Capacity configuration optimization method, electronic device and storage medium of wind-solar hydrogen storage system

Abstract

The present application provides a capacity configuration optimization method, electronic device and storage medium for a wind-solar-hydrogen storage system, which belongs to the technical field of new energy system planning. The method includes: based on a wind-solar-hydrogen storage system model, analyzing the hourly output fluctuations of photovoltaic and wind power, as well as the degree of adaptation between their fluctuating hydrogen production load and the load of the downstream hydrogen production industry; based on the analysis results, determining the overall operation strategy of the wind-solar-hydrogen storage system according to the adaptability of the electrolyzer to load changes and the configuration requirements of the power storage unit; constructing an optimization function according to the overall operation strategy to determine the system optimization boundary conditions, and establishing a capacity configuration optimization model for the wind-solar-hydrogen storage system; based on the capacity configuration optimization model, calculating the optimal capacity configuration solution set of the wind-solar-hydrogen storage system according to the optimization function, and determining the optimal capacity configuration solution set of the wind-solar-hydrogen storage system according to the optimal capacity configuration solution set. The present application scheme can reduce the operation and maintenance costs of the wind-solar-hydrogen storage system.

Description

Technical Field

[0001] The present application relates to the technical field of new energy system planning, and specifically to a capacity configuration optimization method, electronic equipment and storage medium for a wind-solar-hydrogen storage system. Background Art

[0002] In order to maximize the economic benefits and operating efficiency of off-grid wind-solar-hydrogen storage systems, it is crucial to develop a scientific operating strategy. This requires the system to dynamically adjust the output power of wind turbines and solar photovoltaic panels according to weather forecasts and real-time load demand, optimize the process of water electrolysis to produce hydrogen and fuel cell power generation, and reasonably allocate the charging and discharging plan of energy storage equipment.

[0003] Capacity optimization configuration is another key link to ensure the efficient operation of off-grid wind, solar and hydrogen storage systems. It requires comprehensive evaluation and determination of the optimal capacity ratio of wind turbines, solar photovoltaic panels, water electrolysis devices and energy storage equipment based on local wind and solar energy resource conditions, load demand characteristics, and economic costs.

[0004] Through reasonable capacity configuration, the system can effectively reduce construction and operation and maintenance costs while meeting load requirements, thereby further improving overall energy efficiency. However, in the existing technology, the operation and maintenance costs of wind-solar-hydrogen storage systems are relatively high. Therefore, how to reduce the operation and maintenance costs of wind-solar-hydrogen storage systems has become an issue that needs to be resolved. Summary of the invention

[0005] The purpose of this application is to provide a capacity configuration optimization method for a wind-solar-hydrogen storage system, which can solve the problem of high operation and maintenance costs of wind-solar-hydrogen storage systems in the prior art.

[0006] In a first aspect, an embodiment of the present application provides a method for optimizing capacity configuration of a wind-solar-hydrogen storage system, the method comprising: Based on the wind-solar-hydrogen storage system model, the hourly output fluctuations of photovoltaic and wind power, as well as the degree of adaptability between their fluctuating hydrogen production load and the load of downstream hydrogen production industries are analyzed, and the analysis results are obtained; Based on the analysis results, the overall operation strategy of the wind-solar-hydrogen storage system is determined according to the adaptability of the electrolyzer to load changes and the configuration requirements of the power storage unit; According to the overall operation strategy, an optimization function is constructed to determine the system optimization boundary conditions and establish a capacity configuration optimization model for the wind-solar-hydrogen storage system. The optimization function aims to minimize the levelized hydrogen production cost, power failure rate, and wind and solar abandonment rate. Based on the capacity configuration optimization model, the optimal capacity configuration solution set of the wind-solar-hydrogen storage system is calculated according to the optimization function, and the optimal capacity configuration scheme of the wind-solar-hydrogen storage system is determined according to the optimal capacity configuration solution set.

[0007] In a possible implementation manner of the first aspect, the method further includes: Obtain wind and solar resource data, downstream hydrogen production industry demand data, electrolyzer variable load performance data, equipment scale cost and operation constraints in a certain area; establish a wind and solar hydrogen storage system model based on wind and solar resource data, downstream hydrogen production industry demand data, electrolyzer variable load performance data, equipment scale cost and operation constraints.

[0008] In a possible implementation of the first aspect, the wind-solar-hydrogen storage system model includes: a photovoltaic power generation unit model, a wind power generation unit model, an electrolyzer hydrogen production unit model, and a power storage unit model.

[0009] In a possible implementation manner of the first aspect, the photovoltaic power generation unit model includes the following calculation formula:

[0010] in, Indicates the ambient temperature, Indicates the working temperature of photovoltaic cells under standard working conditions. Indicates the ambient temperature under standard working conditions. represents the global irradiance under actual working conditions, represents the global irradiance under standard conditions, represents the heat transfer coefficient under actual working conditions, represents the heat transfer coefficient under standard conditions, represents the actual photovoltaic efficiency, represents the transmittance absorption coefficient;

[0011] in, represents the rated photovoltaic efficiency, represents the temperature coefficient, Indicates the photovoltaic cell temperature under actual working conditions, Indicates the photovoltaic cell temperature under standard operating conditions;

[0012] in, Represents the output of the photovoltaic power generation unit, represents the number of photovoltaic arrays, Represents the effective area of ​​each photovoltaic module, represents the inverter efficiency, Indicates the derating factor.

[0013] In a possible implementation manner of the first aspect, the wind power generation unit model includes the following calculation formula:

[0014] in, Indicates the actual wind speed of the wind turbine. Indicates the rated wind speed of the wind turbine. represents the cut-in wind speed of the wind turbine, represents the cut-out wind speed of the wind turbine, Indicates the rated power of the wind turbine. represents the air density, represents the wind wheel area, represents the wind energy utilization coefficient, It represents the mechanical transmission efficiency. Indicates the power conversion efficiency.

[0015] In a possible implementation manner of the first aspect, the power storage unit model includes the following calculation formula:

[0016] in, Indicates battery Battery capacity at the moment, Indicates battery Battery capacity at the moment, Indicates the battery's self-discharge rate per hour. Indicates the battery charging and discharging status. Indicates the battery charging efficiency, Indicates the battery discharge efficiency, Indicates battery Charging power at the moment, Indicates battery The discharge power at the moment.

[0017] In a possible implementation of the first aspect, the overall operation strategy of the wind-solar hydrogen storage system includes: a first operation strategy when the wind-solar output reaches a first preset condition stage, a second operation strategy when the wind-solar output reaches a second preset condition stage, and a third operation strategy when the wind-solar output reaches a third preset condition stage; The first operation strategy, the second operation strategy and the third operation strategy meet the following power constraints in real time:

[0018] in, Photovoltaic power generation unit t The effort of the moment, Indicates wind power generation unit t The effort of the moment, Represents power storage unit t The effort of the moment, Indicates electrolyzer hydrogen production unit tThe load at the moment, the wind and solar output is: t The sum of the outputs of the photovoltaic power generation unit and the wind power generation unit at that moment.

[0019] In a possible implementation manner of the first aspect, the first preset condition is that the wind and solar power output is greater than the rated load of the electrolyzer hydrogen production unit by a first preset multiple, and the first operation strategy includes: When the state of charge of the electricity storage unit is greater than a preset threshold, the output of the wind turbine is reduced or the wind is abandoned; when the state of charge of the electricity storage unit is less than or equal to the preset threshold, the first excess load of the wind and solar output is used to charge the electricity storage unit until the electricity storage unit is fully charged; wherein the first excess load is: the difference between the wind and solar output and the first preset multiple of the rated load of the electrolyzer hydrogen production unit.

[0020] In a possible implementation manner of the first aspect, the second preset condition is: the second preset multiple of the rated load ≤ wind and solar output ≤ the first preset multiple of the rated load, the second preset condition includes: a first sub-preset condition and a second sub-preset condition, the first sub-preset condition is: n times the rated load ≤ wind and solar output ≤ the first preset multiple of the rated load, the second sub-preset condition is: the second preset multiple of the rated load ≤ wind and solar output ≤ n times the rated load, the second operation strategy includes: When the wind and solar power output reaches the first sub-preset condition, if the charge state of the power storage unit is greater than the preset threshold, the wind and solar power output is supplied to the electrolyzer hydrogen production unit to enable the electrolyzer hydrogen production unit to perform electrolysis; when the wind and solar power output reaches the second sub-preset condition, it is determined whether the battery has a risk of power shortage during the storage cycle; If there is no risk of power shortage, the battery is instructed to increase the power supply load to the electrolyzer hydrogen production unit; if there is a risk of power shortage, or the charge state of the power storage unit is less than or equal to the preset threshold, the second excess load of wind and solar power output is used to charge the power storage unit until the power storage unit is fully charged; Among them, the second excess load is: the difference between the wind and solar power output and n times the rated load of the electrolyzer hydrogen production unit.

[0021] In a possible implementation manner of the first aspect, the third preset condition is: 0≤wind / solar output<second preset multiple of rated load, and the third operation strategy includes: When the state of charge of the power storage unit is greater than or equal to a preset threshold value, and the target supply load of the power storage unit to the electrolyzer hydrogen production unit reaches a second preset multiple of the rated load, the hourly power load of the electrolyzer hydrogen production unit is supplemented to the second preset multiple of the rated load; When the charge state of the power storage unit is less than a preset threshold and the target supply load of the power storage unit to the electrolyzer hydrogen production unit does not reach the second preset multiple of the rated load, the wind and solar power output is used to charge the power storage unit, and the electrolyzer hydrogen production unit is instructed to shut down and enter the insulation state.

[0022] In a possible implementation of the first aspect, the expression of the optimization function is as follows:

[0023] in, represents the minimum levelized hydrogen production cost, Indicates the minimum system power failure rate, represents the minimum wind and solar power abandonment rate, represents the system investment cost, An ordinal number indicating the operating years of the hydrogen production project. Indicates the operating years of the hydrogen production project, represents the system operation and maintenance cost, Indicates the number of times a device in the system is replaced. represents the system equipment replacement cost, represents the residual value of the system at the end of its life cycle, represents the system discount rate, represents the total hydrogen production of the project in the first year, Indicates the attenuation rate of hydrogen production equipment, Indicates the total time the system loses power supply. Indicates the total time the system needs power supply. express t The total photovoltaic power generation at the time, express t The total wind power generation at the time, express t The amount of photovoltaic power used at any time, express t The amount of wind power utilized at any given moment.

[0024] In a possible implementation of the first aspect, the expression of the system optimization boundary condition is as follows:

[0025] in, Indicates the rated load of the electrolyzer hydrogen production unit, Indicates the maximum output of the photovoltaic power generation unit, Indicates the maximum output of the power storage unit, Indicates the total storage capacity of the power storage unit.

[0026] In a possible implementation of the first aspect, obtaining an optimal capacity configuration solution set of a wind-solar-hydrogen storage system according to an optimization function calculation includes: A non-dominated genetic algorithm is used to solve the optimization function and obtain the optimal capacity configuration solution set.

[0027] In a possible implementation of the first aspect, a non-dominated genetic algorithm is used to solve the optimization function to obtain an optimal capacity configuration solution set, including: Select genetic parameters, input data related to the genetic parameters, and generate an initial population according to the decision variables; perform non-dominated sorting on each individual in the initial population, calculate the crowding distance between each individual, select the non-dominated sequence value of the first preset threshold and the crowding distance of the second preset threshold, and obtain the Pareto optimal frontier; Generate a new population according to the Pareto stratification level and crowding degree; determine whether the evolutionary generation number of the new population has reached the maximum evolutionary generation number; if the evolutionary generation number has reached the maximum generation number, the iteration ends and the new population is used as the optimal capacity configuration solution set; otherwise, increase the evolutionary generation number by 1 and continue to execute the step of generating a new population and the steps thereafter.

[0028] In a possible implementation of the first aspect, performing a non-dominated sort on each individual in the initial population includes: According to the preset objective function, the fitness of each individual in the initial population is evaluated to obtain the non-dominated sequence value.

[0029] In a possible implementation of the first aspect, generating a new population according to the Pareto stratification level and the crowding degree includes: According to the stratification level and crowding degree, a new parent population is generated generation by generation, and the new parent population is subjected to selection, crossover and mutation to generate a new child population, and the new parent population and the new child population are combined into a new population.

[0030] In a possible implementation of the first aspect, determining an optimal capacity configuration scheme of a wind-solar-hydrogen storage system according to an optimal capacity configuration solution set includes: The TOPSIS decision method is used to make a comprehensive decision on the optimal capacity configuration solution set and determine the best capacity configuration plan.

[0031] In a possible implementation of the first aspect, a TOPSIS decision method is used to make a comprehensive decision on the optimal capacity configuration solution set to determine the optimal capacity configuration solution, including: For the optimal capacity configuration solution set, the Euclidean distance between each solution is calculated to determine the distance between each point on the non-inferior solution frontier and the ideal point; based on the distance, the solution that is closest to the optimal solution and farthest from the worst solution is determined as the ideal solution, and the ideal solution is used as the optimal capacity configuration solution.

[0032] In a third aspect, an embodiment of the present application provides a capacity configuration optimization device for a wind-solar-hydrogen storage system, the device comprising: The analysis unit is used to analyze the hourly output fluctuation of photovoltaic and wind power, and the adaptability of their fluctuating hydrogen production load and the load of downstream hydrogen production industries based on the wind-solar-hydrogen storage system model, and obtain the analysis results; A determination unit is used to determine the overall operation strategy of the wind-solar-hydrogen storage system based on the analysis results, the adaptability of the electrolyzer to load changes and the configuration requirements of the power storage unit; Establish a unit to construct an optimization function according to the overall operation strategy, determine the system optimization boundary conditions, and establish a capacity configuration optimization model for the wind-solar-hydrogen storage system; the optimization function aims to minimize the levelized hydrogen production cost, power failure rate, and wind and solar abandonment rate; The processing unit is used to calculate the optimal capacity configuration solution set of the wind-solar-hydrogen storage system based on the capacity configuration optimization model and the optimization function, and determine the optimal capacity configuration scheme of the wind-solar-hydrogen storage system based on the optimal capacity configuration solution set.

[0033] In a fourth aspect, an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the capacity configuration optimization method of the wind-solar-hydrogen storage system according to any one of the above-mentioned first aspects is implemented.

[0034] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the capacity configuration optimization method of the wind-solar-hydrogen storage system of any one of the above-mentioned first aspects.

[0035] In a sixth aspect, an embodiment of the present application provides a computer program product. When the computer program product is run on an electronic device, the electronic device executes the capacity configuration optimization method of the wind-solar-hydrogen storage system according to any one of the above-mentioned first aspects.

[0036] This application scheme is based on the wind-solar-hydrogen storage system model, and analyzes the hourly output fluctuations of photovoltaic and wind power, as well as the degree of adaptation of their fluctuating hydrogen production load and the load of downstream hydrogen production industries to obtain analysis results; based on the analysis results, the overall operation strategy of the wind-solar-hydrogen storage system is determined according to the adaptability of the electrolyzer to load changes and the configuration requirements of the storage unit; according to the overall operation strategy, an optimization function is constructed to determine the system optimization boundary conditions, and a capacity configuration optimization model for the wind-solar-hydrogen storage system is established; the optimization function aims to minimize the levelized hydrogen production cost, power outage rate, and wind and solar power abandonment rate; based on the capacity configuration optimization model, the optimal capacity configuration solution set of the wind-solar-hydrogen storage system is calculated according to the optimization function, and the optimal capacity configuration scheme of the wind-solar-hydrogen storage system is determined according to the optimal capacity configuration solution set.

[0037] This application scheme obtains the optimal capacity configuration scheme of the wind-solar-hydrogen storage system through calculation, optimizes the capacity configuration of the wind-solar-hydrogen storage system, can reduce the operation and maintenance cost of the wind-solar-hydrogen storage system, and has strong ease of use and practicality.

[0038] Other features and advantages of the present application will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0040] Figure 1 It is a schematic diagram of the steps of the capacity configuration optimization method of the wind-solar-hydrogen storage system provided in an embodiment of the present application; Figure 2 It is a flowchart of the system operation strategy provided by the embodiment of the present application; Figure 3 It is a structural schematic diagram of a capacity configuration optimization device for a wind-solar hydrogen storage system provided in an embodiment of the present application; Figure 4 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0041] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0042] It should be understood that when used in this specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or photovoltaic components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, photovoltaic components and / or combinations thereof.

[0043] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0044] It should be further understood that the term “and / or” used in the specification and appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0045] As used in this specification and the appended claims, the term "if" may be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrases "if it is determined" or "if [described condition or event] is detected" may be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0046] In addition, in the description of the present application, the terms "first", "second", "third", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0047] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0048] With the increasing attention paid to renewable energy around the world and the clear proposal of my country's "dual carbon" goals, wind and solar renewable energy hydrogen production technology has become an important technical path to promote the development of green industry. Against this background, off-grid wind and solar hydrogen storage systems have emerged. The system integrates wind energy, solar energy and hydrogen energy technologies, and can make full use of local resources to meet energy needs without relying on traditional power networks. This innovation not only promotes the local consumption of renewable energy, but also effectively alleviates the pressure on power grid construction and significantly improves energy utilization efficiency.

[0049] In off-grid wind-solar hydrogen storage systems, hydrogen energy plays a core role with its high efficiency and clean characteristics. Through fuel cell technology, hydrogen energy can convert stored chemical energy into electrical energy to meet load requirements. At the same time, when wind and solar resources are insufficient, hydrogen energy, as a backup energy source, ensures the continuous and stable operation of the system. In addition, with the help of storage facilities such as high-pressure gas cylinders or liquid hydrogen storage tanks, hydrogen can achieve long-term, large-scale energy storage, further enhancing the flexibility and reliability of the system.

[0050] In order to maximize the economic benefits and operating efficiency of the system, it is crucial to formulate a scientific operating strategy. This requires the system to dynamically adjust the output power of wind turbines and solar photovoltaic panels according to weather forecasts and real-time load demand, optimize the process of water electrolysis to produce hydrogen and fuel cell power generation, and reasonably allocate the charging and discharging plan of energy storage equipment. Through this series of refined management measures, the system can maximize the use of energy while ensuring stable operation.

[0051] Capacity optimization configuration is another key link to ensure the efficient operation of off-grid wind-solar-hydrogen storage systems. It is necessary to comprehensively evaluate and determine the optimal capacity ratio of wind turbines, solar photovoltaic panels, water electrolysis devices and energy storage equipment based on local wind and solar energy resources, load demand characteristics, and economic costs. Through reasonable capacity configuration, the system can effectively reduce construction and operation and maintenance costs while meeting load requirements, thereby further improving overall energy efficiency.

[0052] In the existing technology, renewable energy hydrogen production systems have high costs, poor reliability and flexibility. Therefore, how to reduce the operation and maintenance costs of wind-solar-hydrogen storage systems has become an unresolved issue.

[0053] In response to the above-mentioned defects, an embodiment of the present application provides a capacity configuration optimization method for a wind-solar-hydrogen storage system. Based on a wind-solar-hydrogen storage system model, the hourly output fluctuations of photovoltaic and wind power, as well as the degree of adaptation between their fluctuating hydrogen production load and the load of the downstream hydrogen production industry are analyzed to obtain analysis results; based on the analysis results, the overall operation strategy of the wind-solar-hydrogen storage system is determined according to the adaptability of the electrolyzer to load changes and the configuration requirements of the power storage unit; an optimization function is constructed according to the overall operation strategy, the system optimization boundary conditions are determined, and a capacity configuration optimization model for the wind-solar-hydrogen storage system is established; the optimization function takes the lowest levelized hydrogen production cost, power outage rate, and wind and solar abandonment rate as the goal; based on the capacity configuration optimization model, the optimal capacity configuration solution set of the wind-solar-hydrogen storage system is calculated according to the optimization function, and the optimal capacity configuration scheme of the wind-solar-hydrogen storage system is determined according to the optimal capacity configuration solution set.

[0054] This application scheme obtains the optimal capacity configuration scheme of the wind-solar-hydrogen storage system through calculation, optimizes the capacity configuration of the wind-solar-hydrogen storage system, can reduce the operation and maintenance cost of the wind-solar-hydrogen storage system, and has strong ease of use and practicality.

[0055] The specific process implemented by this application is introduced below through specific embodiments.

[0056] See also Figure 1 , Figure 1 Schematic diagram of the steps of the capacity configuration optimization method of the wind-solar hydrogen storage system provided in the embodiment of the present application. The method is implemented as follows: Figure 1 As shown, the method may include the following steps: S101, based on the wind-solar-hydrogen storage system model, analyze the hourly output fluctuations of photovoltaic and wind power, as well as the degree of adaptation of their fluctuating hydrogen production load and the load of downstream hydrogen production industries, and obtain the analysis results.

[0057] According to one embodiment of the present application, the method further includes: Obtain wind and solar resource data, downstream hydrogen production industry demand data, electrolyzer variable load performance data, equipment scale cost and operation constraints for a certain region (such as Gansu, etc.). Build a wind and solar hydrogen storage system model based on wind and solar resource data, downstream hydrogen production industry demand data, electrolyzer variable load performance data, equipment scale cost and operation constraints.

[0058] In some embodiments, the wind and solar resource data mainly include: photovoltaic irradiance, ambient temperature, surface wind speed and hub height wind speed corresponding to the wind turbine in a certain area. The demand data of the downstream hydrogen production industry mainly includes the constraints of the downstream industry on the volatility of hydrogen supply and its working hours. The equipment scale cost mainly includes: the initial investment cost, operation and maintenance cost, and replacement cost of equipment components during the period for equipment such as wind turbines, photovoltaic modules, electrolyzers and batteries. The variable load performance data of the electrolyzer mainly includes: the performance curve of current density and voltage within the adjustable load.

[0059] According to one embodiment of the present application, the wind-solar-hydrogen storage system model includes: a photovoltaic power generation unit model, a wind power generation unit model, an electrolyzer hydrogen production unit model and a power storage unit model.

[0060] In some embodiments, the photovoltaic power generation unit and the wind power generation unit are used as the optimal power supply units for the electrolyzer hydrogen production unit, and the excess power of renewable energy can be stored in the power storage unit for emergency use. At the same time, the power storage unit can also provide power flexibly to ensure the stable operation of the system.

[0061] According to one embodiment of the present application, the photovoltaic power generation unit model includes the following calculation formula:

[0062] in, Indicates the ambient temperature, Indicates the working temperature of photovoltaic cells under standard working conditions. Indicates the ambient temperature under standard working conditions. represents the global irradiance under actual working conditions, represents the global irradiance under standard conditions, represents the heat transfer coefficient under actual working conditions, represents the heat transfer coefficient under standard conditions, represents the actual photovoltaic efficiency, represents the transmittance absorption coefficient;

[0063] in, represents the rated photovoltaic efficiency, represents the temperature coefficient, Indicates the photovoltaic cell temperature under actual working conditions, Indicates the photovoltaic cell temperature under standard operating conditions;

[0064] in, Represents the output of the photovoltaic power generation unit, represents the number of photovoltaic arrays, Represents the effective area of ​​each photovoltaic module, represents the inverter efficiency, Indicates the derating factor.

[0065] According to one embodiment of the present application, the wind power generation unit model includes the following calculation formula:

[0066] in, Indicates the actual wind speed of the wind turbine. Indicates the rated wind speed of the wind turbine. represents the cut-in wind speed of the wind turbine, represents the cut-out wind speed of the wind turbine, Indicates the rated power of the wind turbine. represents the air density, represents the wind wheel area, represents the wind energy utilization coefficient, It represents the mechanical transmission efficiency. Indicates the power conversion efficiency.

[0067] According to one embodiment of the present application, the power storage unit model includes the following calculation formula:

[0068] in, Indicates battery Battery capacity at the moment, Indicates battery Battery capacity at the moment, Indicates the battery's self-discharge rate per hour. Indicates the battery charging and discharging status. Indicates the battery charging efficiency, Indicates the battery discharge efficiency, Indicates battery Charging power at the moment, Indicates battery The discharge power at the moment.

[0069] In some embodiments, the wind and solar data of a certain area in Gansu are input into the photovoltaic power generation model and the wind power generation model to analyze the impact of the hourly output fluctuations of photovoltaic and wind power on the electrolyzer hydrogen production unit. The focus is mainly on three different power generation scenarios: a single photovoltaic power generation system, a single wind power generation system, and a wind-solar coupling power generation system. The power output volatility on the time scales of the whole year, a typical week, and a typical day is comprehensively evaluated. The reasonable matching relationship is analyzed as much as possible based on the lower limit of the electrolyzer hydrogen production unit load, thereby ensuring the safe operation of electrical equipment.

[0070] S102: Based on the analysis results, the overall operation strategy of the wind-solar-hydrogen storage system is determined according to the adaptability of the electrolyzer to load changes and the configuration requirements of the power storage unit.

[0071] According to an implementation mode of the present application, the overall operation strategy of the wind-solar hydrogen storage system includes: a first operation strategy when the wind-solar output reaches the first preset condition stage, a second operation strategy when the wind-solar output reaches the second preset condition stage, and a third operation strategy when the wind-solar output reaches the third preset condition stage; The first operation strategy, the second operation strategy and the third operation strategy meet the following power constraints in real time:

[0072] in, Photovoltaic power generation unit t The effort of the moment, Indicates wind power generation unit t The effort of the moment, Represents power storage unit t The effort of the moment, Indicates electrolyzer hydrogen production unit t The load at the moment, the wind and solar output is: t The sum of the outputs of the photovoltaic power generation unit and the wind power generation unit at that moment.

[0073] According to an implementation mode of the present application, the first preset condition is that the wind and solar power output is greater than the rated load of the electrolyzer hydrogen production unit by a first preset multiple, and the first operation strategy includes: When the state of charge of the electricity storage unit is greater than a preset threshold, the output of the wind turbine is reduced or the wind is abandoned; when the state of charge of the electricity storage unit is less than or equal to the preset threshold, the first excess load of the wind and solar output is used to charge the electricity storage unit until the electricity storage unit is fully charged; wherein the first excess load is: the difference between the wind and solar output and the first preset multiple of the rated load of the electrolyzer hydrogen production unit.

[0074] According to an implementation manner of the present application, the second preset condition is: the second preset multiple of the rated load ≤ wind and solar output ≤ the first preset multiple of the rated load, the second preset condition includes: the first sub-preset condition and the second sub-preset condition, the first sub-preset condition is: n times the rated load ≤ wind and solar output ≤ the first preset multiple of the rated load, the second sub-preset condition is: the second preset multiple of the rated load ≤ wind and solar output ≤ n times the rated load, the second operation strategy includes: When the wind and solar power output reaches the first sub-preset condition, if the charge state of the power storage unit is greater than the preset threshold, the wind and solar power output is supplied to the electrolyzer hydrogen production unit to enable the electrolyzer hydrogen production unit to perform electrolysis; when the wind and solar power output reaches the second sub-preset condition, it is determined whether the battery has a risk of power shortage during the storage cycle; If there is no risk of power shortage, the battery is instructed to increase the power supply load to the electrolyzer hydrogen production unit; if there is a risk of power shortage, or the charge state of the power storage unit is less than or equal to the preset threshold, the second excess load of wind and solar power output is used to charge the power storage unit until the power storage unit is fully charged; Among them, the second excess load is: the difference between the wind and solar power output and n times the rated load of the electrolyzer hydrogen production unit.

[0075] According to an implementation manner of the present application, the third preset condition is: 0≤wind and solar output<rated load of the second preset multiple, and the third operation strategy includes: When the state of charge of the power storage unit is greater than or equal to a preset threshold value, and the target supply load of the power storage unit to the electrolyzer hydrogen production unit reaches a second preset multiple of the rated load, the hourly power load of the electrolyzer hydrogen production unit is supplemented to the second preset multiple of the rated load; When the charge state of the power storage unit is less than a preset threshold and the target supply load of the power storage unit to the electrolyzer hydrogen production unit does not reach the second preset multiple of the rated load, the wind and solar power output is used to charge the power storage unit, and the electrolyzer hydrogen production unit is instructed to shut down and enter the insulation state.

[0076] In some embodiments, according to the fluctuation of wind and solar power output in the wind-solar hydrogen storage system model, the electrolyzer hydrogen production model is used to calculate the fluctuation of the electrolyzer load, and according to the adaptability of the electrolyzer hydrogen production unit, a system operation strategy including three stages of abundant wind and solar power output, partial wind and solar power supply, and insufficient wind and solar power output is designed. The flow chart of the system operation strategy is as follows: Figure 2 shown.

[0077] Phase 1: The stage of abundant wind and solar power output ( ), only the state of charge (SOC) of the storage unit needs to be considered. When the storage unit is fully charged (SoC>0.98), the wind turbine output is reduced or the wind is abandoned. The excess load is all used to charge the storage unit until it is fully charged.

[0078] Phase 2: The wind and solar power supply phase ( ), is divided into two parts, When the power storage unit is fully charged (SoC>0.98), all wind and solar power output is supplied to the electrolyzer hydrogen production unit for electrolysis. When the battery is in a state of low power, determine whether there is a risk of low power during the battery cycle. If there is no risk of low power ( ), the battery increases the power supply load of the electrolyzer hydrogen production unit. When there is a risk of power shortage or SoC<0.98 during the cycle, the battery will be used first. The excess load is all used to charge the storage unit until it is fully charged.

[0079] Stage 3: The stage of insufficient wind and solar power output ( ), when the storage power can supply When the battery makes up for the remaining load, it ensures the safe operation of the electrolyzer hydrogen production unit. All the output is used to charge the power storage unit, and the electrolyzer hydrogen production unit is shut down and enters the insulation state.

[0080] In one embodiment, it is determined whether the power storage unit has power, that is, whether the SOC is ≥ 0.05. If the SOC is ≥ 0.05, the battery can supply power to the electrolytic cell. When the electrolytic cell is charged hourly (in real time), For example, the real-time electrical load of the electrolyzer is , the battery can be replenished to .

[0081] It should be noted that the operation strategy of the wind-solar-hydrogen storage system must always meet the system power constraints ( ).

[0082] S103, construct an optimization function based on the overall operation strategy, determine the system optimization boundary conditions, and establish a capacity configuration optimization model for the wind-solar-hydrogen storage system; the optimization function aims to minimize the levelized hydrogen production cost, power outage rate, and wind and solar abandonment rate.

[0083] According to one implementation of the present application, the expression of the optimization function is as follows:

[0084] in, represents the minimum levelized hydrogen production cost, Indicates the minimum system power failure rate, represents the minimum wind and solar power abandonment rate, represents the system investment cost, An ordinal number indicating the operating years of the hydrogen production project. Indicates the operating years of the hydrogen production project, represents the system operation and maintenance cost, Indicates the number of times a device in the system is replaced. represents the system equipment replacement cost, represents the residual value of the system at the end of its life cycle, represents the system discount rate, represents the total hydrogen production of the project in the first year, Indicates the attenuation rate of hydrogen production equipment, Indicates the total time the system loses power supply. Indicates the total time the system needs power supply. express t The total photovoltaic power generation at the time, express t The total wind power generation at the time, express t The amount of photovoltaic power used at any time, express t The amount of wind power utilized at any given moment.

[0085] According to one embodiment of the present application, the expression of the system optimization boundary condition is as follows:

[0086] in, Indicates the rated load of the electrolyzer hydrogen production unit, Indicates the maximum output of the photovoltaic power generation unit, Indicates the maximum output of the power storage unit, Indicates the total storage capacity of the power storage unit.

[0087] In a series of embodiments, the electrolyzer is in hydrogen production mode when the input power is between 10% and 110% load, and in hot standby mode when the input power is below 10% load. In this mode, the electrolyzer does not produce hydrogen, but the equipment must be kept at the optimal hydrogen production temperature and pressure state, ready for hot start at any time, and it only takes 15 minutes for the electrolyzer input power to increase from 10% to 110% load. The state of charge of the power storage unit is 0.05 to 0.98.

[0088] S104, based on the capacity configuration optimization model, the optimal capacity configuration solution set of the wind-solar-hydrogen storage system is calculated according to the optimization function, and the optimal capacity configuration scheme of the wind-solar-hydrogen storage system is determined according to the optimal capacity configuration solution set.

[0089] According to one implementation of the present application, the optimal capacity configuration solution set of the wind-solar-hydrogen storage system is calculated according to the optimization function, including: using a non-dominated genetic algorithm to solve the optimization function to obtain the optimal capacity configuration solution set.

[0090] According to an implementation of the present application, a non-dominated genetic algorithm is used to solve the optimization function to obtain an optimal capacity configuration solution set, including: Select genetic parameters, input data related to genetic parameters, and generate an initial population based on decision variables. Perform non-dominated sorting on each individual in the initial population, calculate the crowding distance between each individual, select the non-dominated sequence value of the first preset threshold and the crowding distance of the second preset threshold, and obtain the Pareto optimal frontier.

[0091] Generate a new population based on the Pareto stratification level and crowding degree, and determine whether the evolutionary generation of the new population has reached the maximum evolutionary generation. If the evolutionary generation reaches the maximum, the iteration ends and the new population is used as the optimal capacity configuration solution set; otherwise, increase the evolutionary generation by 1 and continue to execute the steps of generating a new population and the steps after that.

[0092] According to an implementation of the present application, performing non-dominated sorting on each individual in the initial population includes: evaluating the fitness of each individual in the initial population according to a preset objective function to obtain a non-dominated sequence value.

[0093] According to one implementation of the present application, a new population is generated according to the Pareto stratification level and the crowding degree, including: generating a new parent population generation by generation according to the stratification level and the crowding degree, performing selection, crossover and mutation processing on the new parent population to generate a new child population, and combining the new parent population and the new child population into a new population.

[0094] The capacity configuration optimization model of the wind-solar-hydrogen storage system is optimized using the non-dominated sorting genetic algorithm (NSGA-II). The steps of the optimization algorithm are as follows: Step 1: Select genetic parameters such as population size N, maximum number of generations M, etc. Input data related to the parameters, including load, irradiance, etc. Initialization is to generate an initial population PM based on the decision variables.

[0095] Step 2: Non-dominated sorting evaluates the fitness of each individual according to the given objective function. Perform fast non-dominated sorting and calculate crowding distance. Select lower rank and higher crowding distance to obtain the Pareto optimal frontier F=(F1, F2, F3). The crowding distance is mainly to maintain the diversity of individuals in the population.

[0096] Step 3: Generate a new parent population P based on Pareto level and crowding m+1 , select, crossover, and mutate the selected parent to generate a new offspring population Q m , and then the parent population P m and the offspring population Q m , synthesize a new population R m Then, proceed to the second step to generate a new parent population P m+1 , calculated generation by generation.

[0097] Step 4: Determine whether the evolutionary algebra is equal to the maximum evolutionary algebra. If it reaches the maximum algebra, the iteration ends; otherwise, the evolutionary algebra m=m+1, and return to step 3.

[0098] According to one implementation of the present application, the optimal capacity configuration scheme of the wind-solar-hydrogen storage system is determined according to the optimal capacity configuration solution set, including: using the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) decision method to make a comprehensive decision on the optimal capacity configuration solution set to determine the optimal capacity configuration scheme.

[0099] According to an implementation mode of the present application, the TOPSIS decision method is used to make a comprehensive decision on the optimal capacity configuration solution set to determine the optimal capacity configuration solution, including: For the optimal capacity configuration solution set, the Euclidean distance between each solution is calculated to determine the distance between each point on the non-inferior solution frontier and the ideal point (lowest point). Based on the distance, the solution closest to the optimal solution and farthest from the worst solution is determined as the ideal solution, and the ideal solution is used as the optimal capacity configuration solution.

[0100] In some embodiments, in order to verify the convergence and optimization results of the established optimization model, the capacity configuration model is solved using mathematical modeling software. The maximum number of iterations of the algorithm is selected as 500, the number of populations is 100, and the case of renewable energy / hydrogen production device capacity configuration of 2 / 1 is used as the reference system for comparison. Among them, the electrolyzer capacity is unified as 100MW, the capacity configuration of the reference system and the optimized system is shown in Table 1, and the comprehensive performance of each scheme is shown in Table 2.

[0101] Table 1

[0102] Table 2

[0103] The standardized hydrogen production cost (LCOH) of the two optimization methods obtained from the above specific implementation plan is lower than 19.4 yuan / kg of the reference system, and the economic benefit optimization effect is more obvious. Among them, the system power failure rate indicator of optimization scheme 1 symbolizes the stability of the system, which is also better than the reference system, and its wind and solar power abandonment rate is also lower. Therefore, this method has a good development and application prospect.

[0104] The capacity configuration optimization method of the wind-solar-hydrogen storage system provided in the embodiment of the present application is based on the wind-solar-hydrogen storage system model, analyzes the hourly output fluctuations of photovoltaic and wind power, and the degree of adaptation of their fluctuating hydrogen production load and the load of the downstream hydrogen production industry, and obtains analysis results; based on the analysis results, the overall operation strategy of the wind-solar-hydrogen storage system is determined according to the adaptability of the electrolyzer to load changes and the configuration requirements of the power storage unit; according to the overall operation strategy, an optimization function is constructed to determine the system optimization boundary conditions, and a capacity configuration optimization model for the wind-solar-hydrogen storage system is established; the optimization function takes the minimum levelized hydrogen production cost, power failure rate and wind and solar power abandonment rate as the goal; based on the capacity configuration optimization model, the optimal capacity configuration solution set of the wind-solar-hydrogen storage system is calculated according to the optimization function, and the optimal capacity configuration scheme of the wind-solar-hydrogen storage system is determined according to the optimal capacity configuration solution set.

[0105] This application scheme obtains the optimal capacity configuration scheme of the wind-solar-hydrogen storage system through calculation, optimizes the capacity configuration of the wind-solar-hydrogen storage system, can reduce the operation and maintenance cost of the wind-solar-hydrogen storage system, and has strong ease of use and practicality.

[0106] This application scheme obtains relevant data such as local resource endowment, equipment performance and cost, and constructs an optimization function with the goal of minimizing the levelized hydrogen production cost, system power outage rate, and wind and solar power abandonment rate. An off-grid wind-solar hydrogen storage system operation strategy is proposed to further improve the system operation constraints. The non-dominated genetic algorithm is used to obtain the optimal capacity configuration solution set of the system, avoiding the problem of local optimal solution and improving the reliability of capacity configuration. The TOPSIS decision-making method is used to select the best wind-solar hydrogen storage system configuration plan according to actual needs, which saves a lot of investment and operating costs for the system and enhances the sustainability of the hydrogen production system.

[0107] This application plan targets local resource endowments, further analyzes the adaptability of electrolyzers to load changes and the configuration requirements of power storage units, and designs wind-solar-hydrogen-storage system operation strategies. Subsequently, a capacity optimization configuration model is constructed with the goal of minimizing the levelized hydrogen production cost, power outage rate, and wind and solar power abandonment rate. Under constraints such as total system investment and system power balance, and factors such as the life loss of major equipment are considered, a non-dominated genetic algorithm is used to solve the Pareto frontier solution set, and then the TOPSIS decision-making method is used to quantitatively evaluate the optimal Pareto solution set. Finally, the best wind-solar-hydrogen-storage system configuration plan is selected based on actual needs.

[0108] This application plan not only focuses on the economic efficiency of the project, but also ensures the stability of the system, which helps to improve the economic benefits of the system and the utilization rate of renewable energy. It has certain reference and application value in the planning and design stage of new energy power stations.

[0109] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0110] Corresponding to the method of the above embodiment, Figure 3 1 is a schematic diagram of the structure of the capacity configuration optimization device of the wind-solar-hydrogen storage system provided in the embodiment of the present application. For the convenience of explanation, only the parts related to the embodiment of the present application are shown.

[0111] Reference Figure 3 , the device comprises: The analysis unit 301 is used to analyze the hourly output fluctuation of photovoltaic and wind power and the adaptability of their fluctuating hydrogen production load and the load of downstream hydrogen production industries based on the wind-solar-hydrogen storage system model to obtain analysis results; A determination unit 302 is used to determine the overall operation strategy of the wind-solar-hydrogen storage system based on the analysis results, according to the adaptability of the electrolyzer to load changes and the configuration requirements of the power storage unit; Establishing unit 303, for constructing an optimization function according to the overall operation strategy, determining the system optimization boundary conditions, and establishing a capacity configuration optimization model for the wind-solar-hydrogen storage system; the optimization function aims to minimize the levelized hydrogen production cost, power failure rate, and wind and solar abandonment rate; Processing unit 304 is used to calculate the optimal capacity configuration solution set of the wind-solar-hydrogen storage system based on the capacity configuration optimization model and the optimization function, and determine the optimal capacity configuration scheme of the wind-solar-hydrogen storage system based on the optimal capacity configuration solution set.

[0112] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0113] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0114] See also Figure 4 , Figure 4 Schematic diagram of the structure of the electronic device 4 provided in the embodiment of the present application. Figure 4 As shown, the electronic device 4 of this embodiment includes: at least one processor 401 ( Figure 4 Only one is shown in the figure), a memory 403, and a computer program 402 stored in the memory 403 and executable on at least one processor 401, wherein the processor 401 implements the steps in the above method embodiment when executing the computer program 402.

[0115] The electronic device 4 may be a computing device such as a desktop computer, a notebook, a PDA, or a mobile phone. The electronic device 4 may include, but is not limited to, a processor 401 and a memory 403. Those skilled in the art will appreciate that Figure 4 It is only an example of the electronic device 4 and does not constitute a limitation on the electronic device 4. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, it may also include input and output devices, network access devices, etc.

[0116] The processor 401 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 photovoltaic modules, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0117] In some embodiments, the memory 403 may be an internal storage unit of the electronic device 4, such as a hard disk or memory of the electronic device 4. In other embodiments, the memory 403 may also be an external storage device of the electronic device 4, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital card (SecureDigital, SD), a flash card (Flash Card), etc. equipped on the electronic device 4. Further, the memory 403 may also include both an internal storage unit of the electronic device 4 and an external storage device. The memory 403 is used to store an operating system, an application program, a boot loader (Boot Loader), data, and other programs, such as program codes of a computer program, etc. The memory 403 may also be used to temporarily store data that has been output or is to be output.

[0118] If the above-mentioned integrated unit 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, when the present application implements all or part of the processes in the above-mentioned embodiment method, it can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, it can implement the steps applied to the above-mentioned method embodiment. Among them, the computer program includes computer program code, which can be in source code form, object code form, executable file or some intermediate form. The computer-readable storage medium may at least include: any entity or device that can carry the computer program code to the computing device / electronic device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, such as USB flash drive, mobile hard disk, disk or optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable storage media cannot be electric carrier signals and telecommunication signals.

[0119] An embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0120] An embodiment of the present application provides a computer program product. When the computer program product is run on an electronic device, the electronic device executes the steps in the above-mentioned method embodiments.

[0121] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0122] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0123] In the embodiments provided in the present application, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. The device / electronic device embodiments described above are merely schematic, and the division of the above modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or photovoltaic components can be combined or integrated into another system, and some features can be ignored and not executed. Another point is that the indirect coupling, direct coupling or communication connection between each other shown or discussed can be an indirect coupling, direct coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0124] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0125] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A capacity configuration optimization method for a wind-solar hydrogen storage system, characterized in that: The method comprises: Based on the wind-solar-hydrogen storage system model, the hourly output fluctuations of photovoltaic and wind power, as well as the degree of adaptability between their fluctuating hydrogen production load and the load of downstream hydrogen production industries are analyzed, and the analysis results are obtained; Based on the analysis results, the overall operation strategy of the wind-solar hydrogen storage system is determined according to the adaptability of the electrolyzer to load changes and the configuration requirements of the power storage unit; According to the overall operation strategy, an optimization function is constructed, the system optimization boundary conditions are determined, and a capacity configuration optimization model of the wind-solar-hydrogen storage system is established; the optimization function aims to minimize the levelized hydrogen production cost, power failure rate, and wind and solar abandonment rate; Based on the capacity configuration optimization model, the optimal capacity configuration solution set of the wind-solar-hydrogen storage system is calculated according to the optimization function, and the optimal capacity configuration scheme of the wind-solar-hydrogen storage system is determined according to the optimal capacity configuration solution set.

2. The capacity configuration optimization method of the wind-solar hydrogen storage system according to claim 1 is characterized in that: The method further comprises: Obtain data on wind and solar resources in a certain region, demand data on downstream hydrogen production industries, variable load performance data on electrolyzers, equipment scale costs, and operating constraints; The wind-solar-hydrogen storage system model is established based on wind-solar-hydrogen resource data, downstream hydrogen production industry demand data, electrolyzer variable load performance data, equipment scale cost and operation constraints.

3. The capacity configuration optimization method of the wind-solar hydrogen storage system according to claim 1 is characterized in that: The wind-solar-hydrogen storage system model includes: a photovoltaic power generation unit model, a wind power generation unit model, an electrolyzer hydrogen production unit model and a power storage unit model.

4. The capacity configuration optimization method of the wind-solar hydrogen storage system according to claim 3 is characterized in that: The photovoltaic power generation unit model includes the following calculation formula: in, Indicates the ambient temperature, Indicates the working temperature of photovoltaic cells under standard working conditions. Indicates the ambient temperature under standard working conditions. represents the global irradiance under actual working conditions, represents the global irradiance under standard conditions, represents the heat transfer coefficient under actual working conditions, represents the heat transfer coefficient under standard conditions, represents the actual photovoltaic efficiency, represents the transmittance absorption coefficient; in, represents the rated photovoltaic efficiency, represents the temperature coefficient, Indicates the photovoltaic cell temperature under actual working conditions, Indicates the photovoltaic cell temperature under standard operating conditions; in, Represents the output of the photovoltaic power generation unit, represents the number of photovoltaic arrays, Represents the effective area of ​​each photovoltaic module, represents the inverter efficiency, Indicates the derating factor.

5. The capacity configuration optimization method of the wind-solar hydrogen storage system according to claim 3 is characterized in that: The wind power generation unit model includes the following calculation formula: in, Indicates the actual wind speed of the wind turbine. Indicates the rated wind speed of the wind turbine. represents the cut-in wind speed of the wind turbine, represents the cut-out wind speed of the wind turbine, Indicates the rated power of the wind turbine. represents the air density, represents the wind wheel area, represents the wind energy utilization coefficient, It represents the mechanical transmission efficiency. Indicates the power conversion efficiency.

6. The capacity configuration optimization method of the wind-solar hydrogen storage system according to claim 3 is characterized in that: The power storage unit model includes the following calculation formula: in, Indicates battery Battery capacity at the moment, Indicates battery Battery capacity at the moment, Indicates the battery's self-discharge rate per hour. Indicates the battery charging and discharging status. Indicates the battery charging efficiency, Indicates the battery discharge efficiency, Indicates battery Charging power at the moment, Indicates battery The discharge power at the moment.

7. The capacity configuration optimization method of the wind-solar hydrogen storage system according to claim 1 is characterized in that: The overall operation strategy of the wind-solar hydrogen storage system includes: a first operation strategy when the wind-solar output reaches the first preset condition stage, a second operation strategy when the wind-solar output reaches the second preset condition stage, and a third operation strategy when the wind-solar output reaches the third preset condition stage; The first operation strategy, the second operation strategy and the third operation strategy meet the following power constraint conditions in real time: in, Photovoltaic power generation unit t The effort of the moment, Indicates wind power generation unit t The effort of the moment, Represents power storage unit t The effort of the moment, Indicates electrolyzer hydrogen production unit t The load at the moment, the wind and solar output is: t The sum of the outputs of the photovoltaic power generation unit and the wind power generation unit at that moment.

8. The capacity configuration optimization method of the wind-solar hydrogen storage system according to claim 7 is characterized in that: The first preset condition is that the wind and solar power output is greater than the rated load of the electrolyzer hydrogen production unit by a first preset multiple, and the first operation strategy includes: When the state of charge of the power storage unit is greater than a preset threshold, the output of the wind turbine is reduced or the wind is abandoned; When the state of charge of the power storage unit is less than or equal to a preset threshold, the first excess load of the wind and solar power output is used to charge the power storage unit until the power storage unit is fully charged; The first excess load is the difference between the wind and solar power output and a first preset multiple of the rated load of the electrolyzer hydrogen production unit.

9. The capacity configuration optimization method of the wind-solar hydrogen storage system according to claim 7 is characterized in that: The second preset condition is: the second preset multiple of the rated load ≤ wind and solar output ≤ the first preset multiple of the rated load, the second preset condition includes: the first sub-preset condition and the second sub-preset condition, the first sub-preset condition is: n times the rated load ≤ wind and solar output ≤ the first preset multiple of the rated load, the second sub-preset condition is: the second preset multiple of the rated load ≤ wind and solar output ≤ n times the rated load, the second operation strategy includes: When the wind and solar power output reaches the first sub-preset condition, if the charge state of the power storage unit is greater than the preset threshold, the wind and solar power output is supplied to the electrolyzer hydrogen production unit so that the electrolyzer hydrogen production unit performs electrolysis; When the wind and solar power output reaches the second sub-preset condition, determining whether the battery has a power shortage risk during the power storage cycle; If there is no risk of power shortage, the battery is instructed to increase the power supply load to the electrolyzer hydrogen production unit; If there is a risk of power shortage, or the state of charge of the power storage unit is less than or equal to the preset threshold, the second excess load of the wind and solar power output is used to charge the power storage unit until the power storage unit is fully charged; The second excess load is the difference between the wind and solar power output and n times the rated load of the electrolyzer hydrogen production unit.

10. The capacity configuration optimization method of the wind-solar hydrogen storage system according to claim 7 is characterized in that: The third preset condition is: 0≤wind and solar output<rated load of the second preset multiple, and the third operation strategy includes: When the state of charge of the power storage unit is greater than or equal to a preset threshold value, and the target supply load of the power storage unit to the electrolyzer hydrogen production unit reaches a second preset multiple of the rated load, the hourly power load of the electrolyzer hydrogen production unit is supplemented to the second preset multiple of the rated load; When the charge state of the power storage unit is less than a preset threshold and the target supply load of the power storage unit to the electrolyzer hydrogen production unit does not reach the second preset multiple of the rated load, the wind and solar power output is used to charge the power storage unit, and the electrolyzer hydrogen production unit is instructed to shut down and enter the insulation state.

11. The capacity configuration optimization method of the wind-solar hydrogen storage system according to claim 1 is characterized in that: The expression of the optimization function is as follows: in, represents the minimum levelized hydrogen production cost, Indicates the minimum system power failure rate, represents the minimum wind and solar power abandonment rate, represents the system investment cost, An ordinal number indicating the operating years of the hydrogen production project. Indicates the operating years of the hydrogen production project, represents the system operation and maintenance cost, Indicates the number of times a device in the system is replaced. represents the system equipment replacement cost, represents the residual value of the system at the end of its life cycle, represents the system discount rate, represents the total hydrogen production of the project in the first year, Indicates the attenuation rate of hydrogen production equipment, Indicates the total time the system loses power supply. Indicates the total time the system needs power supply. express t The total photovoltaic power generation at the time, express t The total wind power generation at the time, express t The amount of photovoltaic power used at any time, express t The amount of wind power utilized at any given moment.

12. The capacity configuration optimization method of the wind-solar hydrogen storage system according to claim 1 is characterized in that: The expression of the system optimization boundary condition is as follows: in, Indicates the rated load of the electrolyzer hydrogen production unit, Indicates the maximum output of the photovoltaic power generation unit, Indicates the maximum output of the power storage unit, Indicates the total storage capacity of the power storage unit.

13. The capacity configuration optimization method of the wind-solar hydrogen storage system according to claim 1 is characterized in that: The optimal capacity configuration solution set of the wind-solar-hydrogen storage system is calculated according to the optimization function, including: A non-dominated genetic algorithm is used to solve the optimization function to obtain the optimal capacity configuration solution set.

14. The capacity configuration optimization method of the wind-solar hydrogen storage system according to claim 13 is characterized in that: The optimization function is solved by using a non-dominated genetic algorithm to obtain the optimal capacity configuration solution set, including: Selecting genetic parameters, inputting data related to the genetic parameters, and generating an initial population based on decision variables; Performing non-dominated sorting on each individual in the initial population, calculating the crowding distance between each individual, selecting a non-dominated sequence value of a first preset threshold and a crowding distance of a second preset threshold, and obtaining a Pareto optimal frontier; Generate new populations based on Pareto stratification level and crowding degree; Determine whether the evolutionary generation number for generating a new population has reached the maximum evolutionary generation number; If the number of evolutionary generations reaches the maximum number of generations, the iteration ends, and the new population is used as the optimal capacity configuration solution set; Otherwise, increase the number of evolutionary generations by 1 and continue to execute the step of generating a new population and the steps thereafter.

15. The capacity configuration optimization method of the wind-solar hydrogen storage system according to claim 14 is characterized in that: Performing a non-dominated sorting on each individual in the initial population includes: According to a preset objective function, the fitness of each individual in the initial population is evaluated to obtain the non-dominated sequence value.

16. The capacity configuration optimization method of the wind-solar hydrogen storage system according to claim 14, characterized in that: Generate new populations based on Pareto stratification level and crowding degree, including: A new parent population is generated generation by generation according to the stratification level and the crowding degree, selection, crossover and mutation processing are performed on the new parent population to generate a new child population, and the new parent population and the new child population are combined into the new population.

17. The capacity configuration optimization method of the wind-solar hydrogen storage system according to claim 1 is characterized in that: Determining the optimal capacity configuration solution of the wind-solar-hydrogen storage system according to the optimal capacity configuration solution set includes: The TOPSIS decision method is used to make a comprehensive decision on the optimal capacity configuration solution set to determine the optimal capacity configuration solution.

18. The capacity configuration optimization method of the wind-solar hydrogen storage system according to claim 17 is characterized in that: The TOPSIS decision method is used to make a comprehensive decision on the optimal capacity configuration solution set to determine the optimal capacity configuration solution, including: For the optimal capacity configuration solution set, calculate the Euclidean distance between each solution, and determine the distance between each point on the frontier of non-inferior solutions and the ideal point; According to the degree of distance, the solution that is closest to the optimal solution and farthest from the worst solution is determined as the ideal solution, and the ideal solution is used as the optimal capacity configuration solution.

19. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the capacity configuration optimization method of the wind-solar-hydrogen storage system described in any one of claims 1-18 is implemented.

20. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the capacity configuration optimization method of the wind-solar-hydrogen storage system described in any one of claims 1-18 is implemented.

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