Wind power-photovoltaic-energy storage system abandoned electricity hydrogen production capacity optimization method

Abstract

The invention relates to the technical field of new energy, and discloses a wind power-photovoltaic-energy storage system abandoned electricity hydrogen production capacity optimization method, which uses abandoned electricity quantity of a wind power plant and a photovoltaic power station to produce hydrogen, uses part of distributed storage capacity of the wind power plant and the photovoltaic power station as a hydrogen production module adjusting power supply, and mainly uses abandoned electricity supply of the wind power plant and the photovoltaic power station to produce hydrogen. The surplus part is used for supplementing the electric quantity of the storage battery; the electric quantity in the storage battery is only used for balancing and coordinating the hydrogen production power utilization quality and the power utilization efficiency. And comparing the hydrogen production income of the off-grid wind power-photovoltaic-energy storage system with the hydrogen production income of the grid-connected wind power-photovoltaic-energy storage system, so as to obtain the optimal total investment return rate of the grid-connected wind power-photovoltaic-energy storage system for hydrogen production by electricity abandoning. Then, a refined wind power-photovoltaic-energy storage system electricity abandoning hydrogen production scheduling strategy is provided, and a capacity optimization system with the total investment return rate and the energy waste rate as objective functions and the power of each module as a constraint condition is established.

Description

Technical Field

[0001] The present invention relates to the field of new energy technology, and more specifically discloses a method for optimizing the capacity of hydrogen production from abandoned electricity in a wind power-photovoltaic-energy storage system. Background Art

[0002] my country's annual hydrogen production is about 33 million tons, of which about 12 million tons meet industrial hydrogen standards, of which less than 1% is produced from renewable energy. The "Medium- and Long-Term Plan for the Development of the Hydrogen Energy Industry (2021-2035)" proposes that by 2025, China's new energy hydrogen production will reach 100,000 to 200,000 tons per year, so new energy power generation and hydrogen production have great development prospects.

[0003] At present, the cost and electricity cost of new energy power generation hydrogen production system are high, resulting in slow development of new energy power generation water electrolysis hydrogen production system. However, the power restriction ratio of wind farms and photovoltaic power stations in the Three Norths is high, and the electricity price is low. The power restriction rate in some areas such as Gansu, Western Meng, Zhangbei, and Kangbao exceeds 10%, resulting in a large waste rate of new energy resources. The high power restriction rate and low electricity price in the Three Norths provide impetus for exploring the development of new energy hydrogen production models.

[0004] Some literatures have proposed a capacity optimization model for a hybrid energy storage system of wind power, photovoltaic power and hydrogen storage, with the goal of minimizing the total net present value cost or the total investment return rate and energy waste rate, and using renewable energy utilization as the system power balance constraint, to optimize the wind power, photovoltaic power, hydrogen energy and electrochemical energy storage capacity using different algorithms. This method uses hydrogen as the fuel cell medium, and hydrogen and electricity are converted into each other. The current technical efficiency of this method is low.

[0005] Most scholars have discussed the capacity optimization model and method of hybrid energy storage systems including hydrogen storage in multi-energy complementary systems; few scholars have explored the economics of different new energy hydrogen production models under the current environment and the use of abandoned power to produce hydrogen to improve the rate of return of new energy projects, while considering the hydrogen revenue; and few scholars have optimized the capacity ratio of abandoned power to produce hydrogen based on detailed scheduling strategies and advanced optimization algorithms, and thus provided the optimal new energy hydrogen production development plan. Summary of the invention

[0006] The present invention mainly provides a method for optimizing the capacity of hydrogen production from abandoned electricity in a wind power-photovoltaic-energy storage system, which can solve the problem that the current method uses hydrogen as a fuel cell medium and the mutual conversion technology between hydrogen and electrical energy is low in efficiency.

[0007] To solve the above technical problems, according to one aspect of the present invention, more specifically, a method for optimizing the capacity of hydrogen production from abandoned electricity in a wind power-photovoltaic-energy storage system is provided, which is characterized in that hydrogen is produced by utilizing the abandoned electricity of wind farms and photovoltaic power stations, and part of the allocated storage capacity of wind farms and photovoltaic power stations is used as the regulating power source for the hydrogen production module, and the abandoned electricity of wind farms and photovoltaic power stations is mainly used to supply hydrogen production, and the surplus is used to supplement the battery power; then, a scheduling strategy for hydrogen production from abandoned electricity in a wind power-photovoltaic-energy storage system is established; finally, with the total investment return rate and energy waste rate as the objective function, and the power and start-stop status of each module as the constraint conditions, a rolling optimization improved particle swarm optimization algorithm is used to optimize the installed capacity of wind farms, photovoltaic power stations, energy storage modules and hydrogen production equipment.

[0008] Furthermore, the objective function constructed is:

[0009]

[0010]

[0011]

[0012] in, , , , and , , , represent the initial investment cost and operation and maintenance cost of wind power, photovoltaic, energy storage and hydrogen production modules respectively; It is the sum of the initial investment cost and total operation and maintenance cost of wind power, photovoltaic, energy storage and hydrogen production modules. , They are the system electricity sales revenue and hydrogen sales revenue, is the total system revenue, is the total investment return rate of the system; SPSP is the energy waste rate, The amount of power abandoned by wind farms and photovoltaic power stations, It is the sum of the power generated by wind farms and photovoltaic power stations.

[0013] Furthermore, the constraints are:

[0014]

[0015]

[0016]

[0017]

[0018] in, , , They are the real-time power, minimum remaining power and maximum capacity of the energy storage module; , , They are the real-time charging and discharging power, minimum charging and discharging power, and rated charging and discharging power of the energy storage module respectively; , , They are the real-time power consumption, minimum startup power consumption and rated power consumption of the hydrogen production module respectively; , , They are the real-time operating power, minimum operating power and rated operating power of the wind power module respectively; , , They are the real-time operating power, minimum operating power and rated operating power of the photovoltaic module respectively.

[0019] Furthermore, rolling optimization improves the particle swarm optimization algorithm. The rolling optimization uses the meteorological data of a period of time in the future to optimize the remaining power in the current energy storage, and then repeatedly optimizes the remaining power of the energy storage module at the previous time node online. The specific optimization process is as follows: (1) Initialize the particle swarm so that each decision variable takes a random value within the value range; (2) Input wind resource data and irradiance data; (3) Update the fitness value, global optimal value, and individual optimal value, and update the particle speed and position using the function under the scheduling strategy; (4) Use the following formula to update the inertia weight coefficient calculated in each iteration. The traditional particle swarm algorithm uses the same weight value before and after optimization, which cannot meet the strong global search capability in the early stage of optimization and the strong local search capability in the later stage;

[0020] (5) Optimize the remaining power generation of the energy storage module in the i-th hour based on the meteorological data from i to i+5 hours; (6) Repeat the calculation, gradually advance the optimization stage, and provide real-time feedback on the remaining power of the energy storage module at the previous time node until the optimization is completed; (7) Obtain Suboptimal annual hydrogen production and corresponding capacity.

[0021] Furthermore, the electricity in the battery is only used to balance the quality and efficiency of electricity used in hydrogen production.

[0022] Furthermore, the wind power-photovoltaic-energy storage system power abandonment hydrogen production scheduling strategy includes: when the sum of the power generation of the wind farm and the photovoltaic power station is less than the grid channel capacity, there are two states: (1) when the remaining power in the energy storage module is less than the minimum remaining power, the energy storage module does not discharge and the hydrogen production equipment stops working; (2) when the remaining power in the energy storage module is greater than the minimum remaining power, the energy storage system discharges and the hydrogen production equipment works.

[0023] Furthermore, the wind power-photovoltaic-energy storage system abandoned power hydrogen production scheduling strategy also includes: when the sum of the power generation of the wind farm and the photovoltaic power station is greater than the grid channel capacity, there are three states: (1) When the abandoned power is greater than the power consumption of the hydrogen production equipment, the remaining power is used to supplement the power in the energy storage module; (2) When the abandoned power is less than the power consumption of the hydrogen production equipment, the energy storage module releases part of the power; (3) When the sum of the abandoned power and the energy storage released power is less than the minimum operating energy of the hydrogen production equipment, the hydrogen production equipment does not operate.

[0024] Furthermore, the method further comprises: a data collection and preprocessing module, a power prediction module, a dynamic adjustment hydrogen production strategy module, a capacity configuration model building module and a multi-objective optimization solution module, each module being connected in sequence and working in coordination; Data collection and preprocessing module: used to collect real-time operating data of wind farms and photovoltaic power plants, and preprocess the collected data to ensure the accuracy and availability of the data; Power prediction module: used to predict wind power and photovoltaic output using prediction algorithms based on the data provided by the data collection and preprocessing module, thereby providing a basis for the formulation of hydrogen production strategies; Dynamically adjust hydrogen production strategy module: used to formulate and adjust hydrogen production scheduling strategy according to the results of the power prediction module; Capacity configuration model building module: used to establish the capacity configuration model of the wind power-photovoltaic-energy storage system abandoned power hydrogen production system, and determine the optimal capacity configuration of each component through mathematical modeling and simulation analysis; Multi-objective optimization solution module: It is used to establish the model provided by the capacity configuration model building module and dynamically adjust the strategy formulated by the hydrogen production strategy module to perform multi-objective optimization solutions and seek the optimal hydrogen production system capacity configuration plan.

[0025] The beneficial effect of the capacity optimization method of wind power-photovoltaic-energy storage system abandoned power hydrogen production of the present invention is: by comparing the off-grid wind power-photovoltaic-energy storage system hydrogen production and grid-connected wind power-photovoltaic-energy storage system abandoned power hydrogen production income, the grid-connected wind power-photovoltaic-energy storage system abandoned power hydrogen production total investment rate of return is obtained. Subsequently, a refined wind power-photovoltaic-energy storage system abandoned power hydrogen production scheduling strategy is proposed, and a capacity optimization system with total investment rate of return and energy waste rate as objective functions and the power of each module as constraint conditions is established. The rolling optimization improved particle swarm algorithm is used to optimize the ratio of wind farms, photovoltaic power stations, energy storage modules and hydrogen production modules under different power limit rates. When the capacity of the abandoned power hydrogen production module of the off-grid wind power-photovoltaic-energy storage system and the grid-connected wind power-photovoltaic-energy storage system is the same, the latter has a greater total investment rate of return than the former, and the economic benefit is better than the former. A refined abandoned power hydrogen production scheduling strategy is proposed to reasonably allocate the energy of hydrogen production and energy storage modules, improve the system energy utilization rate, and provide a reference for the capacity optimization of the new energy abandoned power hydrogen production system. According to the wind and solar resources in the future, the rolling optimization algorithm is used to preset the remaining battery energy storage capacity to avoid cold start of hydrogen production equipment and improve the efficiency of hydrogen production equipment. After optimization, the proportion of wind power, photovoltaic, energy storage and hydrogen production modules is obtained, which will reduce the waste rate of new energy, improve the coordination efficiency of each module and the total investment return rate, and improve the financial internal rate of return of the project. It provides a full range of optimization solutions to solve the high power restriction rate in the three northern regions and explore the development of new energy hydrogen production. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The present invention is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0027] Figure 1 This is a schematic diagram of the wind power-photovoltaic-energy storage system's abandoned electricity hydrogen production model; Figure 2 Schematic diagram of the dispatching strategy when the sum of the power generation of wind farms and photovoltaic power stations is less than the capacity of the power grid channel; Figure 3 Schematic diagram of the dispatching strategy when the sum of the power generation of wind farms and photovoltaic power stations is greater than the capacity of the power grid channel; Figure 4 It is a schematic diagram of the R-PSO algorithm flow; Figure 5 Provide power diagram for wind farms; Figure 6 It is the output diagram of photovoltaic power station; Figure 7 It is a Pareto curve chart. DETAILED DESCRIPTION

[0028] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0029] According to one aspect of the present invention, a method for optimizing the hydrogen production capacity of abandoned electricity in a wind power-photovoltaic-energy storage system is provided, and the method comprises the following contents: 1. Establishing a model for hydrogen production from abandoned electricity in a wind power-photovoltaic-energy storage system In order to reduce the cost of hydrogen production and improve the utilization rate of new energy resources, a wind power-photovoltaic-energy storage system abandoned power production model is established. Hydrogen is produced by using the abandoned power of wind farms and photovoltaic power stations, and part of the allocated storage capacity of wind farms and photovoltaic power stations is used as the power supply for hydrogen production modules. Figure 1 The model mainly uses abandoned electricity from wind farms and photovoltaic power stations to supply hydrogen production, and the surplus is used to supplement the battery power; the power in the battery is only used to balance and coordinate the quality and efficiency of hydrogen production electricity.

[0030] 2. Formulate a refined wind power-photovoltaic-energy storage system power abandonment hydrogen production scheduling strategy Assume that wind farms and photovoltaic power stations are prioritized for power generation and grid connection. The power exceeding the grid channel capacity is used for hydrogen production, and the remaining power is used to replenish the battery power. Due to the storage policy of new energy power stations in my country, the power in the energy storage is only used for hydrogen production and does not participate in grid dispatch. When the sum of the power generation of wind farms and photovoltaic power stations is less than the grid channel capacity, the dispatch strategy is as follows: Figure 2 There are two states in this case: (1) when the remaining power in the energy storage module is less than the minimum remaining power, the energy storage module does not discharge and the hydrogen production equipment stops working; (2) when the remaining power in the energy storage module is greater than the minimum remaining power, the energy storage system discharges and the hydrogen production equipment works.

[0031] When the sum of the power generation of wind farms and photovoltaic power plants is greater than the grid channel capacity, the dispatch strategy is as follows Figure 3 As shown in the figure, there are three states in this case: (1) When the amount of power abandoned is greater than the power consumption of the hydrogen production equipment, the remaining power is used to supplement the power in the energy storage module; (2) When the amount of power abandoned is less than the power consumption of the hydrogen production equipment, the energy storage module releases part of the power; (3) When the sum of the amount of power abandoned and the amount of power released by the energy storage is less than the minimum operating energy of the hydrogen production equipment, the hydrogen production equipment does not operate.

[0032] Among them, i represents the number of hours, PW and PV are the output of wind farm and photovoltaic power station respectively. represents the power abandonment rate, Indicates the remaining power in the energy storage module. , Indicates the maximum and minimum remaining power in the energy storage. Indicates the charging and discharging power of energy storage, , Indicates the maximum and minimum charging and discharging power of energy storage, Indicates the power of the hydrogen production equipment, , Indicates the rated power and minimum starting power of the hydrogen production equipment. Indicates the current power consumption of the hydrogen production equipment.

[0033] 3. Establishment of a wind power-photovoltaic-energy storage system abandoned power hydrogen production capacity optimization model The optimization model for the hydrogen production capacity of abandoned power in the wind power-photovoltaic-energy storage system takes the total investment return rate and energy waste rate as the objective function, and the power and start-stop status of each module as the constraint conditions. It adopts the rolling optimization improved particle swarm optimization algorithm to optimize the installed capacity of wind farms, photovoltaic power stations, energy storage modules and hydrogen production equipment.

[0034] Construct the objective function:

[0035]

[0036]

[0037]

[0038] in, , , , and , , , represent the initial investment cost and operation and maintenance cost of wind power, photovoltaic, energy storage and hydrogen production modules respectively; It is the sum of the initial investment cost and total operation and maintenance cost of wind power, photovoltaic, energy storage and hydrogen production modules. , They are the system electricity sales revenue and hydrogen sales revenue, is the total system revenue, is the total investment return rate of the system; SPSP is the energy waste rate, The amount of power abandoned by wind farms and photovoltaic power stations, The sum of the power generated by wind farms and photovoltaic power stations Constraints:

[0039]

[0040]

[0041]

[0042]

[0043] in, , , They are the real-time power, minimum remaining power and maximum capacity of the energy storage module; , , They are the real-time charging and discharging power, minimum charging and discharging power, and rated charging and discharging power of the energy storage module respectively; , , They are the real-time power consumption, minimum startup power consumption and rated power consumption of the hydrogen production module respectively; , , They are the real-time operating power, minimum operating power and rated operating power of the wind power module respectively; , , They are the real-time operating power, minimum operating power and rated operating power of the photovoltaic module respectively.

[0044] 4. Establishing rolling optimization to improve particle swarm optimization algorithm The hydrogen production module has low operating efficiency under low working conditions, a long startup time after shutdown, and high energy consumption. The remaining power of the energy storage module directly affects the startup time and working efficiency of the hydrogen production module. Therefore, it is particularly important to optimize the real-time remaining power of the energy storage module according to wind resource data and irradiation data to improve the efficiency of hydrogen production. If the power abandonment in the i+1 hour is large and the power abandonment in the i hour is 0, the remaining power of the energy storage module can be controlled in advance to enable the hydrogen production module to operate continuously in the i~i+1 hours.

[0045] Therefore, a rolling optimization improved particle swarm optimization (R-PSO) algorithm is established. The rolling optimization is to use the meteorological data of a period of time in the future to optimize the remaining power in the current energy storage, and then repeatedly optimize the remaining power of the energy storage module at the previous time node online.

[0046] The R-PSO optimization algorithm process is as follows Figure 4 As shown in the figure, the specific optimization process is: (1) Initialize the particle swarm so that each decision variable takes a random value within the value range; (2) Input wind resource data and irradiance data; (3) Update the fitness value, global optimal value, and individual optimal value, and update the particle speed and position using the function under the scheduling strategy; (4) Use the following formula to update the inertia weight coefficient calculated in each iteration. The traditional particle swarm algorithm uses the same weight value before and after optimization, which cannot meet the strong global search capability in the early stage of optimization and the strong local search capability in the later stage;

[0047] (5) Optimize the remaining power generation of the energy storage module in the i-th hour based on the meteorological data from i to i+5 hours; (6) Repeat the calculation, gradually advance the optimization stage, and provide real-time feedback on the remaining power of the energy storage module at the previous time node until the optimization is completed; (7) Obtain Suboptimal annual hydrogen production and corresponding capacity.

[0048] The above method is implemented based on the data collection and preprocessing module, the power prediction module, the dynamic adjustment hydrogen production strategy module, the capacity configuration model establishment module and the multi-objective optimization solution module. Data collection and preprocessing module: used to collect the real-time operation data of wind farms and photovoltaic power stations, and also preprocess the collected data, such as data cleaning, format conversion, etc., to ensure the accuracy and availability of the data. Power prediction module: used to use the prediction algorithm, such as the FPSO neural network variable time prediction model, to predict the wind power and photovoltaic output provided by the data collection and preprocessing module, so as to provide a basis for the formulation of hydrogen production strategy. Dynamic adjustment hydrogen production strategy module: used to formulate and adjust the hydrogen production scheduling strategy according to the results of the power prediction module. Capacity configuration model establishment module: used to establish the capacity configuration model of the wind power-photovoltaic-energy storage system abandoned power hydrogen production system, and determine the optimal capacity configuration of each component (such as wind farm, photovoltaic power station, energy storage module and hydrogen production equipment installed capacity) through mathematical modeling and simulation analysis. Multi-objective optimization solution module: It is used to perform multi-objective optimization solution based on the model provided by the capacity configuration model building module and the strategy formulated by the dynamic adjustment hydrogen production strategy module to seek the optimal hydrogen production system capacity configuration plan. The above-mentioned modules are connected in sequence and work together to achieve the optimization of the wind power-photovoltaic-energy storage system's abandoned power hydrogen production capacity.

[0049] Example The hourly wind resource and irradiation resource data of a project in Northwest my country are used, and the average bidding price of wind power, photovoltaic, battery energy storage and hydrogen production modules in my country is used as a reference. Assume that the wind farm has a power limit rate of 10%, the photovoltaic power station has a power limit rate of 5%, and the battery energy storage duration is 2 hours. The WT software is used to calculate the hourly output of the plain wind farm throughout the year, and the PVsyst software is used to calculate the hourly output of the photovoltaic power station throughout the year. Standardized data processing is used for the output curve, and the mapping range is [0,1]. The data is as follows Figure 5 and Figure 6 shown.

[0050] Assume that the capacities of wind farm, photovoltaic power station, energy storage power station and hydrogen production equipment are 100MW, 100MW, 20MW / 40MWh and 30000Nm 3 The calculated total investment returns for the off-grid wind power-photovoltaic-energy storage hydrogen production system and the grid-connected wind power-photovoltaic-energy storage system for hydrogen production from abandoned power are 1.49 and 1.66, respectively. The grid-connected wind power-photovoltaic-energy storage system for hydrogen production from abandoned power has better economic performance.

[0051] Based on the above grid-connected wind power-photovoltaic-energy storage system abandoned power hydrogen production capacity optimization model, the rolling optimization improved particle swarm algorithm and the above scheduling strategy are used. The number of individuals is initialized to 500 and the maximum number of iterations is 20. The optimized Pareto curve is as follows: Figure 7 As shown. The corresponding capacity ratio of each module can be found according to the energy waste rate of the horizontal axis and the required value of the total investment return rate of the vertical axis. If you are looking for the maximum investment return rate, select the power station and hydrogen production equipment capacity ratio corresponding to the coordinate point in the upper right corner of the figure, which is 997:23:2.3:66.7, the total investment return rate is 1.8319, and the power abandonment rate is 0.0059; if you are looking for the minimum energy waste rate, select the power station and hydrogen production equipment capacity ratio corresponding to the coordinate point in the lower left corner, which is 995:136:9:89, the total investment return rate is 1.7679, and the power abandonment rate is approximately zero.

[0052] In summary, the capacity ratio of wind power, photovoltaic, energy storage and hydrogen production modules obtained by the grid-connected wind power-photovoltaic-energy storage system abandoned power hydrogen production capacity optimization model improves the energy utilization rate and economic benefits of the system, and provides a new energy development model for high power restriction areas to improve energy utilization and enhance economic benefits. At the same time, it also explores a more economical and feasible solution for the development of new energy hydrogen production. This solution is applied to grid-connected wind power abandoned power hydrogen production, grid-connected photovoltaic abandoned power hydrogen production and other projects, which will improve the financial internal rate of return of new energy projects and bring about qualitative changes to some endangered projects.

[0053] Of course, the above description is not a limitation of the present invention, and the present invention is not limited to the above examples. Changes, modifications, additions or substitutions made by ordinary technicians in this technical field within the essential scope of the present invention also fall within the protection scope of the present invention.

Claims

1. A method for optimizing the capacity of hydrogen production from abandoned electricity in a wind power-photovoltaic-energy storage system, characterized in that: The abandoned electricity of wind farms and photovoltaic power stations is used to produce hydrogen, and part of the allocated storage capacity of wind farms and photovoltaic power stations is used as the regulating power supply for hydrogen production module. The abandoned electricity of wind farms and photovoltaic power stations is mainly used to supply hydrogen production, and the surplus is used to supplement the battery power. Then, a scheduling strategy for hydrogen production from abandoned electricity of wind power-photovoltaic-energy storage system is established. Finally, with the total investment return rate and energy waste rate as the objective function and the power and start-stop status of each module as constraints, the rolling optimization improved particle swarm optimization algorithm is used to optimize the installed capacity of wind farms, photovoltaic power stations, energy storage modules and hydrogen production equipment.

2. The method for optimizing the capacity of hydrogen production from abandoned electricity in a wind power-photovoltaic-energy storage system according to claim 1, characterized in that: The constructed objective function is: in, , , , and , , , represent the initial investment cost and operation and maintenance cost of wind power, photovoltaic, energy storage and hydrogen production modules respectively; It is the sum of the initial investment cost and total operation and maintenance cost of wind power, photovoltaic, energy storage and hydrogen production modules. , They are the system electricity sales revenue and hydrogen sales revenue, is the total system revenue, is the total investment return rate of the system; SPSP is the energy waste rate, The amount of power abandoned by wind farms and photovoltaic power stations, It is the sum of the power generated by wind farms and photovoltaic power stations.

3. The method for optimizing the capacity of hydrogen production from abandoned electricity in a wind power-photovoltaic-energy storage system according to claim 1, characterized in that: The constraints are: in, , , They are the real-time power, minimum remaining power and maximum capacity of the energy storage module; , , They are the real-time charging and discharging power, minimum charging and discharging power, and rated charging and discharging power of the energy storage module respectively; , , They are the real-time power consumption, minimum startup power consumption and rated power consumption of the hydrogen production module respectively; , , They are the real-time operating power, minimum operating power and rated operating power of the wind power module respectively; , , They are the real-time operating power, minimum operating power and rated operating power of the photovoltaic module respectively.

4. The method for optimizing the capacity of hydrogen production from abandoned electricity in a wind power-photovoltaic-energy storage system according to claim 1, characterized in that: Rolling optimization improves the particle swarm optimization algorithm. The rolling optimization is to use the meteorological data of a period of time in the future to optimize the remaining power in the current energy storage, and then repeatedly optimize the remaining power of the energy storage module at the previous time node online; the specific optimization process is as follows: (1) Initialize the particle swarm so that each decision variable takes a random value within the value range; (2) Input wind resource data and irradiance data; (3) Update the fitness value, global optimal value, and individual optimal value, and update the particle speed and position using the function under the scheduling strategy; (4) Use the following formula to update the inertia weight coefficient calculated in each iteration. The traditional particle swarm algorithm uses the same weight value before and after optimization, which cannot meet the strong global search capability in the early stage of optimization and the strong local search capability in the later stage; (5) Optimize the remaining power generation of the energy storage module in the i-th hour based on the meteorological data from i to i+5 hours; (6) Repeat the calculation, gradually advance the optimization stage, and provide real-time feedback on the remaining power of the energy storage module at the previous time node until the optimization is completed; (7) Obtain Suboptimal annual hydrogen production and corresponding capacity.

5. The method for optimizing the capacity of hydrogen production from abandoned electricity in a wind power-photovoltaic-energy storage system according to claim 1, characterized in that: The power in the battery is only used to balance the quality and efficiency of electricity used in hydrogen production.

6. The method for optimizing the capacity of hydrogen production from abandoned electricity in a wind power-photovoltaic-energy storage system according to claim 1, characterized in that: The wind power-photovoltaic-energy storage system power abandonment hydrogen production scheduling strategy includes: when the sum of the power generation of the wind farm and the photovoltaic power station is less than the grid channel capacity, there are two states: (1) when the remaining power in the energy storage module is less than the minimum remaining power, the energy storage module does not discharge and the hydrogen production equipment stops working; (2) when the remaining power in the energy storage module is greater than the minimum remaining power, the energy storage system discharges and the hydrogen production equipment works.

7. The method for optimizing the capacity of hydrogen production from abandoned electricity in a wind power-photovoltaic-energy storage system according to claim 1, characterized in that: The wind power-photovoltaic-energy storage system abandoned power hydrogen production scheduling strategy also includes: when the sum of the power generation of the wind farm and the photovoltaic power station is greater than the grid channel capacity, there are three states: (1) When the abandoned power is greater than the power consumption of the hydrogen production equipment, the remaining power is used to supplement the power in the energy storage module; (2) When the abandoned power is less than the power consumption of the hydrogen production equipment, the energy storage module releases part of the power; (3) When the sum of the abandoned power and the energy storage released power is less than the minimum operating energy of the hydrogen production equipment, the hydrogen production equipment does not operate.

8. The method for optimizing the capacity of hydrogen production from abandoned electricity in a wind power-photovoltaic-energy storage system according to claim 1, characterized in that: The method further comprises: a data collection and preprocessing module, a power prediction module, a dynamic hydrogen production strategy adjustment module, a capacity configuration model establishment module and a multi-objective optimization solution module, each module being connected in sequence and working in coordination; Data collection and preprocessing module: used to collect real-time operating data of wind farms and photovoltaic power plants, and preprocess the collected data to ensure the accuracy and availability of the data; Power prediction module: used to predict wind power and photovoltaic output using prediction algorithms based on the data provided by the data collection and preprocessing module, thereby providing a basis for the formulation of hydrogen production strategies; Dynamically adjust hydrogen production strategy module: used to formulate and adjust hydrogen production scheduling strategy according to the results of the power prediction module; Capacity configuration model building module: used to establish the capacity configuration model of the wind power-photovoltaic-energy storage system abandoned power hydrogen production system, and determine the optimal capacity configuration of each component through mathematical modeling and simulation analysis; Multi-objective optimization solution module: It is used to establish the model provided by the capacity configuration model building module and dynamically adjust the strategy formulated by the hydrogen production strategy module to perform multi-objective optimization solutions and seek the optimal hydrogen production system capacity configuration plan.

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