Diversified energy storage power station network-related technical requirement evaluation method

Abstract

The invention belongs to the technical field of diversified energy storage power stations in a power system, particularly relates to a network-related technical requirement evaluation method for the diversified energy storage power stations, and more particularly belongs to the field of auxiliary service, dispatching management and energy storage technology application of the power system. The method comprises the following steps: establishing an evaluation index of energy storage network-related characteristics; standardizing the evaluation index score by adopting a hybrid standardization method; based on an analytic hierarchy process, calculating the relative weight of each standardized evaluation index through matrix normalization; calculating a comprehensive score of each energy storage power station according to the calculated relative weight and the scoring results of each energy storage power station under different indexes; and sorting according to the comprehensive score of each energy storage power station so as to evaluate the network-related performance. The method can effectively evaluate the effects of different energy storage power stations in the power grid, improves the grid-related performance through an optimization strategy, becomes an important technical means for stable operation of a power system, and has important practical significance and application value.

Description

Technical Field

[0001] The present invention belongs to the technical field of diversified energy storage power stations in power systems, and in particular to a method for evaluating network-related technical requirements of diversified energy storage power stations. More specifically, it belongs to the field of power system auxiliary services, dispatching management and energy storage technology applications. Background Art

[0002] With the acceleration of the global energy transition, the proportion of renewable energy sources, such as wind and solar power, in the power grid is gradually increasing. While renewable energy is environmentally friendly, its power output is significantly intermittent and volatile, posing new challenges to power system stability. To maintain grid supply and demand balance and frequency stability, energy storage power stations, as a flexible regulatory tool, are playing an increasingly important role in smoothing fluctuations in renewable energy generation, shifting peak loads, and providing frequency regulation services. Energy storage power stations are equipment systems that store, convert, and release cyclical electrical energy using electrochemical cells or electromagnetic energy storage media. Existing energy storage power station technologies include pumped hydro, thermal storage, and electrochemical energy storage. The grid-connected capabilities of different energy storage technologies vary significantly, and there are currently no unified specifications and standards for the technical requirements of various energy storage power stations. This leads to unclear roles and functions of energy storage power stations in actual grid ancillary services, such as peak shaving and frequency regulation. Furthermore, the responsiveness and economic benefits of energy storage power stations are difficult to accurately quantify. The inconsistent technical requirements of different types of energy storage power stations make cross-station comparative analysis difficult, and the grid lacks effective evaluation methods for the dispatch and control of energy storage power stations.

[0003] Existing research focuses on testing and evaluating the grid-related technical requirements of single energy storage power stations, for example:

[0004] 1. "Research on the Grid-Connected Index System for Electrochemical Energy Storage Power Stations" - In view of the fact that the normative evaluation index system for the active support and economic operation of electrochemical energy storage power stations in the power grid is still imperfect, resulting in safety risks, functional impairments, and poor economic efficiency of electrochemical energy storage power stations, this paper constructs a grid-connected index system for electrochemical energy storage power stations, determines the remote sensing feature quantities and feature weights of electrochemical energy storage power stations, and effectively guides the standardized planning, design, and grid-connected operation of electrochemical energy storage power stations.

[0005] 2. "Analysis of Grid-Related Performance of the Excitation System of the Shahe Pumped Storage Unit" This article collects relevant data on the model characteristics and dynamic characteristics of the generator and excitation system through grid-related tests on the excitation system of the Shahe Power Station. Through calculation and simulation verification, the grid-related performance is analyzed and calculated.

[0006] 3. "Datang Hubei Company Completes Hubei Province's First Full-Capacity Energy Storage Grid-Connected Test." This article overcame technical challenges encountered in ten grid-connected acceptance tests, including power quality, response time, and primary frequency regulation, optimizing system configuration and improving performance parameters. The energy storage power station conducted grid-connected testing. Seizing this new full-capacity grid-connected performance test as an opportunity, the power station focused on the safe, stable, and economical operation of the energy storage station, strengthened equipment operation, maintenance, and monitoring, and actively conducted equipment hazard inspections and remediation efforts to reduce defects and improve performance. The station also focused on and standardized lean management of the energy storage station and actively participated in a number of auxiliary services, including peak and frequency regulation, dynamic response to active and reactive power, and emergency backup power, to ensure energy supply.

[0007] In summary, at present, there are many studies on evaluation methods for single energy storage power stations, but there is a lack of unified standards for the grid-related technical requirements of diversified energy storage power stations. This is specifically reflected in the following aspects:

[0008] Inconsistent performance evaluation standards: Different types of energy storage power stations have different technical requirements and performance indicators, making it difficult to effectively compare and analyze them in actual scheduling.

[0009] Lack of quantitative evaluation tools: Due to the lack of scientific evaluation methods, grid dispatchers find it difficult to quantify the specific contribution of energy storage power stations in ancillary services, thus limiting their application in grid dispatching.

[0010] The current non-standardized grid-related technical requirements for diverse energy storage systems result in a broad-based role in grid control, making it difficult to quantify the cost and value of ancillary services, and hindering standardized improvements to the grid-related performance of diverse energy storage power plants. Therefore, there is an urgent need to develop an evaluation method for the grid-related technical requirements of diverse energy storage power plants. Summary of the Invention

[0011] To address the shortcomings of the aforementioned prior art, the present invention provides a method for evaluating the grid-related technical requirements of diverse energy storage power stations. Its purpose is to effectively assess the role of different energy storage power stations in the grid and, through optimization strategies, improve their grid-related performance.

[0012] The technical solution adopted by the present invention to achieve the above-mentioned purpose is:

[0013] A method for evaluating grid-related technical requirements for diversified energy storage power stations, including:

[0014] Establish evaluation indicators for grid-related characteristics of energy storage;

[0015] The mixed standardization method is used to standardize the evaluation index scores;

[0016] Based on the analytic hierarchy process, the relative weights of each standardized evaluation index are calculated through matrix normalization;

[0017] Calculate the comprehensive score of each energy storage station based on the calculated relative weights and the scoring results of each energy storage station under different indicators;

[0018] The energy storage power stations are ranked according to their comprehensive scores to evaluate their grid-connected performance.

[0019] Furthermore, the evaluation index for establishing the grid-related characteristics of energy storage includes:

[0020] Selection of evaluation indicators;

[0021] Collect data related to the grid-related characteristic evaluation indicators of diversified energy storage power stations, and obtain dynamic response capabilities based on the recorded data of the power stations.

[0022] Furthermore, the evaluation indicators are selected from: dynamic response capability indicators, grid support capability indicators, power quality indicators, energy efficiency indicators, and stability indicators; dynamic response capability indicators include energy storage power station response time and power regulation range, grid support capability indicators include frequency response capability and voltage support capability; power quality indicators include power factor control capability and grid connection quality assessment; energy efficiency indicators include capacity utilization and charge and discharge efficiency; stability indicators include fault ride-through capability and black start capability;

[0023] Furthermore, the data related to the grid-related characteristic evaluation indicators of the diversified energy storage power stations are collected, and the dynamic response capability is obtained based on the recorded data of the power stations; among them, the power quality indicators, voltage support capability indicators, and stability indicators are obtained through actual data analysis and evaluation, and the dynamic response capability indicators and energy efficiency indicators are obtained through calculation.

[0024] Furthermore, the dynamic response capability index is calculated as follows:

[0025] T r =T 0.9P -T st (1)

[0026] In the above formula: T r is the response time; T 0.9P T is the moment when the energy storage power station power responds to 90% of the power instruction; st The moment when the energy storage power station starts power response;

[0027] Power adjustment range P range The calculation formula is as follows:

[0028] P range =P max -P min (2)

[0029] In the above formula: P max is the maximum power of the energy storage station; P minis the minimum power of the energy storage station. According to power supply conventions, the power is positive when the energy storage is discharging and negative when it is charging.

[0030] The energy efficiency index is calculated as follows:

[0031] The calculation formula of efficiency η is as follows:

[0032]

[0033] In the above formula: η is efficiency; E rd E is the amount of electricity discharged during the energy storage station; rc The amount of electricity used in the charging process of the energy storage power station;

[0034] Energy storage capacity utilization rate C u The calculation formula is as follows:

[0035]

[0036] In the above formula: E used is the energy storage capacity that has been used; E total is the total capacity of the energy storage system.

[0037] Furthermore, the evaluation index scores are standardized using a hybrid standardization method, wherein:

[0038] Minimum and maximum normalization, the calculation formula is:

[0039]

[0040] In the above formula: x′ is the normalized value, x is the original value; x min is the minimum value of the indicator; x max is the maximum value of this indicator.

[0041] Furthermore, the relative weights of the standardized evaluation indicators are calculated by matrix normalization based on the hierarchical analysis method, wherein the score normalization is calculated as follows:

[0042]

[0043] In the above formula: Q1 is the first quarterback number; Q3 is the third quarterback number;

[0044] To quantify and score the performance of diversified energy storage power stations on various indicators, the calculation steps of the hierarchical analysis method are as follows:

[0045] Decompose the evaluation of grid-related technical requirements for diversified energy storage power stations into a hierarchical structure, including the target layer, the criteria layer, and the alternative solution layer;

[0046] For the indicators in the criterion layer, a judgment matrix is ​​constructed to measure the importance of each indicator;

[0047] After the judgment matrix is ​​constructed, the weight vector is calculated using the geometric mean method;

[0048] Perform consistency check.

[0049] Furthermore, the evaluation of the grid-related technical requirements for diversified energy storage power stations is broken down into a hierarchical structure, including:

[0050] Target layer: to quantify the dynamic response of the energy storage power station;

[0051] Criteria layer: dynamic response support capability, grid support capability, power quality indicators, energy efficiency indicators and stability indicators;

[0052] Alternative solution layer: including electrochemical energy storage power station, pumped storage power station, heat storage station and compressed air power station;

[0053] For the indicators in the criterion layer, a judgment matrix is ​​constructed to measure the importance of each indicator. The dimension of the judgment matrix A is 5×5;

[0054]

[0055] In the above formula, the element a in the judgment matrix A ij Indicates the importance ratio scale of the i-th indicator relative to the j-th indicator in the criterion layer; based on the 1-9 scale criterion of the hierarchical analysis method, a ij =1 means that indicator i and indicator j are equally important, a ij >1 means that indicator i is more important than indicator j. The larger the value, the higher the importance. ij <1 means that index j is more important than index i;

[0056] After the judgment matrix is ​​constructed, the weight vector is calculated using the geometric mean method;

[0057] Calculate the product of each row of the judgment matrix:

[0058]

[0059] In the above formula, M i is the product of all elements in the i-th row, n is the order of the judgment matrix, that is, the number of criteria layer indicators, j is the column index variable, a ij is the importance ratio scale of the i-th indicator relative to the j-th indicator in the criterion layer;

[0060] Take the nth root of the product:

[0061]

[0062] In the above formula, W iis the geometric mean of the product of the i-th row, and n is the order of the judgment matrix;

[0063] Normalized weight vector:

[0064]

[0065] In the above formula, w i is the weight vector element of the i-th indicator, n is the order of the judgment matrix, j is the column index variable, a ij is the importance ratio scale of the i-th indicator relative to the j-th indicator in the criterion layer;

[0066] Get the weight vector w=[w1,w2,...,w n ];

[0067] The consistency test is performed, wherein the calculation steps of the one-time index CI are as follows:

[0068] Reconstruct the comparison matrix based on the calculated weight vector in:

[0069]

[0070] In the above formula, is the theoretical judgment matrix reconstructed by the weight vector w, is the theoretical importance ratio of indicator i to indicator j, w j is the weight vector element of the j-th indicator;

[0071] Take the logarithmic mean of all element proportions:

[0072]

[0073] In the above formula, λ geom is the geometric mean consistency index, logλ geom is the logarithmic mean of the geometric mean consistency index, which measures the difference between the original matrix A and the reconstructed matrix The deviation of n is the order of the judgment matrix, i is the matrix row index, j is the matrix column index, w i is the weight vector element of the i-th indicator, w j is the weight vector element of the jth indicator; w ij is the indicator weight vector element in the i-th row and j-th column;

[0074] The geometric mean consistency index λ is obtained by calculating the logarithmic value geom , and calculate the one-time indicator CI:

[0075]

[0076] If 0≤CI≤0.1, the judgment matrix has acceptable consistency, otherwise the judgment matrix is ​​adjusted.

[0077] Furthermore, based on the calculated relative weights and the scoring results of each energy storage power station under different indicators, the comprehensive score of each energy storage power station is calculated as follows:

[0078]

[0079] Where: S is the comprehensive score of a certain energy storage power station; w i is the weight vector element of the i-th indicator; s i is the score of the energy storage power station under the i-th indicator.

[0080] Furthermore, the aforementioned ranking based on the comprehensive score of each energy storage power station to evaluate its grid-related performance is based on the comprehensive score of each energy storage power station, resulting in the overall performance of different types of energy storage power stations in terms of dynamic response indicators. This allows for a systematic analysis and quantification of the performance of each energy storage power station to evaluate its grid-related performance. Energy storage power stations with higher scores are suitable for scenarios requiring high performance in frequency regulation and power balancing, while those with lower scores are suitable for requirements that are more sensitive to energy storage duration or costs.

[0081] A device for evaluating grid-related technical requirements for diversified energy storage power stations, comprising:

[0082] Evaluation index establishment module, used to establish evaluation indicators for energy storage grid-related characteristics;

[0083] The standardization module is used to standardize the evaluation index scores using a hybrid standardization method;

[0084] The relative weight calculation module is used to calculate the relative weight of each standardized evaluation index through matrix normalization based on the hierarchical analysis method;

[0085] A comprehensive score calculation module is used to calculate the comprehensive score of each energy storage power station based on the calculated relative weights and the scoring results of each energy storage power station under different indicators;

[0086] The evaluation module is used to sort the energy storage power stations according to their comprehensive scores and evaluate their grid-related performance.

[0087] Furthermore, the evaluation index establishment module is specifically used to establish evaluation indicators for energy storage grid-related characteristics, including:

[0088] Selection of evaluation indicators;

[0089] Collect data related to the grid-related characteristic evaluation indicators of diversified energy storage power stations, and obtain dynamic response capabilities based on the recorded data of the power stations.

[0090] A computer device comprises a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein when the processor executes the computer program, the steps of any one of the methods for evaluating network-related technical requirements of a diversified energy storage power station are implemented.

[0091] A computer storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the computer program implements the steps of any one of the methods for evaluating grid-related technical requirements of a diversified energy storage power station.

[0092] The present invention has the following beneficial effects and advantages:

[0093] This paper provides a grid-related performance evaluation method for different types of energy storage power stations, primarily encompassing dynamic response capability, grid support capability, power quality, energy efficiency, and stability indicators. First, the analytic hierarchy process (AHP) is used to establish the indicators. Next, a hybrid standardization approach is used to standardize the indicator values. A judgment matrix is ​​then constructed to calculate weights and perform a consistency check. Finally, a comprehensive score for the energy storage station is obtained.

[0094] Through the hierarchical analysis method and standardization processing, the present invention converts various network-related performance indicators into a unified scoring standard, providing a reliable quantitative basis for the performance evaluation of diversified energy storage power stations.

[0095] By establishing a systematic evaluation system, this invention can clearly compare the performance of different energy storage plants in key grid-related performance indicators, such as dynamic response, frequency and voltage support, and efficiency. The evaluation results can provide clear guidance for the selection and optimization of energy storage plants, helping to improve their grid-related technical capabilities and better meet the needs of grid operation.

[0096] The present invention comprehensively evaluates the grid-related characteristics of diverse energy storage power stations of different types, deriving their overall performance in terms of dynamic response indicators. Furthermore, the present invention systematically analyzes and quantifies the performance of each energy storage power station, standardizes its technical standards, and improves its grid-related performance. Based on these indicators, effective auxiliary decision-making is provided for grid dispatching, supporting the regulation characteristics and grid-related technical requirements of diverse energy storage power stations.

[0097] This method is applicable to the evaluation of grid-related technical requirements for various types of energy storage power stations, including but not limited to large-scale pumped-storage power stations, thermal storage stations, and electrochemical energy storage stations. It focuses on the performance of energy storage stations in grid-ancillary services such as peak shaving and frequency regulation. It can effectively evaluate the role of different energy storage stations in the grid and improve their grid-related performance through optimization strategies. This method is a key technical means for the stable operation of power systems and has significant practical significance and application value. It also fills a gap in the existing technology, which lacks comprehensive evaluation of the grid-related characteristics of diverse energy storage stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0098] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments with reference to the accompanying drawings, in which:

[0099] Figure 1 It is a flowchart of the method of the present invention. DETAILED DESCRIPTION

[0100] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present invention and the features therein can be combined with each other without conflict.

[0101] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present invention is not limited to the specific embodiments disclosed below.

[0102] Refer to the following Figure 1 Describe the technical solutions of some embodiments of the present invention.

[0103] Example 1

[0104] The present invention provides an embodiment, which is a method for evaluating the network-related technical requirements of a diversified energy storage power station. Figure 1 As shown, Figure 1 It is a flowchart of the method of the present invention.

[0105] The present invention adopts the hierarchical analysis method to construct a set of quantitative evaluation index systems, covering core parameters such as response time, charge and discharge efficiency, power regulation range, cycle life, energy storage capacity utilization, etc., which can comprehensively and quantitatively evaluate the network-related performance of various energy storage power stations such as electrochemical energy storage, pumped storage, and thermal storage power stations in the power grid. In order to avoid excessive subjectivity, the judgment matrix method is used to determine the weight relationship between different indicators, and the various indicators are standardized by the mixed standardization method to eliminate the numerical and dimensional differences between the indicators, and then the total score is calculated according to the calculated weight. For different energy storage power stations, by re-filling the judgment matrix and changing the weight relationship between different indicators, the score of each energy storage power station can be obtained.

[0106] The implementation steps of the method for evaluating network-related technical requirements of a diversified energy storage power station of the present invention are as follows:

[0107] Step 1. Establish evaluation indicators for energy storage grid-related characteristics. The details are as follows:

[0108] (a) Evaluation indicator selection: The selected indicators are divided into dynamic response capability indicators, grid support capability indicators, power quality indicators, energy efficiency indicators, and stability indicators. Dynamic response capability indicators include energy storage station response time and power regulation range; grid support capability indicators include frequency response capability and voltage support capability; power quality indicators include power factor control capability and grid connection quality assessment; energy efficiency indicators include capacity utilization and charge and discharge efficiency; and stability indicators include fault ride-through capability and black start capability.

[0109] (b) Collect data related to the grid-related characteristic evaluation indicators of various energy storage power stations, and obtain dynamic response capabilities based on the power station's recorded data; extract data related to grid support capacity from grid frequency and voltage data records; obtain power quality indicators through power quality monitors and harmonic analyzers; obtain energy efficiency indicators through energy storage station power management system records and power dispatch data calculations; and obtain stability indicators through historical emergency event records or simulation data. Among them, power quality indicators, voltage support capacity indicators, and stability indicators are obtained through actual data analysis and evaluation and do not require calculation; the remaining indicators need to be obtained through calculation.

[0110] Among them, the indicators that need to be calculated include:

[0111] 1. Calculation of dynamic response capability index:

[0112] Response time T r The calculation method is to evaluate the time interval from the energy storage power station receiving the grid instruction to the actual response;

[0113] T r =T 0.9P -T st (1)

[0114] In the above formula: T 0.9P T is the moment when the energy storage power station power responds to 90% of the power instruction; st The moment when the energy storage power station starts power response.

[0115] Power adjustment range P range The maximum and minimum power output of the energy storage power station are used to evaluate its power regulation capability. The calculation formula is as follows:

[0116] P range =P max -P min (2)

[0117] In the above formula: P max is the maximum power of the energy storage station; P min is the minimum power of the energy storage station; according to power supply conventions, the power is positive when the energy storage is discharging and negative when it is charging.

[0118] 2. Calculation of energy efficiency index:

[0119] The efficiency η is calculated as the ratio of energy loss during the discharge and charging process of the energy storage station to the actual output energy. The calculation formula is as follows:

[0120]

[0121] In the above formula: E rd E is the amount of electricity discharged during the energy storage station; rc The amount of electricity used in the charging process of the energy storage power station.

[0122] Energy storage capacity utilization rate C u : The ratio of the effective energy storage capacity of the energy storage power station in actual operation to the designed capacity. The calculation formula is as follows:

[0123]

[0124] In the above formula: E used is the energy storage capacity that has been used; E total is the total capacity of the energy storage system.

[0125] Step 2. Use the hybrid standardization method to standardize the evaluation index scores.

[0126] The present invention adopts a hybrid normalization method. For limited range data such as response time and frequency deviation, minimum and maximum normalization is adopted to keep the range in [0, 1] to facilitate subsequent scoring.

[0127] Minimum and maximum normalization, the calculation formula is:

[0128]

[0129] In the above formula: x′ is the normalized value, x is the original value; x min is the minimum value of the indicator; x max is the maximum value of this indicator.

[0130] Step 3. Based on the hierarchical analysis method, the relative weights of each standardized evaluation index are calculated through matrix normalization.

[0131] The score is normalized and the calculation formula is as follows:

[0132]

[0133] In the above formula: Q1 is the first quarterback number; Q3 is the third quarterback number.

[0134] For data that are relatively stable but may contain extreme values, such as charging and discharging efficiency and power factor, quantile normalization is used to reduce the interference of extreme values ​​on the data.

[0135] This paper constructs a judgment matrix to measure the importance of each indicator, quantifies and scores the performance of diversified energy storage power stations on each indicator. The calculation steps of the hierarchical analysis method are as follows:

[0136] (a) The evaluation of the grid-related technical requirements of diversified energy storage power stations is decomposed into a hierarchical structure, which usually includes the target layer, the criterion layer, and the alternative solution layer.

[0137] The target layer is to quantify the dynamic response of the energy storage power station;

[0138] The criteria layer includes dynamic response support capability, grid support capability, power quality index, energy efficiency index and stability index;

[0139] The alternative solution layer includes electrochemical energy storage power stations, pumped storage power stations, thermal storage stations and compressed air power stations.

[0140] Different types of energy storage power plants, such as electrochemical energy storage, pumped hydro, thermal energy storage, and compressed air energy storage, each have their own technical characteristics and advantages in terms of grid-related characteristics. For example, electrochemical energy storage generally has a faster dynamic response speed, while pumped hydro is more advantageous in large-scale, long-term energy storage. Using the analytic hierarchy process to calculate weights, these differences can be quantified and incorporated into the weights, ensuring that the evaluation focus of each energy storage technology aligns with its actual technical characteristics and grid requirements, avoiding undue evaluation bias.

[0141] (b) For the five indicators in the criterion layer, a judgment matrix is ​​constructed to measure the importance of each indicator. The dimension of the judgment matrix A is 5×5.

[0142]

[0143] In the above formula, the element a in the judgment matrix A ij Indicates the importance ratio scale of the i-th indicator relative to the j-th indicator in the criterion layer. Based on the 1-9 scale criterion of the hierarchical analysis method, a ij =1 means that indicator i and indicator j are equally important, a ij >1 means that indicator i is more important than indicator j. The larger the value, the higher the importance. ij <1 means that index j is more important than index i.

[0144] (c) After the judgment matrix is ​​constructed, the geometric mean method is used to calculate the weight vector.

[0145] First calculate the product of each row of the judgment matrix:

[0146]

[0147] In the above formula, M iis the product of all elements in the i-th row, n is the order of the judgment matrix, that is, the number of criteria layer indicators, for example, n = 5 when there are 5 indicators, j is the column index variable, a ij is the importance ratio scale of the i-th indicator relative to the j-th indicator in the criterion layer, which is mentioned in Formula 7.

[0148] Then take the nth root of the product:

[0149] W i =(M i ) 1 / n (9)

[0150] In the above formula, W i is the geometric mean of the products of the i-th row, and n is the order of the judgment matrix.

[0151] Finally normalize the weight vector:

[0152]

[0153] In the above formula, w i is the weight vector element of the i-th indicator, n is the order of the judgment matrix, j is the column index variable, a ij is the importance ratio scale of the i-th indicator relative to the j-th indicator in the criterion layer.

[0154] Finally, we get the weight vector w=[w1,w2,...,w n ].

[0155] (d) To ensure the rationality of the judgment matrix, a consistency test is performed. The calculation steps of the one-time indicator CI are as follows:

[0156] First, the comparison matrix is ​​reconstructed according to the calculated weight vector in:

[0157]

[0158] In the above formula, is the theoretical judgment matrix reconstructed by the weight vector w, is the theoretical importance ratio of indicator i to indicator j, w j is the weight vector element of the j-th indicator.

[0159] Then take the logarithmic mean of all element proportions:

[0160]

[0161] In the above formula, λ geom is the geometric mean consistency index, logλ geom is the logarithmic mean of the geometric mean consistency index, which measures the difference between the original matrix A and the reconstructed matrix The deviation of n is the order of the judgment matrix, i is the matrix row index, j is the matrix column index, w i is the weight vector element of the i-th indicator, w j is the weight vector element of the jth indicator, w ij is the indicator weight vector element in the i-th row and j-th column.

[0162] Finally, the geometric mean consistency index λ is obtained by numerical calculation geom , and use the formula to calculate the one-time indicator CI:

[0163]

[0164] If 0≤CI≤0.1, the judgment matrix is ​​considered to have acceptable consistency, otherwise the judgment matrix needs to be adjusted.

[0165] Step 4. Calculate the comprehensive score of each energy storage power station based on the relative weights calculated in step 3 and the scores of each energy storage power station under different indicators. The specific steps are as follows:

[0166] The scoring results of each energy storage power station under different indicators refer to the judgment matrix of the alternative solution layer constructed for each indicator of the criterion layer, such as dynamic response support capability and grid support capability, and the weight value of each energy storage power station under a single indicator calculated by the hierarchical analysis method. Each energy storage power station includes electrochemical energy storage, pumped storage, etc.

[0167] The comprehensive score is calculated by multiplying the scores of each energy storage power station under different indicators by the indicator weight:

[0168]

[0169] Where: S is the comprehensive score of a certain energy storage power station; w i is the weight vector element of the i-th indicator; s i is the score of the energy storage power station under the i-th indicator.

[0170] Step 5. Sort the energy storage power stations according to the comprehensive scores calculated in step 4 to evaluate their grid-connected performance.

[0171] Specifically, the comprehensive scores of each energy storage power station calculated in step 4 are ranked to obtain the overall performance of different types of energy storage power stations in terms of dynamic response indicators. Then, the performance of each energy storage power station is systematically analyzed and quantified, and reasonable decisions are made based on these indicators to evaluate its grid-related performance.

[0172] Energy storage power stations with a comprehensive score higher than 0.7 are generally more suitable for scenarios with high performance requirements such as frequency regulation and power balancing, while those with a comprehensive score lower than 0.7 may be suitable for requirements with higher energy storage duration or cost sensitivity.

[0173] Example 2

[0174] The present invention further provides an embodiment, which is a device for evaluating network-related technical requirements of a diversified energy storage power station, comprising:

[0175] Evaluation index establishment module, used to establish evaluation indicators for energy storage grid-related characteristics;

[0176] The standardization module is used to standardize the evaluation index scores using a hybrid standardization method;

[0177] The relative weight calculation module is used to calculate the relative weight of each standardized evaluation index through matrix normalization based on the hierarchical analysis method;

[0178] A comprehensive score calculation module is used to calculate the comprehensive score of each energy storage power station based on the calculated relative weights and the scoring results of each energy storage power station under different indicators;

[0179] The evaluation module is used to sort the energy storage power stations according to their comprehensive scores and evaluate their grid-related performance.

[0180] The device for evaluating the grid-related technical requirements of a diversified energy storage power station described in the present invention is used to implement the operating steps of the method for evaluating the grid-related technical requirements of a diversified energy storage power station described in Example 1.

[0181] The evaluation index establishment module is specifically used to establish evaluation indicators for energy storage grid-related characteristics, including:

[0182] Selection of evaluation indicators;

[0183] Collect data related to the grid-related characteristic evaluation indicators of diversified energy storage power stations, and obtain dynamic response capabilities based on the recorded data of the power stations.

[0184] Example 3

[0185] Based on the same inventive concept, an embodiment of the present invention further provides a computer device comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor. When the processor executes the computer program, the steps of the method for evaluating grid-related technical requirements for diversified energy storage power stations described in Example 1 are implemented.

[0186] Example 4

[0187] Based on the same inventive concept, an embodiment of the present invention further provides a computer storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the method for evaluating the grid-related technical requirements of a diversified energy storage power station described in Example 1 are implemented.

[0188] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0189] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0190] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0191] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0192] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A method for evaluating grid-related technical requirements for diversified energy storage power stations, characterized by: include: Establish evaluation indicators for grid-related characteristics of energy storage; The mixed standardization method is used to standardize the evaluation index scores; Based on the analytic hierarchy process, the relative weights of each standardized evaluation index are calculated through matrix normalization; Calculate the comprehensive score of each energy storage station based on the calculated relative weights and the scoring results of each energy storage station under different indicators; The energy storage power stations are ranked according to their comprehensive scores to evaluate their grid-connected performance.

2. The method for evaluating network-related technical requirements for a diversified energy storage power station according to claim 1 is characterized by: The evaluation indicators for establishing energy storage grid-related characteristics include: Selection of evaluation indicators; Collect data related to the grid-related characteristic evaluation indicators of diversified energy storage power stations, and obtain dynamic response capabilities based on the recorded data of the power stations.

3. The method for evaluating network-related technical requirements for diversified energy storage power stations according to claim 2 is characterized by: The evaluation indicators include dynamic response capability, grid support capability, power quality, energy efficiency, and stability. Dynamic response capability includes the response time and power regulation range of the energy storage power station, while grid support capability includes frequency response and voltage support. Power quality indicators include power factor control capability and grid quality assessment; Energy efficiency indicators include capacity utilization and charge and discharge efficiency; stability indicators include fault ride-through capability and black start capability.

4. The method for evaluating network-related technical requirements for a diversified energy storage power station according to claim 2 is characterized by: The method collects data related to the grid-related characteristic evaluation indicators of the diversified energy storage power station and obtains the dynamic response capability based on the recorded data of the power station; among them, the power quality indicator, voltage support capability indicator, and stability indicator are obtained through actual data analysis and evaluation, and the dynamic response capability indicator and energy efficiency indicator are obtained through calculation.

5. The method for evaluating network-related technical requirements for diversified energy storage power stations according to claim 3 is characterized by: The dynamic response capability index is calculated as follows: T r =T 0.9P -T st (1) In the above formula: T r is the response time; T 0.9P T is the moment when the energy storage power station power responds to 90% of the power instruction; st The moment when the energy storage power station starts power response; Power adjustment range P range The calculation formula is as follows: P range =P max -P min (2) In the above formula: P max is the maximum power of the energy storage station; P min is the minimum power of the energy storage station. According to power supply conventions, the power is positive when the energy storage is discharging and negative when it is charging. The energy efficiency index is calculated as follows: The calculation formula of efficiency η is as follows: In the above formula: η is efficiency; E rd E is the amount of electricity discharged during the energy storage station; rc The amount of electricity used in the charging process of the energy storage power station; Energy storage capacity utilization rate C u The calculation formula is as follows: In the above formula: E used is the energy storage capacity that has been used; E total is the total capacity of the energy storage system.

6. The method for evaluating grid-related technical requirements for diversified energy storage power stations according to claim 1 is characterized by: The evaluation index scores are standardized using a hybrid standardization method, wherein: Minimum and maximum normalization, the calculation formula is: In the above formula: x′ is the normalized value, x is the original value; x min is the minimum value of the indicator; x max is the maximum value of this indicator.

7. The method for evaluating network-related technical requirements for a diversified energy storage power station according to claim 1 is characterized by: Based on the hierarchical analysis method, the relative weights of each standardized evaluation index are calculated by matrix normalization, wherein the score normalization is calculated as follows: In the above formula: Q1 is the first quarterback number; Q3 is the third quarterback number; To quantify and score the performance of diversified energy storage power stations on various indicators, the calculation steps of the hierarchical analysis method are as follows: Decompose the evaluation of grid-related technical requirements for diversified energy storage power stations into a hierarchical structure, including the target layer, the criteria layer, and the alternative solution layer; For the indicators in the criterion layer, a judgment matrix is ​​constructed to measure the importance of each indicator; After the judgment matrix is ​​constructed, the weight vector is calculated using the geometric mean method; Perform consistency check.

8. The method for evaluating network-related technical requirements for diversified energy storage power stations according to claim 7 is characterized by: The target layer is to quantify the dynamic response of the energy storage power station; the criterion layer is to include the dynamic response support capability, grid support capability, power quality indicators, energy efficiency indicators and stability indicators; the alternative solution layer includes electrochemical energy storage power stations, pumped storage power stations, thermal storage stations and compressed air power stations; The dimension of the judgment matrix A is 5×5; In the above formula, the element a in the judgment matrix A ij Indicates the importance ratio scale of the i-th indicator relative to the j-th indicator in the criterion layer; Based on the 1-9 scale criteria of the analytic hierarchy process, a ij =1 means that indicator i and indicator j are equally important, a ij >1 means that indicator i is more important than indicator j. The larger the value, the higher the importance. ij <1 means that index j is more important than index i; The calculating weight vector includes: Calculate the product of each row of the judgment matrix: In the above formula, M i is the product of all elements in the i-th row, n is the order of the judgment matrix, that is, the number of criterion layer indicators, j is the column index variable, a ij is the importance ratio scale of the i-th indicator relative to the j-th indicator in the criterion layer; Take the nth root of the product: W i =(M i ) 1 / n (9) In the above formula, W i is the geometric mean of the product of the i-th row, and n is the order of the judgment matrix; Normalized weight vector: In the above formula, w i is the weight vector element of the i-th indicator, n is the order of the judgment matrix, j is the column index variable, a ij is the importance ratio scale of the i-th indicator relative to the j-th indicator in the criterion layer; Get the weight vector w=[w1,w2,...,w n ]; The consistency test is performed, wherein the calculation steps of the one-time index CI are as follows: Reconstruct the comparison matrix based on the calculated weight vector in: In the above formula, is the theoretical judgment matrix reconstructed by the weight vector w, is the theoretical importance ratio of indicator i to indicator j, w j is the weight vector element of the j-th indicator; Take the logarithmic mean of all element proportions: In the above formula, λ geom is the geometric mean consistency index, logλ geom is the logarithmic mean of the geometric mean consistency index, which measures the difference between the original matrix A and the reconstructed matrix The deviation of n is the order of the judgment matrix, i is the matrix row index, j is the matrix column index, w i is the weight vector element of the i-th indicator, w j is the weight vector element of the jth indicator; w ij is the indicator weight vector element in row i and column j; The geometric mean consistency index λ is obtained by calculating the logarithmic value geom , and calculate the one-time indicator CI: If 0≤CI≤0.1, the judgment matrix has acceptable consistency, otherwise the judgment matrix is ​​adjusted.

9. The method for evaluating grid-related technical requirements for diversified energy storage power stations according to claim 1 is characterized by: Based on the calculated relative weights and the scoring results of each energy storage power station under different indicators, the comprehensive score of each energy storage power station is calculated as follows: Where: S is the comprehensive score of a certain energy storage power station; w i is the weight vector element of the i-th indicator; s i is the score of the energy storage power station under the i-th indicator.

10. The method for evaluating grid-related technical requirements for diversified energy storage power stations according to claim 1 is characterized by: The aforementioned ranking based on the comprehensive score of each energy storage power station is used to evaluate its grid-related performance. This ranking is based on the comprehensive score of each energy storage power station, resulting in the overall performance of different types of energy storage power stations in terms of dynamic response indicators. This allows for a systematic analysis and quantification of the performance of each energy storage power station to evaluate its grid-related performance. Energy storage stations with higher scores are suitable for scenarios requiring high performance in frequency regulation and power balancing, while those with lower scores are more suitable for requirements that are more sensitive to energy storage duration or costs.

11. A device for evaluating grid-related technical requirements for diversified energy storage power stations, characterized by: include: Evaluation index establishment module, used to establish evaluation indicators for energy storage grid-related characteristics; The standardization module is used to standardize the evaluation index scores using a hybrid standardization method; The relative weight calculation module is used to calculate the relative weight of each standardized evaluation index through matrix normalization based on the hierarchical analysis method; A comprehensive score calculation module is used to calculate the comprehensive score of each energy storage power station based on the calculated relative weights and the scoring results of each energy storage power station under different indicators; The evaluation module is used to sort the energy storage power stations according to their comprehensive scores and evaluate their grid-related performance.

12. The device for evaluating network-related technical requirements of a diversified energy storage power station according to claim 11, characterized in that: The evaluation index establishment module is specifically used to establish evaluation indicators for energy storage grid-related characteristics, including: Selection of evaluation indicators; Collect data related to the grid-related characteristic evaluation indicators of diversified energy storage power stations, and obtain dynamic response capabilities based on the recorded data of the power stations.

13. A computer device comprising a storage medium, a processor, and a computer program stored in the storage medium and executable on the processor, wherein: When the processor executes the computer program, the processor implements the steps of a method for evaluating grid-related technical requirements of a diversified energy storage power station as described in any one of claims 1 to 10.

14. A computer storage medium, characterized by: The computer storage medium stores a computer program, which, when executed by a processor, implements the steps of a method for evaluating grid-related technical requirements of a diversified energy storage power station as described in any one of claims 1 to 10.

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