Energy storage income evaluation and cost recovery capacity compensation method and system

Abstract

The invention provides an energy storage income evaluation and cost recovery capacity compensation method and system. The method comprises the following steps: calculating a difference value between the total annual income and the average annual cost of fixed assets as an expected compensation difference; if the expected compensation difference is greater than zero, converting the expected compensation difference into cost view angle compensation unit price based on energy storage rated power, and determining reliability view angle compensation unit price according to system power shortage time and system power shortage quantity provided by the power system; taking the larger one of the cost view angle compensation unit price and the reliability view angle compensation unit price as a final reference unit price; the grading coefficient is determined according to grading of the daily average energy storage duration of the current year, the annual price floating coefficient is determined according to the electricity price floating of the current year, and finally the energy storage compensation unit price is determined. According to the invention, the problems of uncertain energy storage investment return and insufficient capacity compensation level in the current power system are solved, and accurate matching of capacity compensation and project cost is realized.

Description

Technical Field

[0001] The present invention belongs to the field of power system energy storage participating in the power market, and in particular relates to a method and system for energy storage revenue evaluation and cost recovery capacity compensation. Background Art

[0002] Currently, the installed capacity of renewable energy sources such as wind power and photovoltaics is rapidly expanding, and their economic efficiency and competitiveness are increasing. They are gradually evolving from supplementary energy sources to the main energy source in new power systems. However, the inherent volatility, intermittency, and uncertainty of renewable energy pose severe challenges to the power grid, such as large power fluctuations and increased peak-to-valley differences. Energy storage power stations, with their excellent energy time-shifting and bidirectional regulation capabilities, have become a key technical means to enhance system flexibility and absorb renewable energy. However, the large-scale deployment of energy storage systems faces long investment payback cycles, unclear business models and revenue mechanisms, and unquantifiable risks. These issues have directly limited the willingness of social capital to invest in the energy storage sector and have become a major obstacle to its development. Summary of the Invention

[0003] In view of the deficiencies of the existing technology, the present invention provides a method and system for energy storage revenue evaluation and cost recovery capacity compensation.

[0004] In a first aspect, the present invention provides a method for energy storage revenue assessment and cost recovery capacity compensation, comprising: Obtain the annual revenue set and average annual cost of fixed assets for the energy storage project in that year; The total annual income is obtained by weighted summing up the various incomes in the annual income set; Calculate the difference between the total annual income and the average annual cost of the fixed assets as the expected compensation difference; If the expected compensation difference is greater than zero, converting the expected compensation difference into a compensation unit price from a cost perspective based on the energy storage rated power, and determining a compensation unit price from a reliability perspective based on the system power shortage time and system power shortage amount provided by the power system; The larger of the cost-perspective compensation unit price and the reliability-perspective compensation unit price is taken as the final benchmark unit price; Determine the tier coefficient based on the average daily duration of energy storage in that year, and determine the annual price fluctuation coefficient based on the electricity price fluctuation in that year; and determine the energy storage compensation unit price based on the final benchmark unit price, the tier coefficient, and the annual price fluctuation coefficient; The energy storage capacity compensation benefit is obtained by multiplying the energy storage compensation unit price and the maximum charge and discharge power of the energy storage.

[0005] As a preferred embodiment, the calculation formula of the final benchmark unit price CP is: ; in, is the compensation unit price from the cost perspective in year y, is the expected compensation difference, PES represents the maximum charging and discharging power of energy storage; is the unit price of reliability perspective compensation in year y; The social and economic losses or standby fines caused by 1 hour of load loss, is the economic loss caused by 1MWh of unpowered electricity; LOLE is the system power outage time; EENS is the system power outage amount.

[0006] As a preferred embodiment, the energy storage compensation unit price The calculation formula is: ; Where, is the annual floating coefficient, is the binning coefficient, CP max and CP min The upper and lower limits of the preset energy storage compensation unit price.

[0007] As a preferred embodiment, the grading method for determining the grading coefficient according to the daily duration of energy storage is expressed as follows: ; Among them, dur represents the average daily duration of energy storage. 、 、 They are respectively the preset first bin coefficient, second bin coefficient and third bin coefficient.

[0008] As a preferred embodiment, the calculation formula of the annual price fluctuation coefficient is: ; in, is the electricity price fluctuation in year y, is the electricity price fluctuation in the contract year, and s is the sensitivity coefficient.

[0009] As a preferred embodiment, the annual income set R is expressed as: ; Among them, RE represents energy storage electricity revenue, AS represents energy storage ancillary service revenue, CM represents capacity market revenue, and CR represents carbon emission reduction revenue.

[0010] As a preferred embodiment, the calculation formula for the average annual cost of fixed assets is: ; CAPEX refers to the construction investment of an energy storage project, and OPEX refers to the annual operation and maintenance cost of an energy storage project.

[0011] As a preferred embodiment, the method further includes: The evaluation coefficients are the annualized volatility of electricity prices, the annual average utilization rate and the capacity value reduction factor; For each evaluation coefficient, construct a coefficient offset scenario and obtain the energy storage compensation unit price under the coefficient offset scenario; Determine the coefficient impact percentage of each assessment coefficient based on the energy storage compensation unit price under the coefficient baseline scenario and each coefficient offset scenario; The importance of each evaluation coefficient is ranked according to the coefficient influence percentage.

[0012] As a preferred embodiment, the calculation formula of the coefficient influence percentage is: ; in, is the coefficient influence percentage, The unit price of energy storage compensation is obtained under the scenario of coefficient offset of +20%. The unit price of energy storage compensation is obtained under the scenario of coefficient offset of -20%. is the unit price of energy storage compensation obtained under the coefficient benchmark scenario.

[0013] In a second aspect, the present invention provides an energy storage revenue assessment and cost recovery capacity compensation system, which includes: The acquisition module is used to obtain the annual revenue set of the energy storage project and the average annual cost of fixed assets in the current year; An annual revenue total amount calculation module, configured to obtain the annual revenue total amount by weighted summing up each revenue in the annual revenue set; an expected compensation difference calculation module, configured to calculate the difference between the total annual income and the average annual cost of the fixed assets as the expected compensation difference; a compensation unit price determination module, configured to convert the expected compensation difference into a cost-perspective compensation unit price based on the energy storage rated power if the expected compensation difference is greater than zero, and determine the reliability-perspective compensation unit price based on the system power shortage time and system power shortage amount provided by the power system; a final benchmark unit price determination module, configured to take the larger of the cost perspective compensation unit price and the reliability perspective compensation unit price as the final benchmark unit price; An energy storage compensation unit price determination module is configured to determine a tier coefficient based on the average daily duration of energy storage in that year, and an annual price fluctuation coefficient based on the electricity price fluctuation in that year; and to determine the energy storage compensation unit price based on the final benchmark unit price, the tier coefficient, and the annual price fluctuation coefficient; The energy storage capacity compensation benefit determination module is used to multiply the energy storage compensation unit price and the maximum charge and discharge power of the energy storage to obtain the energy storage capacity compensation benefit.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention provides a method and system for energy storage revenue assessment and cost recovery capacity compensation. This method addresses the current problems of uncertain energy storage investment returns and insufficient capacity compensation in power systems, achieving a precise match between capacity compensation and project costs.

[0015] 2. This invention determines an annual revenue set from four revenue dimensions: electricity arbitrage, ancillary services, capacity value, and carbon reduction. It then weights and sums each benefit to arrive at a total annual revenue. This total annual revenue is then reconciled with the average annual cost of fixed assets (ACC) on a year-by-year basis to automatically generate the expected compensation difference. Compared to traditional methods that rely on a single arbitrage calculation, this closed-loop approach significantly reduces revenue estimation bias, avoids miscalculation of investment returns, and provides an objective, systematic, and quantitative starting point for subsequent capacity compensation pricing.

[0016] 3. This invention simultaneously compares compensation unit prices from both a cost perspective and a reliability perspective during pricing. Compensation results are differentiated and adjusted for market conditions using tiered coefficients and annual price fluctuation coefficients. When market volatility increases or the average daily duration of energy storage increases, the compensation unit price automatically increases, while when it decreases, it automatically recovers, achieving precise compensation. This mechanism ensures that energy storage investors receive a full return while effectively controlling the upper limit of capacity market expenditures.

[0017] 4. This invention determines the sensitivity of each assessment coefficient to the energy storage compensation unit price based on the coefficient influence percentage, thereby ranking the three important indicators and finding the factor with the greatest impact on the energy storage compensation unit price in that year, thereby providing an intuitive risk ranking and credit basis. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flow chart of a method for energy storage revenue evaluation and cost recovery capacity compensation in an embodiment of the present invention; Figure 2 A flowchart for determining the difference between the total annual income and the average annual cost of fixed assets in an embodiment of the present invention; Figure 3 Flowchart for determining the energy storage compensation unit price in an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention.

[0020] Among the existing technologies known to the inventors of the present invention, the current technologies for energy storage revenue assessment and capacity compensation mainly have the following problems. First, the existing dimensions for energy storage revenue assessment are single, and factors such as quantified capacity value, carbon emission reduction benefits, and value-added services are not fully considered, resulting in an inability to accurately match fixed costs; second, there is a lack of sensitivity analysis of key assumptions such as electricity price fluctuations and energy storage utilization, which makes it impossible for investors to quantify the risks of energy storage projects, resulting in a forced reduction in financing ratios. Therefore, in order to solve the above problems, a method for energy storage revenue assessment and cost recovery capacity compensation is urgently needed.

[0021] Combine Figure 1 This embodiment provides a method for energy storage revenue evaluation and cost recovery capacity compensation, including the following steps: S1. Data is collected based on the data acquisition module. The collected data is mainly divided into four parts. The first is the technical parameters of the energy storage project, including the maximum charge / discharge power of the energy storage, the rated capacity of the energy storage, the round-trip efficiency, the designed cycle life, and the capacity decay curve. The second is the economic parameters that determine the project cost structure, including the construction cost, operation and maintenance cost, discount rate, and asset life of the energy storage project. Then there are the market parameters that determine the revenue structure, including the time-of-use electricity price sequence, the capacity market bid price, and the ancillary service price. Finally, there are the power system parameters, including the expected number of hours of load loss per year, the expected annual unpowered electricity, and the regional carbon emission factor.

[0022] S2. Evaluate energy storage projects based on a multi-dimensional benefit assessment module, and determine the annual benefit set of energy storage projects based on energy storage electricity benefits, energy storage ancillary service benefits, capacity market benefits, and carbon emission reduction benefits.

[0023] S3. Calculate the cost based on the investment cost calculation module and convert the economic parameters collected in step S1 into the average annual cost of fixed assets (ACC) as a benchmark for subsequent annual cost differences and capacity compensation.

[0024] S4. The cost recovery difference identification module determines the energy storage project's profitability. The total annual revenue, obtained by weighted summation of the various benefits in the annual revenue set obtained in step S2, is compared with the average annual cost of fixed assets obtained in step S3 to determine whether the energy storage project is breaking even. If the total annual revenue is not less than the average annual cost of fixed assets, the annual revenue covers the project's fixed costs. If the total annual revenue is less than the average annual cost of fixed assets, the energy storage project has a cost shortfall and requires capacity compensation to cover the cost. The process then proceeds to step S5 for compensation.

[0025] S5. Compensate the cost gap based on the capacity compensation module, link the cost gap obtained in step S4 with the system reliability, and calculate the energy storage compensation unit price that can be obtained by energy storage.

[0026] S6. Based on the sensitivity analysis and risk assessment module, sensitivity analysis and risk assessment are conducted on the evaluation parameters that affect the energy storage compensation unit price, the impact of key uncertainties on the energy storage compensation unit price and financial indicators is quantified, and confidence intervals and sensitivity rankings are output, thereby providing a basis for capital parties to set compensation caps and financing discounts.

[0027] Specifically, step S1 includes the following steps: S1.1. Collect energy storage technical parameters to obtain rated performance of energy storage, including maximum charge / discharge power , initial rated capacity ; and use the exponential decay model to design the energy storage capacity decay coefficient : ; in, is the total attenuation ratio, is the decay time constant and t is the time period.

[0028] S1.2. Collect project investment and financial plans, including construction investment cost (CAPEX), annual operation and maintenance cost (OPEX), discount rate r, and expected economic life n.

[0029] S1.3. Electricity market parameter collection: specifically including time-of-use electricity price series , Ancillary Services Benchmark Price , Capacity winning bid price and carbon prices ; This embodiment collects the above-mentioned electricity market parameters with a time resolution of 15 minutes.

[0030] All data collected in step S1 are input into a data set for use in subsequent steps. The data input of this embodiment supports three modes: manual entry, batch file import, and on-site real-time collection, ensuring the feasibility and versatility of the method.

[0031] Furthermore, step S2 specifically includes the following steps: S2.1, design the electricity arbitrage optimization model, based on the time-of-use electricity price sequence collected in step S1 As input, the energy storage charging / discharging power / Establish optimization objective function with state of charge SOC F 1 , the formula is as follows: ; Where t is the time period, , is the peak / valley electricity price, For the running time, is the round-trip efficiency of the energy storage device; the corresponding constraints are as follows: ; Based on the constraints, the optimization objective function is solved to obtain the optimal discharge energy. , the energy storage revenue RE is further calculated based on the optimal discharge energy, and the calculation formula is: ; S2.2. Calculate the energy storage ancillary service income. The energy storage ancillary service income AS is based on the effective capacity ratio of energy storage participating in the kth type of ancillary service (such as frequency regulation, peak regulation, backup, etc.) during a certain period of time t within the year. The specific calculation formula is as follows: ; Among them, AS is the income from energy storage participating in auxiliary services. For the period t Participate in k The service benchmark price corresponding to this type of auxiliary services.

[0032] S2.3. Calculate the capacity market revenue. The formula for capacity market revenue is as follows: ; in, The effective capacity reduction coefficient is determined according to market rules. When the energy storage project does not participate in the capacity market, Can be set to 0.

[0033] S2.4. Calculate the carbon emission reduction benefits. Energy storage can be equivalent to reducing the power generation of thermal power units while discharging. The calculation formula for carbon emission reduction benefits is as follows: ; in, is the carbon emission factor, is the carbon price.

[0034] The calculation results of steps S2.1-S2.4 are summarized to obtain the annual benefit set, which is used as the multi-dimensional benefit evaluation of the energy storage project. The specific formula of the annual benefit set R is as follows: ; Specifically, step S3 includes the following steps: S3.1. First, calculate the capital recovery factor (CRF) based on the discount rate and the project's estimated economic lifespan, so that the one-time construction investment can be converted into an equivalent annual cost. The formula is as follows: ; Where r is the discount rate and n is the expected economic life of the energy storage project; S3.2. The average annual fixed asset cost ACC of the energy storage project is then calculated based on the capital recovery factor CRF. The specific formula is as follows: ; Among them, CAPEX is the construction investment of the energy storage project, and OPEX is the annual operation and maintenance cost of the energy storage project.

[0035] S3.3. In order to measure the lifecycle cost per unit of discharged electricity, the levelized cost of storage (LCOS) of the energy storage project is calculated using the following formula: ; The ACC (average annual cost of fixed assets) obtained from S3.1 to S3.3 is used as the cost baseline in the cost recovery difference identification module in step S4.

[0036] Further, combined with Figure 2 , step S4 specifically includes the following steps: S4.1. Take the weighted sum of each income in the annual income set obtained in step S2 to obtain the total annual income for year y: ; in, is the total annual income in year y, are the energy storage electricity revenue, energy storage ancillary service revenue, capacity market revenue and carbon emission reduction revenue in year y respectively; S4.2. Identify the annual cost difference. Subtract the average annual cost of fixed assets ACC obtained in S3 from the total annual income to obtain the expected compensation difference in year y: ; like =0, it means that the total annual revenue in year y can cover the project fixed cost; like >0, it means that there is a cost gap in the energy storage project and capacity compensation is needed to subsidize the cost, and then proceed to step S5.

[0037] This method determines an annual revenue set based on four revenue dimensions: electricity arbitrage, ancillary services, capacity value, and carbon reduction. This is then reconciled year-over-year with the average annual cost of fixed assets (ACC) to automatically generate the expected compensation difference. Compared to traditional methods that rely on a single arbitrage calculation, this closed-loop approach significantly reduces revenue estimation bias, avoids miscalculation of investment returns, and provides an objective, systematic, and quantitative starting point for subsequent capacity compensation pricing.

[0038] Specifically, combined Figure 3 , step S5 specifically includes the following steps: S5.1. Determine the cost compensation unit price based on the investor, and obtain the annual difference based on step S4. , according to the energy storage rated power The unit price of compensation from the cost perspective is converted and the calculation formula is: ; in, The compensation unit price from the cost perspective in year y; S5.2. Determine the reliability compensation unit price based on the power system. The reliability compensation unit price is determined by the power system's system out-of-line time (LOLE) and system out-of-line energy (EENS). The calculation formula is: ; in, is the unit price of reliability perspective compensation in year y, The social and economic losses or standby fines caused by 1 hour of load loss, =Economic loss caused by 1 MWh of unavailable electricity.

[0039] S5.3. Benchmark compensation unit price and dynamic adjustment. Compare the cost perspective compensation unit price and reliability perspective compensation unit price obtained in S5.1 and S5.2 respectively to obtain the final benchmark unit price CP. The formula is as follows: ; In addition, due to differences in energy storage technologies, it is difficult to increase the energy storage electricity revenue obtained by electricity arbitrage at the same rate. The grading coefficient needs to be determined based on the average daily duration of energy storage in that year. , the classification method is as follows: ; Among them, dur represents the average daily duration of energy storage. 、 、 They are respectively the preset first bin coefficient, second bin coefficient and third bin coefficient.

[0040] In addition, it is necessary to design the annual price fluctuation coefficient according to the electricity price fluctuation of the year. The specific formula is as follows: ; in, is the electricity price fluctuation in year y, is the electricity price fluctuation obtained in advance for the contract year, and s is the preset sensitivity coefficient.

[0041] Finally, the energy storage compensation unit price is determined based on the final benchmark unit price, tier coefficient and annual price fluctuation coefficient. .

[0042] ; in, and They are respectively the lower limit and upper limit of the pre-set energy storage compensation unit price.

[0043] S5.4. Energy storage compensation unit price Multiplying the maximum charge and discharge power of the energy storage system yields the energy storage capacity compensation benefit. The energy storage capacity compensation benefit calculation formula is as follows: ; Through the above steps S5.1 to S5.4, it is possible to ensure that the compensation amount is sufficient to cover the actual cost gap, and the payment level is proportional to the degree to which energy storage improves system reliability. It can also be adaptively adjusted with market fluctuations and technological differences to achieve the design goal of precise compensation.

[0044] This embodiment uses a dual-perspective comparison of "compensation unit price from a cost perspective" and "compensation unit price from a reliability perspective" in the pricing phase, and determines the tier coefficient based on the average daily duration of energy storage. and the annual price fluctuation coefficient Compensation results are differentiated and adjusted based on market conditions. When market volatility increases or the average daily duration of energy storage increases, the compensation price is automatically adjusted upwards, while when it decreases, it is automatically withdrawn, thus achieving precise compensation. This mechanism in this embodiment ensures that energy storage investors receive a full return while effectively controlling the upper limit of capacity market expenditures.

[0045] Furthermore, step S6 specifically includes the following steps: Step S6 performs a sensitivity assessment on the three key assumptions of annualized electricity price volatility, annual average utilization rate, and capacity value reduction factor. It specifically includes three sub-steps S6.1 to S6.3 to reveal the main factors affecting the compensation unit price CP′, thereby providing a quantitative basis for the contract terms.

[0046] S6.1. Determine the electricity price volatility , average annual utilization rate of energy storage and capacity attenuation coefficient Three important indicators are used as evaluation coefficients to conduct sensitivity analysis of the unit price of energy storage compensation.

[0047] S6.2. Construct coefficient offset scenarios. In each scenario, set one of the evaluation coefficients A 20% offset is used, and the rest remain at the base value. The coefficient offset scenario is constructed as follows:

[0048] S6.3. For the above six offset scenarios, call the entire process of S2-S5 respectively to obtain the corresponding energy storage compensation unit price under each offset scenario , in order to calculate the coefficient impact percentage of each evaluation coefficient. The calculation formula of the coefficient impact percentage is as follows: ; in, is the coefficient influence percentage, The unit price of energy storage compensation is obtained under the scenario of coefficient offset of +20%. The unit price of energy storage compensation is obtained under the scenario of coefficient offset of -20%. is the unit price of energy storage compensation obtained under the coefficient benchmark scenario.

[0049] The sensitivity of each assessment coefficient to the energy storage compensation unit price is determined based on the coefficient impact percentage, thereby ranking the three important indicators and identifying the factors that have the greatest impact on the energy storage compensation unit price in that year. This embodiment uses a sensitivity analysis method to quickly identify the main sensitive factors of the energy storage compensation unit price, providing an intuitive risk ranking and credit granting basis.

[0050] In another specific embodiment, this embodiment provides an energy storage benefit evaluation and cost recovery capacity compensation system, which includes a data acquisition module, an energy storage project multi-dimensional benefit evaluation module, an investment cost calculation module, a cost recovery difference identification module, a capacity compensation module, and a sensitivity analysis and risk assessment module to respectively execute S1, S2, S3, S4, S5 and S6 described above.

[0051] Those skilled in the art will appreciate 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 aspects. 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.

[0052] 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 1a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0053] 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.

[0054] 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.

[0055] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present invention and the claims, which are all protected by the present invention.

Claims

1. A method for energy storage revenue assessment and cost recovery capacity compensation, characterized in that: include: Obtain the annual revenue set and average annual cost of fixed assets for the energy storage project in that year; The total annual income is obtained by weighted summing up the various incomes in the annual income set; Calculate the difference between the total annual income and the average annual cost of the fixed assets as the expected compensation difference; If the expected compensation difference is greater than zero, converting the expected compensation difference into a compensation unit price from a cost perspective based on the energy storage rated power, and determining a compensation unit price from a reliability perspective based on the system power shortage time and system power shortage amount provided by the power system; The larger of the cost-perspective compensation unit price and the reliability-perspective compensation unit price is taken as the final benchmark unit price; The tier coefficient is determined based on the average daily duration of energy storage in that year, and the annual price fluctuation coefficient is determined based on the electricity price fluctuation in that year; Determine the energy storage compensation unit price based on the final benchmark unit price, tier coefficient, and annual price fluctuation coefficient; The energy storage capacity compensation benefit is obtained by multiplying the energy storage compensation unit price and the maximum charge and discharge power of the energy storage.

2. The energy storage benefit evaluation and cost recovery capacity compensation method according to claim 1 is characterized in that: The calculation formula of the final benchmark unit price CP is: ； in, is the compensation unit price from the cost perspective in year y, is the expected compensation difference, PES represents the maximum charging and discharging power of energy storage; is the unit price of reliability perspective compensation in year y; The social and economic losses or standby fines caused by 1 hour of load loss, is the economic loss caused by 1MWh of unpowered electricity; LOLE is the system power outage time; EENS is the system power outage amount.

3. The energy storage benefit evaluation and cost recovery capacity compensation method according to claim 2 is characterized in that: The energy storage compensation unit price The calculation formula is: ； Where, is the annual floating coefficient, is the binning coefficient, CP max and CP min They are respectively the upper and lower limits of the preset energy storage compensation unit price.

4. The energy storage benefit evaluation and cost recovery capacity compensation method according to claim 3 is characterized in that: The grading method for determining the grading coefficient according to the daily duration of energy storage is expressed as follows: ； Among them, dur represents the average daily duration of energy storage. 、 、 They are respectively the preset first bin coefficient, second bin coefficient and third bin coefficient.

5. The energy storage benefit evaluation and cost recovery capacity compensation method according to claim 3 is characterized in that: The calculation formula for the annual price fluctuation coefficient is: ； in, is the electricity price fluctuation in year y, is the electricity price fluctuation in the contract year, and s is the sensitivity coefficient.

6. The energy storage benefit evaluation and cost recovery capacity compensation method according to claim 1 is characterized in that: The annual income set R is expressed as: ； Among them, RE represents energy storage electricity revenue, AS represents energy storage ancillary service revenue, CM represents capacity market revenue, and CR represents carbon emission reduction revenue.

7. The energy storage benefit evaluation and cost recovery capacity compensation method according to claim 1 is characterized in that: The calculation formula for the average annual cost of fixed assets is: ； CAPEX refers to the construction investment of an energy storage project, and OPEX refers to the annual operation and maintenance cost of an energy storage project.

8. The energy storage benefit evaluation and cost recovery capacity compensation method according to claim 1 is characterized in that: The method further comprises: The evaluation coefficients are the annualized volatility of electricity prices, the annual average utilization rate and the capacity value reduction factor; For each evaluation coefficient, construct a coefficient offset scenario and obtain the energy storage compensation unit price under the coefficient offset scenario; Determine the coefficient impact percentage of each assessment coefficient based on the energy storage compensation unit price under the coefficient baseline scenario and each coefficient offset scenario; The importance of each evaluation coefficient is ranked according to the coefficient influence percentage.

9. The energy storage benefit evaluation and cost recovery capacity compensation method according to claim 8, characterized in that: The calculation formula for the coefficient influence percentage is: ； in, is the coefficient influence percentage, The unit price of energy storage compensation is obtained under the scenario of coefficient offset of +20%. The unit price of energy storage compensation is obtained under the scenario of coefficient offset of -20%. is the unit price of energy storage compensation obtained under the coefficient benchmark scenario.

10. An energy storage revenue assessment and cost recovery capacity compensation system, characterized in that: include: The acquisition module is used to obtain the annual revenue set of the energy storage project and the average annual cost of fixed assets in the current year; An annual revenue total amount calculation module, configured to obtain the annual revenue total amount by weighted summing up each revenue in the annual revenue set; an expected compensation difference calculation module, configured to calculate the difference between the total annual income and the average annual cost of the fixed assets as the expected compensation difference; a compensation unit price determination module, configured to convert the expected compensation difference into a cost-perspective compensation unit price based on the energy storage rated power if the expected compensation difference is greater than zero, and determine the reliability-perspective compensation unit price based on the system power shortage time and system power shortage amount provided by the power system; a final benchmark unit price determination module, configured to take the larger of the cost perspective compensation unit price and the reliability perspective compensation unit price as the final benchmark unit price; The energy storage compensation unit price determination module is used to determine the tier coefficient based on the average daily duration of energy storage in that year, and to determine the annual price fluctuation coefficient based on the electricity price fluctuation in that year; Determine the energy storage compensation unit price based on the final benchmark unit price, tier coefficient, and annual price fluctuation coefficient; The energy storage capacity compensation benefit determination module is used to multiply the energy storage compensation unit price and the maximum charge and discharge power of the energy storage to obtain the energy storage capacity compensation benefit.

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