Method, device, equipment and medium for optimal configuration of capacity of optical hydrogen storage comprehensive system

Abstract

The invention provides a capacity optimization configuration method, device and equipment for a light hydrogen storage comprehensive system and a medium, and belongs to the technical field of new energy. The optical hydrogen storage comprehensive system comprises photovoltaic power generation equipment, a storage battery, an electrolytic bath, a hydrogen storage tank and a fuel cell, and the method comprises the following steps: constructing a payback period function, a power shortage rate function and a light abandoning rate function according to the characteristics of each type of operation equipment in the optical hydrogen storage comprehensive system to determine a target function; setting operation constraint conditions of the optical hydrogen storage integrated system, and constructing a capacity optimization configuration model about the optical hydrogen storage integrated system by combining the objective function; and obtaining operation data of the light-hydrogen storage integrated system, inputting the operation data into the capacity optimization configuration model, and solving the capacity optimization configuration model by adopting an improved pigeon inspired optimization algorithm to obtain an optimal capacity configuration scheme about the light-hydrogen storage integrated system. According to the invention, characteristics and constraint conditions of each operation device in the optical hydrogen storage comprehensive system can be considered, so that the system capacity configuration process is reasonable.

Description

Technical Field

[0001] The present application relates to the field of new energy technology, and in particular to a method, device, equipment and medium for optimizing the capacity configuration of a comprehensive photovoltaic hydrogen storage system. Background Art

[0002] In new microgrid systems with renewable energy as the main body, it is usually chosen to reasonably configure relevant energy storage equipment on the renewable energy side. However, when solving the specific configuration problems of energy storage equipment, most of them start from the perspective of grid-side planning and fail to consider the equipment operating characteristics and equipment operating constraints on the renewable energy side, resulting in the final energy storage capacity configuration result being unreasonable. Summary of the invention

[0003] The main purpose of this application is to propose a method, device, equipment and medium for optimizing the capacity configuration of a comprehensive photohydrogen storage system, which can use an improved pigeon flock optimization algorithm to obtain a more reasonable and reliable capacity optimization configuration plan while fully considering the characteristics and constraints of each operating equipment in the comprehensive photohydrogen storage system.

[0004] To achieve the above objectives, one aspect of the present application proposes a method for optimizing the capacity configuration of a photovoltaic hydrogen storage integrated system, wherein the photovoltaic hydrogen storage integrated system includes photovoltaic power generation equipment, a battery, an electrolyzer, a hydrogen storage tank, and a fuel cell, and the method includes: According to the characteristics of each type of operating equipment included in the solar hydrogen storage integrated system, construct an investment payback period function, a power shortage rate function and a solar abandonment rate function; Constructing an objective function according to the investment payback period function, the power shortage rate function and the abandoned light rate function; Setting the operating constraints of the integrated photovoltaic hydrogen storage system, and then combining the objective function to construct a capacity optimization configuration model for the integrated photovoltaic hydrogen storage system; The operating data of the integrated solar-hydrogen storage system is obtained, and the operating data is input into the capacity optimization configuration model. The capacity optimization configuration model is then solved using an improved pigeon flock optimization algorithm to obtain an optimal capacity configuration plan for the integrated solar-hydrogen storage system.

[0005] Furthermore, the investment payback period function is obtained in the following manner: Constructing an initial investment cost function according to the configuration quantity and unit price of each type of operating equipment included in the solar hydrogen storage integrated system; According to the configuration quantity, operating power and unit power operation and maintenance cost of each type of operating equipment included in the solar hydrogen storage integrated system, an operation and maintenance cost function and a residual cost function are constructed; The battery, the electrolyzer and the fuel cell are recorded as first operating equipment, and a replacement cost function is constructed according to the configuration quantity, replacement frequency and unit replacement cost of each type of the first operating equipment included in the integrated light hydrogen storage system; The storage battery and the electrolyzer are recorded as second operating equipment, and an energy storage benefit function is constructed according to the electricity market price and the configuration quantity and operating power of each type of the second operating equipment included in the solar hydrogen storage integrated system; The investment payback period function is constructed according to the initial investment cost function, the operation and maintenance cost function, the residual value cost function, the replacement cost function and the energy storage benefit function.

[0006] Furthermore, the power failure rate function is obtained in the following manner: The photovoltaic power generation equipment, the storage battery and the fuel cell are recorded as the third operating equipment, and the power shortage rate function is constructed according to the system load demand power and the configuration quantity and operating power of each type of the third operating equipment included in the photo-hydrogen storage integrated system.

[0007] Furthermore, the light abandonment rate function is obtained by the following method: The photovoltaic power generation equipment, the battery and the electrolyzer are recorded as the fourth operating equipment, and the abandonment rate function is constructed according to the system load demand power and the configuration quantity and operating power of each type of the fourth operating equipment included in the integrated light-hydrogen storage system.

[0008] Furthermore, constructing an objective function according to the investment payback period function, the power shortage rate function and the light abandonment rate function includes: Constructing an economic performance index function according to a preset shortest payback period and the payback period function; Constructing a reliability index function according to a preset maximum full-charge rate and the power failure rate function; Constructing an energy utilization rate index function according to a preset maximum photovoltaic utilization rate and the abandoned light rate function; The economic index function, the reliability index function and the energy utilization index function are weightedly summed to obtain the objective function.

[0009] Furthermore, the operating constraints of the photovoltaic hydrogen storage integrated system include: The system power balance constraint, the system equipment capacity constraint, the power constraint of the electrolyzer, the power constraint of the fuel cell, the storage constraint of the hydrogen storage tank, the charge and discharge constraint of the battery and the power constraint of the battery are set to form the operation constraint conditions.

[0010] Furthermore, the improved pigeon flock optimization algorithm is used to solve the capacity optimization configuration model to obtain the optimal capacity configuration scheme for the solar hydrogen storage integrated system, including: Determining a fitness function and a target variable to be optimized according to the capacity optimization configuration model; Setting values ​​of a plurality of basic parameters involved in the improved pigeon flock optimization algorithm, wherein the plurality of basic parameters include a population size, a first maximum number of iterations of an improved compass operator, and a second maximum number of iterations of an improved landmark operator; Initializing the position of the pigeon flock according to the population size, the target variable and the Tent chaotic mapping strategy, and then determining the global optimal position according to the fitness function and the position of the pigeon flock after the initialization; In the improved compass operator, the position of the pigeon flock is updated according to the Levy flight strategy and the latest global optimal position, and then the latest global optimal position is re-determined according to the fitness function, the latest global optimal position and the updated position of the pigeon flock; the improved compass operator is iteratively applied until the current number of iterations reaches the first maximum number of iterations, and the latest global optimal position re-determined under the first maximum number of iterations is recorded as the first global optimal position; In the improved landmark operator, half of the individuals with poor current fitness values ​​are removed from the pigeon flock, the pigeon flock after the individuals are removed is recorded as the current pigeon flock, the position of the current pigeon flock is updated according to the chaotic perturbation strategy and the preset activation function, and then the latest first global optimal position is re-determined according to the fitness function, the latest first global optimal position and the updated position of the current pigeon flock; the improved landmark operator is iteratively applied until the current number of iterations reaches the second maximum number of iterations; The optimal capacity configuration solution is determined according to the latest first global optimal position re-determined under the second maximum number of iterations.

[0011] To achieve the above-mentioned purpose, another aspect of the present application proposes a capacity optimization configuration device for a comprehensive photohydrogen storage system, wherein the comprehensive photohydrogen storage system comprises a photovoltaic power generation device, a battery, an electrolyzer, a hydrogen storage tank and a fuel cell, and the device comprises: The first building module is used to build an investment payback period function, a power shortage rate function and a solar abandonment rate function according to the characteristics of each type of operating equipment included in the solar hydrogen storage integrated system; A second construction module is used to construct an objective function according to the investment payback period function, the power shortage rate function and the abandoned light rate function; The third construction module is used to set the operation constraints of the integrated light-hydrogen storage system, and then build a capacity optimization configuration model for the integrated light-hydrogen storage system in combination with the objective function; A solution module is used to obtain the operating data of the integrated photovoltaic hydrogen storage system, input the operating data into the capacity optimization configuration model, and then use an improved pigeon flock optimization algorithm to solve the capacity optimization configuration model to obtain the optimal capacity configuration plan for the integrated photovoltaic hydrogen storage system.

[0012] To achieve the above objective, another aspect of the present application provides an electronic device, the electronic device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the above method when executing the computer program.

[0013] To achieve the above objective, another aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program implements the above method when executed by a processor.

[0014] The present application includes at least the following beneficial effects: while fully considering the operating characteristics and operating constraints of each device in the integrated photovoltaic hydrogen storage system, a system capacity optimization configuration model is constructed from the perspectives of the investment payback period, power shortage rate and abandonment rate of the integrated photovoltaic hydrogen storage system, and then an improved pigeon flock optimization algorithm is used to solve the model to obtain a more reasonable and reliable system capacity optimization configuration plan, which is beneficial to improving the economy, reliability and energy utilization of the finally configured integrated photovoltaic hydrogen storage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a structural schematic diagram of the comprehensive photohydrogen storage system provided in the embodiment of the present application; Figure 2 It is a flow chart of a capacity optimization configuration method of a comprehensive photovoltaic hydrogen storage system provided in an embodiment of the present application; Figure 3 It is a structural schematic diagram of a capacity optimization configuration device for a comprehensive photohydrogen storage system provided in an embodiment of the present application; Figure 4 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. They are only examples of systems and methods consistent with some aspects of the embodiments of the present application as detailed in the attached claims.

[0017] It is understood that the terms "first", "second", etc. used in this application can be used to describe various concepts in this article, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another concept. For example, without departing from the scope of the embodiment of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein can be interpreted as "at the time of" or "when" or "in response to determination".

[0018] The terms "at least one", "multiple", "each", "any", etc. used in this application, at least one includes one, two or more, multiple includes two or more, each refers to each of the corresponding multiple, and any refers to any one of the multiple.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0020] In new microgrid systems with new energy as the main body, it is usually chosen to reasonably configure relevant energy storage equipment on the new energy side. However, when solving the specific configuration problems of energy storage equipment, most of them start from the perspective of grid planning, and fail to take into account the equipment operation characteristics and equipment operation constraints on the new energy side, resulting in unreasonable final energy storage capacity configuration results. Although there are very few studies that start from the perspective of new energy planning, they are mainly aimed at photovoltaic storage, and relatively few studies that incorporate hydrogen energy into capacity configuration optimization issues.

[0021] In view of this, the embodiments of the present application provide a method, device, equipment and medium for optimizing the capacity configuration of an integrated photohydrogen storage system. This scheme, while fully considering the operating characteristics and operating constraints of each device in the integrated photohydrogen storage system, constructs a system capacity optimization configuration model from the perspectives of the investment payback period, power shortage rate and abandonment rate of the integrated photohydrogen storage system, and then uses an improved pigeon flock optimization algorithm to solve the model to obtain a more reasonable and reliable system capacity optimization configuration scheme, which is beneficial to improving the economy, reliability and energy utilization of the finally configured integrated photohydrogen storage system.

[0022] The embodiment of the present application provides a method for optimizing the capacity configuration of a comprehensive photohydrogen storage system, which relates to the field of new energy technology, and can be applied to a terminal, a server, or software running in a terminal or a server. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, and a vehicle-mounted terminal, etc., but is not limited to this; the server side can be configured as an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network; the software can be an application that implements the above-mentioned method for optimizing the capacity configuration of a comprehensive photohydrogen storage system, etc., but is not limited to the above forms.

[0023] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0024] Figure 1 It is a structural schematic diagram of the integrated photohydrogen storage system provided in an embodiment of the present application, which includes a battery, a photovoltaic power generation device, an electrolyzer, a hydrogen storage tank, a fuel cell, a load and a DC bus, and the hydrogen storage tank is preferably a high-pressure hydrogen storage tank; wherein the battery is connected to the DC bus, the photovoltaic power generation device is connected to the DC bus, the electrolyzer is connected to the DC bus, the electrolyzer is connected to the hydrogen storage tank, the hydrogen storage tank is connected to the fuel cell, the fuel cell is connected to the DC bus, and the load is connected to the DC bus.

[0025] In practical applications, when the output of the photovoltaic power generation equipment is high or the power consumption of the load is low, the surplus electric energy on the DC bus will be divided into two parts, one part of the electric energy is stored by the battery, and the other part of the electric energy is supplied to the electrolyzer for hydrogen production operation, so that the hydrogen produced by the electrolyzer is stored by the hydrogen storage tank; when the output of the photovoltaic power generation equipment is low or the power consumption of the load is high, the battery responds quickly and starts and stops to smooth out the power fluctuations of the power grid. At the same time, the hydrogen storage tank provides hydrogen to the fuel cell, so that the fuel cell generates electricity to supplement the DC bus.

[0026] Figure 2 This is an optional flow chart of a method for optimizing the capacity of a photovoltaic hydrogen storage integrated system provided in an embodiment of the present application, which is specifically applied to Figure 1 In the integrated photo-hydrogen storage system shown, Figure 2 The method may include but is not limited to steps S101 to S104.

[0027] Step S101, constructing an investment payback period function, a power shortage rate function and a power abandonment rate function according to the characteristics of each type of operating equipment included in the solar hydrogen storage integrated system; Step S102: constructing an objective function according to the payback period function, the power shortage rate function and the abandoned light rate function; Step S103, setting the operation constraints of the integrated photovoltaic hydrogen storage system, and then building a capacity optimization configuration model for the integrated photovoltaic hydrogen storage system in combination with the objective function; Step S104, obtaining the operating data of the integrated photovoltaic hydrogen storage system, inputting the operating data into the capacity optimization configuration model, and then using the improved pigeon flock optimization algorithm to solve the capacity optimization configuration model to obtain the optimal capacity configuration plan for the integrated photovoltaic hydrogen storage system.

[0028] Steps S101 to S104 shown in the embodiment of the present application are to construct a system capacity optimization configuration model involving three key factors, namely, energy storage economy, system reliability and energy utilization rate, from the perspectives of the investment payback period, power shortage rate and abandonment rate of the integrated photovoltaic hydrogen storage system, while fully considering the characteristics and constraints of each operating equipment in the integrated photovoltaic hydrogen storage system. The model is then solved by improving the pigeon flock optimization algorithm, making the system capacity configuration process more rational.

[0029] In step S101 of some embodiments, the mathematical model of each type of operating equipment included in the photovoltaic hydrogen storage integrated system is described as follows: (1) The mathematical model of the photovoltaic power generation equipment is:

[0030] In the formula, is the output power of the photovoltaic power generation equipment at the working point, is the rated output power of the photovoltaic power generation equipment under standard conditions, is the actual solar irradiance at the working point, is the solar irradiance under standard conditions, is the power temperature coefficient and is generally taken as , is the working point temperature of the photovoltaic power generation equipment, is the temperature of the photovoltaic power generation equipment under standard conditions and is generally taken as .

[0031] (2) The mathematical model of the battery is:

[0032]

[0033] In the formula, For the battery The state of charge value at the moment, For the battery The state of charge value at the moment, is the intrinsic discharge rate of the battery, For the battery The charging power at the moment, is the charging efficiency of the battery, is the maximum allowable capacity of the battery. For the battery The discharge power at the moment, is the discharge efficiency of the battery.

[0034] (3) The mathematical model of the electrolytic cell is:

[0035] In the formula, is the hydrogen production volume of the electrolyzer, is the hydrogen production efficiency of the electrolyzer, is the electricity consumed by the electrolyzer to produce hydrogen, The low calorific value of hydrogen. is the density of hydrogen.

[0036] (4) The mathematical model of the hydrogen storage tank is:

[0037] In the formula, For the hydrogen storage tank The amount of hydrogen stored at the time, For the hydrogen storage tank The amount of hydrogen stored at the time, is the energy consumption rate of the hydrogen storage tank, For the hydrogen storage tank The gas input at the time, is the gas input efficiency of the hydrogen storage tank, For the hydrogen storage tank The gas output at the time, is the gas output efficiency of the hydrogen storage tank, is the time step.

[0038] (5) The mathematical model of the fuel cell is:

[0039] In the formula, is the output power of the fuel cell, is the rated output voltage of the fuel cell, is the energy conversion efficiency of the fuel cell and is generally taken as , is the volume of hydrogen at room temperature, is Avogadro's constant and its value is , is the molar volume of the gas at room temperature and is , The number of electrons per coulomb produced for the operation of this fuel cell.

[0040] By clarifying the mathematical model of each type of operating equipment included in the integrated solar hydrogen storage system, the foundation can be laid for the subsequent formulation of the objective function and related constraints required to solve the capacity optimization configuration problem of the integrated solar hydrogen storage system.

[0041] In step S101 of some embodiments, the process of constructing the payback period function may include, but is not limited to, steps S201 to S205.

[0042] Step S201: construct an initial investment cost function based on the unit price and configuration quantity of each type of operating equipment included in the solar hydrogen storage integrated system:

[0043] In the formula, is the initial investment cost, is the configuration quantity of the photovoltaic power generation equipment, is the unit price of the photovoltaic power generation equipment, is the number of configurations of the electrolytic cell, is the unit price of the electrolytic cell, is the number of fuel cells configured, is the unit price of the fuel cell, is the number of hydrogen storage tanks configured, is the unit price of the hydrogen storage tank, is the configuration quantity of the battery, is the unit price of the battery.

[0044] Step S202: construct an operation and maintenance cost function according to the operating power, unit power operation and maintenance cost and configuration quantity of each type of operating equipment included in the integrated solar hydrogen storage system:

[0045] And the residual cost function is constructed as:

[0046] In the formula, For operation and maintenance costs, is the system research period and is preferably set to 20 years, is the unit power operation and maintenance cost of the photovoltaic power generation equipment, For the photovoltaic power generation equipment The operating power at the moment, is the unit power operation and maintenance cost of the electrolyzer, For the electrolytic cell The operating power at the moment, is the unit power operation and maintenance cost of the fuel cell, For the fuel cell The operating power at the moment, is the unit power operation and maintenance cost of the hydrogen storage tank, For the hydrogen storage tank The operating power at the moment, is the unit power operation and maintenance cost of the battery, For the battery The operating power at the moment, is the residual cost, is the loss ratio and is preferably set to .

[0047] Step S203: record the electrolyzer, the fuel cell and the storage battery as first operating equipment, and construct a replacement cost function according to the number of replacements, unit replacement cost and configuration quantity of each type of first operating equipment included in the integrated light hydrogen storage system:

[0048] In the formula, is the replacement cost, is the unit replacement cost of the electrolytic cell, is the number of replacements of the electrolytic cell, is the unit replacement cost of the fuel cell, is the number of times the fuel cell is replaced, is the unit replacement cost of the battery, The number of times the battery has been replaced.

[0049] Step S204: record the electrolyzer and the battery as the second operating equipment, and construct an energy storage benefit function according to the electricity market price and the operating power and configuration quantity of each type of second operating equipment included in the solar hydrogen storage integrated system:

[0050] In the formula, For energy storage benefits, The electricity price in the electricity market.

[0051] Step S205: construct an investment payback period function according to the initial investment cost function, the operation and maintenance cost function, the residual value cost function, the replacement cost function and the energy storage income function:

[0052]

[0053] In the formula, is the total investment equal annual cost of the whole life cycle, is the effective annual interest rate, is the system operation life, The investment payback period mainly represents the time required to recover costs at a certain level of income.

[0054] Steps S201 to S205 shown in the embodiment of the present application extend the cost of the energy storage device to the entire life cycle of purchase, operation, maintenance, failure and scrapping when considering the system economic objectives, so that the final system capacity configuration optimization result can be more in line with the actual situation of the system.

[0055] In step S101 of some embodiments, the construction method of the power failure rate function includes the following: The fuel cell, the storage battery and the photovoltaic power generation device are recorded as the third operating device. According to the system load demand power and the operating power and configuration quantity of each type of third operating device included in the photovoltaic hydrogen storage integrated system, the power shortage rate function is constructed as follows:

[0056] In the formula, is the power failure rate, For The system load power required at the time.

[0057] By utilizing the gap between the system power supply capacity and the system load demand to further evaluate the system power supply reliability, the final system capacity configuration optimization result can be made to conform to the actual system situation.

[0058] In step S101 of some embodiments, the method for constructing the light abandonment rate function includes the following: The electrolyzer, the storage battery and the photovoltaic power generation equipment are recorded as the fourth operating equipment. According to the system load demand power and the operating power and configuration quantity of each type of fourth operating equipment included in the photovoltaic hydrogen storage integrated system, the abandoned light rate function is constructed as follows:

[0059] In the formula, The abandonment rate is the rate at which solar energy is abandoned. When solar energy resources are good, the supply of power generation exceeds the demand. At this time, the load and related energy storage equipment cannot absorb all the power generation, resulting in the phenomenon of abandonment of solar energy. This means that the smaller the abandonment rate, the higher the energy utilization rate.

[0060] By using the abandoned light phenomenon presented by the system to further evaluate the system energy utilization rate, the final system capacity configuration optimization result can be made to conform to the actual situation of the system.

[0061] In some embodiments, the above step S102 may include but is not limited to steps S301 to S304.

[0062] Step S301: According to the payback period function and the preset shortest payback period, an economic index function is constructed as follows:

[0063] Step S302: construct a reliability index function according to the power failure rate function and the preset maximum full power rate:

[0064] Step S303: construct an energy utilization index function according to the abandoned light rate function and a preset maximum photovoltaic utilization rate:

[0065] Step S304: perform weighted summation on the economic performance index function, the reliability index function and the energy utilization index function to obtain the objective function:

[0066] In the formula, is the economic index value, is the shortest payback period, is the reliability index value, is the maximum full charge rate, is the energy utilization index value, is the maximum photovoltaic utilization rate, is the target value, is the weight of the economic index function in the objective function, is the weight of the reliability index function in the objective function, is the weight of the energy utilization index function in the objective function.

[0067] Steps S301 to S304 shown in the embodiment of the present application construct corresponding economic index functions, reliability index functions and energy utilization index functions from the perspectives of the investment payback period, power shortage rate and abandonment rate of the integrated solar hydrogen storage system, and form an objective function by considering the criticality of each indicator. This makes it more comprehensive and feasible to solve the capacity optimization configuration problem of the integrated solar hydrogen storage system in the future.

[0068] In some embodiments, the above step S103 may include but is not limited to including steps S401 to S402.

[0069] Step S401, setting system equipment capacity constraints, system power balance constraints, the power constraints of the electrolyzer, the power constraints of the fuel cell, the power constraints of the battery, the storage constraints of the hydrogen storage tank and the charge and discharge constraints of the battery, and then using the above constraints as the operation constraints; Step S402: construct a capacity optimization configuration model for the integrated solar hydrogen storage system based on the objective function and the operating constraints.

[0070] In the above step S401, the constraints are described as follows: (1) The system equipment capacity constraint is:

[0071] In the formula, is the maximum number of photovoltaic power generation equipment. is the maximum number of configurations for the electrolyzer, is the maximum number of fuel cells to be configured, is the maximum number of hydrogen storage tanks to be configured. The maximum number of batteries to be configured; (2) The power balance constraint of the system is:

[0072] In the formula, For this solar hydrogen storage integrated system The input power at the moment, For this solar hydrogen storage integrated system Output power at the moment; (3) The power constraint of the electrolyzer is:

[0073] In the formula, is the lower limit of the electrolytic cell output, is the output upper limit of the electrolytic cell; (4) The power constraint of the fuel cell is:

[0074] In the formula, is the lower limit of the fuel cell output, is the upper limit of the output of the fuel cell; (5) The power constraint of the battery is:

[0075] In the formula, is the minimum charging power allowed for the battery, is the maximum charging power allowed for the battery, is the minimum discharge power allowed for the battery, The maximum discharge power allowed for the battery; (6) The storage constraints of the hydrogen storage tank are:

[0076] In the formula, is the minimum capacity allowed for the hydrogen storage tank, The maximum capacity allowed for the hydrogen storage tank; (7) The charging and discharging constraints of the battery are:

[0077] In the formula, is the minimum capacity value allowed by the battery, The maximum capacity value allowed for the battery.

[0078] By considering the power balance constraints that affect the long-term stable operation of the system and the basic operating characteristics constraints of various operating equipment, the final required operating constraints are set, making it more comprehensive and feasible to solve the capacity optimization configuration problem of the integrated solar hydrogen storage system in the future.

[0079] In some embodiments, the above step S104 may include but is not limited to including steps S501 to S507.

[0080] Step S501, obtaining the operating data of the integrated solar hydrogen storage system and inputting it into the capacity optimization configuration model, wherein the operating data at least includes relevant parameter values ​​required to be applied when solving the objective function.

[0081] It should be noted that before the operating data is formally applied in the capacity optimization configuration model, the operating data is screened so that the screened operating data can meet the operating constraints, so that it can more accurately assist in calculating the fitness value of each individual in the pigeon flock in the subsequent improved pigeon flock optimization algorithm.

[0082] Step S502: According to the capacity optimization configuration model, determine the fitness function and the target variable to be optimized required for the improved pigeon flock optimization algorithm; wherein the fitness function is the target function, and the target variable is .

[0083] Step S503: Set the values ​​of multiple basic parameters required to improve the pigeon population optimization algorithm, including the population size. , Improve the first maximum number of iterations of the compass operator , the second maximum number of iterations of the improved landmark operator , the target variable Dimensions , Compass Factor , Pigeon group classification parameters , Search Radius And the factors affecting the logsig function .

[0084] Step S504: according to the population size , the target variable The position of the pigeon flock is initialized using the Tent chaotic mapping strategy, and then the global optimal position is determined based on the fitness function and the initialized position of the pigeon flock.

[0085] Step S505: in the improved compass operator, according to the Levy flight strategy and the latest global optimal position, the position of the pigeon group is updated, and then according to the fitness function, the latest global optimal position and the updated position of the pigeon group, the latest global optimal position is re-determined; The improved compass operator is iteratively applied until the current number of iterations reaches the first maximum number of iterations. , that is, repeat execution The above step S505 is repeated to continuously update the position of the pigeon group and the latest global optimal position, and finally the first maximum number of iterations is repeated. The latest global optimal position re-determined is recorded as the first global optimal position.

[0086] Step S506, in the improved landmark operator, half of the individuals with poor current fitness values ​​are removed from the pigeon group, the pigeon group after the individuals are removed is recorded as the current pigeon group, the position of the current pigeon group is updated according to the preset activation function and the chaotic perturbation strategy, and then the latest first global optimal position is re-determined according to the fitness function, the latest first global optimal position and the updated position of the current pigeon group; The improved landmark operator is iteratively applied until the current number of iterations reaches the second maximum number of iterations. , that is, repeat execution The above step S506 is repeated to continuously reduce the bad individuals in the pigeon flock and update the positions of the remaining good individuals in the pigeon flock and the latest first global optimal position.

[0087] Step S507: according to the second maximum number of iterations The latest first global optimal position is re-determined to determine the optimal capacity configuration plan for the integrated solar hydrogen storage system.

[0088] It should be noted that in the second maximum number of iterations The latest first global optimal position re-determined under the actual contains the target variable The optimal solution of the optimal capacity configuration plan records the optimal configuration quantity of the photovoltaic power generation equipment, the optimal configuration quantity of the electrolyzer, the optimal configuration quantity of the fuel cell, the optimal configuration quantity of the hydrogen storage tank and the optimal configuration quantity of the battery, and also records the weight value of the economic index function, the weight value of the reliability index function and the weight value of the energy utilization index function; by visualizing the optimal capacity configuration plan, technical personnel can rely on the optimal capacity configuration plan to continue to improve the construction of the integrated photo-hydrogen storage system, and know which indicator of the economic index, reliability index and energy utilization index the optimal quantity configuration plan of each type of operating equipment included in the integrated photo-hydrogen storage system focuses on.

[0089] Steps S501 to S507 shown in the embodiment of the present application require fewer parameters to be adjusted in the improved pigeon flock optimization algorithm, have stronger robustness, stronger global search capability, and faster convergence speed. The improved pigeon flock optimization algorithm can be used to quickly solve the capacity optimization configuration model to obtain stable optimization results, and can solve the disadvantages of the traditional pigeon flock optimization algorithm, such as being easily trapped in the local optimal solution.

[0090] In some embodiments, the above step S504 may include but is not limited to including steps S601 to S603.

[0091] Step S601: according to the population size To limit the number of individuals that need to be initialized, according to the target variable To limit the position dimension of each individual that needs to be initialized, where the position of each individual refers to the target variable A candidate solution for .

[0092] Step S602: Initialize the position of the pigeon flock using the Tent chaotic mapping strategy, which is specifically implemented using the following expression:

[0093]

[0094] In the formula, For the The positions of the pigeons initialize the chaotic sequence. is a chaotic domain and satisfies , is the Tent parameter, For the The location of the pigeon, is the lower bound of the search space where the pigeon group is located, is the upper bound of the search space where the pigeon group is located, It can be understood as the target variable The domain of definition; wherein, this application preferably sets , making the chaotic system in a completely chaotic state. The particles generated by Tent mapping are random and will traverse the entire chaotic domain to facilitate searching for the optimal solution in the global space.

[0095] Step S603, according to the fitness function and the initialized position of the pigeon group, calculate the fitness value corresponding to each individual in the pigeon group, then select the individual with the smallest fitness value, and use the position of the selected individual as the global optimal position.

[0096] It should be noted that after executing the above step S602, a reasonable speed range is pre-set and the speed of the pigeon flock is initialized by random assignment within the speed range.

[0097] By adopting the tent sequence with traversal uniformity to initialize the positions of the pigeon flock, the diversity of initialization can be effectively increased, and the use of chaos theory to traverse within the neighborhood can help solve the problem of existing algorithms that are prone to falling into local optimal solutions.

[0098] In some embodiments, the above step S505 may include but is not limited to including steps S701 to S703.

[0099] Step S701: According to the latest global optimal position, the position of the pigeon group is updated using the Levy flight strategy, which is specifically implemented using the following expression:

[0100]

[0101]

[0102] In the formula, For the Pigeons in the The position at the iteration, For the Pigeons in the The position at the iteration, For A random number in the interval. To comply with Normally distributed random numbers in the range, To comply with A normally distributed random number in the range and Satisfies the normal distribution, is the shape parameter of the jump probability distribution and its value range is , this application preferably sets , For the The latest global optimal position determined at the iteration, is the gamma function.

[0103] Step S702: Calculate the fitness value corresponding to each individual in the pigeon group according to the fitness function and the updated position of the pigeon group, and then select the minimum fitness value and record it as the first fitness value.

[0104] Step S703: The fitness value associated with the latest global optimal position determined in the first iteration is recorded as the second fitness value, and the second fitness value is compared with the first fitness value: when the second fitness value is less than or equal to the first fitness value, the second fitness value is increased in the first iteration. The latest global optimal position determined in the first iteration is used as The latest global optimal position determined in the first iteration; when the second fitness value is greater than the first fitness value, the position of the individual corresponding to the first fitness value is taken as the position of the individual corresponding to the first fitness value. The latest global optimal position determined at the iteration.

[0105] It should be noted that after executing the above step S701, the speed of the pigeon group is updated using the following expression:

[0106] In the formula, For the Pigeons in the The speed at the iteration, For the Pigeons in the The speed at which the iterations are performed.

[0107] By introducing the Levy flight strategy into the original compass operator to update individual positions, some solutions are continuously searched around the optimal solution while some solutions are searched in a farther space, which can help solve the problem of existing algorithms that are prone to falling into local optimal solutions.

[0108] In some embodiments, the above step S506 may include but is not limited to including steps S801 to S804.

[0109] Step S801, according to the current fitness value corresponding to each individual in the pigeon group, delete half of the individuals with the largest current fitness value from the pigeon group, and record the pigeon group after the individuals are deleted as the current pigeon group.

[0110] Step S802: using a preset activation function and a chaotic perturbation strategy to update the position of the current pigeon flock. The preset activation function is preferably set to a logsig function, which is specifically implemented using the following expression:

[0111]

[0112]

[0113] In the formula, For the The optimal individual position determined at the iteration, For the The population size at the iteration, For the The population size at the iteration , For the Pigeons in the The fitness value calculated at the iteration is A reference parameter set for the convenience of description. To adopt the chaotic perturbation strategy for the A chaotic sequence generated by a pigeon.

[0114] Step S803, according to the fitness function and the updated position of the current pigeon group, calculate the fitness value corresponding to each individual in the current pigeon group, and then select the minimum fitness value and record it as the third fitness value.

[0115] Step S804: The fitness value associated with the latest first global optimal position determined in the first iteration is recorded as the fourth fitness value, and the fourth fitness value is compared with the third fitness value: when the fourth fitness value is less than or equal to the third fitness value, the fourth fitness value is added in the first iteration. The latest first global optimal position determined at the first iteration is taken as The latest first global optimal position determined in the first iteration; when the fourth fitness value is greater than the third fitness value, the position of the individual corresponding to the third fitness value is taken as the position of the individual corresponding to the third fitness value in the first iteration; The latest first global optimal position determined at the iteration.

[0116] By introducing the chaotic perturbation strategy and logsig function into the original landmark operator to update the individual position, that is, dividing the pigeon flock into two categories according to the fitness value in each iteration process, and updating the position of the pigeon flock with better fitness value through the logsig function, and updating the position of the pigeon flock with poor fitness value through the chaotic perturbation strategy, it can help solve the problem of the existing algorithm that is easy to fall into the local optimal solution.

[0117] See also Figure 3 The present application also provides a device for optimizing the capacity of a comprehensive photohydrogen storage system, which is specifically applied to Figure 1 In the illustrated integrated photovoltaic hydrogen storage system, the above-mentioned integrated photovoltaic hydrogen storage system capacity optimization configuration method can be implemented, and the device includes: The first construction module 901 is used to construct a solar abandonment rate function, a power shortage rate function and an investment payback period function according to the characteristics of each type of operating equipment included in the solar hydrogen storage integrated system; A second construction module 902 is used to construct an objective function according to the abandoned light rate function, the power shortage rate function and the investment payback period function; The third construction module 903 is used to set the operation constraints of the integrated photovoltaic hydrogen storage system, and then build a capacity optimization configuration model for the integrated photovoltaic hydrogen storage system in combination with the objective function; The solution module 904 is used to obtain the operating data of the integrated photovoltaic hydrogen storage system, input the operating data into the capacity optimization configuration model, and then solve the capacity optimization configuration model through the improved pigeon flock optimization algorithm to obtain the optimal capacity configuration plan for the integrated photovoltaic hydrogen storage system.

[0118] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0119] The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above-mentioned photovoltaic hydrogen storage integrated system capacity optimization configuration method when executing the computer program. The electronic device can be any intelligent terminal including a tablet computer, a car computer, etc.

[0120] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0121] See also Figure 4 , Figure 4 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes: The processor 1001 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application; The memory 1002 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 1002 can store an operating system and other application programs. When the technical solution provided in the embodiment of the present application is implemented by software or firmware, the relevant program code is stored in the memory 1002, and the processor 1001 calls and executes the technical solution provided in the embodiment of the present application; Input / output interface 1003, used to implement information input and output; Communication interface 1004, used to realize communication interaction between the device and other devices, which can be realized through wired mode (such as USB, network cable, etc.) or wireless mode (such as mobile network, WIFI, Bluetooth, etc.); A bus 1005 , which transmits information between various components of the device (e.g., the processor 1001 , the memory 1002 , the input / output interface 1003 , and the communication interface 1004 ); The processor 1001 , the memory 1002 , the input / output interface 1003 and the communication interface 1004 are connected to each other in communication within the device via the bus 1005 .

[0122] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned method for optimizing the capacity configuration of the integrated photovoltaic hydrogen storage system is implemented.

[0123] It can be understood that the contents of the above method embodiments are all applicable to the present storage medium embodiments, the functions specifically implemented by the present storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0124] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0125] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0126] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0127] The system embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

[0128] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0129] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0130] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0131] In the several embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or units, which can be electrical, mechanical or other forms.

[0132] 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.

[0133] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0134] If the 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, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0135] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A method for optimizing the capacity of a comprehensive photovoltaic hydrogen storage system, characterized in that: The photo-hydrogen storage integrated system comprises a photovoltaic power generation device, a storage battery, an electrolyzer, a hydrogen storage tank and a fuel cell, and the method comprises: According to the characteristics of each type of operating equipment included in the solar hydrogen storage integrated system, construct an investment payback period function, a power shortage rate function and a solar abandonment rate function; Constructing an objective function according to the investment payback period function, the power shortage rate function and the abandoned light rate function; Setting the operating constraints of the integrated photovoltaic hydrogen storage system, and then combining the objective function to construct a capacity optimization configuration model for the integrated photovoltaic hydrogen storage system; The operating data of the integrated solar-hydrogen storage system is obtained, and the operating data is input into the capacity optimization configuration model. The capacity optimization configuration model is then solved using an improved pigeon flock optimization algorithm to obtain an optimal capacity configuration plan for the integrated solar-hydrogen storage system.

2. The method for optimizing the capacity of a comprehensive photovoltaic hydrogen storage system according to claim 1, characterized in that: The payback period function is obtained in the following way: Constructing an initial investment cost function according to the configuration quantity and unit price of each type of operating equipment included in the solar hydrogen storage integrated system; According to the configuration quantity, operating power and unit power operation and maintenance cost of each type of operating equipment included in the solar hydrogen storage integrated system, an operation and maintenance cost function and a residual cost function are constructed; The battery, the electrolyzer and the fuel cell are recorded as first operating equipment, and a replacement cost function is constructed according to the configuration quantity, replacement frequency and unit replacement cost of each type of the first operating equipment included in the integrated light hydrogen storage system; The storage battery and the electrolyzer are recorded as second operating equipment, and an energy storage benefit function is constructed according to the electricity market price and the configuration quantity and operating power of each type of the second operating equipment included in the solar hydrogen storage integrated system; The investment payback period function is constructed according to the initial investment cost function, the operation and maintenance cost function, the residual value cost function, the replacement cost function and the energy storage benefit function.

3. The capacity optimization configuration method of the integrated photovoltaic hydrogen storage system according to claim 1 is characterized in that: The power failure rate function is obtained by the following method: The photovoltaic power generation equipment, the storage battery and the fuel cell are recorded as the third operating equipment, and the power shortage rate function is constructed according to the system load demand power and the configuration quantity and operating power of each type of the third operating equipment included in the photo-hydrogen storage integrated system.

4. The method for optimizing the capacity of a comprehensive photovoltaic hydrogen storage system according to claim 1, characterized in that: The light abandonment rate function is obtained by the following method: The photovoltaic power generation equipment, the battery and the electrolyzer are recorded as the fourth operating equipment, and the abandonment rate function is constructed according to the system load demand power and the configuration quantity and operating power of each type of the fourth operating equipment included in the integrated light-hydrogen storage system.

5. The capacity optimization configuration method of the integrated photovoltaic hydrogen storage system according to claim 1 is characterized in that: The constructing of the objective function according to the investment payback period function, the power shortage rate function and the light abandonment rate function comprises: Constructing an economic index function according to a preset shortest payback period and the payback period function; Constructing a reliability index function according to a preset maximum full-charge rate and the power failure rate function; Constructing an energy utilization rate index function according to a preset maximum photovoltaic utilization rate and the abandoned light rate function; The economic index function, the reliability index function and the energy utilization index function are weightedly summed to obtain the objective function.

6. The capacity optimization configuration method of the integrated photovoltaic hydrogen storage system according to claim 1 is characterized in that: The operating constraints for setting the integrated light hydrogen storage system include: The system power balance constraint, the system equipment capacity constraint, the power constraint of the electrolyzer, the power constraint of the fuel cell, the storage constraint of the hydrogen storage tank, the charge and discharge constraint of the battery and the power constraint of the battery are set to form the operation constraint conditions.

7. The capacity optimization configuration method of the integrated photovoltaic hydrogen storage system according to claim 5 is characterized in that: The improved pigeon flock optimization algorithm is used to solve the capacity optimization configuration model to obtain the optimal capacity configuration scheme for the solar hydrogen storage integrated system, including: Determining a fitness function and a target variable to be optimized according to the capacity optimization configuration model; Setting values ​​of a plurality of basic parameters involved in the improved pigeon flock optimization algorithm, wherein the plurality of basic parameters include a population size, a first maximum number of iterations of an improved compass operator, and a second maximum number of iterations of an improved landmark operator; Initializing the position of the pigeon flock according to the population size, the target variable and the Tent chaotic mapping strategy, and then determining the global optimal position according to the fitness function and the position of the pigeon flock after the initialization; In the improved compass operator, the position of the pigeon flock is updated according to the Levy flight strategy and the latest global optimal position, and then the latest global optimal position is re-determined according to the fitness function, the latest global optimal position and the updated position of the pigeon flock; the improved compass operator is iteratively applied until the current number of iterations reaches the first maximum number of iterations, and the latest global optimal position re-determined under the first maximum number of iterations is recorded as the first global optimal position; In the improved landmark operator, half of the individuals with poor current fitness values ​​are removed from the pigeon flock, the pigeon flock after the individuals are removed is recorded as the current pigeon flock, the position of the current pigeon flock is updated according to the chaotic perturbation strategy and the preset activation function, and then the latest first global optimal position is re-determined according to the fitness function, the latest first global optimal position and the updated position of the current pigeon flock; the improved landmark operator is iteratively applied until the current number of iterations reaches the second maximum number of iterations; The optimal capacity configuration solution is determined according to the latest first global optimal position re-determined under the second maximum number of iterations.

8. A device for optimizing the capacity of a comprehensive photovoltaic hydrogen storage system, characterized in that: The photo-hydrogen storage integrated system comprises a photovoltaic power generation device, a storage battery, an electrolyzer, a hydrogen storage tank and a fuel cell, and the device comprises: The first construction module is used to construct an investment payback period function, a power shortage rate function and a solar abandonment rate function according to the characteristics of each type of operating equipment included in the solar hydrogen storage integrated system; A second construction module is used to construct an objective function according to the investment payback period function, the power shortage rate function and the abandoned light rate function; The third construction module is used to set the operation constraints of the integrated light-hydrogen storage system, and then build a capacity optimization configuration model for the integrated light-hydrogen storage system in combination with the objective function; A solution module is used to obtain the operating data of the integrated photovoltaic hydrogen storage system, input the operating data into the capacity optimization configuration model, and then use an improved pigeon flock optimization algorithm to solve the capacity optimization configuration model to obtain the optimal capacity configuration plan for the integrated photovoltaic hydrogen storage system.

9. An electronic device, characterized in that: The electronic device comprises a memory and a processor, the memory stores a computer program, and the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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