Active power distribution network frequency self-healing method considering multiple energy storage modes

Abstract

The invention discloses an active power distribution network frequency self-healing method considering multiple energy storage modes, and the method comprises the following steps: S1, building a Markov chain-based multi-mode energy storage model, determining the residual frequency modulation capacity of the multi-mode energy storage, and carrying out the quantitative analysis of the power output uncertainty of the multi-mode energy storage model; s2, a safety evaluation index system suitable for the distributed energy active power distribution network is constructed, the frequency modulation capability of the multi-mode energy storage model is evaluated, and a first frequency modulation sequence is generated according to the evaluation result of the frequency modulation capability of the multi-mode energy storage model; s3, in the first frequency modulation sequence, an energy storage participation frequency modulation intention strategy is introduced, and a second frequency modulation sequence is generated; and S4, introducing a frequency modulation excitation factor considering the frequency modulation mileage, sequencing the frequency modulation mileage, setting the frequency modulation excitation factor according to the sequence of the frequency modulation mileage, and superposing the frequency modulation excitation factor with the second frequency modulation sequence again to generate a third frequency modulation sequence.

Description

Technical Field

[0001] The present invention relates to the technical field of active distribution network security assessment, and particularly to a frequency self-healing method for an active distribution network considering multiple energy storage modes. Background Technique

[0002] With the acceleration of the global energy transformation, the penetration rates of distributed energy sources such as photovoltaic power generation, wind power generation, and energy storage systems in the distribution network are continuously increasing. These distributed energy sources have the advantages of being clean, efficient, and flexible, and can effectively relieve the pressure of traditional energy sources and improve energy utilization efficiency. However, the access of distributed energy sources has also brought new challenges to the safe operation of the distribution network. Due to the intermittent and uncertain output power of distributed energy sources, and the more complex topological structure and operation mode of the distribution network, traditional distribution network security assessment methods are difficult to adapt to the new operation environment.

[0003] The new distribution network simultaneously includes lithium-ion battery energy storage, flow battery energy storage, flywheel energy storage, compressed air energy storage, and supercapacitor energy storage. Different energy storage types have different power densities and charge and discharge capabilities, and are located in different positions in the power network, distributed on the user side, in the distribution substation area and switch station, and there is also energy storage directly used as shared energy storage for commercial deployment.

[0004] The present invention aims to disclose a frequency self-healing method for an active distribution network considering multiple energy storage modes, to solve the problem that with the large-scale access of multi-mode energy storage, the operation characteristics of the distribution network have changed significantly, and traditional frequency regulation methods are difficult to meet the actual requirements. Summary of the Invention

[0005] Aiming at the above-mentioned prior art, the present invention provides a frequency self-healing method and system for an active distribution network considering multiple energy storage modes, mainly solving the technical problems existing in the above background technique.

[0006] To achieve the above object, the technical solution of the embodiment of the present invention is realized as follows: The present invention discloses a frequency self-healing method for an active distribution network considering multiple energy storage modes, and the method includes the following steps: Step S1: Establish a multi-mode energy storage model based on Markov chain, respectively determine the remaining frequency regulation capacity of multiple modes of energy storage, and quantitatively analyze the uncertainty of the power output of the multi-mode energy storage model; Step S2: Construct a safety evaluation index system applicable to an active distribution network containing distributed energy sources, evaluate the frequency regulation ability of the multi-mode energy storage model, and generate the first frequency regulation order according to the evaluation result of its frequency regulation ability; Step S3: In the first frequency regulation order, introduce a strategy for the willingness of energy storage to participate in frequency regulation to generate the second frequency regulation order; Step S4: Introduce a frequency regulation incentive factor considering the frequency regulation mileage, sort the frequency regulation mileage, set the frequency regulation incentive factor according to the sorted frequency regulation mileage, and superimpose it with the second frequency regulation order again to generate the third frequency regulation order.

[0007] As a preferred embodiment of the present invention, in step S1: for a multi-mode energy storage system, the remaining energy storage capacity is represented by a stationary distribution, and the stationary distribution of the remaining energy storage capacity is obtained by solving the following system of equations: Where, represents the initial distribution of the remaining energy storage capacity of the distributed energy storage ; represents the initial distribution of the remaining energy storage capacity of the small-capacity centralized energy storage ; represents the initial distribution of the remaining energy storage capacity of the large-capacity centralized energy storage ; represents the stationary distribution of the remaining energy storage capacity of the distributed energy storage ; represents the stationary distribution of the remaining energy storage capacity of the small-capacity centralized energy storage ; represents the stationary distribution of the remaining energy storage capacity of the large-capacity centralized energy storage ; represents the state transition matrix of the active distribution network.

[0008] As a preferred embodiment of the present invention, the safety evaluation indicators in the safety evaluation index system applicable to the active distribution network with distributed energy sources constructed in step S2 specifically include: active distribution network power balance, active distribution network power quantity balance, distributed power source consumption risk, distribution network voltage safety risk, and distribution network frequency safety risk.

[0009] As a preferred embodiment of the present invention, step S2 specifically includes: performing normalization and dimensionless processing on the basis of the traditional entropy weight method and using it to calculate the weights of each safety evaluation index. At the same time, the entropy values of each safety evaluation index are solved through the characteristic coefficients of the safety evaluation indexes, as follows: Where, represents the weight of the th safety evaluation index, represents the entropy value corresponding to the th safety evaluation index, represents the total number of safety evaluation indexes.

[0010] As a preferred embodiment of the present invention, step S2 specifically includes: calculating the comprehensive evaluation value of each energy storage mode through the weights of each safety evaluation index, determining the weights of the empowerment results of the safety evaluation indexes lower than or equal to the average level using the entropy method, and setting the weights of the comprehensive evaluation values higher than the average level to 0 to obtain a weight matrix. The comprehensive evaluation value of the th energy storage mode is: Wherein, is the comprehensive evaluation value of the th energy storage mode, is the index entropy value of the th energy storage mode in the first evaluation, represents the total number of each energy storage mode; the comprehensive evaluation value of each energy storage mode specifically represents the frequency modulation capabilities of the generated distributed energy storage Fs, small-capacity centralized energy storage Xs, and large-capacity centralized energy storage Ds, and the first frequency modulation order is generated respectively according to the frequency modulation capabilities of each energy storage mode.

[0011] As a preferred embodiment of the present invention, the specific process of step S3 is as follows: grading the energy storage frequency modulation willingness of the user-side energy storage, distribution transformer area-side energy storage, switch station energy storage, and commercial shared energy storage, setting the energy storage frequency modulation willingness factor of the user-side energy storage as , the energy storage frequency modulation willingness factor of the distribution transformer area-side energy storage as , the energy storage frequency modulation willingness factor of the switch station energy storage as , the energy storage frequency modulation willingness factor of the commercial shared energy storage as , setting the grading as > = > , and integrating each user willingness factor into the frequency modulation strategy to generate the second frequency modulation order.

[0012] As a preferred embodiment of the present invention, step S4 specifically includes: setting the frequency modulation mileage according to the remaining energy storage capacity, setting the frequency modulation rate, sorting the frequency modulation capabilities of each generated energy storage mode according to the frequency modulation mileage, setting the frequency modulation incentive factor according to the sorting of the frequency modulation mileage, and superimposing it with the second frequency modulation order to generate the third frequency modulation order.

[0013] The beneficial effects of the present invention are as follows: Compared with the prior art, the present invention provides an active distribution network frequency self-healing method considering multiple energy storage modes. With the large-scale access of multi-mode energy storage, the operating characteristics of the distribution network have changed significantly, and traditional frequency regulation methods are difficult to meet the actual needs. First, uncertainty analysis is carried out on distributed energy storage, small-capacity centralized energy storage, and large-capacity centralized energy storage based on Markov chains. Incorporating the different uncertainties of multiple energy storage modes, frequency modulation reliability analysis is performed on the active distribution network with multiple energy storage modes. The energy storage frequency modulation reliability coefficients are introduced respectively, and the frequency modulation order is set according to the reliability coefficients. A frequency modulation willingness grading strategy is proposed. By configuring different frequency modulation willingness and frequency modulation incentive factors, the frequency self-healing recovery ability of the local active distribution network is improved, providing strong technical support for the safe operation of the distribution network. At the same time, the frequency self-healing ability and economy of the active distribution network are improved. This method is more in line with the actual operation situation and is applicable to the complex power grid environment with high proportion of renewable energy access. Description of the Drawings

[0014] Figure 1 is the flow chart of the active distribution network frequency self-healing method considering multiple energy storage modes in this application Figure 1 ; Figure 2 is the flow chart of the active distribution network frequency self-healing method considering multiple energy storage modes in this application Figure 2 ; Figure 3 is the schematic diagram of generating the second frequency modulation order provided by this application; Figure 4 is the schematic diagram of generating the third frequency modulation order provided by this application. Detailed Embodiment

[0015] The technical solution of the present invention will be further elaborated in detail below in conjunction with the accompanying drawings of the specification and specific embodiments. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art belonging to the technical field of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention. In the following description, the expression "some embodiments" is described, which describes a subset of all possible embodiments. However, it should be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments and can be combined with each other without conflict.

[0016] In the following description, a large number of specific details are given to provide a more thorough understanding of the present invention. However, it is obvious to those skilled in the art that the present invention can be implemented without one or more of these details. In other examples, in order to avoid confusion with the present invention, some technical features well known to the public are not described.

[0017] It should be understood that the present invention can be implemented in different forms and should not be construed as limited to the embodiments presented herein. On the contrary, providing these embodiments will make the disclosure thorough and complete, and will fully convey the scope of the present invention to those skilled in the art. And the purpose of the terms used herein is only to describe specific embodiments and is not a limitation of the present invention. As used herein, the singular forms "a", "an" and "the" are also intended to include the plural forms unless the context clearly dictates otherwise. It should also be understood that the terms "comprising" and / or "including", when used in this specification, determine the presence of the stated features, integers, steps, operations, elements and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups. As used herein, the term "and / or" includes any and all combinations of the related listed items.

[0018] It should be further noted that when an element is referred to as "fixed to" another element, it can be directly on the other element or there can also be an intermediate element. When an element is considered to be "connected" to another element, it can be directly connected to the other element or there may be an intermediate element at the same time. The terms "vertical", "horizontal", "inner", "outer", "left", "right" and similar expressions used herein are for illustrative purposes only and do not represent the only implementation.

[0019] To thoroughly understand the present invention, detailed structures will be presented in the following description to illustrate the technical solutions proposed by the present invention. The optional embodiments of the present invention are described in detail below. However, in addition to these detailed descriptions, the present invention can also have other implementations.

[0020] Please refer to the attached Figure 1 and the attached Figure 2 , a frequency self-healing method for an active distribution network considering multiple energy storage modes, the method comprising the following steps: Step S1: Establish a multi-mode energy storage model based on a Markov chain, respectively determine the remaining frequency regulation capacity of multiple-mode energy storage, and quantitatively analyze the power output uncertainty of the multi-mode energy storage model; Step S2: Construct a safety evaluation index system applicable to an active distribution network with distributed energy sources, evaluate the frequency regulation ability of the multi-mode energy storage model, and generate the first frequency regulation order according to the evaluation results of its frequency regulation ability; Step S3: In the first frequency regulation order, introduce a strategy for the willingness of energy storage to participate in frequency regulation to generate the second frequency regulation order; Step S4: Introduce a frequency regulation incentive factor considering the frequency regulation mileage, sort the frequency regulation mileage, set the frequency regulation incentive factor according to the frequency regulation mileage sorting, and superimpose it with the second frequency regulation order again to generate the third frequency regulation order.

[0021] Exemplarily, the present invention discloses a frequency self-healing method for active distribution networks considering multiple energy storage modes. With the large-scale access of multi-mode energy storage, the operating characteristics of distribution networks have changed significantly, and traditional frequency regulation methods are difficult to meet the actual requirements. First, uncertainty analysis is carried out on distributed energy storage, small-capacity centralized energy storage, and large-capacity centralized energy storage based on Markov chains. In the existing analysis of the frequency regulation ability of energy storage for active distribution networks, the different frequency regulation abilities of the configurations of multiple energy storage modes in the power network are not considered. According to the reliable capacity, instantaneous power output rate, etc., the first frequency regulation order is generated.

[0022] Introduce the energy storage frequency regulation willingness strategy, classify the energy storage frequency regulation willingness of user-side energy storage, distribution substation side energy storage, switch station energy storage, and commercial shared energy storage, integrate the user willingness into the frequency regulation strategy, and generate the second frequency regulation order.

[0023] Set a frequency regulation incentive factor considering the frequency regulation mileage, so that the preliminary frequency regulation order of the strategy that only considers the frequency regulation ability without considering the frequency regulation willingness is established first, and the third frequency regulation order is generated.

[0024] Successively introduce different frequency regulation influencing factors, and then generate different frequency regulation orders, better apply the energy storage resources in the active distribution network of this region, and improve the frequency self-healing ability of the local active distribution network.

[0025] As a preferred solution of the present invention, in step S1: for the multi-mode energy storage system, the remaining energy storage capacity is represented by a stationary distribution, and the stationary distribution of the remaining energy storage capacity is obtained by solving the following equations: Among them, represents the initial distribution of the remaining energy storage capacity of distributed energy storage ; represents the initial distribution of the remaining energy storage capacity of small-capacity centralized energy storage ; represents the initial distribution of the remaining energy storage capacity of large-capacity centralized energy storage ; represents the stationary distribution of the remaining energy storage capacity of distributed energy storage ; represents the stationary distribution of the remaining energy storage capacity of small-capacity centralized energy storage ; represents the stationary distribution of the remaining energy storage capacity of large-capacity centralized energy storage ; represents the state transition matrix of the active distribution network, that is, the ratio of the number of times the distributed energy in the active distribution network changes from state to state to the remaining state of the frequency regulation power in the active distribution network .

[0026] Specifically, the parameters are derived from the actual operation data of the power system, covering the remaining power information and state change information of various energy storage modes. To ensure the accuracy and availability of the data, the original data is preprocessed, including data cleaning, missing value filling, and outlier handling.

[0027] For energy storage devices with multiple energy storage modes, count the number of transitions between different states and normalize it to the transition probability.

[0028] For example, assume that the state space of the energy storage device with multiple energy storage modes is , based on historical data or observation results, count the frequency of transition from each state to state . Therefore, the active distribution network state transition matrix represents the ratio of the number of times from state to state to the remaining state of the frequency modulation power in the active distribution network .

[0029] Exemplarily, an active distribution network system with multiple energy storage modes can be regarded as containing distributed energy storage, small-capacity centralized energy storage, and large-capacity centralized energy storage in the active distribution network at the same time. To analyze the power output uncertainty of multi-mode energy storage, a model capable of describing its dynamic behavior is established.

[0030] The purpose of uncertainty analysis is to quantify the uncertainty of the system state and evaluate its impact on system performance. In the Markov chain framework, uncertainty can be described by the stationary distribution of the system. The stationary distribution represents the probability of the remaining energy storage capacity of the distributed energy storage, the remaining energy storage capacity of the small-capacity centralized energy storage, and the remaining energy storage capacity of the large-capacity centralized energy storage in the long-term operation .

[0031] Through the Markov chain model, the uncertainty of the active distribution network system with multiple energy storage modes is quantitatively analyzed. Specifically, we calculate the expected power demand and the variance of the power demand of the system to evaluate the uncertainty level of the system. The power demand fluctuation of the system is mainly concentrated in certain specific time periods, which is closely related to the state transition characteristics of multi-mode energy storage. For example, the state transition is more frequent during certain peak periods, resulting in a large power demand fluctuation of the system and a high uncertainty distribution.

[0032] As a preferred embodiment of the present invention, the safety evaluation indicators in the safety evaluation index system applicable to the active distribution network with distributed energy sources constructed in step S2 specifically include: active distribution network power balance, active distribution network power quantity balance, distributed power source consumption risk, distribution network voltage safety risk, and distribution network frequency safety risk.

[0033] As a preferred embodiment of the present invention, step S2 specifically includes: performing normalization and dimensionless processing on the basis of the traditional entropy weight method to avoid the problem of over-amplifying the weight gap when all entropy values approach 1 in the traditional entropy weight method, and using it to calculate the weights of each safety evaluation indicator. At the same time, the entropy value of each safety evaluation indicator is solved through the characteristic coefficient of the safety evaluation indicator, that is, the weight of the \(i\)-th safety evaluation indicator is expressed by the entropy value method, specifically as follows: Among them, represents the weight of the \(i\)-th safety evaluation indicator, represents the entropy value corresponding to the \(i\)-th safety evaluation indicator, represents the total number of safety evaluation indicators.

[0034] As a preferred embodiment of the present invention, step S2 specifically includes: calculating the comprehensive evaluation value of each energy storage mode through the weights of each safety evaluation indicator. For the weighting results of the safety evaluation indicators below or equal to the average level, the entropy value method is used to determine the weights, and the weights of the comprehensive evaluation values higher than the average level are set to 0 to obtain a weight matrix. The comprehensive evaluation value of the \(j\)-th energy storage mode is: Among them, where is the comprehensive evaluation value of the \(j\)-th energy storage mode, is the index entropy value of the \(j\)-th energy storage mode in the first evaluation, represents the total number of each energy storage mode; the comprehensive evaluation value of each energy storage mode specifically represents the frequency modulation capabilities of the generated distributed energy storage Fs, small-capacity centralized energy storage Xs, and large-capacity centralized energy storage Ds, and the first frequency modulation order is generated respectively according to the frequency modulation capabilities of each energy storage mode.

[0035] Exemplarily, through comprehensive evaluation, the frequency modulation capabilities of the generated distributed energy storage Fs, small-capacity centralized energy storage Xs, and large-capacity centralized energy storage Ds are obtained, that is, the comprehensive evaluation value SFs1 of distributed energy storage No. 1, the comprehensive evaluation value SFs2 of distributed energy storage No. 2,..., and the comprehensive evaluation value SFsn of distributed energy storage No. n; the comprehensive evaluation value SXs1 of small-capacity centralized energy storage No. 1, the comprehensive evaluation value SXs2 of small-capacity centralized energy storage No. 2,..., and the comprehensive evaluation value SXs of small-capacity centralized energy storage No. ; The first frequency modulation order of the comprehensive evaluation values SDs1 of large-capacity centralized energy storage No. 1, SDs2 of large-capacity centralized energy storage No. 2, ……, SDs of large-capacity centralized energy storage No. for the first frequency modulation.

[0036] As a preferred solution of the present invention, the specific process of step S3 is as follows: grading the energy storage frequency modulation willingness of user-side energy storage, distribution substation area-side energy storage, switch station energy storage, and commercial shared energy storage, and setting the energy storage frequency modulation willingness factor of user-side energy storage as , the energy storage frequency modulation willingness factor of the distribution substation area-side energy storage as , the energy storage frequency modulation willingness factor of the switch station energy storage as , the energy storage frequency modulation willingness factor of the commercial shared energy storage as , setting the grading as > = > , and integrating each user willingness factor into the frequency modulation strategy to generate the second frequency modulation order, and the second frequency modulation order is shown as Figure 3 shown.

[0037] Specifically, the energy storage frequency modulation willingness factor of the distribution substation area-side energy storage is , the energy storage frequency modulation willingness factor of the switch station energy storage is . Since the distribution substation area-side energy storage is generally installed in the energy storage system of the distribution substation area, which is used for dynamic capacity expansion, suppressing load fluctuations, and smoothing the output of new energy power generation in the substation area, improving the power quality of the substation area and the safety of the power grid, and is usually installed on the low-voltage side of the distribution substation area. The switch station energy storage is an energy storage system installed in the switch station, which is used to quickly restore power supply in case of power grid faults and reduce power outage time. The distribution substation area-side energy storage and the switch station energy storage are generally uniformly dispatched by the power grid operator to protect the stable operation of the power grid. The operators are the same. Different from the other two types of energy storage, the operation responsibility lies with the power grid operator. Therefore, and the energy storage frequency modulation willingness is equal.

[0038] Specifically, the energy storage frequency modulation willingness factor is obtained by normalizing the frequency modulation economic cost, and the range is (0, 1). Then the energy storage frequency modulation willingness factor of user-side energy storage is , the energy storage frequency modulation willingness factor of the distribution substation area-side energy storage is , the energy storage frequency modulation willingness factor of the switch station energy storage is , the energy storage frequency modulation willingness factor of the commercial shared energy storage is ; Among them, the frequency modulation economic cost = frequency modulation mileage cost × frequency modulation mileage + frequency modulation capacity cost × frequency modulation capacity.

[0039] As a preferred solution of the present invention, step S4 specifically includes: setting the frequency modulation mileage according to the remaining energy storage capacity, setting the frequency modulation rate, sorting the frequency modulation capabilities of each energy storage mode generated according to the frequency modulation mileage, and setting the frequency modulation excitation factor according to the sorting result, superimposing it with the second frequency modulation order, and then generating a third frequency modulation order.

[0040] For example, the initial frequency regulation order of the strategy that only considers the frequency regulation capability but not the frequency regulation willingness is prioritized, resulting in the third frequency regulation order. S is the total frequency regulation mileage of the energy storage power station over its entire life cycle; set the frequency regulation mileage = remaining energy storage capacity × frequency regulation rate × frequency regulation capability. Calculate according to this formula and sort from large to small, and the ones with large values ​​will participate first.

[0041] The frequency regulation incentive factors mainly adopt economic measures and policy measures to eliminate the negative participation willingness of energy storage users. However, some frequency regulation willingness will not change due to incentives, and the third frequency regulation is a comprehensive consideration of converting uncertainty into modeling of as certain capacity as possible, as well as considering the frequency regulation capabilities of the entire active distribution network system. Sort the frequency modulation mileage and set the frequency modulation incentive factor according to the frequency modulation mileage sorting ,in, Indicates the frequency modulation excitation factor with the first ranking result, and the meanings of the remaining frequency modulation excitation factors are inferred in the same way, and are superimposed on the second frequency modulation order to produce the third frequency modulation order. At the same time, because some energy storage modes will not change due to the frequency modulation excitation factor, the frequency modulation excitation factor needs to set the excitation limit, so the third frequency modulation order is as follows Figure 4 shown.

[0042] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. The protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A frequency self-healing method for an active distribution network considering multiple energy storage modes, characterized in that: The method comprises the following steps: Step S1: establishing a multi-mode energy storage model based on a Markov chain, respectively determining the remaining frequency modulation capacity of energy storage in various modes, and quantitatively analyzing the power output uncertainty of the multi-mode energy storage model; Step S2: construct a safety evaluation index system suitable for active distribution networks containing distributed energy, evaluate the frequency regulation capability of the multi-mode energy storage model, and generate the first frequency regulation order based on the evaluation results of its frequency regulation capability; Step S3: introduce the energy storage participation frequency regulation willingness strategy into the first frequency regulation order to generate the second frequency regulation order; Step S4: Introduce a frequency modulation excitation factor that takes frequency modulation mileage into consideration, sort the frequency modulation mileage, set the frequency modulation excitation factor based on the frequency modulation mileage sorting, and superimpose it with the second frequency modulation order to generate a third frequency modulation order.

2. A frequency self-healing method for an active distribution network considering multiple energy storage modes, characterized in that: Step S1: For the multi-mode energy storage system, the remaining energy storage capacity is represented by a stable distribution, and the stable distribution of the remaining energy storage capacity is obtained by solving the following equations: in, Indicates the remaining storage capacity of distributed energy storage The initial distribution of Indicates the remaining storage capacity of small-capacity centralized energy storage The initial distribution of Indicates the remaining storage capacity of large-capacity centralized energy storage The initial distribution of Indicates the remaining storage capacity of distributed energy storage The stationary distribution of Indicates the remaining storage capacity of small-capacity centralized energy storage The stationary distribution of Indicates the remaining storage capacity of large-capacity centralized energy storage The stationary distribution of Represents the state transfer matrix of the active distribution network.

3. A frequency self-healing method for an active distribution network considering multiple energy storage modes, characterized in that: The safety evaluation indicators in the safety evaluation indicator system suitable for the active distribution network containing distributed energy constructed in step S2 specifically include: active distribution network power balance, active distribution network electricity balance, distributed power supply absorption risk, distribution network voltage safety risk, and distribution network frequency safety risk.

4. A frequency self-healing method for an active distribution network considering multiple energy storage modes, characterized in that: The step S2 specifically includes: performing normalized dimensionless processing on the basis of the traditional entropy weight method, and using it to calculate the weight of each safety evaluation index, and at the same time, solving the entropy value of each safety evaluation index through the characteristic coefficient of the safety evaluation index, as follows: in, Indicates The weight of the safety evaluation index is Indicates The entropy value corresponding to the security evaluation index is Represents the total number of safety evaluation indicators.

5. A frequency self-healing method for an active distribution network considering multiple energy storage modes, characterized in that: The step S2 specifically includes: calculating the comprehensive evaluation value of each energy storage mode by the weight of each safety evaluation index, using the entropy method to determine the weight of the weighted results of the safety evaluation index that is lower than or equal to the average level, setting the weight of the comprehensive evaluation value that is higher than the average level to 0, and obtaining the weight matrix. The comprehensive evaluation value of each energy storage mode is: in, For the The comprehensive evaluation value of each energy storage mode is For the first evaluation The index entropy value of each energy storage mode, Represents the total number of each energy storage mode; the comprehensive evaluation value of each energy storage mode specifically represents the frequency regulation capability of the generated distributed energy storage Fs, small-capacity centralized energy storage Xs, and large-capacity centralized energy storage Ds, and generates the first frequency regulation order according to the frequency regulation capability of each energy storage mode.

6. A frequency self-healing method for an active distribution network considering multiple energy storage modes, characterized in that: The specific process of step S3 is as follows: the energy storage frequency regulation willingness of the user-side energy storage, the distribution station area-side energy storage, the switch station energy storage, and the commercial shared energy storage is graded, and the energy storage frequency regulation willingness factor of the user-side energy storage is set to , the energy storage frequency regulation willingness factor at the distribution station area side is , the switch station energy storage frequency regulation willingness factor is , the commercial shared energy storage frequency regulation willingness factor is , set the classification to > = > , and integrate each user's willingness factor into the frequency modulation strategy to generate the second frequency modulation order.

7. A frequency self-healing method for an active distribution network considering multiple energy storage modes, characterized in that: The step S4 specifically includes: setting the frequency modulation mileage according to the remaining energy storage capacity, setting the frequency modulation rate, sorting the frequency modulation capabilities of each energy storage mode according to the frequency modulation mileage, and setting the frequency modulation excitation factor according to the frequency modulation mileage sorting, superimposing it with the second frequency modulation order, and then generating a third frequency modulation order.

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