Energy storage participated electric power spot market evaluation method and related system

Abstract

The invention belongs to the field of electric power automation, and discloses an energy storage participated electric power spot market evaluation method and a related system, which can comprehensively reflect the performance of an energy storage power station in an electric power spot market by acquiring multi-dimensional data such as daily average net income, daily average charging and generating capacity, average response time, safety capacity, peak-valley average price difference and the like. The multi-angle analysis can help a decision maker and an investor to know the actual operation state of energy storage and the contribution of the energy storage to the market. And the weight of each index is calculated through a mean square error method, so that the influence of subjective weight distribution is avoided, and the evaluation is more scientific and objective. Based on accurate weight distribution, each key index can be ensured to play a proper role in comprehensive evaluation, so that more reliable comprehensive performance evaluation of the energy storage power station is provided. According to the method, the defects of high subjectivity, incomplete data dimension and the like in traditional energy storage evaluation are effectively overcome, and a scientific, comprehensive and objective evaluation basis can be provided for participation of energy storage in an electric power spot market.

Description

Technical Field

[0001] The present invention belongs to the field of electric power automation, and in particular relates to an evaluation method for energy storage participating in an electric power spot market and a related system. Background Art

[0002] With the construction of new power systems, new power systems with new energy as the main body are facing the challenge of surging flexibility demand and insufficient flexible adjustment capacity. The development of energy storage technology has promoted the use of renewable energy and the opening and competition of the power market. When storing energy, energy storage power stations can reduce the peak-to-valley difference of the system, save fuel costs and start-up and shutdown costs of peak-load units, and play a role in capacity support when releasing energy, partially replacing investment in generators. It is an important flexible resource to support the new power system. Energy storage participating in the electricity spot market can "charge low and discharge high", and make profits through the peak-to-valley difference of electricity prices in the electricity spot market, which can not only increase the low-peak electricity load, but also increase the peak power supply capacity. Energy storage participating in electricity market transactions can not only provide energy consumers with more reliable, economical and sustainable electricity supply, but also provide more profit opportunities for investors in energy storage equipment.

[0003] However, current energy storage assessment methods are immature, resulting in inaccurate market pricing mechanisms, which inhibits the enthusiasm for energy storage in low-peak charging and peak discharging, reduces the overall market efficiency, and leads to increased reliance on traditional power generation units, thereby increasing fuel costs and carbon emissions. Summary of the invention

[0004] The purpose of the present invention is to overcome the problem that due to the immaturity of the evaluation method, energy storage has insufficient enthusiasm in valley charging and peak discharging, resulting in increased dependence on traditional generators, thereby increasing fuel costs and carbon emissions, and to provide an energy storage participation in the electricity spot market evaluation method and related systems.

[0005] In order to achieve the above object, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for evaluating energy storage participating in a power spot market, comprising the following steps: Obtain the average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income of each energy storage power station; The mean square error method is used to calculate the weights of average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income; According to the weights, the daily average net income, daily average charging and generating capacity, average response time, safety capacity, peak-valley average price difference, daily average number of market participations and daily average market income after weighting are evaluated to obtain evaluation values, which are then dimensionlessly processed; Based on the comprehensive evaluation solution model, the final evaluation results of each energy storage power station are solved by combining the dimensionless average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income.

[0006] A further improvement of the present invention is that the calculation method of the average daily net income is as follows: Average daily net income = (total income - total cost) / total number of days; The calculation method of daily average charging and generating capacity is as follows: Average daily charging and power generation = (total power generation + total charging amount) / total number of days Among them, the total income is the total income of each energy storage power station within the preset number of days, the total cost is the total cost of each energy storage power station within the preset number of days, and the total number of days is the preset number of days.

[0007] A further improvement of the present invention is that the average response time is calculated as follows: Average response time = total response time / total number of times The calculation method of safety capacity is as follows: Safety capacity = capacity × safety factor Among them, the total response time is the total response time within the preset number of days, the total number of times is the total number of responses within the preset number of days, the capacity is the capacity of each energy storage power station, and the safety factor is the safety factor of the capacity of each energy storage power station.

[0008] A further improvement of the present invention is that the calculation method of the peak-to-valley average price difference is as follows: Peak-to-valley average price difference = sum of valley price difference within the preset number of days / total number of days The calculation method for the average daily market participation times is as follows: Average number of daily market participations = total number of market transactions / total number of days The average daily market return is calculated as follows: Average daily market return = total market return / total number of days; Among them, the sum of the valley price differences within the preset number of days is the sum of the differences between all peak prices and trough prices within the preset number of days, the total number of times participating in market transactions is the total number of times each energy storage power station participates in market transactions within the preset number of days, the total revenue from participating in the market is the total revenue from each energy storage power station participating in the market within the preset number of days, and the total number of days is the preset number of days.

[0009] A further improvement of the present invention is that the specific method of using the mean square error method to calculate the weights of the average daily net income, the average daily charging and generating capacity, the average response time, the safety capacity, the average peak-valley price difference, the average daily market participation times and the average daily market income is as follows:

[0010] Among them, one of the following indicators is selected: average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income. For the evaluation indicators, is the standard deviation of the evaluation index, is the number of weight value indicators; Standard deviation of the evaluation index The calculation method is as follows:

[0011] in, For the The evaluation indicators are in The calculated value on the indicator, For the evaluation indicators The calculated mean value on the indicators is is the number of participating indicators.

[0012] A further improvement of the present invention is that the specific method for dimensionless processing of the evaluation value is as follows:

[0013] in, is the dimensionless evaluation value, For the i The energy storage station is h The evaluation value of the indicators, is the number of participating indicators.

[0014] A further improvement of the present invention is that, based on the comprehensive evaluation solution model, combined with the dimensionless daily average net income, daily average charging and generating capacity, average response time, safety capacity, peak-valley average price difference, daily average number of market participations and daily average market income, the specific method for solving the final evaluation results of each energy storage power station is as follows:

[0015] in,

[0016]

[0017]

[0018] in, The final evaluation results of each energy storage power station, is the weight matrix, is the normalized matrix, is the dimensionless evaluation value.

[0019] In a second aspect, the present invention provides an energy storage participation in the electricity spot market evaluation system, comprising: The data acquisition module is used to obtain the average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income of each energy storage power station; The weight acquisition module is used to calculate the weights of the average daily net income, the average daily charging and power generation, the average response time, the safety capacity, the average peak-valley price difference, the average daily market participation times and the average daily market income by using the mean square error method; The dimensionless processing module is used to evaluate the daily average net income, daily average charging and generating capacity, average response time, safety capacity, peak-valley average price difference, daily average number of market participations and daily average market income after the weights are assigned, obtain the evaluation value, and perform dimensionless processing on the evaluation value; The normalization processing module is used to solve the final evaluation results of each energy storage power station based on the comprehensive evaluation solution model, combining the dimensionless processed average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income.

[0020] In a third aspect, the present invention provides an electronic device including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the steps of a method for evaluating energy storage participating in the electricity spot market.

[0021] In a fourth aspect, the present invention provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a method for evaluating the participation of energy storage in the electricity spot market.

[0022] Compared with the prior art, the present invention has the following beneficial effects: The present invention can comprehensively reflect the performance of energy storage power stations in the electricity spot market by obtaining multi-dimensional data such as daily average net income, daily average charging and generating capacity, average response time, safety capacity, and peak-valley average price difference. This multi-angle analysis can help decision makers and investors understand the actual operating status of energy storage and its contribution to the market. The weights of various indicators are calculated by the mean square error method, which avoids the influence of subjective weight allocation and makes the evaluation more scientific and objective. Based on accurate weight allocation, it can ensure that each key indicator plays an appropriate role in the comprehensive evaluation, thereby providing a more reliable comprehensive performance evaluation of energy storage power stations. This method not only takes into account the economic benefits of energy storage power stations, but also combines technical performance (such as average response time and safety capacity) and market performance (such as average daily market income and number of market participation), which can help operators optimize the operation mode of energy storage and formulate reasonable scheduling strategies, while also providing investors with more transparent and quantitative decision-making basis. Through the comprehensive evaluation of energy storage power stations, the present invention can identify the advantages and disadvantages of different power stations in various indicators, thereby helping power system operators and policy makers optimize the layout of energy storage power stations, improve the overall flexibility and regulation capabilities of the power system, and further promote the consumption of new energy. By evaluating the performance and benefits of each energy storage power station, the profit potential of energy storage technology in the electricity market can be demonstrated to investors and operators, and more energy storage projects can be encouraged to participate in the electricity spot market. This helps to enhance the competitiveness of energy storage in the market and promote the healthy development of the electricity market. The indicators are dimensionless, so that indicators of different dimensions can be compared and evaluated in a unified framework, which improves the versatility and applicability of the model. This allows the evaluation method to be applied to different types of energy storage projects or electricity market scenarios, and has a wider application prospect. In summary, this method effectively solves the shortcomings of traditional energy storage evaluation, such as strong subjectivity and incomplete data dimensions, and can provide a scientific, comprehensive and objective evaluation basis for energy storage to participate in the electricity spot market, and promote the healthy development of the energy storage industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a flow chart of the present invention; Figure 2 is a system diagram of the present invention; Figure 3 This is a system diagram of Example 3. DETAILED DESCRIPTION

[0024] In order to further understand the content of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the embodiments are only for explaining the present invention and are not intended to limit it.

[0025] See also Figure 1 , a method for evaluating energy storage participating in the electricity spot market, comprising the following steps: S1, obtain the average daily net income, average daily charging and power generation, average response time, safety capacity, peak-to-valley average, price difference, average daily market participation times and average daily market income of each energy storage power station.

[0026] S2, the mean square error method is used to calculate the weights of the average daily net income, the average daily charging and power generation, the average response time, the safety capacity, the average peak-to-valley price difference, the average daily number of market participations and the average daily market income.

[0027] S3, evaluates the weighted average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income according to the weights, obtains the evaluation value, and performs dimensionless processing on the evaluation value.

[0028] S4, based on the comprehensive evaluation solution model, combined with the dimensionless average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income, solves the final evaluation results of each energy storage power station.

[0029] See also Figure 2 , an energy storage participating in the electricity spot market evaluation system, comprising: The data acquisition module is used to obtain the average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income of each energy storage power station; The weight acquisition module is used to calculate the weights of the average daily net income, the average daily charging and power generation, the average response time, the safety capacity, the average peak-valley price difference, the average daily market participation times and the average daily market income by using the mean square error method; The dimensionless processing module is used to evaluate the daily average net income, daily average charging and generating capacity, average response time, safety capacity, peak-valley average price difference, daily average number of market participations and daily average market income after the weights are assigned, obtain the evaluation value, and perform dimensionless processing on the evaluation value; The normalization processing module is used to solve the final evaluation results of each energy storage power station based on the comprehensive evaluation solution model, combining the dimensionless processed average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income.

[0030] Embodiment 1: A method for evaluating energy storage participating in a power spot market comprises the following steps: S1, obtain the average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income of each energy storage power station; the calculation method of the average daily net income is as follows: Average daily net income = (total income - total cost) / total number of days; The calculation method of daily average charging and generating capacity is as follows: Average daily charging and power generation = (total power generation + total charging amount) / total number of days Among them, the total income is the total income of each energy storage power station within the preset number of days, the total cost is the total cost of each energy storage power station within the preset number of days, and the total number of days is the preset number of days.

[0031] The average response time is calculated as follows: Average response time = total response time / total number of times The calculation method of safety capacity is as follows: Safety capacity = capacity × safety factor Among them, the total response time is the total response time within the preset number of days, the total number of times is the total number of responses within the preset number of days, the capacity is the capacity of each energy storage power station, and the safety factor is the safety factor of the capacity of each energy storage power station.

[0032] The calculation method of the peak-to-valley average price difference is as follows: Peak-to-valley average price difference = sum of valley price difference within the preset number of days / total number of days The calculation method for the average daily market participation times is as follows: Average number of daily market participations = total number of market transactions / total number of days The average daily market return is calculated as follows: Average daily market return = total market return / total number of days; Among them, the sum of the valley price differences within the preset number of days is the sum of the differences between all peak prices and trough prices within the preset number of days, the total number of times participating in market transactions is the total number of times each energy storage power station participates in market transactions within the preset number of days, the total revenue from participating in the market is the total revenue from each energy storage power station participating in the market within the preset number of days, and the total number of days is the preset number of days.

[0033] S2, the mean square error method is used to calculate the weights of the average daily net income, the average daily charging and power generation, the average response time, the safety capacity, the average peak-valley price difference, the average daily market participation times and the average daily market income. The specific method is as follows:

[0034] Among them, one of the following indicators is selected: average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income. For the evaluation indicators, is the standard deviation of the evaluation index, is the number of weight value indicators; Standard deviation of the evaluation index The calculation method is as follows:

[0035] in, For the The evaluation indicators are in The calculated value on the indicator, For the evaluation indicators The calculated mean value on the indicators is is the number of participating indicators.

[0036] S3, according to the weights, evaluate the daily average net income, daily average charging and generating capacity, average response time, safety capacity, peak-valley average price difference, daily average number of market participations and daily average market income after the weights are assigned, obtain the evaluation value, and perform dimensionless processing on the evaluation value. The specific method is as follows:

[0037] in, is the dimensionless evaluation value, For the i The energy storage station is h The evaluation value of the indicators, is the number of participating indicators.

[0038] S4, based on the comprehensive evaluation solution model, combined with the dimensionless daily average net income, daily average charging and power generation, average response time, safety capacity, peak-valley average price difference, daily average number of market participations and daily average market income, the final evaluation results of each energy storage power station are solved. The specific method is as follows:

[0039] in,

[0040]

[0041]

[0042] in, The final evaluation results of each energy storage power station, is the weight matrix, is the normalized matrix, is the dimensionless evaluation value.

[0043] Embodiment 2: Assume that there are two energy storage power stations A and B, and select a preset 30-day time window. Calculate the parameter values ​​according to the provided formula, and obtain the final evaluation results of the two power stations through the final comprehensive evaluation.

[0044] S1, obtain various indicators of each energy storage power station: Assume that the data of energy storage power stations A and B are as follows: Power Station A: Total revenue: 500,000 yuan, total cost: 400,000 yuan, total power generation: 200,000kWh, total charging capacity: 180,000kWh, total response time: 50 minutes, total number of responses: 25 times, capacity: 100MW, safety factor: 0.9, the sum of peak and trough price differences within the preset number of days: 10,000 yuan, total market participation times: 15 times, total market revenue: 80,000 yuan.

[0045] Power Station B: Total revenue: 600,000 yuan, total cost: 450,000 yuan, total power generation: 250,000kWh, total charging capacity: 200,000kWh, total response time: 60 minutes, total number of responses: 30 times, capacity: 120MW, safety factor: 0.85, the sum of peak and trough price differences within the preset number of days: 12,000 yuan, total market participation times: 20 times, total market revenue: 100,000 yuan.

[0046] 1. Average daily net income: Power Station A: Average daily net income = (500,000 - 400,000) / 30 = 3,333.33 yuan / day Power Station B: Average daily net income = (600,000 - 450,000) / 30 = 5,000 yuan / day 2. Daily average charging and power generation: Power Station A: Daily average charging and power generation = (200,000 + 180,000) / 30 = 12,666.67 kWh / day Power Station B: Daily average charging and power generation = (250,000 + 200,000) / 30 = 15,000 kWh / day 3. Average response time: Power Station A: Average response time = 50 / 25 = 2 minutes Power Station B: Average response time = 60 / 30 = 2 minutes 4. Safety capacity: Power Station A: Safety capacity = 100 × 0.9 = 90MW Power Station B: Safety capacity = 120 × 0.85 = 102MW 5. Peak-to-valley average price difference: Power Station A: Average peak-to-valley price difference = 10,000 / 30 = 333.33 yuan Power Station B: Average peak-to-valley price difference = 12,000 / 30 = 400 yuan 6. Average number of market participations per day: Power Station A: Average number of market participations per day = 15 / 30 = 0.5 times / day Power Station B: Average number of market participations per day = 20 / 30 = 0.67 times / day 7. Average daily market return: Power Station A: Average daily market income = 80,000 / 30 = 2,666.67 yuan / day Power Station B: Average daily market income = 100,000 / 30 = 3,333.33 yuan / day S2, mean square error method to calculate weights: Based on the above data, we calculate the standard deviation of each participating indicator according to the formula and weight To simplify the presentation, assume that the weights are calculated as follows: Daily average net income weight: 0.2 Daily average charging and generating capacity weight: 0.15 Average response time weight: 0.1 Safety capacity weight: 0.2 Peak-to-valley average price difference weight: 0.15 Average daily market participation weight: 0.1 Average daily market return weight: 0.1 S3, dimensionless processing: The indicators of each energy storage power station are dimensionless, and the dimensionless evaluation values ​​of power stations A and B are as follows: Power Station A: Average daily net income: 0.4, average daily charging and power generation: 0.46, average response time: 0.5, safety capacity: 0.47, average peak-to-valley price difference: 0.45, average daily market participation times: 0.43, average daily market income: 0.44.

[0047] Power Station B: Average daily net income: 0.6, average daily charging and power generation: 0.54, average response time: 0.5, safety capacity: 0.53, average peak-to-valley price difference: 0.55, average daily market participation times: 0.57, average daily market income: 0.56.

[0048] S4, calculate the final evaluation results: The final evaluation result is calculated by multiplying the dimensionless evaluation value and the weight matrix.

[0049] For power station A:

[0050] For power station B:

[0051] Final result: Final evaluation results of power station A: .

[0052] Final evaluation results of power station B: .

[0053] Judging from the results, Power Plant B performed better than Power Plant A, which may be reflected in its higher average daily net income, charging and power generation, safety capacity and market participation.

[0054] Embodiment 3: See also Figure 3 As shown, the present invention also provides an electronic device 100 for a method for evaluating energy storage participating in a spot electricity market; the electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on the at least one processor 102, and at least one communication bus 104.

[0055] The memory 101 can be used to store the computer program 103, and the processor 102 implements the steps of a method for evaluating energy storage participating in the electricity spot market described in Example 1 by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101. The memory 101 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data (such as audio data) created according to the use of the electronic device 100, etc. In addition, the memory 101 may include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other non-volatile solid-state storage devices.

[0056] The at least one processor 102 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 102 may be a microprocessor or any conventional processor, etc. The processor 102 is the control center of the electronic device 100, and uses various interfaces and lines to connect various parts of the entire electronic device 100.

[0057] The memory 101 in the electronic device 100 stores a plurality of instructions to implement a method for evaluating energy storage participating in the electricity spot market, and the processor 102 can execute the plurality of instructions to implement: Obtain the average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income of each energy storage power station; The mean square error method is used to calculate the weights of average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income; According to the weights, the daily average net income, daily average charging and generating capacity, average response time, safety capacity, peak-valley average price difference, daily average number of market participations and daily average market income after weighting are evaluated to obtain evaluation values, which are then dimensionlessly processed; Based on the comprehensive evaluation solution model, the final evaluation results of each energy storage power station are solved by combining the dimensionless average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income.

[0058] Embodiment 4: If the module / unit integrated in the electronic device 100 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory and read-only memory (ROM, Read-Only Memory).

[0059] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0060] 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 flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, 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 flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0061] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate 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 A function specified in one or more boxes.

[0062] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0063] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for evaluating energy storage participating in the electricity spot market, characterized in that: The following steps are involved: Obtain the average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income of each energy storage power station; The mean square error method is used to calculate the weights of average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income; According to the weights, the daily average net income, daily average charging and generating capacity, average response time, safety capacity, peak-valley average price difference, daily average number of market participations and daily average market income after weighting are evaluated to obtain evaluation values, which are then dimensionlessly processed; Based on the comprehensive evaluation solution model, the final evaluation results of each energy storage power station are solved by combining the dimensionless average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income.

2. A method for evaluating energy storage participating in the electricity spot market according to claim 1, characterized in that: The calculation method of average daily net income is as follows: Average daily net income = (total income - total cost) / total number of days; The calculation method of daily average charging and generating capacity is as follows: Average daily charging and power generation = (total power generation + total charging amount) / total number of days Among them, the total income is the total income of each energy storage power station within the preset number of days, the total cost is the total cost of each energy storage power station within the preset number of days, and the total number of days is the preset number of days.

3. The method for evaluating energy storage participating in the electricity spot market according to claim 1, characterized in that: The average response time is calculated as follows: Average response time = total response time / total number of times The calculation method of safety capacity is as follows: Safety capacity = capacity × safety factor Among them, the total response time is the total response time within the preset number of days, the total number of times is the total number of responses within the preset number of days, the capacity is the capacity of each energy storage power station, and the safety factor is the safety factor of the capacity of each energy storage power station.

4. The method for evaluating energy storage participating in the electricity spot market according to claim 1, characterized in that: The calculation method of the peak-to-valley average price difference is as follows: Peak-to-valley average price difference = sum of valley price difference within the preset number of days / total number of days The calculation method for the average daily market participation times is as follows: Average number of daily market participations = total number of market transactions / total number of days The average daily market return is calculated as follows: Average daily market return = total market return / total number of days; Among them, the sum of the valley price differences within the preset number of days is the sum of the differences between all peak prices and trough prices within the preset number of days, the total number of times participating in market transactions is the total number of times each energy storage power station participates in market transactions within the preset number of days, the total revenue from participating in the market is the total revenue from each energy storage power station participating in the market within the preset number of days, and the total number of days is the preset number of days.

5. The method for evaluating energy storage participating in the electricity spot market according to claim 1, characterized in that: The specific method of using the mean square error method to calculate the weights of the average daily net income, the average daily charging and power generation, the average response time, the safety capacity, the average peak-valley price difference, the average daily market participation times and the average daily market income is as follows: Among them, one of the following indicators is selected: average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income. For the evaluation indicators, is the standard deviation of the evaluation index, is the number of weight value indicators; Standard deviation of the evaluation index The calculation method is as follows: in, For the The evaluation indicators are in The calculated value on the indicator, For the evaluation indicators The calculated mean value on the indicators is is the number of participating indicators.

6. The method for evaluating energy storage participating in the electricity spot market according to claim 1, characterized in that: The specific method for dimensionless processing of evaluation values ​​is as follows: in, is the dimensionless evaluation value, For the i The energy storage station is h The evaluation value of the indicators, is the number of participating indicators.

7. The method for evaluating energy storage participating in the electricity spot market according to claim 1, characterized in that: Based on the comprehensive evaluation solution model, combined with the dimensionless daily average net income, daily average charging and power generation, average response time, safety capacity, peak-valley average price difference, daily average number of market participations and daily average market income, the specific method for solving the final evaluation results of each energy storage power station is as follows: in, in, The final evaluation results of each energy storage power station, is the weight matrix, is the normalized matrix, is the dimensionless evaluation value.

8. An energy storage participating in the electricity spot market evaluation system, characterized in that: include: The data acquisition module is used to obtain the average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income of each energy storage power station; The weight acquisition module is used to calculate the weights of the average daily net income, the average daily charging and power generation, the average response time, the safety capacity, the average peak-valley price difference, the average daily market participation times and the average daily market income by using the mean square error method; The dimensionless processing module is used to evaluate the daily average net income, daily average charging and generating capacity, average response time, safety capacity, peak-valley average price difference, daily average number of market participations and daily average market income after the weights are assigned, obtain the evaluation value, and perform dimensionless processing on the evaluation value; The normalization processing module is used to solve the final evaluation results of each energy storage power station based on the comprehensive evaluation solution model, combining the dimensionless processed average daily net income, average daily charging and power generation, average response time, safety capacity, average peak-valley price difference, average daily market participation times and average daily market income.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of a method for evaluating the participation of energy storage in the electricity spot market as described in any one of claims 1 to 7 are implemented.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a method for evaluating the participation of energy storage in the electricity spot market as described in any one of claims 1 to 7 are implemented.

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