Dynamic control method and device for solar-driven air water collection coupling hydrogen production system

Abstract

The invention provides a dynamic control method and device for a solar-driven air water collection coupling hydrogen production system, and relates to the technical field of new energy utilization, the solar-driven air water collection coupling hydrogen production system comprises a photovoltaic module, a solar thermal power generation module, a solar air water collector, a water electrolysis hydrogen production device and a water photolysis hydrogen production device; the dynamic control method comprises the following steps: constructing an output prediction model of the solar-driven air water collection coupling hydrogen production system; dynamically adjusting the solar-driven air water collection coupling hydrogen production system based on output data of the output prediction model; wherein the output data of the output prediction model comprises hydrogen yield, system efficiency, total energy consumption, total cost, system stability index, photovoltaic module output power, solar thermal power generation module output power, solar air water collector water yield, water electrolysis hydrogen production device efficiency and water photolysis hydrogen production device efficiency. According to the invention, the hydrogen yield can be effectively improved while the cost is minimized and solar energy is utilized to the maximum extent.

Description

Background Art

[0002] With the growing global demand for clean energy and increasing attention to environmental protection, solar energy utilization technology, solar air water collection technology and hydrogen production technology have received widespread attention and development.

[0003] Solar energy utilization technology can convert abundant solar energy into electrical energy or thermal energy, providing sustainable energy for human production and life. The more common solar energy utilization technologies include photovoltaic power generation and solar thermal power generation. Among them, photovoltaic power generation directly converts sunlight into electrical energy through solar cells, which has the advantages of flexible installation and convenient maintenance; solar thermal power generation uses solar collectors to convert sunlight into thermal energy, and then converts thermal energy into electrical energy through heat engines, which is suitable for large-scale electricity production.

[0004] Solar air water collection technology can collect and extract moisture from the air, and can provide water solutions for water-scarce areas. The more common solar air water collection technologies include solar air water collectors and solar-driven air water collection systems. Among them, solar air water collectors use the heat energy and hot steam converted from solar energy to collect and extract moisture from the air, and the equipment is relatively simple; the solar-driven air water collection system uses solar collectors, air compressors, and water vapor generators to work together to improve the efficiency of moisture collection and extraction, but the equipment cost is high and requires a lot of energy to operate.

[0005] Hydrogen production technology can convert water or other raw materials into hydrogen. As a clean energy carrier, hydrogen has the advantages of high combustion calorific value and no pollution. The more common hydrogen production technologies include water electrolysis and photocatalytic hydrogen production. Among them, water electrolysis produces hydrogen and oxygen by electrolyzing water. The technology is relatively mature, but the energy utilization efficiency is low and requires a lot of electricity; photocatalytic hydrogen production uses photocatalysts to decompose water molecules into hydrogen and oxygen under light conditions. It has good environmental protection characteristics, but the energy conversion efficiency is low and ultraviolet light is required.

[0006] However, in the process of utilizing solar energy to drive air water collection coupled with hydrogen production, the energy conversion efficiency of photovoltaic power generation technology and solar thermal power generation technology is generally not high, only 15%-25% and 20%-30% respectively, and there is still a lot of room for improvement; the solar air water collector has low efficiency in water collection and extraction in low humidity environments, and although the solar-driven air water collection system is more efficient, the equipment cost is high and the operating energy consumption is large; the energy utilization efficiency of water electrolysis hydrogen production technology is low and it relies on a large amount of electricity, and the energy conversion efficiency of photocatalytic hydrogen production technology is low and requires ultraviolet light. Summary of the invention

[0007] In order to overcome the problems existing in the related art, the present invention provides a dynamic control method and device for a solar-driven air-water collection coupled hydrogen production system.

[0008] According to a first aspect of an embodiment of the present invention, a dynamic control method of a solar-driven air-water collection coupled hydrogen production system is provided, wherein the solar-driven air-water collection coupled hydrogen production system comprises a photovoltaic component, a solar thermal power generation component, a solar-air water collector, a water electrolysis hydrogen production device, and a water photolysis hydrogen production device; The dynamic control method comprises: Construct an output prediction model for a solar-driven air-water harvesting coupled hydrogen production system; Dynamically adjusting the solar-driven air-water collection coupled hydrogen production system based on the output data of the output prediction model; Among them, the output data of the output prediction model include: hydrogen production, system efficiency, total energy consumption, total cost, system stability index, photovoltaic module output power, solar thermal power generation module output power, solar air water collector water production, water electrolysis hydrogen production device efficiency and photolysis water hydrogen production device efficiency.

[0009] In some exemplary embodiments of the present invention, based on the above scheme, constructing an output prediction model of a solar-driven air-water collection coupled hydrogen production system includes: Acquiring meteorological data and relevant running data and operation data of the solar-driven air-water collection coupled hydrogen production system; Preprocessing the meteorological data, the relevant operation data and the operation data to obtain preprocessed input data; According to the pre-processed input data, the objective function and constraint conditions of the output prediction model are established with the goals of maximizing system efficiency, maximizing hydrogen production, minimizing energy consumption, minimizing costs and optimizing system stability; Solving the objective function to obtain an optimal solution set; Based on the optimal solution set, an output prediction model is obtained.

[0010] In some example embodiments of the present invention, based on the above scheme, the objective function of the output prediction model includes: in, , , , , is the weight coefficient, which is used to balance the importance of different objectives. represents the system efficiency, is the hydrogen production, represents the total energy consumption of the system, represents the total cost, Indicates system performance indicators.

[0011] In some exemplary embodiments of the present invention, based on the above scheme, the system efficiency maximization is expressed as: The maximum hydrogen production is expressed as: The energy consumption minimization is expressed as: The cost minimization is expressed as: The system stability is optimally expressed as: in, represents the system efficiency, is the hydrogen production, represents the solar energy input, Indicates at time The volume of hydrogen produced in Indicates the time interval, represents the total energy consumption, Indicates the energy consumed by the photovoltaic module, Indicates the energy consumed by the air water pump, The energy consumed by electrolyzing water to produce hydrogen is represents the total cost, represents the capital cost, represents the operating cost, represents the energy cost, Indicates system performance indicators. Indicates hydrogen production The standard deviation of Indicates at time The hydrogen production in represents the average value of hydrogen production, Represents the number of data points.

[0012] In some exemplary embodiments of the present invention, based on the above solution, the constraint conditions include: The hydrogen production is greater than or equal to the minimum production requirement; The ratio of hydrogen production to solar energy input is greater than or equal to the minimum energy efficiency ratio; The performance fluctuation index is less than or equal to the maximum fluctuation tolerance; Solar input is less than or equal to the maximum solar capture capacity; The equipment load is less than or equal to the maximum capacity of the equipment; The equipment operation time is less than or equal to the equipment life; The total cost is less than or equal to the budget cap; The operating cost is less than or equal to the maximum operating cost; Environmental impact indicators are less than or equal to environmental standards; The safety risk index is less than or equal to the safety threshold; The operating parameter is greater than or equal to the lower limit of the operating parameter and less than or equal to the upper limit of the operating parameter; The maintenance frequency is greater than or equal to the minimum maintenance frequency.

[0013] In some example embodiments of the present invention, based on the above solution, solving the objective function includes: The objective function is solved using a non-dominated sorting genetic algorithm II.

[0014] In some example embodiments of the present invention, based on the above scheme and based on the optimal solution set, obtaining the output prediction model includes: The optimal solution set is used to train a neural network to obtain the output prediction model.

[0015] According to a second aspect of an embodiment of the present invention, there is provided a device for a dynamic control method of the above-mentioned solar-driven air-water collection coupled hydrogen production system, comprising: Model building module, used to build the output prediction model of the solar-driven air-water harvesting coupled hydrogen production system; A dynamic control module is used to dynamically adjust the solar-driven air-water collection coupled hydrogen production system based on the output data of the output prediction model.

[0016] According to a third aspect of an embodiment of the present invention, there is provided an electronic device, comprising: a processor; and a memory, wherein the memory stores computer-readable instructions, and the computer-readable instructions implement the method in the first aspect when executed by the processor.

[0017] According to a fourth aspect of an embodiment of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the method in the first aspect when executed by a processor.

[0018] The technical solution provided by the embodiments of the present invention may have the following beneficial effects: The present invention can accurately predict key indicators such as hydrogen production and system efficiency by constructing an output prediction model. Dynamic adjustments based on these prediction data can enable the system to always operate in the optimal state, fully utilize solar energy resources, avoid energy waste, improve the conversion efficiency of solar energy, and significantly improve hydrogen production and system efficiency.

[0019] In addition, the present invention can be adjusted according to different climatic conditions, solar radiation intensity, air humidity and other factors, so that the system can maintain a good operating state in various environments and has strong adaptability.

[0020] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0022] Figure 1 A schematic diagram showing a system architecture of an exemplary application environment of a dynamic control method and device for a solar-driven air-water collection coupled hydrogen production system to which an embodiment of the present invention can be applied; Figure 2 A schematic diagram of a process flow of a dynamic control method of a solar-driven air-water collection coupled hydrogen production system according to some embodiments of the present invention is shown; Figure 3 Schematically showing a schematic diagram of a dynamic control device of a solar-driven air-water collection coupled hydrogen production system according to some embodiments of the present invention; Figure 4 A schematic diagram schematically shows a structure of a computer system of an electronic device according to some embodiments of the present invention; Figure 5 A schematic diagram of a computer-readable storage medium according to some embodiments of the present invention is schematically shown. DETAILED DESCRIPTION

[0023] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0024] The terms used in the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The singular forms "a", "the" and "the" used in the present invention and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0025] It should be understood that although the terms first, second, third, etc. may be used in the present invention to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present invention, 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 word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0026] Figure 1 A schematic diagram of a system architecture of an exemplary application environment of a dynamic control method and device for a solar-driven air-water collection coupled hydrogen production system to which an embodiment of the present invention can be applied is shown.

[0027] like Figure 1 As shown, the system architecture 100 may include one or more terminal devices such as a desktop computer 101, a portable computer 102, a smart phone 103, a network 104 and a server 105. The network 104 is used to provide a medium for a communication link between the terminal device and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc. The terminal device may be various electronic devices with data processing functions, and the electronic device has a display screen, which is used to display the dynamic control information of the solar-driven air-water collection coupled hydrogen production system to the user, including but not limited to the above-mentioned desktop computers, portable computers, smart phones, etc. It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. According to the implementation requirements, there may be any number of terminal devices, networks and servers. For example, the server 105 may be a sub-server cluster composed of multiple sub-servers.

[0028] The dynamic control method of the solar-driven air-water-collection coupled hydrogen production system provided in the embodiment of the present invention can generally be executed by the terminal device, and accordingly, the dynamic control device of the solar-driven air-water-collection coupled hydrogen production system is generally arranged in the terminal device. However, it is easy for those skilled in the art to understand that the dynamic control method of the solar-driven air-water-collection coupled hydrogen production system provided in the embodiment of the present invention can also be executed by the server 105, and accordingly, the dynamic control device of the solar-driven air-water-collection coupled hydrogen production system can also be arranged in the server 105, and this is not particularly limited in this exemplary embodiment.

[0029] In addition, it should be understood that the dynamic control method of the solar-driven air-water-collection coupled hydrogen production system of the embodiment of the present invention can be configured as a software module. In some implementation scenarios, the dynamic control scheme of the solar-driven air-water-collection coupled hydrogen production system of the present invention can be deployed separately to realize the construction and generation of three-dimensional spatial information corresponding to different types of independent pipelines. In other implementation scenarios, the dynamic control scheme of the solar-driven air-water-collection coupled hydrogen production system of the present invention can be deployed in other software as a functional module of the software, such as deployed in the analysis software of underground pipelines. The present invention does not place any special restrictions on the application of the dynamic control method of the solar-driven air-water-collection coupled hydrogen production system.

[0030] Next, the embodiments of the present invention are described in detail.

[0031] The solar-driven air-water-collection coupled hydrogen production system of the present invention includes photovoltaic modules, solar thermal power generation modules, solar air water collectors, water electrolysis hydrogen production devices, and photolysis water hydrogen production devices. Among them, photovoltaic modules and solar thermal power generation modules are mainly used to generate electricity using solar energy resources; solar air water collectors are used to collect water with the help of solar energy resources; water electrolysis hydrogen production devices use the electricity generated by photovoltaic modules and solar thermal power generation modules, and photolysis water hydrogen production devices use sunlight, and the two respectively convert the water collected by the solar air water collector into hydrogen.

[0032] On this basis, reference Figure 2 As shown, Figure 2 The present invention is a flowchart of a dynamic control method of a solar-driven air-water collection coupled hydrogen production system according to an exemplary embodiment of the present invention, comprising the following steps: S210: Construct an output prediction model for a solar-driven air-water harvesting coupled hydrogen production system; S220: Dynamically adjusting the solar-driven air-water collection coupled hydrogen production system based on the output data of the output prediction model; Among them, the output data of the output prediction model include: hydrogen production, system efficiency, total energy consumption, total cost, system stability index, photovoltaic module output power, solar thermal power generation module output power, solar air water collector water production, water electrolysis hydrogen production device efficiency and photolysis water hydrogen production device efficiency.

[0033] In S210, an output prediction model of a solar-driven air-water collection coupled hydrogen production system is constructed.

[0034] By building an output prediction model, key indicators such as hydrogen production and system efficiency can be accurately predicted.

[0035] In some embodiments, an output prediction model of the solar-driven air-water-collection coupled hydrogen production system can be constructed based on relevant data of the solar-driven air-water-collection coupled hydrogen production system using machine learning methods, deep learning methods, etc.

[0036] In the embodiment provided by the present invention, constructing an output prediction model of a solar-driven air-water collection coupled hydrogen production system includes: Acquiring meteorological data and relevant running data and operation data of the solar-driven air-water collection coupled hydrogen production system; Preprocessing the meteorological data, the relevant operation data and the operation data to obtain preprocessed input data; According to the pre-processed input data, the objective function and constraint conditions of the output prediction model are established with the goals of maximizing system efficiency, maximizing hydrogen production, minimizing energy consumption, minimizing costs and optimizing system stability; Solving the objective function to obtain an optimal solution set; Based on the optimal solution set, an output prediction model is obtained.

[0037] Here, meteorological data include light intensity, temperature, humidity, wind speed, etc., which have an important impact on the performance of solar energy related equipment; system operation data include the output power of photovoltaic modules, the output power of solar thermal power generation modules, the water production of solar air water collectors, the working state parameters of water electrolysis hydrogen production devices and photolysis water hydrogen production devices, etc. Operation data include the opening time and closing time of the equipment, the tilt angle of the photovoltaic modules, the operating mode of the air water extraction device, the working current of the electrolyzer, etc.

[0038] Since these data are huge and complex, they need to be preprocessed first. In some embodiments, the preprocessing process is not limited to: Data cleaning, data normalization or standardization, data compression, feature selection, feature construction, and data conversion, etc. Since these data processing processes are prior art, the present invention will not elaborate on them.

[0039] Based on the preprocessed input data, the objective function and constraints of the output prediction model are established with the goals of maximizing system efficiency, maximizing hydrogen production, minimizing energy consumption, minimizing costs, and optimizing system stability. These five goals cover multiple aspects such as system performance, economic benefits, and stability, reflecting the comprehensive optimization of the system. The objective function can be a weighted sum of multiple objectives or other forms of combination, and the constraints may include equipment performance limitations, resource availability limitations, safety limitations, etc.

[0040] In some embodiments, the objective function of the output prediction model includes: in, , , , , is the weight coefficient, which is used to balance the importance of different objectives. represents the system efficiency, is the hydrogen production, represents the total energy consumption of the system, represents the total cost, Indicates system performance indicators.

[0041] Furthermore, the system efficiency maximization is expressed as: The maximum hydrogen production is expressed as: The energy consumption minimization is expressed as: The cost minimization is expressed as: The system stability is optimally expressed as: in, represents the system efficiency, is the hydrogen production, represents the solar energy input, Indicates at time The volume of hydrogen produced in Indicates the time interval, represents the total energy consumption, Indicates the energy consumed by the photovoltaic module, Indicates the energy consumed by the air water pump, The energy consumed by electrolyzing water to produce hydrogen is represents the total cost, represents the capital cost, represents the operating cost, represents the energy cost, Indicates system performance indicators. Indicates hydrogen production The standard deviation of Indicates at time The hydrogen production in represents the average value of hydrogen production, Represents the number of data points.

[0042] On this basis, the constraints of the present invention include: The hydrogen production is greater than or equal to the minimum production requirement; The ratio of hydrogen production to solar energy input is greater than or equal to the minimum energy efficiency ratio; The performance fluctuation index is less than or equal to the maximum fluctuation tolerance; Solar input is less than or equal to the maximum solar capture capacity; The equipment load is less than or equal to the maximum capacity of the equipment; The equipment operation time is less than or equal to the equipment life; The total cost is less than or equal to the budget cap; The operating cost is less than or equal to the maximum operating cost; Environmental impact indicators are less than or equal to environmental standards; The safety risk index is less than or equal to the safety threshold; The operating parameter is greater than or equal to the lower limit of the operating parameter and less than or equal to the upper limit of the operating parameter; The maintenance frequency is greater than or equal to the minimum maintenance frequency.

[0043] Through these constraints, it can be fully reflected that the present invention pursues the optimal solution of the objective function on the basis of considering practicality, economy and safety.

[0044] The objective function of the present invention can be solved using a multi-objective optimization algorithm, such as a genetic algorithm, a particle swarm optimization algorithm, a simulated annealing algorithm, and the like. The present invention is not limited thereto. As an embodiment, the present invention uses a non-dominated sorting genetic algorithm II to solve the objective function. The non-dominated sorting genetic algorithm II (NSGA-II) uses fast non-dominated sorting to classify individuals in a population, which helps to quickly identify non-dominated solutions at different layers and improve computational efficiency. In addition, not only is there no need to define weights during the calculation process, but the crowding distance of each solution within its neighborhood can also be calculated to maintain population diversity and prevent the algorithm from converging to a local optimal solution too early. Since the objective function of the present invention is produced with full consideration of multiple factors, the use of NSGA-II can better solve the calculation problem of the objective function.

[0045] Specifically, the process of solving the objective function using the non-dominated sorting genetic algorithm II includes: 1. Initialize the population; 2. Calculate the objective function value and constraint violation degree of each individual in the current population; 3. Perform non-dominated sorting on the population according to the objective function value, and divide the individuals into different non-dominated frontiers; 4. Use the tournament selection method to select parent individuals for crossover and mutation to generate a new generation of population; 5. Merging the new generation population and the old population; 6. Sort the merged population according to non-dominated sorting and crowding distance, and select the best individuals to form a new population; 7. Determine whether the current iteration meets the termination condition. If so, output the new population as the optimal solution set; otherwise, take the new population as the current population and return to step 2.

[0046] Here, the termination condition may be that a preset number of iterations is met.

[0047] On this basis, after obtaining the optimal solution, the optimal solution set can be used as input data for a mathematical model, a statistical model, or a machine learning model to train the model and obtain an output prediction model. In an embodiment of the present invention, the optimal solution set is used to train the neural network model to obtain an output prediction model. The neural network model can be any form of neural network model, and the present invention is not limited thereto.

[0048] In S220, the solar-driven air-water collection coupled hydrogen production system is dynamically adjusted based on the output data of the output prediction model.

[0049] Dynamic adjustment of the solar-driven air-water collection coupled hydrogen production system can make the system always operate in the optimal state, make full use of solar energy resources, avoid energy waste, improve the conversion efficiency of solar energy, and significantly improve hydrogen production and system efficiency. Moreover, the present invention can keep the system in a good operating state in various environments without being limited to the influence of factors such as climatic conditions, solar radiation intensity, and air humidity, and has strong adaptability.

[0050] The output prediction model will generate a series of data, including hydrogen production, system efficiency, total energy consumption, total cost, system stability index, photovoltaic module output power, solar thermal power module output power, solar air water collector water production, water electrolysis hydrogen production device efficiency and photolysis water hydrogen production device efficiency, etc. These data fully reflect the performance of the solar-driven air water collection coupled hydrogen production system under different conditions.

[0051] According to a second aspect of an embodiment of the present invention, a dynamic control device for a solar-driven air-water collection coupled hydrogen production system is also provided. Figure 3 As shown, the dynamic control device of the solar-driven air-water collection coupled hydrogen production system includes a model building module 310 and a dynamic control module 320; A model building module 310 is used to build an output prediction model of a solar-driven air-water collection coupled hydrogen production system; The dynamic control module 320 is used to dynamically adjust the solar-driven air-water collection coupled hydrogen production system based on the output data of the output prediction model.

[0052] In an exemplary embodiment of the present invention, based on the above solution, the model building module 310 may further include: A data acquisition submodule, used to acquire meteorological data and relevant running data and operation data of the solar-driven air-water collection coupled hydrogen production system; A preprocessing submodule, used for preprocessing the meteorological data, the relevant operation data and the operation data to obtain preprocessed input data; A function establishment submodule is used to establish the objective function and constraint conditions of the output prediction model according to the preprocessed input data with the goals of maximizing system efficiency, maximizing hydrogen production, minimizing energy consumption, minimizing costs and optimizing system stability; A function solving submodule, used to solve the objective function to obtain an optimal solution set; The model generation submodule is used to obtain an output prediction model based on the optimal solution set.

[0053] It should be noted that although several modules and sub-modules of the dynamic control device of the solar-driven air-water collection coupled hydrogen production system are mentioned in the above detailed description, this division is not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more modules or sub-modules described above can be concretized in one module or unit. Conversely, the features and functions of one module or sub-module described above can be further divided into multiple modules or sub-modules to be concretized.

[0054] In addition, in an exemplary embodiment of the present invention, an electronic device capable of implementing the dynamic control method of the above-mentioned solar-driven air-water collection coupled hydrogen production system is also provided.

[0055] Those skilled in the art will appreciate that various aspects of the present invention may be implemented as systems, methods or program products. Therefore, various aspects of the present invention may be specifically implemented in the following forms, namely: complete hardware embodiments, complete software embodiments (including firmware, microcode, etc.), or embodiments combining hardware and software aspects, which may be collectively referred to herein as "circuits", "modules" or "systems".

[0056] Refer to the following Figure 4 An electronic device 400 according to such an embodiment of the present invention is described. Figure 4 The electronic device 400 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0057] like Figure 4As shown, the electronic device 400 is in the form of a general computing device. The components of the electronic device 400 may include but are not limited to: the at least one processing unit 410, the at least one storage unit 420, a bus 430 connecting different system components (including the storage unit 420 and the processing unit 410), and a display unit 440.

[0058] The storage unit stores program codes, which can be executed by the processing unit 410, so that the processing unit 410 performs the steps of various exemplary embodiments of the present invention described in the above “Exemplary Method” section. For example, the processing unit 410 can perform the following steps: Figure 2 In S210 shown in the figure, an output prediction model of a solar-driven air-water-collection coupled hydrogen production system is constructed; and in S220, the solar-driven air-water-collection coupled hydrogen production system is dynamically adjusted based on output data of the output prediction model.

[0059] The storage unit 420 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 421 and / or a cache memory unit 422 , and may further include a read-only memory unit (ROM) 423 .

[0060] The storage unit 420 may also include a program / utility 424 having a set (at least one) of program modules 425, such program modules 425 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0061] Bus 430 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0062] The electronic device 400 may also communicate with one or more external devices 470 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 400, and / or communicate with any device that enables the electronic device 400 to communicate with one or more other computing devices (e.g., routers, modems, etc.). This communication may be performed through an input / output (I / O) interface 450. In addition, the electronic device 400 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) through a network adapter 460. As shown, the network adapter 460 communicates with other modules of the electronic device 400 through a bus 430. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 400, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0063] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the exemplary embodiments described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiment of the present invention.

[0064] In an exemplary embodiment of the present invention, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present invention is stored. In some possible embodiments, various aspects of the present invention can also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal device, the program code is used to enable the terminal device to perform the steps of various exemplary embodiments of the present invention described in the above "Exemplary Method" section of the present invention.

[0065] refer to Figure 5 As shown, a program product 500 for implementing the dynamic control method of the above-mentioned solar-driven air-water collection coupled hydrogen production system according to an embodiment of the present invention is described, which can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In the present invention, the readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, an apparatus or a device.

[0066] The program product may use any combination of one or more readable storage media. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0067] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0068] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to an exemplary embodiment of the present invention, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0069] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the exemplary embodiments described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiment of the present invention.

[0070] Other embodiments of the invention will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. The invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the claims.

[0071] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A dynamic control method for a solar-driven air-water collection coupled hydrogen production system, characterized in that: The solar-driven air-water collection coupled hydrogen production system comprises a photovoltaic module, a solar thermal power generation module, a solar-air water collector, a water electrolysis hydrogen production device and a water photolysis hydrogen production device; The dynamic control method comprises: Construct an output prediction model for a solar-driven air-water harvesting coupled hydrogen production system; Dynamically adjusting the solar-driven air-water collection coupled hydrogen production system based on the output data of the output prediction model; Among them, the output data of the output prediction model include: hydrogen production, system efficiency, total energy consumption, total cost, system stability index, photovoltaic module output power, solar thermal power generation module output power, solar air water collector water production, water electrolysis hydrogen production device efficiency and photolysis water hydrogen production device efficiency.

2. The dynamic control method of the solar-driven air-water collection coupled hydrogen production system according to claim 1 is characterized in that: The output prediction model of the solar-driven air-water harvesting coupled hydrogen production system is constructed including: Acquiring meteorological data and relevant running data and operation data of the solar-driven air-water collection coupled hydrogen production system; Preprocessing the meteorological data, the relevant operation data and the operation data to obtain preprocessed input data; According to the pre-processed input data, the objective function and constraint conditions of the output prediction model are established with the goals of maximizing system efficiency, maximizing hydrogen production, minimizing energy consumption, minimizing costs and optimizing system stability; Solving the objective function to obtain an optimal solution set; Based on the optimal solution set, an output prediction model is obtained.

3. The dynamic control method of the solar-driven air-water collection coupled hydrogen production system according to claim 2 is characterized in that: The objective function of the output prediction model includes: in, , , , , is the weight coefficient, which is used to balance the importance of different objectives. represents the system efficiency, is the hydrogen production, represents the total energy consumption of the system, represents the total cost, Indicates system performance indicators.

4. The dynamic control method of the solar-driven air-water collection coupled hydrogen production system according to claim 2 is characterized in that: The system efficiency maximization is expressed as: The maximum hydrogen production is expressed as: The energy consumption minimization is expressed as: The cost minimization is expressed as: The system stability is optimally expressed as: in, represents the system efficiency, is the hydrogen production, represents the solar energy input, Indicates at time The volume of hydrogen produced in Indicates the time interval, represents the total energy consumption, Indicates the energy consumed by the photovoltaic module, Indicates the energy consumed by the air water pump, The energy consumed by electrolyzing water to produce hydrogen is represents the total cost, represents the capital cost, represents the operating cost, represents the energy cost, Indicates system performance indicators. Indicates hydrogen production The standard deviation of Indicates at time The hydrogen production in represents the average value of hydrogen production, Represents the number of data points.

5. The dynamic control method of the solar-driven air-water collection coupled hydrogen production system according to any one of claims 2 to 4, characterized in that: The constraints include: The hydrogen production is greater than or equal to the minimum production requirement; The ratio of hydrogen production to solar energy input is greater than or equal to the minimum energy efficiency ratio; The performance fluctuation index is less than or equal to the maximum fluctuation tolerance; Solar input is less than or equal to the maximum solar capture capacity; The equipment load is less than or equal to the maximum capacity of the equipment; The equipment operation time is less than or equal to the equipment life; The total cost is less than or equal to the budget cap; The operating cost is less than or equal to the maximum operating cost; Environmental impact indicators are less than or equal to environmental standards; The safety risk index is less than or equal to the safety threshold; The operating parameter is greater than or equal to the lower limit of the operating parameter and less than or equal to the upper limit of the operating parameter; The maintenance frequency is greater than or equal to the minimum maintenance frequency.

6. The dynamic control method of the solar-driven air-water collection coupled hydrogen production system according to claim 2 is characterized in that: Solving the objective function includes: The objective function is solved using a non-dominated sorting genetic algorithm II.

7. The dynamic control method of the solar-driven air-water collection coupled hydrogen production system according to claim 2 is characterized in that: Based on the optimal solution set, the output prediction model is obtained including: The optimal solution set is used to train a neural network to obtain the output prediction model.

8. A device for dynamically controlling the solar-driven air-water collection coupled hydrogen production system according to any one of claims 1 to 7, characterized in that: The device comprises: Model building module, used to build the output prediction model of the solar-driven air-water harvesting coupled hydrogen production system; A dynamic control module is used to dynamically adjust the solar-driven air-water collection coupled hydrogen production system based on the output data of the output prediction model.

9. An electronic device, characterized in that: include: processor; as well as A memory having computer-readable instructions stored thereon, wherein the computer-readable instructions, when executed by the processor, implement the dynamic control method of the solar-driven air-water collection coupled hydrogen production system according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the dynamic control method of the solar-driven air-water collection coupled hydrogen production system as described in any one of claims 1 to 7 is implemented.

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