matrix and calculating the subjective weight for the energy storage power station safety assessment index by using the three-scale method of the optimal transfer matrix in step S102, it mainly includes the following steps:

[0141] Construct a judgment matrix A according to the importance degree of influencing factors:

[0142]

[0143] In the formula, a ij = 1 indicates that index i is more important than index j; a ij = 0 indicates that index i and index j are equally important; a ij = -1 indicates that index j is more important than index i;

[0144] Calculate the optimal transfer matrix R of the judgment matrix A according to the following formula:

[0145]

[0146] For any element in the optimal transfer matrix R, it satisfies:

[0147]

[0148] In the formula, n is the number of evaluation indexes;

[0149] Calculate the judgment matrix D of the optimal transfer matrix R according to the following formula:

[0150]

[0151] For any element in the judgment matrix D, it satisfies:

[0152] d ij = exp(r ij )

[0153] Calculate the subjective weight of each energy storage power station safety assessment index according to the following formula:

[0154]

[0155] The CRITIC (Criteria Importance Through Intercriteria Correlation) method is a widely used method for determining weights in the field of multi-index comprehensive evaluation. Its core idea is to evaluate the importance of each index by quantifying the conflict between indexes, so as to allocate reasonable weights to each index in the process of decision-making analysis and comprehensive evaluation. The main principle of the CRITIC method is to determine the objective weights of indexes by comparing the intensity and the conflict between indexes. Among them, the comparison intensity represents the size of the value gap of each evaluation scheme of the same index, which is expressed in the form of standard deviation; the conflict is based on the correlation between indexes. If there is a strong positive correlation between two indexes, it means that their conflict is smaller. The calculation steps of the CRITIC method mainly include the following aspects:

[0156] Data standardization: Since the order of magnitude and dimension of each index may be different, it is necessary to standardize the original data for subsequent calculations. The standardization process usually includes the processing of positive indexes and negative indexes. The positive index uses the formula of "the larger the better", and the negative index uses the formula of "the smaller the better".

[0157] Calculate the comparison intensity: The comparison intensity is measured by calculating the standard deviation of each index. The larger the standard deviation, the greater the value fluctuation of the corresponding index, that is, the greater the value gap between each scheme. Therefore, the weight of this index will be higher.

[0158] Calculate the conflict: The conflict reflects the degree of correlation between different indexes. If there is a significant positive correlation between two indexes, they may reflect similar information in the evaluation system, and the conflict value is smaller. The conflict is usually measured by calculating the Pearson correlation coefficient between indexes, and the conflict value is obtained by subtracting the correlation coefficient from 1.

[0159] Calculate the information carrying capacity: The information carrying capacity is the product of the comparison intensity and the conflict, which reflects the importance of the index in the evaluation system. The larger the information carrying capacity, the more information the index contains in the evaluation system, so the weight is larger.

[0160] Calculate the weight: The weight is the ratio of the information carrying capacity to the sum of the information carrying capacities of all indexes. By calculating the weight, the relative importance of each index in the evaluation system can be obtained.

[0161] Calculate the comprehensive score: Finally, according to the weights of each index and the standardized data, calculate the comprehensive scores of each evaluation scheme for sorting and comparison.

[0162] The CRITIC method is very suitable for the safety assessment of energy storage power stations.

[0163] In a possible implementation manner, when calculating the objective weight of the energy storage power station safety evaluation index by using the comprehensive index evaluation CRITIC method of contrast intensity and conflict, step S103 mainly includes the following steps:

[0164] Establish a decision matrix according to the following expression:

[0165]

[0166] In the formula, i = 1, 2,..., m, j = 1, 2,..., n, x ij is the preference of the i-th alternative relative to the j-th criterion;

[0167] Calculate the correlation according to the following expression to measure the degree of correlation between criteria:

[0168]

[0169] Calculate the standard deviation of each index according to the following formula:

[0170]

[0171] Calculate the objective weight of each energy storage power station safety evaluation index according to the following formula:

[0172]

[0173] The larger the standard deviation, the greater the difference in the evaluation index values, the greater the amount of information contained, and the greater the weight that needs to be assigned.

[0174] The embodiment of the present invention uses the game theory combination weighting method to determine the comprehensive weight. This method not only considers the subjective preference of the decision maker but also takes into account the objective characteristics of the data, making the weight allocation more reasonable and accurate.

[0175] In a possible implementation manner, when calculating the comprehensive weight of the energy storage power station safety evaluation index based on the subjective weight and the objective weight by using the game theory method, step S104 mainly includes the following steps:

[0176] Establish a basic weight vector set according to the following formula:

[0177] W q ={W 1 ,W 2 ,...,W n}

[0178] In the formula, q = 1, 2,..., p, W p is the weight set determined by the p-th weighting method, n is the number of design indexes, and p is the number of methods for obtaining weights;

[0179] Let α = {α1 , α 2} are the linear combination coefficients, and the linear combination of the two weight vectors is determined according to the following formula:

[0180]

[0181] In the formula, W 1 is the set of subjective weight vectors of the indicators; W 2 is the set of objective weight vectors of the indicators; α 1 , α 2 are the coefficients of the subjective weight and the objective weight of the indicators respectively;

[0182] Based on the idea of the game aggregation model, with the goal of minimizing the deviation, optimize the linear combination coefficients of the two weight vectors to obtain the target weights in W, and establish the following objective function:

[0183]

[0184] In the formula, min ∥ 2 represents solving the L2 norm, represents the set of vectors for summing the comprehensive weights; therefore, the meaning expressed by the above formula is to minimize the Euclidean distance between the target vector set and the original vector set.

[0185] According to the matrix differential property, equivalently transform the above formula into the first-order derivative condition of optimization, and obtain the following linear equations:

[0186]

[0187] Calculate the optimized combination coefficients α 1 , α 2 , and perform normalization processing according to the following formula:

[0188]

[0189] Calculate the comprehensive weight of the energy storage power station safety assessment index according to the following formula:

[0190]

[0191] In a possible implementation manner, when obtaining the safety assessment level of the energy storage power station by using the fuzzy comprehensive evaluation method according to the comprehensive weight of the energy storage power station safety assessment index in step S105, it mainly includes the following steps:

[0192] a. Determine the factor set U and the evaluation set V of the evaluation object. The factor set U is the set of energy storage power station safety assessment indicators;

[0193] b. Select the membership function according to the factor set U and construct the membership matrix;

[0194] c. Multiply the comprehensive weight of the energy storage power station safety assessment index by the membership degree matrix to obtain the fuzzy comprehensive evaluation result;

[0195] d. Compare the fuzzy comprehensive evaluation result with the evaluation set V to obtain the safety assessment level of the energy storage power station.

[0196] In step a, taking the safety of the energy storage power station as the evaluation object, the factor set U = {u 1 , u 2 , u 3 , u 4 , u 5} is the energy storage power station safety assessment index set, which are the battery operation conditions, key equipment and facilities, operation environment, safety rules and regulations, and personnel factors respectively. The evaluation set is V = {v 1 , v 2 , v 3 , v 4}, which are low risk, general risk, relatively large risk, and major risk, and each level corresponds to a fuzzy subset. In a possible implementation manner, the specific level division rules are as follows: low risk (score ≥ 90), general risk (80 ≤ score < 90), relatively large risk (70 ≤ score < 80), major risk (score < 70).

[0197] Furthermore, in step b, the normal distribution type is selected as the membership function, and the expression is as follows:

[0198]

[0199] In the formula, z i is the specific score of a certain evaluation index;

[0200] The average value Z mean is the midpoint of each level interval, and the calculation expression is:

[0201] z mean = (z 1 + z 2 ) / 2

[0202] When z = Z mean , the membership degree is 1;

[0203] The standard deviation σ is calculated according to the following expression:

[0204]

[0205] When the value of the evaluation index is at the interval endpoint, it is considered that the fuzziness of the corresponding index is the highest and it is difficult to determine which level it belongs to, then the membership degrees of the two adjacent evaluation levels are both 0.5.

[0206] Solving the above equation gives: σ = (z 1 - z2 ) / 1.66。

[0207] Construct the membership degree matrix according to the following formula:

[0208]

[0209] In the formula, r ij is the membership degree of the j-th index of the i-th plan relative to the evaluation set V = {v 1 , v 2 , v 3 , v 4}.

[0210] In step c, multiply the comprehensive weight W of the energy storage power station safety evaluation index by the membership degree matrix R i to obtain the fuzzy comprehensive evaluation result, that is, S = W · R i = [s 1 , s 2 ,..., s p . Any element in S corresponds to the membership degree of the 4 levels in the evaluation set V.

[0211] Please refer to Figure 2 , another embodiment of the present invention also proposes an energy storage safety evaluation system based on game theory and fuzzy comprehensive evaluation, including:

[0212] Index acquisition module 201, used to acquire energy storage power station safety evaluation indexes;

[0213] Subjective weight calculation module 202, used to construct a judgment matrix for the energy storage power station safety evaluation indexes by using the three-scale method of the optimal transfer matrix and calculate the subjective weight;

[0214] Objective weight calculation module 203, used to calculate the objective weight of the energy storage power station safety evaluation indexes by using the CRITIC method of comprehensive evaluation of contrast intensity and conflict;

[0215] Comprehensive weight calculation module 204, used to calculate the comprehensive weight of the energy storage power station safety evaluation indexes based on the subjective weight and the objective weight by using the game theory method;

[0216] Safety evaluation level determination module 205, used to obtain the energy storage power station safety evaluation level by using the fuzzy comprehensive evaluation method according to the comprehensive weight of the energy storage power station safety evaluation indexes.

[0217] In a possible implementation manner, the subjective weight calculation module 202 constructs a judgment matrix A according to the importance degree of influencing factors:

[0218]

[0219] In the formula, a ij= 1 indicates that index i is more important than index j; a ij = 0 indicates that index i and index j are equally important; a ij = -1 indicates that index j is more important than index i;

[0220] Calculate the optimal transfer matrix R of the judgment matrix A according to the following formula:

[0221]

[0222] For any element in the optimal transfer matrix R, it satisfies:

[0223]

[0224] In the formula, n is the number of evaluation indicators;

[0225] Calculate the judgment matrix D of the optimal transfer matrix R according to the following formula:

[0226]

[0227] For any element in the judgment matrix D, it satisfies:

[0228] d ij = exp(r ij )

[0229] Calculate the subjective weights of the safety evaluation indicators of each energy storage power station according to the following formula:

[0230]

[0231] In a possible implementation, the objective weight calculation module 203 establishes a decision matrix according to the following expression:

[0232]

[0233] In the formula, i = 1, 2,..., m, j = 1, 2,..., n, x ij is the preference of the i-th alternative solution with respect to the j-th criterion;

[0234] Calculate the correlation according to the following expression to measure the degree of correlation between criteria:

[0235]

[0236] Calculate the standard deviation of each indicator according to the following formula:

[0237]

[0238] Calculate the objective weights of the safety evaluation indicators of each energy storage power station according to the following formula:

[0239]

[0240] In a possible implementation, the comprehensive weight calculation module 204 establishes a basic weight vector set according to the following formula:

[0241] W q ={W 1 ,W 2 ,...,W n}

[0242] In the formula, q = 1, 2,..., p, W p is the weight set determined by the p-th weighting method, n is the number of design indicators, and p is the number of methods for obtaining weights;

[0243] Let α={α 1 ,α 2} be the linear combination coefficient, and determine the linear combination of two weight vectors according to the following formula:

[0244]

[0245] In the formula, W 1 is the set of subjective weight vectors of the indicators; W 2 is the set of objective weight vectors of the indicators; α 1 ,α 2 are the coefficients of the subjective weight and the objective weight of the indicators respectively;

[0246] Based on the idea of the game aggregation model, with the goal of minimizing the deviation, optimize the linear combination coefficients of the two weight vectors to obtain the target weights in W, and establish the following objective function:

[0247]

[0248] In the formula, min∥ 2 represents solving the L2 norm, represents the vector set for summing the comprehensive weights;

[0249] According to the matrix differential property, equivalently transform the above formula into the optimization first derivative condition to obtain the following linear equations:

[0250]

[0251] Calculate the optimized combination coefficients α 1 ,α 2 , and perform normalization processing according to the following formula:

[0252]

[0253] Calculate the comprehensive weight of the energy storage power station safety assessment index according to the following formula:

[0254]

[0255] In a possible implementation manner, when the safety assessment level determination module 205 obtains the safety assessment level of the energy storage power station by using the fuzzy comprehensive evaluation method, it determines the factor set U and the evaluation set V of the evaluation object. The factor set U is the set of safety assessment indicators of the energy storage power station;

[0256] Select a membership function according to the factor set U and construct a membership matrix;

[0257] Multiply the comprehensive weight of the safety assessment indicators of the energy storage power station by the membership matrix to obtain a fuzzy comprehensive evaluation result;

[0258] Compare the fuzzy comprehensive evaluation result with the evaluation set V to obtain the safety assessment level of the energy storage power station.

[0259] Another embodiment of the present invention also proposes an electronic device, including a processor and a memory. The processor is configured to execute a computer program stored in the memory to implement the energy storage safety assessment method based on game theory and fuzzy comprehensive evaluation.

[0260] Another embodiment of the present invention also proposes a computer-readable storage medium. The computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, it implements the energy storage safety assessment method based on game theory and fuzzy comprehensive evaluation.

[0261] The computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable storage medium may include: any entity or device, medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory, random access memory, electrical carrier signal, telecommunication signal, and software distribution medium that can carry the computer program code. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals. For the sake of convenience of description, only the parts related to the embodiments of the present invention are shown above. For the specific technical details not disclosed, please refer to the method part of the embodiments of the present invention. This computer-readable storage medium is non-transitory and can be stored in a storage device formed by various electronic devices, and can implement the execution process recorded in the method of the embodiments of the present invention.

[0262] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) that contain computer-usable program code.

[0263] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems) and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in Figure 1 one or more of the flows Figure 1 or a plurality of flows and / or blocks

[0264] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured product including an instruction device, and the instruction device realizes the functions specified in Figure 1 one or more of the flows Figure 1 or a plurality of flows and / or blocks

[0265] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Therefore, the instructions executed on the computer or other programmable device provide steps for realizing the functions specified in Figure 1 one or more of the flows Figure 1 or a plurality of flows and / or blocks

[0266] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: the specific implementation manners of the present invention can still be modified or equivalently replaced, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the protection scope of the claims of the present invention.

Claims

1. A method for energy storage safety assessment based on game theory and fuzzy comprehensive evaluation, characterized in that: include: Collect safety assessment indicators of energy storage power stations; The three-scaling method of the optimal transfer matrix is ​​used to construct the judgment matrix and calculate the subjective weights for the safety assessment indicators of the energy storage power station. The safety assessment index of energy storage power station is evaluated by using the CRITIC method to calculate the objective weights using the comparative strength and conflict comprehensive index evaluation method; The game theory method is used to calculate the comprehensive weight of the safety assessment index of the energy storage power station based on the subjective weight and objective weight; According to the comprehensive weights of the safety assessment indicators of the energy storage power station, the fuzzy comprehensive evaluation method is used to obtain the safety assessment level of the energy storage power station.

2. The energy storage safety assessment method based on game theory and fuzzy comprehensive evaluation according to claim 1 is characterized in that: The steps of constructing a judgment matrix and calculating subjective weights for the energy storage power station safety assessment index using the three-scaling method of the optimal transfer matrix include: Construct the judgment matrix A according to the importance of the influencing factors: In the formula, a ij =1 means that indicator i is more important than indicator j; a ij =0 means that indicator i and indicator j are equally important; a ij =-1 means that indicator j is more important than indicator i; The optimal transfer matrix R of the judgment matrix A is calculated as follows: For any element in the optimal transfer matrix R, it satisfies: In the formula, n is the number of evaluation indicators; The judgment matrix D of the optimal transfer matrix R is calculated as follows: For any element in the judgment matrix D, it satisfies: d ij =exp(r ij ) The subjective weight of each energy storage power station safety assessment indicator is calculated as follows:

3. The energy storage safety assessment method based on game theory and fuzzy comprehensive evaluation according to claim 1 is characterized in that: The steps of calculating the objective weights of the energy storage power station safety assessment index using the comparative strength and conflict comprehensive index evaluation CRITIC method include: Establish a decision matrix according to the following expression: Where i = 1, 2, ..., m, j = 1, 2, ..., n, x ij is the preference of the ith alternative relative to the jth criterion; The correlation is calculated according to the following expression to measure the degree of correlation between the criteria: The standard deviation of each indicator is calculated as follows: The objective weight of each energy storage power station safety assessment index is calculated as follows:

4. The energy storage safety assessment method based on game theory and fuzzy comprehensive evaluation according to claim 1 is characterized in that: The step of using the game theory method to calculate the comprehensive weight of the energy storage power station safety assessment index based on the subjective weight and the objective weight includes: The basic weight vector set is established as follows: IN q ={W1,W2,...,W n } Where q = 1, 2, ..., p, W p is the weight set determined by the pth weighting method, n is the number of design indicators, and p is the number of weighting methods; Assume α = {α1, α2} as the linear combination coefficient, and determine the linear combination of the two weight vectors as follows: Where W1 is the subjective weight vector set of indicators; W2 is the objective weight vector set of indicators; α1 and α2 are the coefficients of the subjective weight and objective weight of indicators respectively; Based on the idea of ​​game aggregation model, with the goal of minimizing the deviation, the linear combination coefficients of the two weight vectors are optimized to obtain the target weight in W, and the following objective function is established: In the formula, min∥2 means solving the L2 norm. A vector set representing the summed comprehensive weights; According to the matrix differential properties, the above equation is equivalently transformed into the optimal first-order derivative condition, and the following linear equations are obtained: The optimized combination coefficients α1 and α2 are calculated and normalized as follows: The comprehensive weight of the safety assessment index of the energy storage power station is calculated as follows:

5. The energy storage safety assessment method based on game theory and fuzzy comprehensive evaluation according to claim 1 is characterized in that: The step of obtaining the safety assessment level of the energy storage power station by using the fuzzy comprehensive evaluation method according to the comprehensive weight of the safety assessment indicators of the energy storage power station comprises: Determine the factor set U and evaluation set V of the evaluation object, where the factor set U is a set of safety evaluation indicators for energy storage power stations; Select the membership function according to the factor set U and construct the membership matrix; The fuzzy comprehensive evaluation result is obtained by multiplying the comprehensive weight of the safety assessment index of the energy storage power station with the membership matrix; The fuzzy comprehensive evaluation results are compared with the evaluation set V to obtain the safety assessment level of the energy storage power station.

6. The energy storage safety assessment method based on game theory and fuzzy comprehensive evaluation according to claim 5 is characterized in that: Select the normal distribution type as the membership function, the expression is as follows: In the formula, z i The specific score of a certain evaluation indicator; Average value z mean is the midpoint of each level interval, and the calculation expression is: With mean =(z1+z2) / 2 When z = z mean When , the membership degree is 1; The standard deviation σ is calculated as follows: The membership matrix is ​​constructed as follows: In the formula, r ij is the membership degree of the jth indicator of the ith solution with respect to the evaluation set V = {v1, v2, v3, v4}.

7. An energy storage safety assessment system based on game theory and fuzzy comprehensive evaluation, characterized in that: include: Index collection module, used to collect safety assessment indicators of energy storage power stations; The subjective weight calculation module is used to construct a judgment matrix and calculate the subjective weight for the safety assessment index of the energy storage power station using the three-scaling method of the optimal transfer matrix; Objective weight calculation module, used to calculate objective weights for energy storage power station safety assessment indicators using the comparative intensity and conflict comprehensive index evaluation CRITIC method; A comprehensive weight calculation module is used to calculate the comprehensive weight of the safety assessment index of the energy storage power station based on the subjective weight and the objective weight using the game theory method; The safety assessment level determination module is used to obtain the safety assessment level of the energy storage power station using a fuzzy comprehensive evaluation method based on the comprehensive weights of the safety assessment indicators of the energy storage power station.

8. The energy storage safety assessment system based on game theory and fuzzy comprehensive evaluation according to claim 7 is characterized in that: The subjective weight calculation module constructs a judgment matrix A according to the importance of the influencing factors: In the formula, a ij =1 means that indicator i is more important than indicator j; a ij =0 means that indicator i and indicator j are equally important; a ij =-1 means that indicator j is more important than indicator i; The optimal transfer matrix R of the judgment matrix A is calculated as follows: For any element in the optimal transfer matrix R, it satisfies: In the formula, n is the number of evaluation indicators; The judgment matrix D of the optimal transfer matrix R is calculated as follows: For any element in the judgment matrix D, it satisfies: d ij =exp(r ij ) The subjective weight of each energy storage power station safety assessment indicator is calculated as follows:

9. The energy storage safety assessment system based on game theory and fuzzy comprehensive evaluation according to claim 7 is characterized in that: The objective weight calculation module establishes a decision matrix according to the following expression: Where i = 1, 2, ..., m, j = 1, 2, ..., n, x ij is the preference of the ith alternative relative to the jth criterion; The correlation is calculated according to the following expression to measure the degree of correlation between the criteria: The standard deviation of each indicator is calculated as follows: The objective weight of each energy storage power station safety assessment index is calculated as follows:

10. The energy storage safety assessment system based on game theory and fuzzy comprehensive evaluation according to claim 7 is characterized in that: The comprehensive weight calculation module establishes a basic weight vector set according to the following formula: IN q ={W1,W2,...,W n } Where q = 1, 2, ..., p, W p is the weight set determined by the pth weighting method, n is the number of design indicators, and p is the number of weighting methods; Assume α = {α1, α2} as the linear combination coefficient, and determine the linear combination of the two weight vectors as follows: Where W1 is the subjective weight vector set of indicators; W2 is the objective weight vector set of indicators; α1 and α2 are the coefficients of the subjective weight and objective weight of indicators respectively; Based on the idea of ​​game aggregation model, with the goal of minimizing the deviation, the linear combination coefficients of the two weight vectors are optimized to obtain the target weight in W, and the following objective function is established: In the formula, min∥2 means solving the L2 norm. A vector set representing the summed comprehensive weights; According to the matrix differential properties, the above equation is equivalently transformed into the optimal first-order derivative condition, and the following linear equations are obtained: The optimized combination coefficients α1 and α2 are calculated and normalized as follows: The comprehensive weight of the safety assessment index of the energy storage power station is calculated as follows:

11. The energy storage safety assessment system based on game theory and fuzzy comprehensive evaluation according to claim 7 is characterized in that: When the safety assessment level determination module adopts the fuzzy comprehensive evaluation method to obtain the safety assessment level of the energy storage power station, it determines the factor set U and the evaluation set V of the evaluation object, where the factor set U is a set of safety assessment indicators of the energy storage power station; Select the membership function according to the factor set U and construct the membership matrix; The fuzzy comprehensive evaluation result is obtained by multiplying the comprehensive weight of the safety assessment index of the energy storage power station with the membership matrix; The fuzzy comprehensive evaluation results are compared with the evaluation set V to obtain the safety assessment level of the energy storage power station.

12. An electronic device, characterized in that: It comprises a processor and a memory, wherein the processor is used to execute a computer program stored in the memory to implement the energy storage safety assessment method based on game theory and fuzzy comprehensive evaluation as claimed in any one of claims 1 to 6.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by the processor, the energy storage safety assessment method based on game theory and fuzzy comprehensive evaluation as described in any one of claims 1 to 6 is implemented.

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