Energy storage power station evaluation method and system based on storage network load

Abstract

This invention proposes an evaluation method and system for energy storage power stations based on grid-grid-storage (SGG), comprising: establishing reliability indicators, coordination indicators, quality indicators, and economic indicators for energy storage power stations; and finally, calculating a score for the operational performance of the energy storage power station based on subjective and objective weights. Specifically, establishing reliability indicators includes calculating the annual charge-discharge efficiency of energy storage units, grid interface failure outage rate, and load support shortfall rate; establishing coordination indicators includes calculating power response accuracy, energy time-shift efficiency, and multi-timescale coordination; establishing quality indicators includes calculating dynamic voltage regulation accuracy, harmonic interaction suppression rate, frequency tracking accuracy, and equipment operating efficiency degradation rate; establishing economic indicators includes calculating the levelized cost of electricity (LCOE), dynamic revenue model, and return on investment; and managing battery degradation and risks.

Description

Technical Field

[0001] This invention proposes an evaluation method and system for energy storage power stations based on energy storage grid load, which relates to the field of power grid upgrading and transformation. Background Technology

[0002] The cost and efficiency of energy storage power stations have a significant impact on their economic benefits, and current cost-benefit assessment systems have several shortcomings. On the one hand, when evaluating the economic benefits of energy storage power stations, only the main revenue sources are often considered, while implicit economic and social benefits such as delaying grid equipment upgrades and reducing the reserve capacity required for renewable energy generation are ignored. On the other hand, the economic evaluation methods for energy storage do not fully consider the costs and benefits of the entire system, including renewable energy, especially the significant impact of regional and temporal differences in electricity prices on the evaluation results and the feasibility of energy storage systems. Therefore, there is an urgent need to construct a comprehensive and scientific cost-benefit assessment system to comprehensively consider various factors, accurately assess the economic benefits of energy storage power stations, and promote the commercialization and practical development of energy storage technology. Summary of the Invention

[0003] In view of this, in order to fill the gaps and deficiencies in the existing technology, this invention proposes an evaluation method and system for energy storage power stations based on energy storage grid load, in order to solve the current problems.

[0004] This invention proposes an evaluation method for energy storage power stations based on energy storage grid load, characterized by the following:

[0005] The evaluation of energy storage power stations is conducted from three aspects: energy storage system, grid interface, and load support. This includes setting reliability indicators, coordination indicators, quality indicators, and economic indicators for energy storage power stations. Finally, a score for the operational performance of the energy storage power station is calculated based on subjective and objective weights.

[0006] Furthermore, the reliability indicators for energy storage power stations include the following:

[0007] Developing reliability indicators for energy storage power stations includes calculating the annual charge and discharge efficiency of energy storage units, calculating the grid interface failure outage rate, and calculating the load support deficit rate.

[0008] The calculation of the annual charge-discharge efficiency of the energy storage unit includes:

[0009] Suppose the rated capacity of a certain energy storage unit is , The unit is kWh, and the rated number of cycles is The theoretical annual rated discharge is:

[0010] ;

[0011] Among the variables For design efficiency, charging and discharging losses are taken into account;

[0012] The actual annual discharge capacity (Eanua,actual) can be obtained through monitoring data; furthermore, the annual charge-discharge efficiency is:

[0013] ;

[0014] Among them, the annual charge-discharge efficiency reflects the degree of performance degradation of the energy storage system over long-term operation and is a core parameter for assessing the health status of the equipment.

[0015] The calculation of the power grid interface fault outage rate includes:

[0016] The converter's failure downtime rate is defined as:

[0017] ;

[0018] in, This refers to the annual cumulative downtime due to faults in the converter. Total annual operating time;

[0019] Furthermore, by combining the redundancy configuration strategy to analyze the grid interface failure outage rate, and using the N+1 redundancy design correction formula, the availability factor A is obtained. inv The expression:

[0020] ;

[0021] Where the availability factor is N is the number of redundant devices and the availability factor. Used to evaluate system-level reliability.

[0022] Furthermore, the development of reliability indicators for energy storage power stations also includes the following:

[0023] The calculation of the load support deficit rate includes:

[0024] The deficit rate for energy storage power stations is defined as follows:

[0025] ;

[0026] in, Electricity demand from the load; This represents the actual power supply from energy storage.

[0027] Furthermore, the shortfall rate is revised, including the following:

[0028] ;

[0029] in The revised deficit rate reflects the differentiated guarantee capacity for different levels of load.

[0030] Furthermore, the coordination indicators for energy storage power stations include the following:

[0031] The formulation of coordination indicators for energy storage power stations includes calculating power response accuracy, calculating energy time-shift efficiency, and calculating multi-timescale coordination.

[0032] The accuracy of power response calculation includes:

[0033] Define the deviation rate between the actual output power (Pactua) of the energy storage system and the dispatch command (Pe):

[0034] ;

[0035] Furthermore, for second-level frequency modulation applications satisfying Δt=1s, a dynamic weighting function f(t) is introduced to correct the deviation rate, resulting in:

[0036] ;

[0037] Among them, f(t) can be dynamically adjusted according to the frequency regulation needs of the power grid, including increasing the weight during peak periods;

[0038] The calculation of energy time-shift efficiency includes:

[0039] Peak-hour electricity pricing Off-peak electricity prices The energy storage charging and discharging efficiency is The theoretical gain is:

[0040] ;

[0041] The design time-shift efficiency is defined as the ratio of the actual revenue Ractua to the theoretical maximum value Rm.

[0042] ;

[0043] Among them, time-shift efficiency is combined with an electricity price fluctuation model for Monte Carlo simulation to evaluate long-term economic viability;

[0044] Calculating multi-timescale coordination includes:

[0045] Define the multi-timescale coordination factor K:

[0046] ;

[0047] in and These represent short-time and long-time control efficiencies, respectively, and are reference values. and Determined by historical best data; multi-timescale coordination is used to quantify the comprehensive coordination capability of energy storage systems under complex operating conditions.

[0048] Furthermore, the quality indicators for energy storage power stations include the following:

[0049] The quality indicators for energy storage power stations include calculating dynamic voltage regulation accuracy, harmonic interaction suppression rate, frequency tracking accuracy, and equipment operating efficiency attenuation rate.

[0050] The calculation of dynamic voltage regulation accuracy includes defining the dynamic voltage deviation rate:

[0051] ;

[0052] in The voltage value is the dispatch command voltage value. This is the actual output voltage;

[0053] The calculation of harmonic interaction suppression rate includes:

[0054] ;

[0055] in The background harmonic distortion rate of the power grid. The measured total harmonic distortion rate at the grid connection point.

[0056] The calculation of frequency tracking accuracy includes:

[0057] ;

[0058] in It is a reverse harmonic current; The h-th harmonic current on the power grid side;

[0059] Furthermore, the total harmonic suppression efficiency is the weighted sum of the suppression rates of each harmonic:

[0060] ;

[0061] in The weight of the h-th harmonic;

[0062] The calculation of frequency tracking accuracy also includes:

[0063] Define the root mean square value of frequency deviation :

[0064] ;

[0065] Among them, when ≤0.05Hz is considered to meet the primary frequency modulation requirements;

[0066] Furthermore, when the energy storage power station participates in secondary frequency regulation, the accumulated phase error is constrained;

[0067] ;

[0068] in This is the cumulative phase error;

[0069] The calculation of equipment operating efficiency degradation rate includes:

[0070] Define efficiency annual decay rate :

[0071] ;

[0072] in For initial charge / discharge efficiency, Annual measured efficiency;

[0073] Furthermore, the Arrhenius model is used to express the mathematical relationship between efficiency decay and the number of cycles (Ncycle) and depth of discharge (DOD):

[0074] ;

[0075] Where k is the material coefficient, E is the activation energy, and R is the gas constant. This refers to the operating temperature.

[0076] Furthermore, the economic indicators for energy storage power stations include the following:

[0077] Developing economic indicators for energy storage power stations includes calculating the levelized cost of electricity (LCOE), calculating the revenue dynamic model and return on investment, and calculating battery degradation and risk management.

[0078] The calculation of the levelized cost of electricity includes:

[0079] Define the average cost per unit of discharge over the entire lifecycle, LCOS, where the LCOS expression is:

[0080] ;

[0081] The present value of total cost includes: initial investment and residuals;

[0082] Furthermore, based on the initial investment, the operation and maintenance costs are calculated using an annual growth rate model and allocated over the construction period, yielding the following results:

[0083] ;

[0084] in, γ represents the initial investment; k is the operation and maintenance coefficient, with a value ranging from 2% to 5%; γ is the annual growth rate, with an optimal value of 3%.

[0085] According to the linear depreciation model, the residual value is:

[0086] ;

[0087] in Represents residual value; Indicates the assumed lifespan;

[0088] The present value of the total discharge includes:

[0089] Considering capacity decay and efficiency loss, calculate the annual discharge:

[0090] ;

[0091] in, Annual discharge amount; For rated capacity, The unit is: MWh;

[0092] in For charge / discharge cycle efficiency; This refers to the annual capacity decay rate. Let t be the number of cycles in year t.

[0093] The calculation of dynamic profit models and investment returns includes the following:

[0094] Energy storage revenue includes electricity sales revenue, ancillary service revenue, and policy subsidies. Based on market mechanism modeling, the following results are obtained:

[0095] Electricity sales revenue:

[0096] ;

[0097] in For time-of-use pricing; further, based on geometric Brownian motion simulation of random fluctuations, the following is obtained:

[0098] ;

[0099] Where μ is the average annual growth rate of electricity prices, and σ is the volatility. For Wiener process;

[0100] Ancillary service revenue includes frequency regulation and reserve capacity compensation:

[0101] ;

[0102] in This is for compensation of the reserve capacity in year t; For the frequency modulation in year t; The unit price for FM service;

[0103] Dynamic payback period: The dynamic payback period is defined as the number of years from which the net present value (NPV) becomes zero through iterative solutions.

[0104] ;

[0105] in The discount rate; This represents the net income in year t.

[0106] The calculation of battery degradation and risk management includes calculating the unit cycle degradation cost, including:

[0107] ;

[0108] Define the expression for the actual cycle lifetime depth of discharge:

[0109] ;

[0110] in This represents the actual cycle life depth of discharge.

[0111] Furthermore, the scoring of the energy storage power station's operational performance, based on subjective and objective weights, includes the following:

[0112] The subjective weighting method and the objective weighting method are used to calculate the score of the operation effect of the energy storage power station;

[0113] The subjective weighting method compares the importance of adjacent indicators one by one to determine the importance ratio coefficient of adjacent indicators, and then recursively calculates the importance coefficient of each indicator. Finally, the weight of each indicator is obtained through normalization, including the following:

[0114] Calculate the ranking and importance score of the indicators, then calculate the corrected score, and finally calculate the total corrected score and normalized weight.

[0115] The ranking and importance score of the calculated indicators include:

[0116] The indicators are arranged in descending order of importance as follows: Then, for adjacent indicators and The importance of the score is scored and a ratio is defined. :

[0117] ;

[0118] The corrected score calculation includes:

[0119] The scoring is revised iteratively starting with the most important indicators. : ; ;

[0120] The calculation of the total corrected score and normalized weights includes:

[0121] Calculate the total corrected score ;

[0122] Then the normalized weights are obtained. ;

[0123] in This represents the normalized weight.

[0124] Furthermore, the scoring of the energy storage power station's operational performance based on subjective and objective weights also includes the following:

[0125] The calculation of objective weights using the entropy weight method includes the following:

[0126] By calculating the entropy value and difference coefficient of each indicator, the objective fluctuation characteristics of the data are transformed into weight coefficients, including first standardizing the data; then calculating the entropy value; and finally defining the difference coefficient and calculating the objective weight.

[0127] Data standardization includes:

[0128] For the original data matrix Normalize:

[0129] ;

[0130] The entropy calculation includes:

[0131] Calculate the entropy value of the j-th index:

[0132] ;

[0133] in Entropy is a value that reflects the degree of disorder in the data distribution.

[0134] The definition of the difference coefficient and the calculation of the objective weights include:

[0135] ;

[0136] ;

[0137] in The coefficient of variation; For objective weighting.

[0138] Furthermore, the method also includes the following:

[0139] Step S1: Develop reliability indicators for energy storage power stations, including calculating the annual charge and discharge efficiency of energy storage units, calculating the grid interface failure outage rate, and calculating the load support deficit rate.

[0140] Step S2: Develop coordination indicators for energy storage power stations, including calculating power response accuracy, calculating energy time-shift efficiency, and calculating multi-timescale coordination.

[0141] Step S3: Develop quality indicators for energy storage power stations, including calculating dynamic voltage regulation accuracy, harmonic interaction suppression rate, frequency tracking accuracy, and equipment operating efficiency attenuation rate.

[0142] Step S4: Develop economic indicators for energy storage power stations, including calculating the levelized cost of electricity (LCOE), calculating the revenue dynamic model and return on investment; and calculating battery degradation and risk management.

[0143] Step S5: Calculate the score of the energy storage power station's operating performance based on subjective and objective weights, including calculating the score of the energy storage power station's operating performance using the subjective weight method and the objective weight method.

[0144] According to a second aspect of the present invention, the present invention proposes an energy storage power station evaluation system based on energy storage grid load, for performing an energy storage power station evaluation method based on energy storage grid load as described in the present invention, characterized in that the energy storage power station evaluation system based on energy storage grid load includes an energy storage power station reliability evaluation module, an energy storage power station coordination evaluation module, an energy storage power station quality evaluation module, an energy storage power station economic evaluation module, and an energy storage power station operation effect evaluation module.

[0145] The reliability evaluation module for energy storage power stations evaluates the reliability of energy storage power stations by calculating the annual charge and discharge efficiency of energy storage units, the outage rate due to grid interface failures, and the load support deficit rate.

[0146] The energy storage power station coordination evaluation module evaluates the coordination of energy storage power stations by calculating power response accuracy, energy time-shift efficiency, and multi-timescale coordination.

[0147] The energy storage power station quality evaluation module evaluates the quality of the energy storage power station by calculating the dynamic voltage regulation accuracy, harmonic interaction suppression rate, frequency tracking accuracy, and equipment operating efficiency attenuation rate.

[0148] The energy storage power station economic evaluation module evaluates the economics of energy storage power stations by calculating the levelized cost per kilowatt-hour, calculating the revenue dynamic model and return on investment, and calculating battery degradation and risk management.

[0149] The energy storage power station operation performance evaluation module evaluates the operation performance of energy storage power stations by calculating a score based on subjective and objective weights.

[0150] The present invention has the following advantages:

[0151] This invention proposes an evaluation method and system for energy storage power stations based on a grid-storage-load (GSLT) architecture. The method includes: establishing reliability indicators, coordination indicators, quality indicators, and economic indicators for energy storage power stations; and finally, calculating a score for the operational performance of the energy storage power station based on subjective and objective weights. This invention constructs a comprehensive and scientific cost-benefit evaluation system, comprehensively considering various factors to accurately assess the economic benefits of energy storage power stations and promote the commercialization and practical application of energy storage technology. Attached Figure Description

[0152] Figure 1 This is a schematic diagram of the steps of the present invention.

[0153] Figure 2 This is a schematic diagram of the system of the present invention.

[0154] Figure 3 This is a schematic diagram of the set of factors affecting the reliability of the energy storage power station according to the present invention.

[0155] Figure 4 This is a schematic diagram of the set of factors affecting the coordination of energy storage power stations according to the present invention.

[0156] Figure 5 This is a schematic diagram of the set of factors influencing the quality of the energy storage power station according to the present invention.

[0157] Figure 6 This is a schematic diagram of the economic factors affecting the energy storage power station of the present invention. Detailed Implementation

[0158] The technical solution of the present invention will now be described in detail with reference to the accompanying drawings.

[0159] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0160] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments of the present invention; as used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise; furthermore, it should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0161] like Figures 1 to 6As shown, this invention proposes an evaluation method and system for energy storage power stations based on energy storage grid load, characterized by including the following:

[0162] This invention proposes an evaluation method for energy storage power stations based on energy storage grid load, characterized by the following:

[0163] The evaluation of energy storage power stations is conducted from three aspects: energy storage system, grid interface, and load support. This includes setting reliability indicators, coordination indicators, quality indicators, and economic indicators for energy storage power stations. Finally, a score for the operational performance of the energy storage power station is calculated based on subjective and objective weights.

[0164] Furthermore, the reliability indicators for energy storage power stations include the following:

[0165] Developing reliability indicators for energy storage power stations includes calculating the annual charge and discharge efficiency of energy storage units, calculating the grid interface failure outage rate, and calculating the load support deficit rate.

[0166] The calculation of the annual charge-discharge efficiency of the energy storage unit includes:

[0167] Assume the rated capacity of the energy storage unit is , The unit is kWh, and the rated number of cycles is The theoretical annual rated discharge is:

[0168] ;

[0169] Among the variables For design efficiency, charging and discharging losses are taken into account;

[0170] The actual annual discharge capacity (Eanua,actual) can be obtained through monitoring data; furthermore, the annual charge-discharge efficiency is:

[0171] ;

[0172] Among them, the annual charge-discharge efficiency reflects the degree of performance degradation of the energy storage system over long-term operation and is a core parameter for assessing the health status of the equipment.

[0173] The calculation of the power grid interface fault outage rate includes:

[0174] The converter's failure downtime rate is defined as:

[0175] ;

[0176] in, This refers to the annual cumulative downtime due to faults in the converter. Total annual operating time;

[0177] Furthermore, by combining the redundancy configuration strategy to analyze the grid interface failure outage rate, and using the N+1 redundancy design correction formula, the availability factor A is obtained. inv The expression:

[0178] ;

[0179] Where the availability factor is N is the number of redundant devices and the availability factor. Used to evaluate system-level reliability.

[0180] Furthermore, the development of reliability indicators for energy storage power stations also includes the following:

[0181] The calculation of the load support deficit rate includes:

[0182] The deficit rate for energy storage power stations is defined as follows:

[0183] ;

[0184] in, Electricity demand from the load; This represents the actual power supply from energy storage.

[0185] Furthermore, the shortfall rate is revised, including the following:

[0186] ;

[0187] in The revised deficit rate reflects the differentiated guarantee capacity for different levels of load.

[0188] Furthermore, the coordination indicators for energy storage power stations include the following:

[0189] The formulation of coordination indicators for energy storage power stations includes calculating power response accuracy, calculating energy time-shift efficiency, and calculating multi-timescale coordination.

[0190] The accuracy of power response calculation includes:

[0191] Define the deviation rate between the actual output power (Pactua) of the energy storage system and the dispatch command (Pe):

[0192] ;

[0193] Furthermore, for second-level frequency modulation applications satisfying Δt=1s, a dynamic weighting function f(t) is introduced to correct the deviation rate, resulting in:

[0194] ;

[0195] Among them, f(t) can be dynamically adjusted according to the frequency regulation needs of the power grid, including increasing the weight during peak periods;

[0196] The calculation of energy time-shift efficiency includes:

[0197] Peak-hour electricity pricing Off-peak electricity prices The energy storage charging and discharging efficiency is The theoretical gain is:

[0198] ;

[0199] The design time-shift efficiency is defined as the ratio of the actual revenue Ractua to the theoretical maximum value Rm.

[0200] ;

[0201] Among them, time-shift efficiency is combined with an electricity price fluctuation model for Monte Carlo simulation to evaluate long-term economic viability;

[0202] Calculating multi-timescale coordination includes:

[0203] Define the multi-timescale coordination factor K:

[0204] ;

[0205] in and These represent short-time and long-time control efficiencies, respectively, and are reference values. and Determined by historical best data; multi-timescale coordination is used to quantify the comprehensive coordination capability of energy storage systems under complex operating conditions.

[0206] Furthermore, the quality indicators for energy storage power stations include the following:

[0207] The quality indicators for energy storage power stations include calculating dynamic voltage regulation accuracy, harmonic interaction suppression rate, frequency tracking accuracy, and equipment operating efficiency attenuation rate.

[0208] The calculation of dynamic voltage regulation accuracy includes defining the dynamic voltage deviation rate:

[0209] ;

[0210] in The voltage value is the dispatch command voltage value. This is the actual output voltage;

[0211] The calculation of harmonic interaction suppression rate includes:

[0212] ;

[0213] in The background harmonic distortion rate of the power grid. The measured total harmonic distortion rate at the grid connection point.

[0214] The calculation of frequency tracking accuracy includes:

[0215] ;

[0216] in It is a reverse harmonic current; The h-th harmonic current on the power grid side;

[0217] Furthermore, the total harmonic suppression efficiency is the weighted sum of the suppression rates of each harmonic:

[0218] ;

[0219] in The weight of the h-th harmonic;

[0220] The calculation of frequency tracking accuracy also includes:

[0221] Define the root mean square value of frequency deviation :

[0222] ;

[0223] Among them, when ≤0.05Hz is considered to meet the primary frequency modulation requirements;

[0224] Furthermore, when the energy storage power station participates in secondary frequency regulation, the accumulated phase error is constrained;

[0225] ;

[0226] in This is the cumulative phase error;

[0227] The calculation of equipment operating efficiency degradation rate includes:

[0228] Define efficiency annual decay rate :

[0229] ;

[0230] in For initial charge / discharge efficiency, Annual measured efficiency;

[0231] Furthermore, the Arrhenius model is used to express the mathematical relationship between efficiency decay and the number of cycles (Ncycle) and depth of discharge (DOD):

[0232] ;

[0233] Where k is the material coefficient, E is the activation energy, and R is the gas constant. This refers to the operating temperature.

[0234] Furthermore, the economic indicators for energy storage power stations include the following:

[0235] Developing economic indicators for energy storage power stations includes calculating the levelized cost of electricity (LCOE), calculating the revenue dynamic model and return on investment, and calculating battery degradation and risk management.

[0236] The calculation of the levelized cost of electricity includes:

[0237] Define the average cost per unit of discharge over the entire lifecycle, LCOS, where the LCOS expression is:

[0238] ;

[0239] The present value of total cost includes: initial investment and residuals;

[0240] Furthermore, based on the initial investment, the operation and maintenance costs are calculated using an annual growth rate model and allocated over the construction period, yielding the following results:

[0241] ;

[0242] in, γ represents the initial investment; k is the operation and maintenance coefficient, with a value ranging from 2% to 5%; γ is the annual growth rate, with an optimal value of 3%.

[0243] According to the linear depreciation model, the residual value is:

[0244] ;

[0245] in Represents residual value; Indicates the assumed lifespan;

[0246] The present value of the total discharge includes:

[0247] Considering capacity decay and efficiency loss, calculate the annual discharge:

[0248] ;

[0249] in, Annual discharge amount; For rated capacity, The unit is: MWh;

[0250] in For charge / discharge cycle efficiency; This refers to the annual capacity decay rate. Let t be the number of cycles in year t.

[0251] The calculation of dynamic profit models and investment returns includes the following:

[0252] Energy storage revenue includes electricity sales revenue, ancillary service revenue, and policy subsidies. Based on market mechanism modeling, the following results are obtained:

[0253] Electricity sales revenue:

[0254] ;

[0255] in For time-of-use pricing; further, based on geometric Brownian motion simulation of random fluctuations, the following is obtained:

[0256] ;

[0257] Where μ is the average annual growth rate of electricity prices, and σ is the volatility. For Wiener process;

[0258] Ancillary service revenue includes frequency regulation and reserve capacity compensation:

[0259] ;

[0260] in This is for compensation of the reserve capacity in year t; For the frequency modulation in year t; The unit price for FM service;

[0261] Dynamic payback period: The dynamic payback period is defined as the number of years from which the net present value (NPV) becomes zero through iterative solutions.

[0262] ;

[0263] in The discount rate; This represents the net income in year t.

[0264] The calculation of battery degradation and risk management includes calculating the unit cycle degradation cost, including:

[0265] ;

[0266] Define the expression for the actual cycle lifetime depth of discharge:

[0267] ;

[0268] in This represents the actual cycle life depth of discharge.

[0269] In one embodiment of the present invention, the risk management method includes:

[0270] Monte Carlo simulation: Generate 1000 sets of electricity price and attenuation rate paths, calculate the LCOS probability distribution, and assess project risk.

[0271] Sensitivity analysis: Plot the curves of LCOS as a function of β, r, and γ to determine the critical parameter threshold.

[0272] Furthermore, the scoring of the energy storage power station's operational performance, based on subjective and objective weights, includes the following:

[0273] The subjective weighting method and the objective weighting method are used to calculate the score of the operation effect of the energy storage power station;

[0274] The subjective weighting method compares the importance of adjacent indicators one by one to determine the importance ratio coefficient of adjacent indicators, and then recursively calculates the importance coefficient of each indicator. Finally, the weight of each indicator is obtained through normalization, including the following:

[0275] Calculate the ranking and importance score of the indicators, then calculate the corrected score, and finally calculate the total corrected score and normalized weight.

[0276] The ranking and importance score of the calculated indicators include:

[0277] The indicators are arranged in descending order of importance as follows: Then, for adjacent indicators and The importance of the score is scored and a ratio is defined. :

[0278] ;

[0279] The corrected score calculation includes:

[0280] The scoring is revised iteratively starting with the most important indicators. : ; ;

[0281] The calculation of the total corrected score and normalized weights includes:

[0282] Calculate the total corrected score ;

[0283] Then the normalized weights are obtained. ;

[0284] in This represents the normalized weight.

[0285] Furthermore, the scoring of the energy storage power station's operational performance based on subjective and objective weights also includes the following:

[0286] The calculation of objective weights using the entropy weight method includes the following:

[0287] By calculating the entropy value and difference coefficient of each indicator, the objective fluctuation characteristics of the data are transformed into weight coefficients, including first standardizing the data; then calculating the entropy value; and finally defining the difference coefficient and calculating the objective weight.

[0288] Data standardization includes:

[0289] For the original data matrix Normalize:

[0290] ;

[0291] The entropy calculation includes:

[0292] Calculate the entropy value of the j-th index:

[0293] ;

[0294] in Entropy is a value that reflects the degree of disorder in the data distribution.

[0295] The definition of the difference coefficient and the calculation of the objective weights include:

[0296] ;

[0297] ;

[0298] in The coefficient of variation; For objective weighting.

[0299] Furthermore, such as Figure 1 As shown, in one embodiment of the present invention, the method further includes the following:

[0300] Step S1: Develop reliability indicators for energy storage power stations, including calculating the annual charge and discharge efficiency of energy storage units, calculating the grid interface failure outage rate, and calculating the load support deficit rate.

[0301] Step S2: Develop coordination indicators for energy storage power stations, including calculating power response accuracy, calculating energy time-shift efficiency, and calculating multi-timescale coordination.

[0302] Step S3: Develop quality indicators for energy storage power stations, including calculating dynamic voltage regulation accuracy, harmonic interaction suppression rate, frequency tracking accuracy, and equipment operating efficiency attenuation rate.

[0303] Step S4: Develop economic indicators for energy storage power stations, including calculating the levelized cost of electricity (LCOE), calculating the revenue dynamic model and return on investment; and calculating battery degradation and risk management.

[0304] Step S5: Calculate the score of the energy storage power station's operating performance based on subjective and objective weights, including calculating the score of the energy storage power station's operating performance using the subjective weight method and the objective weight method.

[0305] According to a second aspect of the present invention, the present invention proposes an energy storage power station evaluation system based on energy storage grid load, for performing an energy storage power station evaluation method based on energy storage grid load as described in the present invention, characterized in that the energy storage power station evaluation system based on energy storage grid load includes an energy storage power station reliability evaluation module, an energy storage power station coordination evaluation module, an energy storage power station quality evaluation module, an energy storage power station economic evaluation module, and an energy storage power station operation effect evaluation module.

[0306] The reliability evaluation module for energy storage power stations evaluates the reliability of energy storage power stations by calculating the annual charge and discharge efficiency of energy storage units, the outage rate due to grid interface failures, and the load support deficit rate.

[0307] The energy storage power station coordination evaluation module evaluates the coordination of energy storage power stations by calculating power response accuracy, energy time-shift efficiency, and multi-timescale coordination.

[0308] The energy storage power station quality evaluation module evaluates the quality of the energy storage power station by calculating the dynamic voltage regulation accuracy, harmonic interaction suppression rate, frequency tracking accuracy, and equipment operating efficiency attenuation rate.

[0309] The energy storage power station economic evaluation module evaluates the economics of energy storage power stations by calculating the levelized cost per kilowatt-hour, calculating the revenue dynamic model and return on investment, and calculating battery degradation and risk management.

[0310] The energy storage power station operation performance evaluation module evaluates the operation performance of energy storage power stations by calculating a score based on subjective and objective weights.

[0311] like Figure 2 As shown in one embodiment of the present invention, the energy storage power station, as an important component of the new power system, requires systematic analysis of its operational performance through a multi-dimensional comprehensive evaluation system. This study, based on the synergistic perspective of "storage-grid-load," constructs an evaluation framework covering four core dimensions: reliability, coordination, economy, and quality. This framework aims to comprehensively reflect the performance of the energy storage power station in terms of technical performance, dynamic coordination, and overall value.

[0312] like Figure 3As shown, in one embodiment of the present invention, the reliability dimension focuses on the long-term stable operation capability of the energy storage system. It assesses the health status of the equipment by quantifying indicators such as battery cycle life degradation rate and power module failure frequency. Simultaneously, it introduces "capacity reliability" to dynamically track the deviation between the actual available capacity and the nominal capacity. Furthermore, the grid interaction stability index is incorporated into the evaluation system to analyze the impact of power fluctuations at the grid connection point on the main grid.

[0313] like Figure 4 As shown, in one embodiment of the present invention, the coordination dimension emphasizes the dynamic adaptability of the energy storage power station to the power system, and differentiates the evaluation criteria for scenarios such as frequency regulation, renewable energy consumption, and islanding operation. For example, in the frequency regulation scenario, the millisecond-level response success rate (≥99%) is the core; in the renewable energy consumption scenario, the "fluctuation mitigation rate" is used to measure the suppression effect on wind and solar power output fluctuations; and in the islanding mode, the black start success rate and reserve capacity availability rate are used to evaluate the resilience under extreme operating conditions.

[0314] like Figure 5 and Figure 6 As shown, in one embodiment of the present invention, economic efficiency and quality together constitute the comprehensive value assessment system for energy storage power stations. At the economic level, it breaks through traditional cost analysis by proposing a "Cost Per Cycle (CSC)" model to quantify the economic efficiency of charging and discharging, and combines "carbon emission reduction efficiency coefficient" and "grid upgrade substitution value" to expand the assessment of environmental and social benefits. At the quality level, it focuses on power quality and energy conversion efficiency, systematically evaluating the role of energy storage in improving grid power quality through indicators such as charge-discharge cycle efficiency, voltage fluctuation suppression rate, and total harmonic distortion (THD).

[0315] The above are preferred embodiments of the present invention. Any changes made to the technical solution of the present invention that do not exceed the scope of the technical solution of the present invention shall fall within the protection scope of the present invention.

Claims

1. An evaluation method for energy storage power stations based on grid-grid-storage systems, characterized in that, Includes the following: The evaluation of energy storage power stations is conducted from three aspects: energy storage system, grid interface, and load support. This includes setting reliability indicators, coordination indicators, quality indicators, and economic indicators for energy storage power stations. Finally, a score for the operational performance of the energy storage power station is calculated based on subjective and objective weights.

2. The evaluation method for energy storage power stations based on grid-grid load according to claim 1, characterized in that, The reliability indicators for energy storage power stations include the following: Developing reliability indicators for energy storage power stations includes calculating the annual charge and discharge efficiency of energy storage units, calculating the grid interface failure outage rate, and calculating the load support deficit rate. The calculation of the annual charge-discharge efficiency of the energy storage unit includes: Assume the rated capacity of the energy storage unit is , The unit is kWh, and the rated number of cycles is The theoretical annual rated discharge is: ； Among the variables For design efficiency, charging and discharging losses are taken into account; The actual annual discharge capacity (Eanua,actual) can be obtained through monitoring data; furthermore, the annual charge-discharge efficiency is: ； Among them, the annual charge-discharge efficiency reflects the degree of performance degradation of the energy storage system over long-term operation and is a core parameter for assessing the health status of the equipment. The calculation of the power grid interface fault outage rate includes: The converter's failure downtime rate is defined as: ； in, This refers to the annual cumulative downtime due to faults in the converter. Total annual operating time; Furthermore, by combining the redundancy configuration strategy to analyze the grid interface failure outage rate, and using the N+1 redundancy design correction formula, the availability factor A is obtained. inv The expression: ； Where the availability factor is N is the number of redundant devices and the availability factor. Used to evaluate system-level reliability.

3. The evaluation method for energy storage power stations based on grid-grid load according to claim 2, characterized in that, The development of reliability indicators for energy storage power stations also includes the following: The calculation of the load support deficit rate includes: The deficit rate for energy storage power stations is defined as follows: ； in, Electricity demand from the load; This represents the actual power supply from energy storage. Furthermore, the shortfall rate is revised, including the following: ； in The revised deficit rate reflects the differentiated guarantee capacity for different levels of load.

4. The evaluation method for energy storage power stations based on grid-grid load according to claim 1, characterized in that, The following are included in the formulation of coordination indicators for energy storage power stations: The formulation of coordination indicators for energy storage power stations includes calculating power response accuracy, calculating energy time-shift efficiency, and calculating multi-timescale coordination. The accuracy of power response calculation includes: Define the deviation rate between the actual output power (Pactua) of the energy storage system and the dispatch command (Pe): ； Furthermore, for second-level frequency modulation applications satisfying Δt=1s, a dynamic weighting function f(t) is introduced to correct the deviation rate, resulting in: ； Among them, f(t) can be dynamically adjusted according to the frequency regulation needs of the power grid, including increasing the weight during peak periods; The calculation of energy time-shift efficiency includes: Peak-hour electricity pricing Off-peak electricity prices The energy storage charging and discharging efficiency is The theoretical gain is: ； The design time-shift efficiency is defined as the ratio of the actual revenue Ractua to the theoretical maximum value Rm. ； Among them, time-shift efficiency is combined with an electricity price fluctuation model for Monte Carlo simulation to evaluate long-term economic viability; Calculating multi-timescale consistency includes: Define the multi-timescale reconciliation factor K: ； in and These represent short-time and long-time control efficiencies, respectively, and are reference values. and Determined by historical best data; multi-timescale coordination is used to quantify the comprehensive coordination capability of energy storage systems under complex operating conditions.

5. The evaluation method for energy storage power stations based on grid-grid load according to claim 1, characterized in that, The quality indicators for energy storage power stations include the following: The quality indicators for energy storage power stations include calculating dynamic voltage regulation accuracy, harmonic interaction suppression rate, frequency tracking accuracy, and equipment operating efficiency attenuation rate. The calculation of dynamic voltage regulation accuracy includes defining the dynamic voltage deviation rate: ； in The voltage value is the dispatch command voltage value. This is the actual output voltage; The calculation of harmonic interaction suppression rate includes: ； in The background harmonic distortion rate of the power grid. The measured total harmonic distortion rate at the grid connection point; The calculation of frequency tracking accuracy includes: ； in It is a reverse harmonic current; This refers to the h-th harmonic current on the power grid side. Furthermore, the total harmonic suppression efficiency is the weighted sum of the suppression rates of each harmonic: ； in The weight of the h-th harmonic; The calculation of frequency tracking accuracy also includes: Define the root mean square value of frequency deviation : ； Among them, when ≤0.05Hz is considered to meet the primary frequency modulation requirements; Furthermore, when the energy storage power station participates in secondary frequency regulation, the accumulated phase error is constrained; ； in This refers to the cumulative phase error; The calculation of equipment operating efficiency degradation rate includes: Define efficiency annual decay rate : ； in For initial charge / discharge efficiency, Annual measured efficiency; Furthermore, the Arrhenius model is used to express the mathematical relationship between efficiency decay and the number of cycles (Ncycle) and depth of discharge (DOD): ； Where k is the material coefficient, E is the activation energy, and R is the gas constant. This refers to the operating temperature.

6. The evaluation method for energy storage power stations based on energy storage grid load according to claim 1, characterized in that, The economic indicators for energy storage power stations include the following: Developing economic indicators for energy storage power stations includes calculating the levelized cost per kilowatt-hour, calculating the revenue dynamic model, and calculating the return on investment. Computational battery degradation and risk management; The calculation of the levelized cost of electricity includes: Define the average cost per unit of discharge over the entire lifecycle, LCOS, where the LCOS expression is: ； The present value of total cost includes: initial investment and residuals; Furthermore, based on the initial investment, the operation and maintenance costs are calculated using an annual growth rate model and allocated over the construction period, yielding the following results: ； in, γ represents the initial investment; k is the operation and maintenance coefficient, with a value ranging from 2% to 5%; γ is the annual growth rate, with an optimal value of 3%. According to the linear depreciation model, the residual value is: ； in Represents residual value; Indicates the assumed lifespan; The present value of the total discharge includes: Considering capacity decay and efficiency loss, calculate the annual discharge: ； in, Annual discharge amount; For rated capacity, The unit is: MWh; in For charge / discharge cycle efficiency; This refers to the annual capacity decay rate. Let t be the number of cycles in year t. The calculation of dynamic profit models and investment returns includes the following: Energy storage revenue includes electricity sales revenue, ancillary service revenue, and policy subsidies. Based on market mechanism modeling, the following results are obtained: Electricity sales revenue: ； in For time-of-use pricing; further, based on geometric Brownian motion simulation of random fluctuations, the following is obtained: ； Where μ is the average annual growth rate of electricity prices, and σ is the volatility. For Wiener process; Ancillary service revenue includes frequency regulation and reserve capacity compensation: ； in This is for compensation of the reserve capacity in year t; For the frequency modulation in year t; The unit price for FM service; Dynamic payback period: The dynamic payback period is defined as the number of years from which the net present value (NPV) becomes zero through iterative solutions. ； in The discount rate; This represents the net income in year t. The calculation of battery degradation and risk management includes calculating the unit cycle degradation cost, including: ； Define the expression for the actual cycle lifetime depth of discharge: ； in This represents the actual cycle life depth of discharge.

7. The evaluation method for energy storage power stations based on energy storage grid load according to claim 1, characterized in that, The scoring of the energy storage power station's operational performance, based on subjective and objective weights, includes the following: The subjective weighting method and the objective weighting method are used to calculate the score of the operation effect of the energy storage power station; The subjective weighting method compares the importance of adjacent indicators one by one to determine the importance ratio coefficient of adjacent indicators, and then recursively calculates the importance coefficient of each indicator. Finally, the weight of each indicator is obtained through normalization, including the following: Calculate the ranking and importance score of the indicators, then calculate the corrected score, and finally calculate the total corrected score and normalized weight. The ranking and importance score of the calculated indicators include: The indicators are arranged in descending order of importance as follows: Then, for adjacent indicators and The importance of the score is scored and a ratio is defined. : ； The corrected score calculation includes: The scoring is revised iteratively starting with the most important indicators. : ; ; The calculation of the total corrected score and normalized weights includes: Calculate the total corrected score ; Then the normalized weights are obtained. ; in This represents the normalized weight.

8. The evaluation method for an energy storage power station based on grid-connected energy storage according to claim 7, characterized in that, The scoring of energy storage power station operation performance based on subjective and objective weights also includes the following: The calculation of objective weights using the entropy weight method includes the following: By calculating the entropy value and difference coefficient of each indicator, the objective fluctuation characteristics of the data are transformed into weight coefficients, including first standardizing the data; then calculating the entropy value; and finally defining the difference coefficient and calculating the objective weight. Data standardization includes: For the original data matrix Normalize: ； The entropy calculation includes: Calculate the entropy value of the j-th index: ； in Entropy is a value that reflects the degree of disorder in the data distribution. The definition of the difference coefficient and the calculation of the objective weights include: ； ； in The coefficient of variation; For objective weighting.

9. The evaluation method for an energy storage power station based on grid-grid load according to claims 1 to 8, characterized in that, The method also includes the following: Step S1: Develop reliability indicators for energy storage power stations, including calculating the annual charge and discharge efficiency of energy storage units, calculating the grid interface failure outage rate, and calculating the load support deficit rate. Step S2: Develop coordination indicators for energy storage power stations, including calculating power response accuracy, calculating energy time-shift efficiency, and calculating multi-timescale coordination. Step S3: Develop quality indicators for energy storage power stations, including calculating dynamic voltage regulation accuracy, harmonic interaction suppression rate, frequency tracking accuracy, and equipment operating efficiency attenuation rate. Step S4: Develop economic indicators for energy storage power stations, including calculating the levelized cost of electricity (LCOE), calculating the revenue dynamic model and return on investment; and calculating battery degradation and risk management. Step S5: Calculate the score of the energy storage power station's operating performance based on subjective and objective weights, including calculating the score of the energy storage power station's operating performance using the subjective weight method and the objective weight method.

10. An evaluation system for energy storage power stations based on grid-grid-load, used to execute the evaluation method for energy storage power stations based on grid-grid-load as described in claims 1 to 8, characterized in that, An energy storage power station evaluation system based on energy storage grid load includes an energy storage power station reliability evaluation module, an energy storage power station coordination evaluation module, an energy storage power station quality evaluation module, an energy storage power station economic evaluation module, and an energy storage power station operation effect evaluation module. The reliability evaluation module for energy storage power stations evaluates the reliability of energy storage power stations by calculating the annual charge and discharge efficiency of energy storage units, the outage rate due to grid interface failures, and the load support deficit rate. The energy storage power station coordination evaluation module evaluates the coordination of energy storage power stations by calculating power response accuracy, energy time-shift efficiency, and multi-timescale coordination. The energy storage power station quality evaluation module evaluates the quality of the energy storage power station by calculating the dynamic voltage regulation accuracy, harmonic interaction suppression rate, frequency tracking accuracy, and equipment operating efficiency attenuation rate. The energy storage power station economic evaluation module evaluates the economics of energy storage power stations by calculating the levelized cost per kilowatt-hour, calculating the revenue dynamic model and return on investment, and calculating battery degradation and risk management. The energy storage power station operation performance evaluation module evaluates the operation performance of energy storage power stations by calculating a score based on subjective and objective weights.

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