Power storage system selection method and apparatus, electronic device and storage medium

Abstract

Provided are a power storage system selection method and apparatus, an electronic device, and a storage medium. When selecting a suitable target power storage system for a target new energy power station, it is possible quantify the degree of adaptation of each candidate power storage system to the target new energy power station based on a spherical fuzzy analytic hierarchy process, a spherical fuzzy normalized aggregation method, and at least one evaluation criterion of each candidate power storage system, along with at least one assessment indicator corresponding to the evaluation criterion, thereby selecting the most suitable target power storage system for the target new energy power station from the candidate power storage systems.

Description

Selection methods, devices, electronic equipment and storage media for power energy storage systems

[0001] This application claims priority to Chinese Patent Application No. 202410862166.8, filed with the Chinese Patent Office on June 28, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of data processing technology, such as a method, apparatus, electronic device, and storage medium for selecting a power energy storage system. Background Technology

[0003] Energy storage systems are considered a promising solution to address the intermittency and uncertainty of new energy power generation, accelerate renewable energy production, and ensure the reliability of power supply. They have become a key factor in the sustainable development of new energy.

[0004] Each energy storage system has its unique advantages and disadvantages, making the selection of a suitable system a challenging task, as multiple dimensions and indicators influence the choice of optimal energy storage. In this regard, the evaluation of energy storage system performance is based on a range of factors, including but not limited to energy density, efficiency, economic feasibility, lifetime, and discharge time. Summary of the Invention

[0005] This application provides a method, apparatus, electronic device, and storage medium for selecting a power energy storage system, in order to solve the problem of difficulty in selecting a power energy storage system that is more suitable for new energy power plants.

[0006] According to one aspect of this application, a method for selecting an energy storage system is provided, the method comprising:

[0007] Identify at least one candidate power storage system for the target new energy power plant, at least one evaluation standard corresponding to the candidate power storage system, and at least one evaluation indicator corresponding to the evaluation standard;

[0008] Based on the pre-constructed first spherical fuzzy number, a second spherical fuzzy number is established. The first spherical fuzzy number is composed of each linguistic scale and the corresponding spherical fuzzy number. The spherical fuzzy number includes membership degree, non-membership degree and hesitation degree. The second spherical fuzzy number is the spherical fuzzy number of at least one evaluation index corresponding to the candidate power storage system.

[0009] An initial evaluation matrix is ​​established based on at least one candidate power storage system and the spherical fuzzy number of at least one evaluation index corresponding to the candidate power storage system;

[0010] Based on a pre-built priority function, the initial evaluation matrix is ​​subjected to inverse fuzzification to obtain the sharpness value calculation results corresponding to each evaluation index in the initial evaluation matrix. The initial evaluation matrix is ​​then adjusted based on the sharpness value calculation results to obtain the evaluation matrix.

[0011] The evaluation matrix is ​​normalized to obtain the normalized evaluation matrix;

[0012] Based on the normalized evaluation matrix, the evaluation values ​​corresponding to each candidate power storage system are determined.

[0013] The candidate energy storage system with the highest evaluation value is selected as the target energy storage system for the target new energy power plant.

[0014] According to another aspect of this application, a power storage system selection device is provided, the device comprising:

[0015] The data acquisition module is configured to determine at least one candidate power storage system for the target new energy power station, at least one evaluation standard corresponding to the candidate power storage system, and at least one evaluation indicator corresponding to the evaluation standard.

[0016] The fuzzy number determination module is set to establish a second spherical fuzzy number based on a pre-constructed first spherical fuzzy number. The first spherical fuzzy number is composed of each linguistic scale and the corresponding spherical fuzzy number. The spherical fuzzy number includes membership degree, non-membership degree and hesitation degree. The second spherical fuzzy number is the spherical fuzzy number of at least one evaluation index corresponding to the candidate power storage system.

[0017] The initial matrix determination module is configured to establish an initial evaluation matrix based on at least one candidate power storage system and the spherical fuzzy number of at least one evaluation index corresponding to the candidate power storage system.

[0018] The evaluation matrix determination module is configured to perform inverse fuzzification operation on the initial evaluation matrix based on a pre-built priority function, obtain the sharpness value calculation results corresponding to each evaluation index in the initial evaluation matrix, and adjust the initial evaluation matrix based on the sharpness value calculation results to obtain the evaluation matrix.

[0019] The normalization module is configured to normalize the evaluation matrix to obtain a normalized evaluation matrix.

[0020] The evaluation value determination module is set to determine the evaluation values ​​corresponding to each candidate power storage system based on the normalized evaluation matrix.

[0021] The target system determination module is set up to determine the candidate power storage system with the largest evaluation value, which will be used as the target power storage system for the target new energy power station.

[0022] According to another aspect of this application, an electronic device is provided, the electronic device comprising:

[0023] At least one processor; and

[0024] A memory that is communicatively connected to at least one processor; wherein,

[0025] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to execute the power storage system selection method of any embodiment of this application.

[0026] According to another aspect of this application, a computer-readable storage medium is provided, which stores computer instructions for causing a processor to execute and implement the power storage system selection method of any embodiment of this application.

[0027] The technical solution of this application embodiment determines at least one candidate power storage system for the target new energy power station, at least one evaluation standard corresponding to the candidate power storage system, and at least one evaluation index corresponding to the evaluation standard; based on a pre-constructed first spherical fuzzy number, at least one candidate power storage system, at least one evaluation standard corresponding to the candidate power storage system, and at least one evaluation index corresponding to the evaluation standard, the first spherical fuzzy number is composed of each linguistic scale and the spherical fuzzy number corresponding to each linguistic scale, and the spherical fuzzy number includes membership degree, non-membership degree, and hesitation degree; the second spherical fuzzy number is the spherical fuzzy number of the at least one evaluation index corresponding to the candidate power storage system, thereby clarifying the importance of each evaluation index corresponding to each candidate power storage system and the corresponding membership degree, non-membership degree, and hesitation degree; based on the second spherical fuzzy number, an initial... An evaluation matrix is ​​generated, and based on a pre-constructed priority function, an inverse fuzzification operation is performed on the initial evaluation matrix to obtain the clear values ​​of each evaluation index in the initial evaluation matrix. The initial evaluation matrix is ​​then adjusted based on the clear values ​​to obtain a clearer evaluation matrix. By normalizing the evaluation matrix, a normalized evaluation matrix is ​​obtained. Based on the normalized evaluation matrix, the evaluation values ​​corresponding to each candidate energy storage system are determined, thereby quantifying the suitability of each candidate energy storage system with the target new energy power station. Finally, the candidate energy storage system with the largest evaluation value is selected as the target energy storage system for the target new energy power station. This process selects the most suitable candidate energy storage system for the target new energy power station. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 is a flowchart of a power storage system selection method according to Embodiment 1 of this application;

[0030] Figure 2 is a schematic diagram of a power storage system selection device according to Embodiment 2 of this application;

[0031] Figure 3 is a schematic diagram of the structure of an electronic device that implements the power storage system selection method of the present application embodiment. Detailed Implementation

[0032] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0033] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0034] Example 1

[0035] Figure 1 is a flowchart of a power storage system selection method provided in Embodiment 1 of this application. This embodiment is applicable to situations where it is difficult to determine a more suitable power storage system for a new energy power station when selecting a power storage system. This method can be executed by a power storage system selection device, which can be implemented in hardware and / or software and can be configured in an electronic device with data processing capabilities. As shown in Figure 1, the method includes:

[0036] S110. Determine at least one candidate power storage system for the target new energy power plant, at least one evaluation standard corresponding to the candidate power storage system, and at least one evaluation indicator corresponding to the evaluation standard.

[0037] The target renewable energy power plant can be a power plant that requires the selection of a power storage system, and which utilizes renewable energy for electricity production. Renewable energy power plants can be solar power plants, wind power plants, hydropower plants, and biomass power plants, etc. Power storage systems store electrical energy when there is a surplus and output electrical energy when there is a shortage, playing a role in balancing power supply and demand and improving the stability and reliability of the power system. Candidate power storage systems can be of various types, including thermal energy storage, chemical energy storage, mechanical energy storage, electrical energy storage, and electrochemical energy storage systems; this application does not limit their application. Evaluation criteria can be the perspectives used to evaluate power storage systems, including economic standards, technical standards, and environmental standards. Evaluation indicators can be specific measures of the evaluation criteria, including but not limited to energy efficiency, energy density, storage capacity, operation and maintenance costs, and investment costs.

[0038] Select at least one candidate energy storage system suitable for the target new energy power plant from various types of energy storage systems, such as thermal energy storage, chemical energy storage, mechanical energy storage, electrical energy storage, and electrochemical energy storage systems. Examples include hydrogen energy storage systems, pumped hydro storage systems, supercapacitor energy storage systems, and lithium-ion battery energy storage systems.

[0039] By reviewing relevant literature on the target new energy power plant and the work experience of the staff, at least one evaluation standard and corresponding evaluation indicators for each standard can be selected.

[0040] For example, the evaluation criteria can be based on four standards: technical standards (D1), economic standards (D2), environmental standards (D3), and other standards (D4) to select a power storage system for the target new energy power plant. Furthermore, at least one evaluation indicator corresponding to each of the four evaluation standards is determined. For example, the technical standards (D1) correspond to energy efficiency (D11), energy density (D12), technology maturity (D13), and energy storage capacity (D14); the economic standards (D2) correspond to investment cost (D21), operation and maintenance cost (D22), and the life cycle (D23) of the selected power storage system; the environmental standards (D3) correspond to carbon emission reduction (D31) and coal consumption savings (D32); and the other standards (D4) correspond to other 1 (D41) and other 2 (D42).

[0041] For example, a selection table for energy storage systems can be generated based on the identified candidate energy storage systems, as follows:

[0042] Table 1 Energy Storage System Selection Table

[0043] S120. Based on the pre-constructed first spherical fuzzy number, at least one candidate power energy storage system, at least one evaluation standard corresponding to the candidate power energy storage system, and at least one evaluation index corresponding to the evaluation standard, establish a second spherical fuzzy number. The first spherical fuzzy number is composed of each linguistic scale and the spherical fuzzy number corresponding to each linguistic scale. The spherical fuzzy number includes membership degree, non-membership degree, and hesitation degree. The second spherical fuzzy number is the spherical fuzzy number of at least one evaluation index corresponding to the candidate power energy storage system.

[0044] After obtaining at least one evaluation criterion and at least one evaluation index corresponding to the candidate energy storage system, a second spherical fuzzy number can be obtained by using a pre-constructed first spherical fuzzy number to determine the at least one evaluation criterion and at least one evaluation index corresponding to the candidate energy storage system.

[0045] For example, Table 2 is a table corresponding to the pre-constructed first spherical fuzzy number:

[0046] Table 2 First Spherical Fuzzy Number

[0047] After determining the evaluation criteria, including technical criteria (D1), economic criteria (D2), environmental criteria (D3), and other criteria (D4), and selecting a power storage system for the target new energy power plant, and considering the following: technical criteria (D1) corresponding to energy efficiency (D11), energy density (D12), technology maturity (D13), and energy storage capacity (D14); economic criteria (D2) corresponding to investment cost (D21), operation and maintenance cost (D22), and the life cycle (D23) of the selected power storage system; environmental criteria (D3) corresponding to carbon emission reduction (D31) and coal consumption saving (D32); and other criteria (D4) corresponding to other 1 (D41) and other 2 (D42), the above data can be generated into a second spherical fuzzy number according to Table 2, as shown in Table 3:

[0048] Table 3 Second Spherical Fuzzy Number

[0049] S130. Based on the second spherical fuzzy number, establish the initial evaluation matrix.

[0050] The initial evaluation matrix consists of various evaluation indicators.

[0051] After obtaining the second spherical fuzzy number, the elements of the second spherical fuzzy number are used as elements of the initial evaluation matrix to generate the evaluation index matrix, as shown in the following formula:

[0052] In the formula, y ij Let represent the j-th evaluation index corresponding to the i-th candidate energy storage system. Where i = 1, 2, 3, ..., m; m is the number of candidate energy storage systems. j = 1, 2, 3, ..., n; n is the number of evaluation indexes.

[0053] By constructing the initial evaluation matrix using the second spherical fuzzy number, the second spherical fuzzy number can be transformed into a mathematically calculable matrix while ensuring data integrity.

[0054] For example, after obtaining Table 3, an initial evaluation matrix can be generated based on Table 3, as shown below:

[0055] In the formula, y ij This represents the j-th evaluation index corresponding to the i-th candidate power storage system.

[0056] S140. Based on the pre-constructed priority function, perform inverse fuzzification operation on the initial evaluation matrix to obtain the sharpness value calculation results corresponding to each evaluation index in the initial evaluation matrix, and adjust the initial evaluation matrix based on the sharpness value calculation results to obtain the evaluation matrix.

[0057] The expression for the precedence function is: x ij =u ij *(1-v ij )*(1-π ij );

[0058] In the formula, x ij u represents the weight of the j-th evaluation index corresponding to the i-th candidate energy storage system; ij v represents the membership degree of the j-th evaluation index corresponding to the i-th candidate energy storage system in the second spherical fuzzy number; ij π represents the non-membership degree of the j-th evaluation index corresponding to the i-th candidate energy storage system in the second spherical fuzzy number; ij It represents the degree of hesitation of the j-th evaluation index corresponding to the i-th candidate power storage system in the second spherical fuzzy number.

[0059] Since the initial evaluation matrix is ​​calculated using the second spherical fuzzy number, it needs to be clarified. This is done by using a pre-built priority function to perform inverse fuzzification on the initial evaluation matrix, calculate the clarification values ​​of each evaluation index in the initial evaluation matrix, and thus obtain the evaluation matrix.

[0060] S150. Normalize the evaluation matrix to obtain the normalized evaluation matrix.

[0061] The calculated values ​​of each evaluation indicator in the evaluation matrix are processed and normalized to generate a normalized evaluation matrix.

[0062] In one alternative approach, normalizing the evaluation matrix to obtain a normalized evaluation matrix may include steps A1-A2:

[0063] Step A1: Integrate the linear sum normalization formula, the linear ratio normalization formula, and the linear minimum-maximum normalization formula to obtain the target normalization formula.

[0064] Step A2: Based on the target normalization formula, normalize the evaluation matrix to obtain the normalized evaluation matrix.

[0065] The linear and normalized formulas are shown below:

[0066] The formula for normalizing the linear ratio is shown below:

[0067] The linear minimum-maximum normalization formula is shown below:

[0068] To reduce the bias caused by a single normalization technique, the linear sum normalization formula, the linear ratio normalization formula, and the linear minimum-maximum normalization formula are integrated to obtain the target normalization formula, as shown in the following equation:

[0069] To ensure the generality of the result, we can set λ = 0.5 and z = 0.5 in the formula.

[0070] S160. Based on the normalized evaluation matrix, determine the evaluation values ​​corresponding to each candidate power storage system.

[0071] After obtaining the normalized evaluation matrix, the evaluation indicators of each candidate energy storage system can be summarized based on the normalized evaluation matrix to obtain the evaluation values ​​corresponding to each candidate energy storage system.

[0072] Based on the normalized evaluation matrix, the evaluation values ​​corresponding to each candidate power storage system are determined, thereby quantifying the compatibility of each candidate power storage system with the target new energy power station.

[0073] In one alternative approach, determining the evaluation values ​​for each candidate energy storage system based on a normalized evaluation matrix may include steps B1-B3:

[0074] Step B1: Based on the first spherical fuzzy number, determine the third spherical fuzzy number. The third spherical fuzzy number is the spherical fuzzy number of at least one evaluation standard and at least one evaluation index corresponding to the evaluation standard.

[0075] Step B2: Determine the global weights of the candidate comparison matrix based on the third spherical fuzzy number.

[0076] Step B3: Based on the global weights corresponding to the candidate comparison matrix and the corresponding normalized evaluation matrix, determine the evaluation values ​​corresponding to the candidate power storage system.

[0077] Based on the first spherical fuzzy number, determine the spherical fuzzy number of each evaluation standard and the evaluation index corresponding to each evaluation standard, which is also the third spherical fuzzy number.

[0078] Based on the third spherical fuzzy number, the weights of each evaluation index are calculated, where the sum of the weights of each evaluation index is also 1. Based on the weights of each evaluation index and the weights of each evaluation standard, the global weights of the candidate comparison matrix are determined, as shown in the following formula:

[0079] w i*j This represents the weight of the j-th evaluation index in the i-th candidate power storage system.

[0080] Finally, the evaluation values ​​of the candidate power storage systems are determined based on the global weights corresponding to the candidate comparison matrices and the corresponding normalized evaluation matrices.

[0081] Based on the weights of the evaluation indicators corresponding to each evaluation standard, the evaluation value for each candidate energy storage system is calculated using the following formula:

[0082] in, Y represents ij y in ij , Represent each y ij The average value.

[0083] To make the results more general, we can choose v = 0.5 and δ = 0.5.

[0084] Finally, S is expressed by the following formula. 1i With S 2i By integrating the data, we obtain the evaluation values ​​corresponding to the candidate energy storage systems:

[0085] Among them, S i This represents the evaluation value corresponding to the i-th candidate energy storage system.

[0086] In one alternative approach, determining the global weights corresponding to each candidate comparison matrix based on the third spherical fuzzy number may include steps C1-C4:

[0087] Step C1: Based on the third spherical fuzzy number, determine the candidate comparison matrix. The candidate comparison matrix consists of at least one evaluation criterion in the third spherical fuzzy number and at least one evaluation index corresponding to the evaluation criterion.

[0088] Step C2: Perform inverse fuzzification on the candidate comparison matrix to obtain the candidate score matrix corresponding to the candidate comparison matrix.

[0089] Step C3: Based on the candidate score matrix, obtain the local weights, which are the weights of each evaluation indicator corresponding to an evaluation criterion.

[0090] Step C4: Based on the local weights, determine the global weights corresponding to the candidate comparison matrix. The global weights are the weights of each evaluation indicator corresponding to each evaluation criterion.

[0091] Based on the third spherical fuzzy number, a candidate comparison matrix containing various evaluation criteria and indicators is generated, as shown in the following formula:

[0092] The local weights are obtained by performing a fuzzification operation on the candidate comparison matrix based on the priority function, as shown in the following formula:

[0093] w i*j This represents the weight of the j-th evaluation index in the i-th candidate power storage system.

[0094] Based on local weights, the weights of each evaluation indicator corresponding to each evaluation standard can be determined.

[0095] For example, the third spherical fuzzy number is determined based on the first spherical fuzzy number, as shown in Table 4 below:

[0096] Table 4. Third Spherical Fuzzy Number

[0097] The candidate comparison matrix using Table 4 is constructed as shown in the following formula:

[0098] By performing a fuzzy operation on the candidate comparison matrix using a priority function, the evaluation criteria and the local weights of the corresponding evaluation indicators are obtained, as shown in the following formula:

[0099] Finally, by using local weights, the overall weights of the evaluation criteria and corresponding evaluation indicators are calculated to obtain the global weights, as shown in Table 5 below:

[0100] Table 5 Overall Weights

[0101] Among them, the sum of the local weights of D11, D12, D13 and D14 is 1; the sum of the local weights of D21, D22 and D23 is 1; the sum of the local weights of D31 and D32 is 1; the sum of the local weights of D41 and D42 is 1; and the sum of the global weights of D11, D12, D13, D14, D21, D22, D23, D31, D32, D41 and D42 is 1.

[0102] S170. Identify the candidate energy storage system with the largest evaluation value as the target energy storage system for the target new energy power station.

[0103] Since the magnitude of the evaluation data indicates whether the energy storage power system is more suitable for the target new energy power station, the candidate energy storage systems are ranked according to their evaluation data. The candidate energy storage system with the highest ranking, i.e. the largest evaluation value, is selected as the target energy storage system for the target new energy power station.

[0104] According to the technical solution of this application embodiment, by determining at least one candidate power storage system for the target new energy power station, at least one evaluation standard corresponding to the candidate power storage system, and at least one evaluation index corresponding to the evaluation standard; based on a pre-constructed first spherical fuzzy number, at least one candidate power storage system, at least one evaluation standard corresponding to the candidate power storage system, and at least one evaluation index corresponding to the evaluation standard, the first spherical fuzzy number is composed of each linguistic scale and the spherical fuzzy number corresponding to each linguistic scale, and the spherical fuzzy number includes membership degree, non-membership degree, and hesitation degree; the second spherical fuzzy number is the spherical fuzzy number of at least one evaluation index corresponding to the candidate power storage system, thereby clarifying the importance of each evaluation index corresponding to each candidate power storage system and the corresponding membership degree, non-membership degree, and hesitation degree; based on the second spherical fuzzy number, an initial... An initial evaluation matrix is ​​generated, and based on a pre-constructed priority function, an inverse fuzzification operation is performed on the initial evaluation matrix to obtain the clear values ​​of each evaluation index in the initial evaluation matrix. The initial evaluation matrix is ​​then adjusted based on the clear values ​​to obtain a clearer evaluation matrix. By normalizing the evaluation matrix, a normalized evaluation matrix is ​​obtained. Based on the normalized evaluation matrix, the evaluation values ​​corresponding to each candidate power storage system are determined, thereby quantifying the compatibility between each candidate power storage system and the target new energy power station. Finally, the candidate power storage system with the largest evaluation value is selected as the target power storage system for the target new energy power station. This process selects the most suitable candidate power storage system for the target new energy power station.

[0105] Example 2

[0106] Figure 2 is a structural block diagram of a power storage system selection device provided in an embodiment of this application. This embodiment is applicable to situations where it is difficult to determine a more suitable power storage system for a new energy power station when selecting a power storage system. The power storage system selection device can be implemented in hardware and / or software, and can be configured in an electronic device with data processing capabilities. As shown in Figure 2, the power storage system selection device of this embodiment may include: a data acquisition module 210, a fuzzy number determination module 220, an initial matrix determination module 230, an evaluation matrix determination module 240, a normalization processing module 250, an evaluation value determination module 260, and a target system determination module 270. Wherein:

[0107] The data acquisition module 210 is used to determine at least one candidate power storage system of the target new energy power station, at least one evaluation standard corresponding to the candidate power storage system, and at least one evaluation indicator corresponding to the evaluation standard.

[0108] The fuzzy number determination module 220 is used to establish a second spherical fuzzy number based on a pre-constructed first spherical fuzzy number, at least one candidate power energy storage system, at least one evaluation standard corresponding to the candidate power energy storage system, and at least one evaluation index corresponding to the evaluation standard. The first spherical fuzzy number is composed of each linguistic scale and the spherical fuzzy number corresponding to each linguistic scale. The spherical fuzzy number includes membership degree, non-membership degree, and hesitation degree. The second spherical fuzzy number is the spherical fuzzy number of at least one evaluation index corresponding to the candidate power energy storage system.

[0109] The initial matrix determination module 230 is used to establish an initial evaluation matrix based on the second spherical fuzzy number;

[0110] The evaluation matrix determination module 240 is used to perform inverse fuzzification operation on the initial evaluation matrix based on a pre-built priority function to obtain the sharpness value calculation results corresponding to each evaluation index in the initial evaluation matrix, and adjust the initial evaluation matrix based on the sharpness value calculation results to obtain the evaluation matrix.

[0111] The normalization processing module 250 is used to normalize the evaluation matrix to obtain a normalized evaluation matrix;

[0112] The evaluation value determination module 260 is used to determine the evaluation values ​​corresponding to each candidate power storage system based on the normalized evaluation matrix.

[0113] The target system determination module 270 is used to determine the candidate power storage system with the largest evaluation value, which will be used as the target power storage system for the target new energy power station.

[0114] Based on the above embodiments, optionally, the normalization processing module 250 includes:

[0115] By integrating the linear and normalization formulas, the linear ratio normalization formula, and the linear minimum-maximum normalization formula, we obtain the target normalization formula.

[0116] Based on the target normalization formula, the evaluation matrix is ​​normalized to obtain the normalized evaluation matrix.

[0117] Based on the above embodiments, optionally, the evaluation value determination module 360 ​​includes:

[0118] Based on the first spherical fuzzy number, a third spherical fuzzy number is determined. The third spherical fuzzy number is the spherical fuzzy number of at least one evaluation standard and at least one evaluation index corresponding to the evaluation standard.

[0119] Based on the third spherical fuzzy number, the global weights corresponding to each candidate comparison matrix are determined.

[0120] Based on the global weights corresponding to each candidate comparison matrix and the corresponding normalized evaluation matrix, the evaluation values ​​corresponding to each candidate power storage system are determined.

[0121] Based on the above embodiments, optionally, the global weights corresponding to each candidate comparison matrix are determined based on the third spherical fuzzy number, including:

[0122] Based on the third spherical fuzzy number, a candidate comparison matrix is ​​determined. The candidate comparison matrix consists of at least one evaluation criterion in the third spherical fuzzy number and at least one evaluation index corresponding to the evaluation criterion.

[0123] Perform inverse fuzzification on the candidate comparison matrix to obtain the candidate score matrix corresponding to the candidate comparison matrix;

[0124] Based on the candidate score matrix, local weights are obtained, which are the weights of each evaluation indicator corresponding to an evaluation criterion.

[0125] Based on local weights, the global weights corresponding to the candidate comparison matrix are determined. The global weights are the weights of each evaluation indicator corresponding to each evaluation criterion.

[0126] The power storage system selection device provided in this application embodiment can execute the power storage system selection method provided in any embodiment of this application, and has the corresponding functional modules and effects of the execution method.

[0127] Example 3

[0128] Figure 3 illustrates a schematic diagram of the structure of an electronic device 10 that can be used to implement embodiments of this application. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the application described and / or claimed herein.

[0129] As shown in Figure 3, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer programs stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0130] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0131] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the method for selecting an energy storage system.

[0132] In some embodiments, the power storage system selection method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the power storage system selection method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the power storage system selection method by any other suitable means (e.g., by means of firmware).

[0133] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0134] Computer programs used to implement the methods of this application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0135] In the context of this application, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0136] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0137] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0138] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0139] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this application can be achieved, and this is not limited herein.

Claims

1. A method for selecting an energy storage system, comprising: Identify at least one candidate power storage system for the target new energy power plant, at least one evaluation standard corresponding to the candidate power storage system, and at least one evaluation indicator corresponding to the evaluation standard; Based on a pre-constructed first spherical fuzzy number, at least one candidate energy storage system, at least one evaluation standard corresponding to the candidate energy storage system, and at least one evaluation index corresponding to the evaluation standard, a second spherical fuzzy number is established. The first spherical fuzzy number is composed of each linguistic scale and the spherical fuzzy number corresponding to each linguistic scale. The spherical fuzzy number includes membership degree, non-membership degree, and hesitation degree. The second spherical fuzzy number is the spherical fuzzy number of at least one evaluation index corresponding to the candidate energy storage system. Based on the second spherical fuzzy number, establish the initial evaluation matrix; Based on a pre-constructed priority function, the initial evaluation matrix is ​​subjected to inverse fuzzification to obtain the sharpness value calculation results corresponding to each evaluation index in the initial evaluation matrix. The initial evaluation matrix is ​​then adjusted based on the sharpness value calculation results to obtain the evaluation matrix. The evaluation matrix is ​​normalized to obtain a normalized evaluation matrix; Based on the normalized evaluation matrix, the evaluation values ​​corresponding to each candidate power storage system are determined; The candidate energy storage system with the largest evaluation value is selected as the target energy storage system for the target new energy power station.

2. The method according to claim 1, wherein, The evaluation matrix is ​​normalized to obtain a normalized evaluation matrix, including: By integrating the linear and normalization formulas, the linear ratio normalization formula, and the linear minimum-maximum normalization formula, we obtain the target normalization formula. Based on the target normalization formula, the evaluation matrix is ​​normalized to obtain the normalized evaluation matrix.

3. The method according to claim 1, wherein, Based on the normalized evaluation matrix, the evaluation values ​​corresponding to each candidate energy storage system are determined, including: Based on the first spherical fuzzy number, a third spherical fuzzy number is determined, wherein the third spherical fuzzy number is the spherical fuzzy number of at least one evaluation standard and at least one evaluation index corresponding to the evaluation standard; Based on the third spherical fuzzy number, the global weights corresponding to each candidate comparison matrix are determined; Based on the global weights corresponding to each candidate comparison matrix and the corresponding normalized evaluation matrix, the evaluation values ​​corresponding to each candidate power storage system are determined.

4. The method according to claim 3, wherein, Based on the third spherical fuzzy number, the global weights corresponding to each candidate comparison matrix are determined, including: Based on the third spherical fuzzy number, a candidate comparison matrix is ​​determined. The candidate comparison matrix is ​​composed of at least one evaluation criterion in the third spherical fuzzy number and at least one evaluation index corresponding to the evaluation criterion. Perform inverse fuzzification on the candidate comparison matrix to obtain the candidate score matrix corresponding to the candidate comparison matrix; Based on the candidate score matrix, local weights are obtained, where each local weight is the weight of an evaluation indicator corresponding to an evaluation criterion. Based on the local weights, the global weights corresponding to the candidate comparison matrix are determined, where the global weights are the weights of each evaluation index corresponding to each evaluation criterion.

5. The method according to claim 4, wherein, The expression for the candidate comparison matrix is: in, Candidate energy storage system A i The membership degree of the j-th evaluation index in the second spherical fuzzy number; Candidate energy storage system A i The non-membership degree of the j-th evaluation index in the second spherical fuzzy number; Candidate energy storage system A i The degree of hesitation of the j-th evaluation index in the second spherical fuzzy number; A ij This represents the j-th evaluation index in the j-th candidate energy storage system; Accordingly, the expression for the local weights corresponding to the candidate comparison matrix is: among them, x ij =u ij *(1-v ij )*(1-π ij ); x ij u represents the weight of the j-th evaluation index corresponding to the i-th candidate energy storage system; ij v represents the membership degree of the j-th evaluation index corresponding to the i-th candidate energy storage system in the second spherical fuzzy number; ij π represents the non-membership degree of the j-th evaluation index corresponding to the i-th candidate energy storage system in the second spherical fuzzy number; ij It represents the degree of hesitation of the j-th evaluation index corresponding to the i-th candidate power storage system in the second spherical fuzzy number.

6. The method according to claim 5, wherein, The expression for the initial evaluation matrix is: In the formula, y ij This represents the j-th evaluation index corresponding to the i-th candidate power storage system.

7. The method according to claim 2, wherein, The expression for the target normalization formula is: in, In the formula, Represents the linear and normalization formulas; This represents the formula for normalizing linear ratios; This represents the linear minimum-maximum normalization formula; This represents the objective normalization formula; y ij This represents the j-th evaluation index corresponding to the i-th candidate power storage system.

8. A power storage system selection device, comprising: The data acquisition module is configured to determine at least one candidate power storage system for the target new energy power station, at least one evaluation standard corresponding to the candidate power storage system, and at least one evaluation indicator corresponding to the evaluation standard. The fuzzy number determination module is configured to establish a second spherical fuzzy number based on a pre-constructed first spherical fuzzy number, at least one candidate power storage system, at least one evaluation standard corresponding to the candidate power storage system, and at least one evaluation index corresponding to the evaluation standard. The first spherical fuzzy number is composed of each linguistic scale and the spherical fuzzy number corresponding to each linguistic scale. The spherical fuzzy number includes membership degree, non-membership degree, and hesitation degree. The second spherical fuzzy number is the spherical fuzzy number of at least one evaluation index corresponding to the candidate power storage system. The initial matrix determination module is configured to establish an initial evaluation matrix based on the second spherical fuzzy number; The evaluation matrix determination module is configured to perform inverse fuzzification operation on the initial evaluation matrix based on a pre-built priority function to obtain the sharpness value calculation results corresponding to each evaluation index in the initial evaluation matrix, and adjust the initial evaluation matrix based on the sharpness value calculation results to obtain the evaluation matrix; The normalization processing module is configured to normalize the evaluation matrix to obtain a normalized evaluation matrix; The evaluation value determination module is configured to determine the evaluation value corresponding to each candidate power storage system based on the normalized evaluation matrix. The target system determination module is configured to determine the candidate power storage system with the largest evaluation value as the target power storage system of the target new energy power station.

9. An electronic device, comprising: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the power storage system selection method according to any one of claims 1-7.

10. A computer-readable storage medium storing computer instructions that, when executed by a processor, implement the power storage system selection method according to any one of claims 1-7.

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