Method, device, equipment and medium for optimizing the capacity configuration of a comprehensive optical storage and hydrogen system

Abstract

The present application provides a method, device, equipment and medium for optimizing the capacity configuration of a photovoltaic energy storage hydrogen integrated system, belonging to the field of new energy technologies. The photovoltaic energy storage hydrogen integrated system includes a photovoltaic power generation device, a storage battery, an electrolyzer, a hydrogen storage tank and a fuel cell. The method includes: constructing an investment payback period function, a power shortage rate function and a light abandonment rate function according to the characteristics of each type of operating equipment in the photovoltaic energy storage hydrogen integrated system to determine an objective function; setting the operating constraint conditions of the photovoltaic energy storage hydrogen integrated system, and constructing a capacity optimization configuration model for the photovoltaic energy storage hydrogen integrated system in combination with the objective function; obtaining the operating data of the photovoltaic energy storage hydrogen integrated system and inputting the data into the capacity optimization configuration model, and using an improved pigeon flock optimization algorithm to solve the capacity optimization configuration model to obtain an optimal capacity configuration scheme for the photovoltaic energy storage hydrogen integrated system. The present application can take into account the characteristics and constraint conditions of each operating equipment in the photovoltaic energy storage hydrogen integrated system, making the system capacity configuration process reasonable.

Description

Technical Field

[0001] The present application relates to the field of new energy technologies, and particularly to a method, device, equipment and medium for optimizing the capacity configuration of a photovoltaic-hydrogen storage integrated system. Background Art

[0002] In a new type of microgrid system with new energy as the main body, it is usually chosen to reasonably configure relevant energy storage devices on the new energy side. However, when solving the specific configuration problem of energy storage devices, most of them start from the perspective of grid-side planning, failing to consider the operating characteristics and operating constraints of the devices on the new energy side, resulting in an unreasonable final energy storage capacity configuration result. Summary of the Invention

[0003] The main purpose of the present application is to propose a method, device, equipment and medium for optimizing the capacity configuration of a photovoltaic-hydrogen storage integrated system, which can, while fully considering the characteristics and constraint conditions of each operating device in the photovoltaic-hydrogen storage integrated system, use an improved pigeon flock optimization algorithm to obtain a more reasonable and reliable capacity optimization configuration scheme.

[0004] To achieve the above object, on the one hand, the present application proposes a method for optimizing the capacity configuration of a photovoltaic-hydrogen storage integrated system. The photovoltaic-hydrogen storage integrated system includes a photovoltaic power generation device, a storage battery, an electrolyzer, a hydrogen storage tank and a fuel cell. The method includes:

[0005] Construct an investment payback period function, a power shortage rate function and a light curtailment rate function according to the characteristics of each type of operating device included in the photovoltaic-hydrogen storage integrated system;

[0006] Construct an objective function according to the investment payback period function, the power shortage rate function and the light curtailment rate function;

[0007] Set the operating constraint conditions of the photovoltaic-hydrogen storage integrated system, and then combine with the objective function to construct a capacity optimization configuration model for the photovoltaic-hydrogen storage integrated system;

[0008] Obtain the operating data of the photovoltaic-hydrogen storage integrated 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 an optimal capacity configuration scheme for the photovoltaic-hydrogen storage integrated system.

[0009] Further, the investment payback period function is obtained through the following method:

[0010] Construct an initial investment cost function according to the configuration quantity and unit price of each type of operating device included in the photovoltaic-hydrogen storage integrated system;

[0011] Construct an operation and maintenance cost function and a residual value cost function according to the configuration quantity, operating power, and unit power operation and maintenance cost of each type of operating equipment included in the integrated photovoltaic energy storage and hydrogen production system;

[0012] Denote the storage battery, the electrolyzer, and the fuel cell as the first operating equipment, and construct a replacement cost function according to the configuration quantity, replacement times, and unit replacement cost of each type of the first operating equipment included in the integrated photovoltaic energy storage and hydrogen production system;

[0013] Denote the storage battery and the electrolyzer as the second operating equipment, and construct an energy storage revenue function according to the electricity price in the power market and the configuration quantity and operating power of each type of the second operating equipment included in the integrated photovoltaic energy storage and hydrogen production system;

[0014] Construct the 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 revenue function.

[0015] Further, the power shortage rate function is obtained through the following method:

[0016] Denote the photovoltaic power generation equipment, the storage battery, and the fuel cell as the third operating equipment, and construct the power shortage rate function 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 integrated photovoltaic energy storage and hydrogen production system.

[0017] Further, the light curtailment rate function is obtained through the following method:

[0018] Denote the photovoltaic power generation equipment, the storage battery, and the electrolyzer as the fourth operating equipment, and construct the light curtailment rate function 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 photovoltaic energy storage and hydrogen production system.

[0019] Further, constructing the objective function according to the investment payback period function, the power shortage rate function, and the light curtailment rate function includes:

[0020] Construct an economic index function according to the preset shortest investment payback period and the investment payback period function;

[0021] Construct a reliability index function according to the preset maximum full charge rate and the power shortage rate function;

[0022] Construct an energy utilization rate index function according to the preset maximum photovoltaic utilization rate and the light curtailment rate function;

[0023] Perform weighted summation on the economic index function, the reliability index function, and the energy utilization rate index function to obtain the objective function.

[0024] Furthermore, setting the operating constraint conditions of the integrated photovoltaic-hydrogen storage system includes:

[0025] Setting system power balance constraints, system equipment capacity constraints, power constraints of the electrolyzer, power constraints of the fuel cell, storage constraints of the hydrogen storage tank, charge and discharge constraints of the battery, and power constraints of the battery to form the operating constraint conditions.

[0026] Furthermore, using the improved pigeon flock optimization algorithm to solve the capacity optimization configuration model to obtain the optimal capacity configuration scheme for the integrated photovoltaic-hydrogen storage system includes:

[0027] According to the capacity optimization configuration model, determine the fitness function and the target variables to be optimized;

[0028] Set the values of multiple basic parameters involved in the improved pigeon flock optimization algorithm. The multiple basic parameters include the population size, the first maximum number of iterations of the improved compass operator, and the second maximum number of iterations of the improved landmark operator;

[0029] According to the population size, the target variables, and the Tent chaotic mapping strategy, initialize the positions of the pigeon flock, and then determine the global optimal position according to the fitness function and the initialized positions of the pigeon flock;

[0030] In the improved compass operator, update the positions of the pigeon flock according to the Lévy flight strategy and the latest global optimal position, and then re-determine the latest global optimal position according to the fitness function, the latest global optimal position, and the updated positions of the pigeon flock; Iteratively apply the improved compass operator until the current number of iterations reaches the first maximum number of iterations, and record the latest global optimal position re-determined at the first maximum number of iterations as the first global optimal position;

[0031] In the improved landmark operator, eliminate the half of the individuals with relatively poor current fitness values from the pigeon flock, and denote the pigeon flock after eliminating the individuals as the current pigeon flock. Update the positions of the current pigeon flock according to the chaotic perturbation strategy and the preset activation function, and then re-determine the latest first global optimal position according to the fitness function, the latest first global optimal position, and the updated positions of the current pigeon flock; Iteratively apply the improved landmark operator until the current number of iterations reaches the second maximum number of iterations;

[0032] Determine the optimal capacity configuration scheme according to the latest first global optimal position re-determined at the second maximum number of iterations.

[0033] To achieve the above object, on the other hand, the present application proposes a device for optimizing the capacity configuration of a photovoltaic-hydrogen storage integrated system, where the photovoltaic-hydrogen storage integrated system includes a photovoltaic power generation device, a storage battery, an electrolyzer, a hydrogen storage tank, and a fuel cell. The device includes:

[0034] A first construction module, configured to construct an investment payback period function, a power shortage rate function, and a light curtailment rate function according to the characteristics of each type of operating equipment included in the photovoltaic-hydrogen storage integrated system;

[0035] A second construction module, configured to construct an objective function according to the investment payback period function, the power shortage rate function, and the light curtailment rate function;

[0036] A third construction module, configured to set the operating constraint conditions of the photovoltaic-hydrogen storage integrated system, and then combine with the objective function to construct a capacity optimization configuration model for the photovoltaic-hydrogen storage integrated system;

[0037] A solution module, configured to obtain the operating data of the photovoltaic-hydrogen storage integrated 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 an optimal capacity configuration scheme for the photovoltaic-hydrogen storage integrated system.

[0038] To achieve the above object, on the other hand, the present application proposes an electronic device, where the electronic device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the above method is implemented.

[0039] To achieve the above object, on the other hand, the present application proposes a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above method is implemented.

[0040] The present application has at least the following beneficial effects: Considering the operating characteristics and operating constraint conditions of each device in the photovoltaic-hydrogen storage integrated system, a system capacity optimization configuration model is constructed from the perspectives of the investment payback period, power shortage rate, and light curtailment rate of the photovoltaic-hydrogen storage integrated 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 scheme, which is beneficial to improving the economy, reliability, and energy utilization rate of the finally configured photovoltaic-hydrogen storage integrated system. Description of the Drawings

[0041] Figure 1 is a schematic structural diagram of a photovoltaic-hydrogen storage integrated system provided by an embodiment of the present application;

[0042] Figure 2 is a flowchart of a method for optimizing the capacity configuration of a photovoltaic-hydrogen storage integrated system provided by an embodiment of the present application;

[0043] Figure 3 It is a schematic structural diagram of a device for optimizing the configuration of the capacity of an integrated optical energy storage and hydrogen production system provided by an embodiment of the present application;

[0044] Figure 4 It is a schematic hardware structure diagram of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0045] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the embodiments of the present application. They are only examples of systems and methods that are consistent with some aspects of the embodiments of the present application detailed in the appended claims.

[0046] It can be understood that the terms "first", "second", etc. used in the present application can be used in this document to describe various concepts, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of the present application, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as the first information. Depending on the context, the words "if", "when" as used herein can be interpreted as "when...", "while...", or "in response to determining".

[0047] The terms "at least one", "a plurality of", "each", "any one", etc. used in the present application, at least one includes one, two or more than two, a plurality includes two or more than two, each refers to each of the corresponding plurality, and any one refers to any one of the plurality.

[0048] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

[0049] In a new type of microgrid system with new energy as the main body, it is usually chosen to reasonably configure relevant energy storage devices on the new energy side. However, when solving the specific configuration problem of energy storage devices, most start from the perspective of grid-side planning and fail to consider the operating characteristics and operating constraints of the devices on the new energy side, resulting in an unreasonable final configuration result of the energy storage capacity. Although there are a very few starting from the perspective of new energy side planning, but mainly for the photovoltaic and energy storage aspects, the research on incorporating hydrogen energy into the capacity configuration optimization problem is relatively less.

[0050] In view of this, the embodiments of the present application provide a method, device, equipment and medium for optimizing the capacity configuration of a photovoltaic-energy storage-hydrogen integrated system. This solution constructs a system capacity optimization configuration model from the perspectives of the investment payback period, power shortage rate and light abandonment rate of the photovoltaic-energy storage-hydrogen integrated system while fully considering the operating characteristics and operating constraints of each device in the 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 rate of the finally configured photovoltaic-energy storage-hydrogen integrated system.

[0051] A method for optimizing the capacity configuration of a photovoltaic-energy storage-hydrogen integrated system provided by the embodiments of the present application relates to the field of new energy technologies and can be applied to terminals, servers, or software running on terminals or servers. 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, a vehicle-mounted terminal, etc., but is not limited thereto; 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 providing 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 implementing the above method for optimizing the capacity configuration of a photovoltaic-energy storage-hydrogen integrated system, etc., but is not limited to the above forms.

[0052] This application can be used in numerous general or specific computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multi-processor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and so on. This 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. This application can also be practiced in a distributed computing environment where 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.

[0053] Figure 1 FIG. 4 is a schematic structural diagram of an integrated optical energy storage and hydrogen storage system provided by an embodiment of the present application. The integrated optical energy storage and hydrogen storage system includes a storage battery, a photovoltaic power generation device, an electrolyzer, a hydrogen storage tank, a fuel cell, a load, and a DC bus. The hydrogen storage tank preferably adopts a high-pressure hydrogen storage tank; wherein, the storage 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.

[0054] In practical applications, when the output of the photovoltaic power generation device 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 via the storage battery, and the other part of the electric energy is supplied to the electrolyzer for hydrogen production operation, so that the hydrogen generated by the electrolyzer is stored via the hydrogen storage tank; when the output of the photovoltaic power generation device is low or the power consumption of the load is high, the storage battery quickly reacts and performs start-stop actions to smooth the power grid power fluctuation. At the same time, hydrogen is provided from the hydrogen storage tank to the fuel cell, so that the fuel cell generates electricity to supplement the DC bus.

[0055] Figure 2 FIG. 11 is an optional flowchart of a method for optimizing the capacity configuration of an integrated optical energy storage and hydrogen storage system provided by an embodiment of the present application, and is specifically applied to the integrated optical energy storage and hydrogen storage system shown in Figure 1 FIG. 13. Figure 2 The method in FIG. 15 may include but is not limited to steps S101 to S104.

[0056] Step S101: Construct an investment payback period function, a power outage rate function, and a light curtailment rate function according to the characteristics of each type of operating equipment included in the integrated optical energy storage and hydrogen storage system;

[0057] Step S102: Construct an objective function according to the investment payback period function, the power shortage rate function, and the curtailment of light rate function.

[0058] Step S103: Set the operating constraint conditions of the integrated photovoltaic-battery-hydrogen system, and then combine with the objective function to construct a capacity optimization configuration model for the integrated photovoltaic-battery-hydrogen system.

[0059] Step S104: Obtain the operating data of the integrated photovoltaic-battery-hydrogen system, input the operating data into the capacity optimization configuration model, and then use the improved pigeon flock optimization algorithm to solve the capacity optimization configuration model to obtain the optimal capacity configuration plan for the integrated photovoltaic-battery-hydrogen system.

[0060] Steps S101 to S104 shown in the embodiments of the present application, by fully considering the characteristics and constraint conditions of each operating device in the integrated photovoltaic-battery-hydrogen system, starting from the perspectives of the investment payback period, power shortage rate, and curtailment of light rate of the integrated photovoltaic-battery-hydrogen system, construct a system capacity optimization configuration model involving three key factors of energy storage economy, system reliability, and energy utilization rate, and then solve the model through the improved pigeon flock optimization algorithm, making the system capacity configuration process more reasonable.

[0061] In step S101 of some embodiments, the mathematical models of each type of operating device included in the integrated photovoltaic-battery-hydrogen system are described as follows:

[0062] (1) The mathematical model of the photovoltaic power generation device is:

[0063]

[0064] In the formula, is the output power of the photovoltaic power generation device at the operating point, is the rated output power of the photovoltaic power generation device under standard conditions, is the actual solar irradiance at the operating point, is the solar irradiance under standard conditions, is the power temperature coefficient and generally takes a value of , is the operating point temperature of the photovoltaic power generation device, is the temperature of the photovoltaic power generation device under standard conditions and generally takes a value of .

[0065] (2) The mathematical model of the storage battery is:

[0066]

[0067]

[0068] In the formula, is the state of charge value of the battery at moment, is the state of charge value of the battery at moment, is the internal discharge rate of the battery, is the charging power of the battery at moment, is the charging efficiency of the battery, is the maximum allowable capacity of the battery, is the discharging power of the battery at moment, is the discharging efficiency of the battery.

[0069] (3) The mathematical model for the electrolyzer is:

[0070]

[0071] In the formula, is the hydrogen production volume of the electrolyzer, is the hydrogen production efficiency of the electrolyzer, is the power consumption for hydrogen production of the electrolyzer, is the lower heating value of hydrogen, is the hydrogen density.

[0072] (4) The mathematical model for the hydrogen storage tank is:

[0073]

[0074] In the formula, is the hydrogen storage amount of the hydrogen storage tank at moment, is the hydrogen storage amount of the hydrogen storage tank at moment, is the energy storage consumption rate of the hydrogen storage tank, is the gas input amount of the hydrogen storage tank at moment, is the gas input efficiency of the hydrogen storage tank, is the gas output amount of the hydrogen storage tank at moment, is the gas output efficiency of the hydrogen storage tank, is the time step.

[0075] (5) The mathematical model for the fuel cell is:

[0076]

[0077] 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 generally takes a value of , is the volume of hydrogen at room temperature, is Avogadro's constant and takes a value of , is the molar volume of gas at room temperature and takes a value of , is the number of unit Coulomb electrons generated by the operation of the fuel cell.

[0078] By clarifying the mathematical models of each type of operating equipment included in the integrated photovoltaic-hydrogen storage system, it can lay a foundation for formulating the objective function and related constraint conditions required for solving the capacity optimization configuration problem of the integrated photovoltaic-hydrogen storage system.

[0079] In step S101 of some embodiments, regarding the construction process of the payback period function, it may include, but is not limited to, steps S201 to S205.

[0080] Step S201: According to the unit price and configuration quantity of each type of operating equipment included in the integrated photovoltaic-hydrogen storage system, construct the initial investment cost function as:

[0081]

[0082] 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 configuration quantity of the electrolyzer, is the unit price of the electrolyzer, is the configuration quantity of the fuel cell, is the unit price of the fuel cell, is the configuration quantity of the hydrogen storage tank, is the unit price of the hydrogen storage tank, is the configuration quantity of the storage battery, is the unit price of the storage battery.

[0083] Step S202: According to the operating power, unit power operation and maintenance cost, and configuration quantity of each type of operating equipment included in the integrated photovoltaic-hydrogen storage system, construct the operation and maintenance cost function as:

[0084]

[0085] And construct the residual value cost function as:

[0086]

[0087] In the formula, is the operation and maintenance cost, 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, is at the operating power of the photovoltaic power generation equipment at the moment, is the unit power operation and maintenance cost of the electrolyzer, is at the operating power of the electrolyzer at the moment, is the unit power operation and maintenance cost of the fuel cell, is at the operating power of the fuel cell at the moment, is the unit power operation and maintenance cost of the hydrogen storage tank, is at the operating power of the hydrogen storage tank at the moment, is the unit power operation and maintenance cost of the battery, is at the operating power of the battery at the moment, is the residual value cost, is the depreciation ratio and is preferably set to .

[0088] Step S203: Denote the electrolyzer, the fuel cell and the battery as the first operating equipment. According to the replacement times, unit replacement cost and configuration quantity of each type of first operating equipment included in the integrated photovoltaic-hydrogen storage system, construct a replacement cost function as:

[0089]

[0090] In the formula, is the replacement cost, is the unit replacement cost of the electrolyzer, is the replacement times of the electrolyzer, is the unit replacement cost of the fuel cell, is the replacement times of the fuel cell, is the unit replacement cost of the battery, is the replacement times of the battery.

[0091] Step S204: Denote the electrolyzer and the battery as the second operating equipment. According to the electricity price in the power market and the operating power and configuration quantity of each type of second operating equipment included in the integrated photovoltaic-hydrogen storage system, construct a energy storage revenue function as:

[0092]

[0093] Wherein, is the energy storage revenue, is the electricity price in the electricity market.

[0094] Step S205, according to the initial investment cost function, the operation and maintenance cost function, the salvage value cost function, the replacement cost function and the energy storage revenue function, construct the payback period function as:

[0095]

[0096]

[0097] Wherein, is the equivalent annual value cost of the total investment in the whole life cycle, is the actual annual interest rate, is the system operation years, is the payback period, which mainly represents the time to recover the cost at a certain revenue level.

[0098] Steps S201 to S205 shown in the embodiments of the present application, by considering the system economic target problem and comprehensively extending the energy storage device cost to the entire life cycle including purchase, operation, maintenance, failure and scrapping, etc., can make the finally obtained system capacity configuration optimization result more in line with the actual situation of the system.

[0099] In step S101 of some embodiments, the construction method of the power shortage rate function is as follows:

[0100] Record the fuel cell, the storage battery and the photovoltaic power generation equipment as the third operating equipment, and construct the power shortage rate function according to the system load demand power and the operating power and configuration quantity of each type of third operating equipment included in the integrated hydrogen production system with light storage as:

[0101]

[0102] Wherein, is the power shortage rate, is at the system load demand power at the moment.

[0103] By using the gap between the system power supply capacity and the system load demand to further evaluate the system power supply reliability, the finally obtained system capacity configuration optimization result can be made to conform to the actual situation of the system.

[0104] In step S101 of some embodiments, the construction method of the light curtailment rate function is as follows:

[0105] Record the electrolyzer, the storage battery, and the photovoltaic power generation equipment 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 integrated system, construct a curtailment rate function as follows:

[0106]

[0107] In the formula, is the curtailment rate. When the light energy resource is good, the power generation is in oversupply. At this time, the load and related energy storage equipment cannot fully consume the power generation, presenting a curtailment phenomenon, indicating that the smaller the curtailment rate, the higher the energy utilization rate conversely.

[0108] By using the curtailment phenomenon presented by the system to further evaluate the system energy utilization rate, the optimized result of the final system capacity configuration can be made to conform to the actual situation of the system.

[0109] In some embodiments, the above step S102 may but is not limited to including steps S301 to S304.

[0110] Step S301: According to the investment payback period function and the preset shortest investment payback period, construct an economic index function as follows:

[0111]

[0112] Step S302: According to the power outage rate function and the preset maximum full charge rate, construct a reliability index function as follows:

[0113]

[0114] Step S303: According to the curtailment rate function and the preset maximum photovoltaic utilization rate, construct an energy utilization rate index function as follows:

[0115]

[0116] Step S304: Perform a weighted sum of the economic index function, the reliability index function, and the energy utilization rate index function to obtain the objective function as follows:

[0117]

[0118] In the formula, is the economic index value, is the shortest investment payback period, is the reliability index value, is the maximum full charge rate, is the energy utilization rate 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 rate index function in the objective function.

[0119] Steps S301 to S304 shown in the embodiments of the present application, by starting from the perspectives of the investment payback period, power shortage rate, and light curtailment rate of the integrated photovoltaic-hydrogen storage system, construct corresponding economic index functions, reliability index functions, and energy utilization rate index functions, and form an objective function by considering the key degrees of each index, making it more comprehensive and feasible to solve the capacity optimization configuration problem of the integrated photovoltaic-hydrogen storage system subsequently.

[0120] In some embodiments, the above step S103 may but is not limited to including steps S401 to S402.

[0121] Step S401: Set the system equipment capacity constraint, system power balance constraint, power constraint of the electrolyzer, power constraint of the fuel cell, power constraint of the battery, storage constraint of the hydrogen storage tank, and charge-discharge constraint of the battery, and then use the above constraints as the operation constraint conditions;

[0122] Step S402: Construct a capacity optimization configuration model for the integrated photovoltaic-hydrogen storage system according to the objective function and the operation constraint conditions.

[0123] In the above step S401, the following explanations are made for each constraint:

[0124] (1) The system equipment capacity constraint is:

[0125]

[0126] In the formula, is the maximum configuration number of the photovoltaic power generation equipment, is the maximum configuration number of the electrolyzer, is the maximum configuration number of the fuel cell, is the maximum configuration number of the hydrogen storage tank, is the maximum configuration number of the battery;

[0127] (2) The system power balance constraint is:

[0128]

[0129] In the formula, is the input power of the integrated photovoltaic-hydrogen storage system at time, is the integrated photovoltaic-hydrogen storage system at Output power at a certain moment;

[0130] (3) The power constraint of the electrolyzer is:

[0131]

[0132] Wherein, is the lower limit of the output of the electrolyzer, is the upper limit of the output of the electrolyzer;

[0133] (4) The power constraint of the fuel cell is:

[0134]

[0135] Wherein, is the lower limit of the output of the fuel cell, is the upper limit of the output of the fuel cell;

[0136] (5) The power constraint of the battery is:

[0137]

[0138] Wherein, is the minimum charging power allowed for the battery, is the maximum charging power allowed for the battery, is the minimum discharging power allowed for the battery, is the maximum discharging power allowed for the battery;

[0139] (6) The storage constraint of the hydrogen storage tank is:

[0140]

[0141] Wherein, is the minimum capacity value allowed for the hydrogen storage tank, is the maximum capacity value allowed for the hydrogen storage tank;

[0142] (7) The charge and discharge constraint of the battery is:

[0143]

[0144] Wherein, is the minimum capacity value allowed for the battery, is the maximum capacity value allowed for the battery.

[0145] By considering the power balance constraint affecting the long-term stable operation of the system and the basic operation characteristic constraints of various operating equipment, the final required operation constraint conditions are set, making it more comprehensive and feasible to solve the capacity optimization configuration problem of the integrated photovoltaic-hydrogen storage system subsequently.

[0146] In some embodiments, the above step S104 may but is not limited to include steps S501 to S507.

[0147] Step S501: Obtain the operation data of the integrated photovoltaic-hydrogen storage system and input it into the capacity optimization configuration model. The operation data at least includes the relevant parameter values required for solving the objective function.

[0148] It should be noted that before the operation data is formally applied in the capacity optimization configuration model, the operation data is screened once so that the screened operation data can meet the operation constraint conditions, facilitating more accurate calculation of the fitness value of each individual in the pigeon flock in the subsequent improved pigeon flock optimization algorithm.

[0149] 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 objective function, and the target variable is .

[0150] Step S503: Set the numerical values of multiple basic parameters required for the improved pigeon flock optimization algorithm. The multiple basic parameters include the population size , the first maximum iteration number of the improved compass operator , the second maximum iteration number of the improved landmark operator , the dimension of the target variable , the compass factor , the pigeon flock category division parameter , the search radius , and the influencing factor regarding the logsig function . .

[0151] Step S504: According to the population size , the target variable and the Tent chaotic mapping strategy, initialize the positions of the pigeon flock, and then determine the global optimal position according to the fitness function and the positions of the initialized pigeon flock.

[0152] Step S505: In the improved compass operator, update the positions of the pigeon flock according to the Lévy flight strategy and the latest global optimal position, and then re-determine the latest global optimal position according to the fitness function, the latest global optimal position, and the updated positions of the pigeon flock;

[0153] Iteratively apply the improved compass operator until the current iteration number reaches the first maximum iteration number , that is, repeat the execution Repeat the above step S505 continuously to update the positions of the pigeon flock and the latest global optimal position. Finally, at the first maximum number of iterations the latest global optimal position re-determined is denoted as the first global optimal position.

[0154] Step S506: In this improved landmark operator, eliminate half of the individuals with relatively poor current fitness values from the pigeon flock. Denote the pigeon flock after eliminating the individuals as the current pigeon flock. Update the positions of the current pigeon flock according to the preset activation function and chaotic perturbation strategy. Then, according to the fitness function, the latest first global optimal position, and the updated positions of the current pigeon flock, re-determine the latest first global optimal position;

[0155] Iteratively apply this improved landmark operator until the current number of iterations reaches the second maximum number of iterations , that is, repeat the execution of the above step S506 a certain number of times to continuously reduce the bad individuals in the pigeon flock and update the positions of the remaining excellent individuals in the pigeon flock and the latest first global optimal position.

[0156] Step S507: Determine the optimal capacity configuration plan for the integrated photovoltaic, energy storage, and hydrogen production system according to the latest first global optimal position re-determined at the second maximum number of iterations .

[0157] It should be noted that the latest first global optimal position re-determined at the second maximum number of iterations actually contains the optimal solution of the target variable . The optimal capacity configuration plan records the optimal configuration quantities of the photovoltaic power generation equipment, the electrolyzer, the fuel cell, the hydrogen storage tank, and the storage battery, and at the same time records the weight values of the economic index function, the reliability index function, and the energy utilization rate index function; by visualizing the optimal capacity configuration plan, technicians can rely on the optimal capacity configuration plan to continue to improve the construction work of the integrated photovoltaic, energy storage, and hydrogen production system, and know which one of the economic index, reliability index, and energy utilization rate index the optimal quantity configuration plan of each type of operating equipment included in the integrated photovoltaic, energy storage, and hydrogen production system focuses on determining.

[0158] Steps S501 to S507 shown in the embodiments of the present application, due to fewer parameters to be adjusted in the improved pigeon flock optimization algorithm, have stronger robustness, stronger global search ability, and faster convergence speed. Using the improved pigeon flock optimization algorithm can quickly solve the capacity optimization configuration model to obtain stable optimization results, and can solve the disadvantages such as being easily trapped in local optimal solutions in the traditional pigeon flock optimization algorithm.

[0159] In some embodiments, the above step S504 may but is not limited to including steps S601 to S603.

[0160] Step S601: Determine the number of individuals to be initialized according to the population size and determine the position dimension of each individual to be initialized according to the target variable where the position of each individual represents a candidate solution of the target variable .

[0161] Step S602: Initialize the positions of the pigeon flock using the Tent chaotic mapping strategy, which is specifically implemented using the following expression:

[0162]

[0163]

[0164] In the formula, is the chaotic sequence related to the position initialization of the th pigeon, is the chaotic domain and satisfies , is the Tent parameter, is the position of the th pigeon, is the lower bound of the search space where the pigeon flock is located, is the upper bound of the search space where the pigeon flock is located, can be understood as the domain of definition of the target variable ; among them, in the present application, it is preferably set that so that the chaotic system is in a completely chaotic state, and the particles generated by the Tent mapping are random and will traverse the entire chaotic domain to facilitate the search for the optimal solution in the global space.

[0165] Step S603: Calculate the fitness value corresponding to each individual in the pigeon flock according to the fitness function and the positions of the initialized pigeon flock, then select the individual with the smallest fitness value from them, and use the position of the selected individual as the global optimal position.

[0166] It should be noted that after performing the above step S602, by presetting a reasonable speed range, the speed of the pigeon flock is initialized by means of random assignment within this speed range.

[0167] By using the Tent sequence with traversal uniformity to initialize the position of the pigeon flock, the diversity of initialization can be effectively increased, and the use of chaos theory to traverse within the neighborhood can assist in solving the problem that the existing algorithms are prone to falling into local optimal solutions.

[0168] In some embodiments, the above step S505 may but is not limited to including steps S701 to S703.

[0169] Step S701: According to the latest global optimal position, the Levy flight strategy is adopted to update the position of the pigeon flock, which is specifically implemented by the following expression:

[0170]

[0171]

[0172]

[0173] In the formula, is the position of the th pigeon at the th iteration, is the position of the th pigeon at the th iteration, is a random number taking values in the interval, is a random number conforming to the range of normal distribution, is a random number conforming to the range of normal distribution, and and satisfy the normal distribution, is the shape parameter of the jump probability distribution and its value range is , and in this application, it is preferably set to , is the latest global optimal position determined at the th iteration, is the Gamma function.

[0174] Step S702: According to the fitness function and the updated position of the pigeon flock, calculate the fitness value corresponding to each individual in the pigeon flock, and then screen out the smallest fitness value and record it as the first fitness value.

[0175] Step S703. Denote the fitness value associated with the latest global optimal position determined at the -th iteration as the second fitness value, and compare this second fitness value with the first fitness value: When the second fitness value is less than or equal to the first fitness value, take the latest global optimal position determined at the -th iteration as the latest global optimal position determined at the -th iteration; when the second fitness value is greater than the first fitness value, take the position of the individual corresponding to the first fitness value as the latest global optimal position determined at the -th iteration.

[0176] It should be noted that after performing the above step S701, the velocity of the pigeon flock is updated using the following expression:

[0177]

[0178] In the formula, is the velocity of the -th pigeon at the -th iteration, and is the velocity of the -th pigeon at the -th iteration.

[0179] By introducing the Lévy flight strategy into the original compass operator for individual position update, while some solutions continuously search around the optimal solution, there are also some solutions searching in a relatively far space, which can help solve the problem that the existing algorithm is prone to falling into local optimal solutions.

[0180] In some embodiments, the above step S506 may but is not limited to including steps S801 to S804.

[0181] Step S801. According to the current fitness value corresponding to each individual in the pigeon flock, delete half of the individuals with the largest current fitness value from the pigeon flock, and denote the pigeon flock after removing the individuals as the current pigeon flock.

[0182] Step S802. Update the position of the current pigeon flock using a preset activation function and a chaotic perturbation strategy. The preset activation function is preferably set as the logsig function and is specifically implemented using the following expression:

[0183]

[0184]

[0185]

[0186] In the formula, is the optimal individual position determined at the th iteration, is the population size at the th iteration, is the population size at the th iteration and , is the fitness value calculated for the th pigeon at the th iteration, is a reference parameter set for convenience of description, is a chaotic sequence generated for the th pigeon using the chaotic perturbation strategy.

[0187] Step S803: According to the fitness function and the updated position of the current pigeon flock, calculate the fitness value corresponding to each individual in the current pigeon flock, and then screen out the smallest fitness value and denote it as the third fitness value.

[0188] Step S804: Denote the fitness value associated with the latest first global optimal position determined at the th iteration as the fourth fitness value, and compare the fourth fitness value with the third fitness value: when the fourth fitness value is less than or equal to the third fitness value, use the latest first global optimal position determined at the th iteration as the latest first global optimal position determined at the th iteration; when the fourth fitness value is greater than the third fitness value, use the position of the individual corresponding to the third fitness value as the latest first global optimal position determined at the th iteration.

[0189] By introducing the chaotic perturbation strategy and the logsig function into the original landmark operator for individual position update, that is, dividing the pigeon flock into two categories according to the fitness value size during each iteration process, using the logsig function to update the position of the pigeon flock with better fitness value, and using the chaotic perturbation strategy to update the position of the pigeon flock with worse fitness value, it can help solve the problem that the existing algorithm is prone to falling into the local optimal solution.

[0190] Please refer to Figure 3 , this application embodiment also provides an optimal configuration device for the capacity of the integrated optical storage and hydrogen system, which is specifically applied to the integrated optical storage and hydrogen system as shown in Figure 1 , and can implement the above-mentioned optimal configuration method for the capacity of the integrated optical storage and hydrogen system. The device includes:

[0191] The first construction module 901 is configured to construct a curtailment 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 integrated photovoltaic, energy storage, and hydrogen production system;

[0192] The second construction module 902 is configured to construct an objective function according to the curtailment rate function, the power shortage rate function, and the investment payback period function;

[0193] The third construction module 903 is configured to set the operating constraint conditions of the integrated photovoltaic, energy storage, and hydrogen production system, and then construct a capacity optimization configuration model for the integrated photovoltaic, energy storage, and hydrogen production system in combination with the objective function;

[0194] The solution module 904 is configured to obtain the operating data of the integrated photovoltaic, energy storage, and hydrogen production system, input the operating data into the capacity optimization configuration model, and then solve the capacity optimization configuration model by an improved pigeon flock optimization algorithm to obtain an optimal capacity configuration scheme for the integrated photovoltaic, energy storage, and hydrogen production system.

[0195] It can be understood that the content in the above method embodiments is applicable to the device embodiments. The functions specifically implemented in the device embodiments are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those in the above method embodiments.

[0196] The embodiment of the present application further provides an electronic device. The electronic device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the above-mentioned capacity optimization configuration method for the integrated photovoltaic, energy storage, and hydrogen production system is implemented. The electronic device can be any intelligent terminal including a tablet computer, an in-vehicle computer, etc.

[0197] It can be understood that the content in the above method embodiments is applicable to the device embodiments. The functions specifically implemented in the device embodiments are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those in the above method embodiments.

[0198] Please refer to Figure 4 , Figure 4 which shows the hardware structure of an electronic device in another embodiment. The electronic device includes:

[0199] The processor 1001 can be implemented in a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, etc., and is used to execute relevant programs to implement the technical solutions provided by the embodiments of the present application;

[0200] 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), etc. The memory 1002 can store an operating system and other application programs. When implementing the technical solutions provided in the embodiments of the present application through software or firmware, the relevant program codes are stored in the memory 1002 and are called by the processor 1001 to execute the technical solutions provided in the embodiments of the present application;

[0201] The input / output interface 1003 is used to implement information input and output;

[0202] The communication interface 1004 is used to implement communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or through wireless means (such as mobile network, WIFI, Bluetooth, etc.);

[0203] The bus 1005 transmits information between the various components of the device (such as the processor 1001, the memory 1002, the input / output interface 1003, and the communication interface 1004);

[0204] Among them, the processor 1001, the memory 1002, the input / output interface 1003, and the communication interface 1004 achieve communication connections with each other inside the device through the bus 1005.

[0205] The embodiments of the present application also provide a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the above-mentioned method for optimizing the configuration of the capacity of the integrated optical storage and hydrogen system.

[0206] It can be understood that the content in the above method embodiments is applicable to the embodiments of this storage medium. The functions specifically implemented by the embodiments of this storage medium are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those of the above method embodiments.

[0207] As a non-transitory computer-readable storage medium, the memory can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory can include high-speed random access memory and can also include non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory may optionally include a memory remotely set relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above networks include, but are not limited to, the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0208] The embodiments described in the embodiments of the present application are for more clearly illustrating the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art can know that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of the present application are equally applicable to similar technical problems.

[0209] Those skilled in the art can understand 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 those shown in the figures, or combine certain steps, or different steps.

[0210] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0211] Those of ordinary skill in the art can understand that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, and their appropriate combinations.

[0212] 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 do not have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0213] It should be understood that in this application, "at least one (item)" means one or more, and "a plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships can exist. For example, "A and / or B" can mean: only A exists, only B exists, and both A and B exist at the same time. Among them, A and B can be singular or plural. The character " / " generally indicates that the associated objects before and after are in an "or" relationship. "At least one (one) of the following" or its similar expressions refer to any combination of these items, including any combination of single item (one) or plural items (ones). For example, at least one (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.

[0214] In several embodiments provided in this 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 illustrative. For example, the above division of units is only a logical function division. In actual implementation, there can be other division methods. For example, 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 displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of systems or units can be in electrical, mechanical or other forms.

[0215] The units described above as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place, or they can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0216] In addition, the functional units in each embodiment of this application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0217] When 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 such an understanding, the technical solution of this application, in essence, or the part that makes a contribution to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of various embodiments of this application. The foregoing storage medium includes: various media that can store programs, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs.

[0218] The preferred embodiments of the embodiments of this application have been described above with reference to the accompanying drawings, which does not limit the scope of rights of the embodiments of this application. Any modifications, equivalent replacements, and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of this application shall fall within the scope of rights of the embodiments of this application.

Claims

1. A method for optimizing the capacity configuration of a comprehensive optical energy storage and hydrogen production system, characterized in that The photovoltaic-hydrogen storage integrated system includes a photovoltaic power generation device, a storage battery, an electrolyzer, a hydrogen storage tank, and a fuel cell. The method includes: Construct an investment payback period function, a power outage rate function, and a curtailment rate function according to the characteristics of each type of operating equipment included in the photovoltaic-hydrogen storage integrated system; Construct an objective function according to the investment payback period function, the power outage rate function, and the curtailment rate function; Set the operating constraints of the photovoltaic-hydrogen storage integrated system, and then combine with the objective function to construct a capacity optimization configuration model for the photovoltaic-hydrogen storage integrated system; Obtain the operating data of the photovoltaic-hydrogen storage integrated 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 an optimal capacity configuration plan for the photovoltaic-hydrogen storage integrated system; Among them, the step of using the improved pigeon flock optimization algorithm to solve the capacity optimization configuration model to obtain an optimal capacity configuration plan for the photovoltaic-hydrogen storage integrated system includes: Determine a fitness function and target variables to be optimized according to the capacity optimization configuration model; Set the values of multiple basic parameters involved in the improved pigeon flock optimization algorithm. The multiple basic parameters include the population size, the first maximum number of iterations of the improved compass operator, and the second maximum number of iterations of the improved landmark operator; Initialize the positions of the pigeon flock according to the population size, the target variables, and the Tent chaos mapping strategy, and then determine the global optimal position according to the fitness function and the initialized positions of the pigeon flock; In the improved compass operator, update the positions of the pigeon flock according to the Lévy flight strategy and the latest global optimal position, and then re-determine the latest global optimal position according to the fitness function, the latest global optimal position, and the updated positions of the pigeon flock; Iteratively apply the improved compass operator until the current number of iterations reaches the first maximum number of iterations, and record the latest global optimal position determined at the first maximum number of iterations as the first global optimal position; In the improved landmark operator, remove the half of the individuals with relatively poor current fitness values from the pigeon flock, and record the pigeon flock after removing the individuals as the current pigeon flock. Update the positions of the current pigeon flock according to the chaos perturbation strategy and a preset activation function, and then re-determine the latest first global optimal position according to the fitness function, the latest first global optimal position, and the updated positions of the current pigeon flock; Iteratively apply the improved landmark operator until the current number of iterations reaches the second maximum number of iterations; Determine the optimal capacity configuration plan according to the latest first global optimal position determined at the second maximum number of iterations.

2. The method for optimizing the capacity allocation of the integrated optical energy storage and hydrogen production system according to claim 1, wherein The investment payback period function is obtained through the following method: Construct an initial investment cost function according to the configuration quantity and unit price of each type of operating equipment included in the photovoltaic-hydrogen storage integrated system; Construct an operation and maintenance cost function and a residual value cost function according to the configuration quantity, operating power, and unit power operation and maintenance cost of each type of operating equipment included in the photovoltaic-hydrogen storage integrated system; Denote the storage battery, the electrolyzer and the fuel cell as the first operating equipment, and construct a replacement cost function according to the configuration quantity, replacement times and unit replacement cost of each type of the first operating equipment included in the photovoltaic-hydrogen storage integrated system; Denote the storage battery and the electrolyzer as the second operating equipment, and construct a energy storage revenue function according to the electricity price in the power market and the configuration quantity and operating power of each type of the second operating equipment included in the photovoltaic-hydrogen storage integrated system; Construct the investment payback period function according to the initial investment cost function, the operation and maintenance cost function, the salvage value cost function, the replacement cost function and the energy storage revenue function.

3. The method for optimizing the capacity configuration of the integrated optical energy storage and hydrogen production system according to claim 1, wherein The power shortage rate function is obtained by the following method: Denote the photovoltaic power generation equipment, the storage battery and the fuel cell as the third operating equipment, and construct the power shortage rate function 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 photovoltaic-hydrogen storage integrated system.

4. The method for optimizing the capacity configuration of the integrated optical energy storage and hydrogen production system according to claim 1, wherein The curtailment rate function is obtained by the following method: Denote the photovoltaic power generation equipment, the storage battery and the electrolyzer as the fourth operating equipment, and construct the curtailment rate function 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 photovoltaic-hydrogen storage integrated system.

5. The method for optimizing the capacity allocation of the integrated optical energy storage and hydrogen production system according to claim 1, characterized in that, The construction of the objective function according to the investment payback period function, the power shortage rate function and the curtailment rate function includes: Construct an economic index function according to the preset shortest investment payback period and the investment payback period function; Construct a reliability index function according to the preset maximum full charge rate and the power shortage rate function; Construct an energy utilization rate index function according to the preset maximum photovoltaic utilization rate and the curtailment rate function; Perform weighted summation on the economic index function, the reliability index function and the energy utilization rate index function to obtain the objective function.

6. The method for optimizing the capacity allocation of the integrated optical energy storage and hydrogen production system according to claim 1, wherein The setting of the operation constraint conditions of the photovoltaic-hydrogen storage integrated system includes: Set 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 storage battery and the power constraint of the storage battery to form the operation constraint conditions.

7. An optimization configuration device for the capacity of a comprehensive optical energy storage and hydrogen production system, characterized in that, The photovoltaic-hydrogen storage integrated system includes photovoltaic power generation equipment, a storage battery, an electrolyzer, a hydrogen storage tank and a fuel cell, and the device includes: A first construction module, configured to construct an investment payback period function, a power shortage rate function and a curtailment rate function according to the characteristics of each type of operating equipment included in the photovoltaic-hydrogen storage integrated system; A second construction module, configured to construct an objective function according to the investment payback period function, the power shortage rate function and the curtailment rate function; A third construction module, configured to set the operation constraint conditions of the photovoltaic-hydrogen storage integrated system, and then combine the objective function to construct a capacity optimization configuration model for the photovoltaic-hydrogen storage integrated system; A solution module, configured to obtain the operation data of the integrated photovoltaic-hydrogen storage system, input the operation data into the capacity optimization configuration model, and then solve the capacity optimization configuration model by using an improved pigeon flock optimization algorithm to obtain an optimal capacity configuration scheme for the integrated photovoltaic-hydrogen storage system; Wherein, the process of solving the capacity optimization configuration model by using the improved pigeon flock optimization algorithm to obtain an optimal capacity configuration scheme for the integrated photovoltaic-hydrogen storage system includes: Determine a fitness function and target variables to be optimized according to the capacity optimization configuration model; Set the values of multiple basic parameters involved in the improved pigeon flock optimization algorithm, and the multiple basic parameters include the population size, the first maximum iteration number of the improved compass operator, and the second maximum iteration number of the improved landmark operator; Initialize the positions of the pigeon flock according to the population size, the target variables, and the Tent chaos mapping strategy, and then determine the global optimal position according to the fitness function and the positions of the initialized pigeon flock; In the improved compass operator, update the positions of the pigeon flock according to the Lévy flight strategy and the latest global optimal position, and then re-determine the latest global optimal position according to the fitness function, the latest global optimal position, and the updated positions of the pigeon flock; Iteratively apply the improved compass operator until the current iteration number reaches the first maximum iteration number, and record the latest global optimal position re-determined at the first maximum iteration number as the first global optimal position; In the improved landmark operator, remove the half of the individuals with relatively poor current fitness values from the pigeon flock, and denote the pigeon flock after removing the individuals as the current pigeon flock. Update the positions of the current pigeon flock according to the chaos perturbation strategy and a preset activation function, and then re-determine the latest first global optimal position according to the fitness function, the latest first global optimal position, and the updated positions of the current pigeon flock; Iteratively apply the improved landmark operator until the current iteration number reaches the second maximum iteration number; Determine the optimal capacity configuration scheme according to the latest first global optimal position re-determined at the second maximum iteration number.

8. An electronic device, characterized in that, The electronic device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, the method according to any one of claims 1 to 6 is implemented.

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