A method for capacity optimization configuration of a wind-solar-storage coupled off-grid hydrogen production microgrid system

Abstract

This invention discloses a capacity optimization configuration method for a wind-solar-storage coupled off-grid hydrogen production microgrid system, belonging to the field of microgrid technology. The method includes: 1) establishing mathematical models for each unit of the wind-solar-storage coupled off-grid hydrogen production microgrid system, which includes a DC bus, wind power generation units, photovoltaic power generation units, battery energy storage units, water electrolysis hydrogen production units, hydrogen storage units, and DC load units; 2) establishing an operation strategy for the wind-solar-storage coupled off-grid hydrogen production microgrid system; 3) establishing an objective function for capacity optimization configuration of the wind-solar-storage coupled off-grid hydrogen production microgrid system; 4) using environmental parameters as input to a weighted mutated particle swarm optimization algorithm, running the algorithm to obtain the optimal capacity ratio of the wind-solar-storage coupled off-grid hydrogen production microgrid system. This invention fully considers the volatility of new energy power generation and the dynamic characteristics of alkaline water electrolysis hydrogen production equipment, thus improving the economic efficiency of the system.

Description

Technical Field

[0001] This invention relates to the fields of water electrolysis for hydrogen production and microgrid technology, and particularly to a method for configuring the capacity of a microgrid for water electrolysis for hydrogen production. Background Technology

[0002] Compared with traditional fossil fuels, new energy sources, mainly wind power and photovoltaics, are more efficient and environmentally friendly. Moreover, wind and solar energy are inexhaustible and can effectively address energy crises and environmental pollution problems. Therefore, new energy power generation technologies have received high attention and widespread application from countries around the world.

[0003] Hydrogen is an ideal energy carrier with advantages such as high energy density, no pollution during use, recyclability, and suitability for large-scale storage and transportation. The technology of producing hydrogen by electrolyzing water using an alkaline electrolyzer (AEL) is mature and low-cost, making it suitable for large-scale hydrogen production applications. Therefore, using wind and solar coupled hydrogen production is an effective way to solve the problem of new energy utilization and one of the effective ways to achieve sustainable development.

[0004] However, the power generation capacity and quality of wind and solar power are easily affected by environmental factors, exhibiting characteristics such as high randomness, large fluctuations, and intermittent power generation, which creates difficulties in the use of new energy sources. Furthermore, the hydrogen production efficiency of AEL is affected by various factors such as input current, electrolyte concentration, and temperature, resulting in different hydrogen production efficiencies under different input power conditions and operating environments. In addition, AEL systems have high inertia and weak dynamic load tracking capabilities.

[0005] Therefore, taking into full account the characteristics of wind and solar power generation capacity and quality being susceptible to environmental factors and the dynamic and static characteristics of AEL, researching the capacity configuration method of wind and solar off-grid hydrogen production systems is of great significance for improving the utilization rate of new energy and enhancing the overall efficiency of wind and solar off-grid hydrogen production systems. Summary of the Invention

[0006] In view of this, the purpose of this invention is to provide a capacity optimization configuration method for a wind-solar-storage coupled off-grid hydrogen production microgrid system, so as to solve the technical problems that affect the maximization of economic benefits of the wind-solar-storage coupled off-grid hydrogen production microgrid system, which are caused by the instability and high randomness of wind and photovoltaic power generation capacity and the weak dynamic load tracking capability of alkaline electrolyzers.

[0007] The capacity optimization configuration method for a wind-solar-storage coupled off-grid hydrogen production microgrid system of the present invention includes the following steps:

[0008] 1) Establish mathematical models for each unit of the wind-solar-storage coupled off-grid hydrogen production microgrid system. The system includes a DC bus, wind power generation units, photovoltaic power generation units, battery energy storage units, water electrolysis hydrogen production units, hydrogen storage units, and DC load units. The wind power generation unit includes a wind turbine and an AC / DC rectifier connecting the wind turbine to the DC bus. The photovoltaic power generation unit includes photovoltaic cells and a unidirectional DC / DC converter connecting the photovoltaic cells to the DC bus. The battery energy storage unit includes a lithium-ion battery and a bidirectional DC / DC converter connecting the lithium-ion battery to the DC bus. The water electrolysis hydrogen production unit includes an alkaline electrolyzer and a unidirectional DC / DC converter connecting the alkaline electrolyzer to the DC bus. The hydrogen storage unit includes a hydrogen storage tank and a hydrogen compressor that pressurizes and stores the hydrogen produced by the alkaline electrolyzer into the storage tank. The DC load unit includes a DC load and a unidirectional DC / DC converter connecting the DC load to the DC bus.

[0009] The mathematical model for a wind power generation unit is as follows:

[0010]

[0011] Among them, P WT_t P represents the power output of a wind turbine. wt_rated The rated power of a wind turbine, v t Let v be the wind speed at time t. cut_in v cut_out v rated These are the cut-in wind speed, cut-out wind speed, and rated wind speed of the wind turbine, respectively.

[0012] The mathematical model for a photovoltaic power generation unit is as follows:

[0013]

[0014] Among them, P PV_t P represents the power generation of a photovoltaic cell. PV_rated G represents the rated output power of a photovoltaic cell under standard conditions. t Let G be the solar radiation intensity at time t. STC The standard illumination test intensity is given by k, where k is the photovoltaic cell power temperature coefficient, and T is the standard illumination test intensity. ct T represents the surface temperature of the photovoltaic cell. STC Standard test temperature;

[0015] The SOC model for the charging process of energy storage lithium batteries is as follows:

[0016] SOC(t+1)=SOC(t)+P BAT_t ·Δt·η c / C

[0017] Where SOC(t+1) and SOC(t) are the SOCs of the energy storage lithium battery at time t+1 and time t, respectively; P BAT_t η represents the power of the energy storage lithium battery at time t, with positive for charging and negative for discharging; c C represents the charging efficiency of the energy storage lithium battery, and C represents the capacity of the energy storage lithium battery.

[0018] The SOC model for the discharge process of an energy storage lithium battery is as follows:

[0019]

[0020] Where, η d For the discharge efficiency of energy storage lithium batteries;

[0021] The SOC model for hydrogen storage tanks is as follows:

[0022]

[0023] Among them, SOC TANK (t+1), SOC TANK (t) represents the hydrogen storage capacity (SOC) of the hydrogen storage tank at time t and time t+1, respectively. max This represents the maximum hydrogen storage capacity of the hydrogen storage tank.

[0024] The production model for the electrolyzer is as follows:

[0025]

[0026] Among them, Q H2_t P represents the hydrogen production of the electrolyzer during time period t. in_t Let η be the input power of the microgrid during time period t. t HHV represents the hydrogen production efficiency of the electrolyzer, and HHV represents the higher heating value of hydrogen.

[0027] 2) Based on step 1), establish an operation strategy for the wind-solar-storage coupled off-grid hydrogen production microgrid system. The operation strategy includes the following steps:

[0028] 2.1) First, determine if the current hydrogen storage tank is full. If it is, replace it with an empty hydrogen storage tank and fill it with hydrogen; read the wind turbine power generation P within each time period Δt. WT_t With photovoltaic cell power generation P PV_t The sum of the two is the input power P of the microgrid during that time period. in_t ;

[0029] 2.2) Determine the microgrid input power P in_t Is it less than the starting power threshold of the alkaline electrolyzer? If P in_tIf the power level is less than the starting power threshold of the alkaline electrolyzer, then it is determined whether the energy storage lithium battery has power. If the energy storage lithium battery has power, it provides the deficit power to the electrolyzer, allowing the electrolyzer to operate at the starting power threshold of the alkaline electrolyzer. Otherwise, the alkaline electrolyzer does not operate. Next, it is determined whether the SOC of the energy storage lithium battery is full. If the battery SOC is not full, the microgrid power charges the battery; otherwise, the microgrid power is consumed through the DC load. If P... in_t If the power is greater than or equal to the starting power threshold of the alkaline electrolyzer, proceed to step 2.3);

[0030] 2.3) Determine the input power P on the source side of the microgrid. in_t Is it greater than the rated power P of the electrolytic cell? AEL If P in_t ≤P AEL Then all the power from the source side is injected into the alkaline electrolyzer for hydrogen production; if P in_t >P AEL If the input power of the alkaline electrolyzer is its rated power, the excess power of the grid is used to charge the energy storage lithium battery or consumed through the DC load; and calculate the hydrogen production of the alkaline electrolyzer, the SOC of the energy storage lithium battery and the SOC of the hydrogen storage tank in the current time period.

[0031] 3) Based on the mathematical model, environmental parameters, and operation strategies of the wind-solar-storage coupled off-grid hydrogen production microgrid system, establish the objective function for capacity optimization configuration:

[0032]

[0033] Among them, maxPRO represents the maximum economic benefit over the entire lifecycle of a wind-solar-storage coupled off-grid hydrogen production microgrid system, and R... H2 For the system's hydrogen production revenue, P AEL Where C is the rated power of the alkaline electrolyzer, and N is the capacity of the energy storage lithium battery. TANK C represents the number of hydrogen storage tanks. AEL C BAT C TANK C WT C PV C YS The costs are respectively for the electrolyzer, energy storage lithium battery, hydrogen storage tank, wind turbine, photovoltaic cell and hydrogen compressor;

[0034]

[0035] Among them, S H2 For the price of hydrogen, C AELinv C AELom These represent the unit construction cost and operation and maintenance cost of the alkaline electrolyzer, respectively. aelss represents the actual number of start-ups and shutdowns during the operation of the alkaline electrolyzer, and AELss represents the allowable number of start-ups and shutdowns of the alkaline electrolyzer.

[0036] 4) The weighted mutated particle swarm optimization algorithm is used as the capacity configuration optimization algorithm for the wind-solar-storage coupled off-grid hydrogen production microgrid system. The optimization objective, decision variables, constraints, and downtime of the alkaline electrolyzer throughout its entire lifecycle are set for the capacity configuration of the wind-solar-storage coupled off-grid hydrogen production microgrid system. The iteration termination conditions of the weighted mutated particle swarm optimization algorithm are also set, specifically including:

[0037] Set the optimization target to maxPRO;

[0038] The decision variable is set as the rated power P of the alkaline electrolyzer. AEL The capacity C of the energy storage lithium battery and the number N of hydrogen storage tanks. TANK ;

[0039] The capacity configuration constraints for the wind-solar-storage coupled off-grid hydrogen production microgrid system include:

[0040] System power balance constraints:

[0041] P in_t +P load_t =P WT_t +P PV_t +P BAT_t

[0042] Among them, P in_t P is the input power of the alkaline electrolyzer. load_t For DC load power, P WT_t P represents the power output of a wind turbine. PV_t P represents the power generation capacity of a photovoltaic cell. BAT_t Battery power;

[0043] Capacity constraints of alkaline electrolyzers:

[0044] 0 < P AEL <P WT_rated +P PV_rated

[0045] Among them, P AEL P is the rated power of the alkaline electrolyzer. WT_rated P is the rated power output of the wind turbine. PV_rated The rated power output of the photovoltaic cell;

[0046] State of charge (SOC) constraints for energy storage lithium batteries:

[0047] SOC min ≤SOC(t)≤SOC max

[0048] Where SOC(t) is the real-time charge of the energy storage lithium battery at time t. min and SOC maxThese are the lower and upper limits of the capacity of energy storage lithium batteries, respectively.

[0049] State of charge (SOC) constraints for hydrogen storage tanks:

[0050] 0.05≤SOC TANK (t)≤1

[0051] For hydrogen storage tanks, since the internal pressure of the tank needs to be maintained at a positive value, a State of Charge (SOC) setting is installed here. TANK The lower limit is 5% of its rated capacity; the capacity of the storage tank shall not exceed its rated capacity.

[0052] Set the downtime for the alkaline electrolyzer throughout its entire lifecycle;

[0053] Set the iteration termination condition to the allowed number of iterations;

[0054] According to the operating strategy described in step 2), the environmental parameters are used as the input of the weighted mutated particle swarm optimization algorithm. The weighted mutated particle swarm optimization algorithm is run repeatedly and iterated to obtain the optimal capacity ratio of the wind-solar-storage coupled off-grid hydrogen production microgrid system.

[0055] Furthermore, the starting power threshold for the alkaline electrolyzer in step 2.2) is 0.3P. AEL .

[0056] The beneficial effects of this invention are:

[0057] 1. The present invention provides a capacity optimization configuration method for a wind-solar-storage coupled off-grid hydrogen production microgrid system, wherein the proposed wind-solar-storage coupled off-grid hydrogen production microgrid system provides a new approach for the comprehensive utilization of new energy sources.

[0058] 2. The capacity optimization configuration method for a wind-solar-storage coupled off-grid hydrogen production microgrid system of the present invention fully considers the characteristics of unstable and highly random wind and solar power generation capacity and weak dynamic load tracking capability of alkaline electrolyzers. By establishing an operation strategy for the wind-solar-storage coupled off-grid hydrogen production microgrid system, and taking the maximization of the economic benefit PRO throughout the entire life cycle of the wind-solar-storage coupled off-grid hydrogen production microgrid system as the optimization objective, the capacity configuration of the wind-solar off-grid hydrogen production system is scientific and reasonable, which can reduce the impact of factors such as unstable and highly random wind and solar power generation capacity and weak dynamic load tracking capability of alkaline electrolyzers on the economic benefits of the system. Attached Figure Description

[0059] Figure 1 This is an architecture diagram of a wind-solar-storage coupled off-grid hydrogen production microgrid system;

[0060] Figure 2 This is a flowchart of the capacity configuration of a wind-solar-storage coupled off-grid hydrogen production microgrid system;

[0061] Figure 3This is an operation strategy diagram of a wind-solar-storage coupled off-grid hydrogen production microgrid system. Detailed Implementation

[0062] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0063] The capacity optimization configuration method for the wind-solar-storage coupled off-grid hydrogen production microgrid system in this embodiment includes the following steps:

[0064] 1) Establish mathematical models for each unit of the wind-solar-storage coupled off-grid hydrogen production microgrid system. For example... Figure 1 As shown, the wind-solar-storage coupled off-grid hydrogen production microgrid system includes a DC bus, a wind power generation unit, a photovoltaic power generation unit, a battery energy storage unit, a water electrolysis hydrogen production unit, a hydrogen storage unit, and a DC load unit. The wind power generation unit includes a wind turbine and an AC / DC rectifier connecting the wind turbine to the DC bus; the photovoltaic power generation unit includes photovoltaic cells and a unidirectional DC / DC converter connecting the photovoltaic cells to the DC bus; the battery energy storage unit includes a lithium-ion battery and a bidirectional DC / DC converter connecting the lithium-ion battery to the DC bus; the water electrolysis hydrogen production unit includes an alkaline electrolyzer and a unidirectional DC / DC converter connecting the alkaline electrolyzer to the DC bus; the hydrogen storage unit includes a hydrogen storage tank and a hydrogen compressor that pressurizes the hydrogen produced by the alkaline electrolyzer and stores it in the hydrogen storage tank; the DC load unit includes a DC load and a unidirectional DC / DC converter connecting the DC load to the DC bus, and the DC load can specifically be a load-discharging resistor.

[0065] The mathematical model for a wind power generation unit is as follows:

[0066]

[0067] Among them, P WT_t P represents the power output of a wind turbine. wt_rated The rated power of a wind turbine, v t Let v be the wind speed at time t. cut_in v cut_out v rated These are the cut-in wind speed, cut-out wind speed, and rated wind speed of the wind turbine, respectively.

[0068] The mathematical model for a photovoltaic power generation unit is as follows:

[0069]

[0070] Among them, P PV_t P represents the power generation of a photovoltaic cell. PV_rated G represents the rated output power of a photovoltaic cell under standard conditions. t Let G be the solar radiation intensity at time t. STCThe standard illumination test intensity is given by k, where k is the photovoltaic cell power temperature coefficient, and T is the standard illumination test intensity. ct T represents the surface temperature of the photovoltaic cell. STC This is the standard test temperature.

[0071] The SOC model for the charging process of energy storage lithium batteries is as follows:

[0072] SOC(t+1)=SOC(t)+P BAT_t ·Δt·η c / C

[0073] Where SOC(t+1) and SOC(t) are the SOCs of the energy storage lithium battery at time t+1 and time t, respectively; P BAT_t η represents the power of the energy storage lithium battery at time t, with positive for charging and negative for discharging; c C represents the charging efficiency of the energy storage lithium battery, and C represents the capacity of the energy storage lithium battery.

[0074] The SOC model for the discharge process of an energy storage lithium battery is as follows:

[0075]

[0076] Where, η d This refers to the discharge efficiency of energy storage lithium batteries.

[0077] The SOC model for hydrogen storage tanks is as follows:

[0078]

[0079] Among them, SOC TANK (t+1), SOC TANK (t) represents the hydrogen storage capacity (SOC) of the hydrogen storage tank at time t and time t+1, respectively. max This represents the maximum hydrogen storage capacity of the hydrogen storage tank.

[0080] The production model for the electrolyzer is as follows:

[0081]

[0082] Among them, Q H2_t P represents the hydrogen production of the electrolyzer during time period t. in_t Let η be the input power of the microgrid during time period t. t HHV represents the hydrogen production efficiency of the electrolyzer, and HHV represents the higher heating value of hydrogen.

[0083] 2) Based on step 1), establish an operation strategy for the wind-solar-storage coupled off-grid hydrogen production microgrid system. The operation strategy includes the following steps:

[0084] 2.1) First, determine if the current hydrogen storage tank is full. If it is, replace it with an empty hydrogen storage tank and fill it with hydrogen; read the wind turbine power generation P within each time period Δt. WT_t With photovoltaic cell power generation P PV_t The sum of the two is the input power P of the microgrid during that time period. in_t ;

[0085] 2.2) Determine the microgrid input power P in_t Whether it is less than the starting power threshold of the alkaline electrolyzer. In this embodiment, the starting power threshold of the alkaline electrolyzer is set to 0.3P. AEL If P in_t <0.3P AEL Next, it is determined whether the energy storage lithium battery has power. If the energy storage lithium battery has power, it provides the shortfall power to the electrolyzer, allowing the electrolyzer to operate at 0.3P. AEL Otherwise, the alkaline electrolyzer will not operate. Next, it checks if the lithium-ion battery's SOC is full. If the battery's SOC is not full, the microgrid power charges the battery; otherwise, the microgrid power is consumed through the DC load. If P in_t ≥0.3P AEL Proceed to step 2.3);

[0086] 2.3) Determine the input power P on the source side of the microgrid. in_t Is it greater than the rated power P of the electrolytic cell? AEL If P in_t ≤P AEL Then all the power from the source side is injected into the alkaline electrolyzer for hydrogen production; if P in_t >P AEL If the input power of the alkaline electrolyzer is its rated power, the excess power of the grid is used to charge the energy storage lithium battery or is consumed through the DC load; and calculate the hydrogen production of the alkaline electrolyzer, the SOC of the energy storage lithium battery, and the SOC of the hydrogen storage tank during the current time period.

[0087] 3) Based on the mathematical model, environmental parameters, and operation strategies of the wind-solar-storage coupled off-grid hydrogen production microgrid system, establish the objective function for capacity optimization configuration:

[0088]

[0089] Among them, max PRO represents the maximum economic benefit over the entire lifecycle of a wind-solar-storage coupled off-grid hydrogen production microgrid system, and R... H2 For the system's hydrogen production revenue, P AEL Where C is the rated power of the alkaline electrolyzer, and N is the capacity of the energy storage lithium battery. TANK C represents the number of hydrogen storage tanks. AEL C BAT C TANK C WTC PV C YS These are the costs of the electrolyzer, energy storage lithium battery, hydrogen storage tank, wind turbine, photovoltaic cell, and hydrogen compressor, respectively.

[0090]

[0091] Among them, S H2 For the price of hydrogen, C AELinv C AELom These represent the unit construction cost and operation and maintenance cost of the alkaline electrolyzer, respectively. aelss represents the actual number of start-ups and shutdowns during the operation of the alkaline electrolyzer, while AELss represents the allowable number of start-ups and shutdowns of the alkaline electrolyzer, which is given by the equipment manufacturer.

[0092] 4) The weighted mutated particle swarm optimization algorithm is used as the capacity configuration optimization algorithm for the wind-solar-storage coupled off-grid hydrogen production microgrid system. The optimization objective, decision variables, constraints, and downtime of the alkaline electrolyzer throughout its entire lifecycle are set for the capacity configuration of the wind-solar-storage coupled off-grid hydrogen production microgrid system. The iteration termination conditions of the weighted mutated particle swarm optimization algorithm are also set, specifically including:

[0093] Set the optimization target to maxPRO.

[0094] The decision variable is set as the rated power P of the alkaline electrolyzer. AEL The capacity C of the energy storage lithium battery and the number N of hydrogen storage tanks. TANK .

[0095] The capacity configuration constraints for the wind-solar-storage coupled off-grid hydrogen production microgrid system include:

[0096] System power balance constraints:

[0097] P in_t +P load_t =P WT_t +P PV_t +P BAT_t

[0098] Among them, P in_t P is the input power of the alkaline electrolyzer. load_t For DC load power, P WT_t P represents the power output of a wind turbine. PV_t P represents the power generation capacity of a photovoltaic cell. BAT_t This refers to the battery power.

[0099] Capacity constraints of alkaline electrolyzers:

[0100] 0 < P AEL <P WT_rated +P PV_rated

[0101] Among them, P AEL P is the rated power of the alkaline electrolyzer. WT_rated P is the rated power output of the wind turbine. PV_rated This refers to the rated power output of the photovoltaic cell.

[0102] State of charge (SOC) constraints for energy storage lithium batteries:

[0103] SOC min ≤SOC(t)≤SOC max

[0104] Where SOC(t) is the real-time charge of the energy storage lithium battery at time t. min and SOC max These represent the lower and upper limits of the capacity of energy storage lithium batteries, respectively.

[0105] State of charge (SOC) constraints for hydrogen storage tanks:

[0106] 0.05≤SOC TANK (t)≤1

[0107] For hydrogen storage tanks, since the internal pressure of the tank needs to be maintained at a positive value, a State of Charge (SOC) setting is installed here. TANK The lower limit is 5% of its rated capacity; the capacity of the storage tank shall not exceed its rated capacity.

[0108] Set the downtime for the alkaline electrolyzer throughout its entire lifecycle.

[0109] Set the iteration termination condition to the allowed number of iterations.

[0110] According to the operating strategy described in step 2), environmental parameters are used as inputs to the weighted mutation particle swarm optimization algorithm. These environmental parameters include the aforementioned wind speed v. t Sunlight intensity G t and the surface temperature T of photovoltaic cells ct The weighted mutated particle swarm optimization algorithm was run repeatedly and iterated to obtain the optimal capacity ratio of the wind-solar-storage coupled off-grid hydrogen production microgrid system.

[0111] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for optimizing the capacity configuration of a wind-solar-storage coupled off-grid hydrogen production microgrid system, characterized in that: Includes the following steps: 1) Establish mathematical models for each unit of the wind-solar-storage coupled off-grid hydrogen production microgrid system. The system includes a DC bus, wind power generation units, photovoltaic power generation units, battery energy storage units, water electrolysis hydrogen production units, hydrogen storage units, and DC load units. The wind power generation unit includes a wind turbine and an AC / DC rectifier connecting the wind turbine to the DC bus. The photovoltaic power generation unit includes photovoltaic cells and a unidirectional DC / DC converter connecting the photovoltaic cells to the DC bus. The battery energy storage unit includes a lithium-ion battery and a bidirectional DC / DC converter connecting the lithium-ion battery to the DC bus. The water electrolysis hydrogen production unit includes an alkaline electrolyzer and a unidirectional DC / DC converter connecting the alkaline electrolyzer to the DC bus. The hydrogen storage unit includes a hydrogen storage tank and a hydrogen compressor that pressurizes and stores the hydrogen produced by the alkaline electrolyzer into the storage tank. The DC load unit includes a DC load and a unidirectional DC / DC converter connecting the DC load to the DC bus. The mathematical model for a wind power generation unit is as follows: Among them, P WT_t P represents the power output of a wind turbine. wt_rated The rated power of a wind turbine, v t Let v be the wind speed at time t. cut_in v cut_out v rated These are the cut-in wind speed, cut-out wind speed, and rated wind speed of the wind turbine, respectively. The mathematical model for a photovoltaic power generation unit is as follows: Among them, P PV_t P represents the power generation of a photovoltaic cell. PV_rated G represents the rated output power of a photovoltaic cell under standard conditions. t Let G be the solar radiation intensity at time t. STC The standard illumination test intensity is given by k, where k is the photovoltaic cell power temperature coefficient, and T is the standard illumination test intensity. ct T represents the surface temperature of the photovoltaic cell. STC Standard test temperature; The SOC model for the charging process of energy storage lithium batteries is as follows: SOC(t+1)=SOC(t)+P BAT_t ·Δt·η c / C Where SOC(t+1) and SOC(t) are the SOCs of the energy storage lithium battery at time t+1 and time t, respectively; P BAT_t η represents the power of the energy storage lithium battery at time t, with positive for charging and negative for discharging; c C represents the charging efficiency of the energy storage lithium battery, and C represents the capacity of the energy storage lithium battery. The SOC model for the discharge process of an energy storage lithium battery is as follows: Where, η d For the discharge efficiency of energy storage lithium batteries; The SOC model for hydrogen storage tanks is as follows: SOCIETY TANK (t+1)=SOC TANK (t)+Q H2_t / Q max Among them, SOC TANK (t+1), SOC TANK (t) represents the hydrogen storage capacity (SOC) of the hydrogen storage tank at time t and time t+1, respectively. max This represents the maximum hydrogen storage capacity of the hydrogen storage tank. The production model for the electrolyzer is as follows: Q H2_t =P in_t ·Δt·η t / HHV Among them, Q H2_t P represents the hydrogen production of the electrolyzer during time period t. in_t Let η be the input power of the microgrid during time period t. t HHV represents the hydrogen production efficiency of the electrolyzer, and HHV represents the higher heating value of hydrogen. 2) Based on step 1), establish an operation strategy for the wind-solar-storage coupled off-grid hydrogen production microgrid system. The operation strategy includes the following steps: 2.1) First, determine if the current hydrogen storage tank is full. If it is, replace it with an empty hydrogen storage tank and fill it with hydrogen; read the wind turbine power generation P within each time period Δt. WT_t With photovoltaic cell power generation P PV_t The sum of the two is the input power P of the microgrid during that time period. in_t ; 2.2) Determine the microgrid input power P in_t Is it less than the starting power threshold of the alkaline electrolyzer? If P in_t If the power level is less than the starting power threshold of the alkaline electrolyzer, then it is determined whether the energy storage lithium battery has power. If the energy storage lithium battery has power, it provides the deficit power to the electrolyzer, allowing the electrolyzer to operate at the starting power threshold of the alkaline electrolyzer. Otherwise, the alkaline electrolyzer does not operate. Next, it is determined whether the SOC of the energy storage lithium battery is full. If the battery SOC is not full, the microgrid power charges the battery; otherwise, the microgrid power is consumed through the DC load. If P... in_t If the power is greater than or equal to the starting power threshold of the alkaline electrolyzer, proceed to step 2.3); 2.3) Determine the input power P on the source side of the microgrid. in_t Is it greater than the rated power P of the electrolytic cell? AEL If P in_t ≤P AEL Then all the power from the source side is injected into the alkaline electrolyzer for hydrogen production; if P in_t >P AEL If the input power of the alkaline electrolyzer is its rated power, the excess power of the grid is used to charge the energy storage lithium battery or consumed through the DC load; and calculate the hydrogen production of the alkaline electrolyzer, the SOC of the energy storage lithium battery and the SOC of the hydrogen storage tank in the current time period. 3) Based on the mathematical model, environmental parameters, and operation strategies of the wind-solar-storage coupled off-grid hydrogen production microgrid system, establish the objective function for capacity optimization configuration: Among them, maxPRO represents the maximum economic benefit over the entire lifecycle of a wind-solar-storage coupled off-grid hydrogen production microgrid system, and R... H2 For the system's hydrogen production revenue, P AEL Where C is the rated power of the alkaline electrolyzer, and N is the capacity of the energy storage lithium battery. TANK C represents the number of hydrogen storage tanks. AEL C BAT C TANK C WT C PV C YS The costs are respectively for the electrolyzer, energy storage lithium battery, hydrogen storage tank, wind turbine, photovoltaic cell and hydrogen compressor; Among them, S H2 For the price of hydrogen, C AELinv C AELom These represent the unit construction cost and operation and maintenance cost of the alkaline electrolyzer, respectively. aelss represents the actual number of start-ups and shutdowns during the operation of the alkaline electrolyzer, and AELss represents the allowable number of start-ups and shutdowns of the alkaline electrolyzer. 4) The weighted mutated particle swarm optimization algorithm is used as the capacity configuration optimization algorithm for the wind-solar-storage coupled off-grid hydrogen production microgrid system. The optimization objective, decision variables, constraints, and downtime of the alkaline electrolyzer throughout its entire lifecycle are set for the capacity configuration of the wind-solar-storage coupled off-grid hydrogen production microgrid system. The iteration termination conditions of the weighted mutated particle swarm optimization algorithm are also set, specifically including: Set the optimization target to max PRO; The decision variable is set as the rated power P of the alkaline electrolyzer. AEL The capacity C of the energy storage lithium battery and the number N of hydrogen storage tanks. TANK ; The capacity configuration constraints for the wind-solar-storage coupled off-grid hydrogen production microgrid system include: System power balance constraints: P in_t +P load_t =P WT_t +P PV_t +P BAT_t Among them, P in_t P is the input power of the alkaline electrolyzer. load_t For DC load power, P WT_t P represents the power output of a wind turbine. PV_t P represents the power generation capacity of a photovoltaic cell. BAT_t Battery power; Capacity constraints of alkaline electrolyzers: 0<P AEL <P WT_rated +P PV_rated Among them, P AEL P is the rated power of the alkaline electrolyzer. WT_rated P is the rated power output of the wind turbine. PV_rated The rated power output of the photovoltaic cell; State of charge (SOC) constraints for energy storage lithium batteries: SOC min ≤SOC(t)≤SOC max Where SOC(t) is the real-time charge of the energy storage lithium battery at time t. min and SOC max These are the lower and upper limits of the capacity of energy storage lithium batteries, respectively. Hydrogen storage tank SOC constraints: 0.05≤SOC TANK (t)≤1 For hydrogen storage tanks, since the internal pressure of the tank needs to be maintained at a positive value, a State of Charge (SOC) setting is installed here. TANK The lower limit is 5% of its rated capacity; the capacity of the storage tank shall not exceed its rated capacity. Set the downtime for the alkaline electrolyzer throughout its entire lifecycle; Set the iteration termination condition to the allowed number of iterations; According to the operating strategy described in step 2), the environmental parameters are used as the input of the weighted mutated particle swarm optimization algorithm. The weighted mutated particle swarm optimization algorithm is run repeatedly and iterated to obtain the optimal capacity ratio of the wind-solar-storage coupled off-grid hydrogen production microgrid system.

2. The capacity optimization configuration method for a wind-solar-storage coupled off-grid hydrogen production microgrid system according to claim 1, characterized in that: The starting power threshold for the alkaline electrolyzer in step 2.2) is 0.3P. AEL .

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