Wind power hydrogen production regulation and control method based on real-time power and related device

Abstract

The invention discloses a wind power hydrogen production regulation and control method and related device based on real-time power, and the method comprises the steps: obtaining the historical operation information of a wind turbine generator, the operation information comprising the minute-level output power of the wind turbine generator; according to the historical operation information of the wind turbine generator, calculating the optimal power generation power of the wind turbine generator by using a particle swarm optimization algorithm; the minute-level generation power of the current wind turbine generator is obtained, the minute-level generation power of the current wind turbine generator is compared with the optimal generation power of the wind turbine generator, and the wind turbine generator, a hydrogen production device and an energy storage device are controlled according to the comparison result. According to the method and the related device, the problems that sharp power generation power peak valley is too high and energy grid connection is not matched in the electrolytic hydrogen production process can be solved.

Description

Technical Field

[0001] The present invention belongs to the field of new energy wind turbine regulation, and relates to a wind power to hydrogen regulation method and related devices based on real-time power. Background Art

[0002] With the progress of science and technology, the cost of wind power generation has gradually decreased, and its market scale has been continuously expanding. A wind turbine generally consists of components such as a wind wheel, a generator (including devices), a yaw device (tail fin), a tower, a speed limit safety mechanism, and an energy storage device. The power generation principle is to use wind power to drive the rotation of the windmill blades, and then increase the rotation speed through a speed increaser to drive the generator to generate electric energy. With the continuous innovation and improvement of wind power generation technology, as well as the breakthrough of energy storage technology and the construction of smart grids, the stability and reliability of wind power generation have been further improved.

[0003] In addition, using renewable energy to produce hydrogen is considered a cleaner, more economical, and sustainable way of energy utilization. Using wind energy and other power generation and electrolysis to produce hydrogen can reduce greenhouse gases such as carbon dioxide, and can also be used as a substitute for fossil fuels. In addition, the application of clean energy hydrogen production can alleviate the impact of renewable energy power generation on the grid, solve the problem of unstable supply of renewable energy such as wind and light, and strongly support the achievement of the carbon peak goal.

[0004] Currently, the electric energy generated by wind power generation can be directly applied to water electrolysis hydrogen production through simple processing, which effectively stabilizes the operation process of wind power generation. However, this method has problems such as too high peak and valley of wind power generation power, and mismatch of energy on the grid during the electrolytic hydrogen production process. Summary of the Invention

[0005] The purpose of the present invention is to overcome the above-mentioned disadvantages of the prior art, and provides a wind power to hydrogen regulation method and related devices based on real-time power, which can solve the problems of too high peak and valley of sharp power generation power and mismatch of energy on the grid during the electrolytic hydrogen production process.

[0006] To achieve the above purpose, the present invention discloses a wind power to hydrogen regulation method based on real-time power, including:

[0007] Obtain the historical operation information of the wind turbine, and the operation information includes the minute-level output power of the wind turbine;

[0008] According to the historical operation information of the wind turbine, use the particle swarm optimization algorithm to calculate the optimal power generation power of the wind turbine;

[0009] Obtain the minute-level power generation power of the current wind turbine, compare the minute-level power generation power of the current wind turbine with the optimal power generation power of the wind turbine, and control the wind turbine, the hydrogen production device, and the energy storage device according to the comparison result.

[0010] A further improvement of the wind power to hydrogen regulation method based on real-time power according to the present invention lies in:

[0011] Further, when V < 0.8V 参 , the power of the wind turbine is not supplied to the hydrogen production device, and the hydrogen production device is powered by the energy storage device, where V 参 is the optimal power generation power of the wind turbine;

[0012] When 0.8V 参 < V < 1.2V 参 , the excess power of the wind turbine is supplied to the energy storage device, and the excess power generation exceeding 0.8 times the optimal power generation power is supplied to the energy storage device for energy storage, and the energy storage device supplies energy to the hydrogen production device;

[0013] When 1.2V 参 < V, the excess power of the wind turbine is supplied to the energy storage device and the hydrogen production device, the excess power generation exceeding 0.8 times and less than 1.2 times the optimal power generation power is supplied to the energy storage device for energy storage, and the excess power exceeding 1.2 times is additionally supplied to the hydrogen production device.

[0014] Further, in the process of calculating the optimal power generation power of the wind turbine by using the particle swarm optimization algorithm, the current fitness f(x) of the particle is:

[0015] f(x) = -(x - 10) 2 + xsin(x)cox(2x) - 5xsin(3x)

[0016] where x is the current position of the particle.

[0017] Further, in the process of calculating the optimal power generation power of the wind turbine by using the particle swarm optimization algorithm, the update formula is:

[0018] v i = w × v i + c1 × rand() × (p best，i ) + c2 × rand() × (g best - x i )

[0019] x i = v i + x i

[0020] where v i is the velocity of the particle at that time, x i is the position of the particle at that time, rand() is a random function, p bestis the optimal position, c1 is the self-learning factor of the particle, c2 is the group learning factor of the particle, and w is the inertia weight.

[0021] The present invention discloses a wind power hydrogen production regulation system based on real-time power, including:

[0022] An acquisition module, configured to acquire historical operation information of a wind turbine, where the operation information includes the minute-level output power of the wind turbine;

[0023] A calculation module, configured to calculate the optimal power generation power of the wind turbine by using a particle swarm optimization algorithm according to the historical operation information of the wind turbine;

[0024] A control module, configured to acquire the minute-level power generation power of the current wind turbine, compare the minute-level power generation power of the current wind turbine with the optimal power generation power of the wind turbine, and control the wind turbine, the hydrogen production device, and the energy storage device according to the comparison result.

[0025] A further improvement of the wind power hydrogen production regulation system based on real-time power according to the present invention lies in:

[0026] Further, when V < 0.8V 参 then the electric energy of the wind turbine is not supplied to the hydrogen production device, and the hydrogen production device is powered by the energy storage device, where V 参 is the optimal power generation power of the wind turbine;

[0027] When 0.8V 参 < V < 1.2V 参 then the surplus electric energy of the wind turbine is supplied to the energy storage device, and the surplus power generation amount exceeding 0.8 times the optimal power generation power is supplied to the energy storage device for energy storage, and the energy storage device supplies energy to the hydrogen production device;

[0028] When 1.2V 参 < V, then the surplus electric energy of the wind turbine is supplied to the energy storage device and the hydrogen production device, the surplus power generation amount exceeding 0.8 times and less than 1.2 times the optimal power generation power is supplied to the energy storage device for energy storage, and the surplus power generation amount exceeding 1.2 times is additionally supplied to the hydrogen production device.

[0029] Further, in the process of calculating the optimal power generation power of the wind turbine by using the particle swarm optimization algorithm, the current fitness f(x) of the particle is:

[0030] f(x) = -(x - 10) 2 + xsin(x)cox(2x) - 5xsin(3x)

[0031] where x is the current position of the particle.

[0032] Further, the update formula in the process of calculating the optimal power generation of the wind turbine using the particle swarm optimization algorithm is as follows:

[0033] v i = w × v i + c1 × rand() × (p best，i ) + c2 × rand() × (g best - x i )

[0034] x i = v i + x i

[0035] Wherein, v i is the velocity of the particle at that time, x i is the position of the particle at that time, rand() is a random function, p best is the best position, c1 is the self-learning factor of the particle, c2 is the swarm learning factor of the particle, and w is the inertia weight.

[0036] The present invention discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the wind power to hydrogen regulation method based on real-time power are implemented.

[0037] The present invention discloses a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the steps of the wind power to hydrogen regulation method based on real-time power are implemented.

[0038] The present invention has the following beneficial effects:

[0039] When the wind power to hydrogen regulation method based on real-time power and related devices of the present invention are specifically operated, according to the historical operation information of the wind turbine, the particle swarm optimization algorithm is used to calculate the optimal power generation power table of the wind turbine, and the wind turbine, the hydrogen production device, and the energy storage device are controlled accordingly, so as to solve the problems of excessive peak and valley of the sharp power generation power and the mismatch of energy on the grid during the electrolytic hydrogen production process, and effectively improve the applicability, timeliness, and efficiency of the regulation system. In addition, based on different rating structures to manage the power distribution, not only effectively solves the problem of excessive peak and valley of the power generation power of the wind turbine, but also improves the efficiency of hydrogen production by using the energy storage device. Description of the Drawings

[0040] The specification drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The schematic embodiments and descriptions of the present invention are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0041] Figure 1 This is the flowchart of the method of the present invention. Specific embodiments

[0042] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0043] In the description of the present invention, it should be understood that the terms "including" and "comprising" indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or their combinations.

[0044] It should also be understood that the terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0045] It should be further understood that the term " / and" used in the specification of the present invention and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations. For example, A and / or B can represent: the case where A exists alone, the case where A and B exist simultaneously, and the case where B exists alone. In addition, the character " / " in the present invention generally represents an "or" relationship between the front and back associated objects.

[0046] It should be understood that although the terms first, second, third, etc. may be used in the embodiments of the present invention to describe preset ranges, etc., these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from each other. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0047] Depending on the context, the word "if" as used herein can be interpreted as "when" or "while" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrase "if determined" or "if detected (stated condition or event)" can be interpreted as "when determined" or "in response to determining" or "when detected (stated condition or event)" or "in response to detecting (stated condition or event)".

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. Usually, the components described and shown in the accompanying drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0049] Various structural schematic diagrams according to the disclosed embodiments of the present invention are shown in the accompanying drawings. These figures are not drawn to scale, where for the purpose of clear expression, some details are enlarged and some details may be omitted. The shapes of various regions and layers shown in the figures, as well as their relative sizes and positional relationships, are merely exemplary. In practice, there may be deviations due to manufacturing tolerances or technical limitations, and those skilled in the art can design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0050] The Particle Swarm Optimization (PSO) algorithm is an evolutionary computing technique that originated from the study of the foraging behavior of bird flocks. This algorithm finds the optimal solution by simulating the cooperation and information sharing of individuals (i.e., "particles") in the bird flock in the search space. It has the advantages of being easy to program, having fewer parameters, being convenient for adjustment and optimization, having a fast convergence speed, and strong global search ability, and has been widely applied to various optimization problems.

[0051] Embodiment 1

[0052] Reference Figure 1 , the real-time power-based wind power to hydrogen regulation method of the present invention includes the following steps:

[0053] 1) Obtain the historical operation information of the wind turbine;

[0054] Specifically, obtain the historical operation information of the wind turbine, and the operation information includes the minute-level output power of the wind turbine.

[0055] 2) Optimize and store the historical operation information of the wind turbine, eliminate abnormal data that is too high or too low, and then calculate the optimal power generation of the wind turbine based on the historical operation information of the wind turbine and the particle swarm optimization algorithm. The specific process is as follows:

[0056] 21) Initialize the algorithm, program it, and set the population size N, i.e., the number of particles; set the velocity range and position space. The position space is the search space for the entire data. Randomly initialize the velocity and position of each particle within the velocity range and position space;

[0057] 22) Calculate the fitness value of each particle according to the objective function to evaluate the quality of the solution of each particle in the problem space, i.e.:

[0058] f(x) = -(x - 10) 2 + xsin(x)cox(2x) - 5xsin(3x)

[0059] where x is the current position of the particle and f(x) is the current fitness of the particle.

[0060] 23) Take the current fitness value of each particle and the best result in its historical optimum p i as the local optimum value of each particle. The particle continuously approaches the optimal solution through its own iterative calculation. Then compare the local optimum value p i of each particle with the historical optimum value p g of the population. When p i is closer to the target value than p g , select the local optimum value p i as the local optimum solution of each particle. Otherwise, select the historical optimum value p g as the local optimum solution of each particle;

[0061] 24) When the optimal value obtained by iterative calculation reaches the predetermined minimum fitness threshold or the number of calculated iterations exceeds the set maximum number of iteration steps, the algorithm terminates, and output the optimal power generation of the wind turbine and the number of iterations. If the conditions are not met, update the velocity and position of the particle. The update formulas are:

[0062] v i = w × v i + c1 × rand() × (p best，i ) + c2 × rand() × (g best - x i )

[0063] x i = v i + x i

[0064] where v i is the velocity of the particle at that time, x i is the position of the particle at that time, rand() is a random function, p bestis the optimal position, c1 is the self-learning factor of the particle, c2 is the swarm learning factor of the particle, and w is the inertia weight.

[0065] 3) Compare the optimal power generation with the minute-level power generation V of the real-time monitored wind turbine. The judgment criteria are the dual judgment criteria composed of 80% and 120% of the optimal power generation value. When V < 0.8V 参 , then issue instruction 1. When 0.8V 参 < V < 1.2V 参 , then issue instruction 2. When 1.2V 参 < V, then issue instruction 3. By dividing into three levels of judgment, the excess power generation of the wind turbine can be reasonably distributed, and the working efficiency of the regulation system can be improved.

[0066] 4) The terminal analyzes the uploaded instructions and conducts regulation according to the issued instructions. Instruction 1 is that the power of the wind turbine is not supplied to the hydrogen production device, and the hydrogen production device is only powered by the energy storage device; Instruction 2 is that the excess power of the wind turbine is supplied to the energy storage device, and the excess power generation exceeding 0.8 times the optimal power generation is supplied to the energy storage device for energy storage, and the energy storage device powers the hydrogen production device; Instruction 3 is that the excess power of the wind turbine is supplied to the energy storage device and the hydrogen production device. The excess power generation exceeding 0.8 times and less than 1.2 times the optimal power generation is supplied to the energy storage device for energy storage, and the excess power exceeding 1.2 times is additionally supplied to the hydrogen production device, so as to ensure the stable operation of the wind turbine and efficiently produce hydrogen energy.

[0067] The present invention has the following characteristics:

[0068] The present invention obtains the optimal power generation of the wind turbine based on the historical operation information of the wind turbine and uses it as the judgment standard for the wind power hydrogen production system, so that the regulation system can operate more reasonably and reliably.

[0069] The present invention uses the particle swarm optimization algorithm to find the global optimal value through continuous iterative calculation of each particle swarm according to the target requirements, realizes the maximum use of the operation data of the wind turbine, and finally determines the judgment standard most suitable for the regulation system, effectively improving the accuracy and reasonableness of the system judgment.

[0070] The present invention divides the judgment criteria into three instruction results, and reasonably distributes the excess power generation to the energy storage device and the hydrogen production device according to the real-time power generation situation of the wind turbine. It can not only minimize the negative impact of unstable power generation, but also enable the energy storage device to continuously supply energy to the hydrogen production system, ensure the efficiency of hydrogen production, and solve the problem of excessive power generation valley peaks of the wind turbine.

[0071] Embodiment 2

[0072] The wind power to hydrogen regulation system based on real-time power according to the present invention includes:

[0073] An acquisition module for acquiring the historical operation information of the wind turbine, where the operation information includes the minute-level output power of the wind turbine;

[0074] A calculation module for calculating the optimal power generation power of the wind turbine by using the particle swarm optimization algorithm according to the historical operation information of the wind turbine;

[0075] A control module for acquiring the minute-level power generation power of the current wind turbine, comparing the minute-level power generation power of the current wind turbine with the optimal power generation power of the wind turbine, and controlling the wind turbine, the hydrogen production device, and the energy storage device according to the comparison result.

[0076] A further improvement of the wind power to hydrogen regulation system based on real-time power according to the present invention lies in:

[0077] In this embodiment, when V < 0.8V 参 then the power of the wind turbine is not supplied to the hydrogen production device, and the hydrogen production device is powered by the energy storage device, where V 参 is the optimal power generation power of the wind turbine;

[0078] When 0.8V 参 < V < 1.2V 参 then the excess power of the wind turbine is supplied to the energy storage device, and the excess power generation exceeding 0.8 times the optimal power generation power is supplied to the energy storage device for energy storage, and the energy storage device supplies energy to the hydrogen production device;

[0079] When 1.2V 参 < V, then the excess power of the wind turbine is supplied to the energy storage device and the hydrogen production device, the excess power generation exceeding 0.8 times and less than 1.2 times the optimal power generation power is supplied to the energy storage device for energy storage, and the excess power exceeding 1.2 times is additionally supplied to the hydrogen production device.

[0080] In this embodiment, in the process of calculating the optimal power generation power of the wind turbine by using the particle swarm optimization algorithm, the current fitness f(x) of the particle is:

[0081] f(x) = -(x - 10) 2 + xsin(x)cox(2x) - 5xsin(3x)

[0082] where x is the current position of the particle.

[0083] In this embodiment, the update formula in the process of calculating the optimal power generation power of the wind turbine by using the particle swarm optimization algorithm is:

[0084] v i= w × v i + c1 × rand() × (p best，i ) + c2 × rand() × (g best - x i )

[0085] x i = v i + x i

[0086] where v i is the velocity of the particle at that time, x i is the position of the particle at that time, rand() is a random function, p best is the best position, c1 is the self-learning factor of the particle, c2 is the swarm learning factor of the particle, and w is the inertia weight.

[0087] The division of modules in the embodiments of this application is illustrative. It is only a logical function division. In actual implementation, there may be other division methods. In addition, in each embodiment of this application, each functional module can be integrated in a processor, can exist alone physically, or two or more modules can be integrated in one module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules.

[0088] Embodiment 3

[0089] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the wind power to hydrogen production regulation method based on real-time power. For example, it includes: obtaining the historical operation information of the wind turbine, where the operation information includes the minute-level output power of the wind turbine; according to the historical operation information of the wind turbine, using the particle swarm optimization algorithm to calculate the optimal power generation of the wind turbine; obtaining the minute-level power generation of the current wind turbine, comparing the minute-level power generation of the current wind turbine with the optimal power generation of the wind turbine, and controlling the wind turbine, the hydrogen production device, and the energy storage device according to the comparison result. Among them, the memory may include internal memory, such as high-speed random access memory, and may also include non-volatile memory, such as at least one disk memory, etc.; the processor, network interface, and memory are interconnected through an internal bus, and this internal bus can be an Industry Standard Architecture bus, a Peripheral Component Interconnect standard bus, an Extended Industry Standard Architecture bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. The memory is used to store programs. Specifically, the program may include program code, and the program code includes computer operation instructions. The memory can include internal memory and non-volatile memory and provide instructions and data to the processor.

[0090] Example 4

[0091] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the steps of the wind power hydrogen production regulation method based on real-time power. For example, it includes: obtaining the historical operation information of the wind turbine, where the operation information includes the minute-level output power of the wind turbine; according to the historical operation information of the wind turbine, using the particle swarm optimization algorithm to calculate the optimal power generation power of the wind turbine; obtaining the minute-level power generation power of the current wind turbine, comparing the minute-level power generation power of the current wind turbine with the optimal power generation power of the wind turbine, and controlling the wind turbine, hydrogen production device, and energy storage device according to the comparison result. Specifically, the computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. The volatile memory may include random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include read-only memory (ROM), hard disk, flash memory, optical disc, magnetic disk, etc.

[0092] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0093] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0094] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the functions in the process Figure 1One or more processes and / or blocks Figure 1 The functions specified in one or more blocks.

[0095] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one Figure 1 One or more processes and / or blocks Figure 1 The steps of the functions specified in one or more blocks.

[0096] After considering the specification and the disclosure of the invention, those skilled in the art will readily conceive of other embodiments of the present invention. This application is intended to cover any variations, uses, or adaptations of the present invention, which follow the general principles of the present invention and include known common general knowledge or conventional technical means in the technical field not disclosed by the present invention. The specification and the embodiments are only regarded as exemplary, and the true scope and spirit of the present invention are pointed out by the following claims.

[0097] It should be understood that the present invention is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is only limited by the appended claims.

[0098] As described above, these are only the preferred embodiments of the present invention, and do not impose any limitations on the present invention. Any simple modifications, changes, and equivalent structural changes made to the above embodiments according to the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A wind power to hydrogen regulation method based on real-time power, characterized in that, Including: Obtain the historical operation information of the wind turbine, where the operation information includes the minute-level output power of the wind turbine; According to the historical operation information of the wind turbine, use the particle swarm optimization algorithm to calculate the optimal power generation of the wind turbine; Obtain the minute-level power generation of the current wind turbine, compare the minute-level power generation of the current wind turbine with the optimal power generation of the wind turbine, and control the wind turbine, hydrogen production device, and energy storage device according to the comparison result.

2. The wind power to hydrogen regulation method based on real-time power according to claim 1, wherein When V < 0.8V 参 , the power of the wind turbine is not supplied to the hydrogen production device, and the hydrogen production device is powered by the energy storage device, where V 参 is the optimal power generation of the wind turbine; When 0.8V 参 <V<1.2V 参 , the excess power of the wind turbine is supplied to the energy storage device, and the excess power generation exceeding 0.8 times the optimal power generation is supplied to the energy storage device for energy storage, and the energy storage device supplies energy to the hydrogen production device; When 1.2V 参 <V, the excess power of the wind turbine is supplied to the energy storage device and the hydrogen production device. The excess power generation exceeding 0.8 times and less than 1.2 times the optimal power generation is supplied to the energy storage device for energy storage, and the excess power exceeding 1.2 times is additionally supplied to the hydrogen production device.

3. The wind power to hydrogen regulation method based on real-time power according to claim 1, wherein In the process of using the particle swarm optimization algorithm to calculate the optimal power generation of the wind turbine, the current fitness f(x) of the particle is: f(x)=-(x - 10) 2 + xsin(x)cox(2x)-5xsin(3x) It should be noted that "cox" in the original text might be a misspelling. It's likely supposed to be "cos". If that's the case, the corrected translation for the relevant part would be: + xsin(x)cos(2x)-5xsin(3x) where x is the current position of the particle.

4. The real-time power-based wind power to hydrogen regulation method according to claim 1, wherein The update formula in the process of using the particle swarm optimization algorithm to calculate the optimal power generation of the wind turbine is: v i = w × v i + c1 × rand() × (p best，i ) + c2 × rand() × (g best - x i ) x i = v i + x i where v i is the velocity of the particle at that time, x i is the position of the particle at that time, rand() is a random function, p best is the best position, c1 is the self-learning factor of the particle, c2 is the swarm learning factor of the particle, and w is the inertia weight.

5. A wind power to hydrogen regulation system based on real-time power, characterized in that, Including: An acquisition module for obtaining the historical operation information of the wind turbine, where the operation information includes the minute-level output power of the wind turbine; A calculation module for calculating the optimal power generation of the wind turbine using the particle swarm optimization algorithm according to the historical operation information of the wind turbine; A control module for obtaining the minute-level power generation of the current wind turbine, comparing the minute-level power generation of the current wind turbine with the optimal power generation of the wind turbine, and controlling the wind turbine, hydrogen production device, and energy storage device according to the comparison result.

6. The wind power hydrogen production regulation system based on real-time power according to claim 5, wherein When V < 0.8V 参 , the electric power of the wind turbine is not supplied to the hydrogen production device, and the hydrogen production device is powered by the energy storage device, where V 参 is the optimal power generation power of the wind turbine; When 0.8V 参 <V<1.2V 参 , the excess power of the wind turbine is supplied to the energy storage device, and the excess power generation exceeding 0.8 times the optimal power generation is supplied to the energy storage device for energy storage. The energy storage device supplies energy to the hydrogen production device; When 1.2V 参 <V, the excess power of the wind turbine is supplied to the energy storage device and the hydrogen production device. The excess power generation exceeding 0.8 times and less than 1.2 times the optimal power generation is supplied to the energy storage device for energy storage, and the excess power exceeding 1.2 times is additionally supplied to the hydrogen production device.

7. The wind power hydrogen production regulation system based on real-time power according to claim 5, wherein In the process of using the particle swarm optimization algorithm to calculate the optimal power generation of the wind turbine, the current fitness f(x) of the particle is: f(x)=-(x - 10) 2 + xsin(x)cox(2x)-5xsin(3x) It should be noted that there may be a misspelling in "cox(2x)" in the original text. It might be "cos(2x)". where x is the current position of the particle.

8. The wind power to hydrogen regulation system based on real-time power according to claim 5, characterized in that, The update formula in the process of using the particle swarm optimization algorithm to calculate the optimal power generation of the wind turbine is: v i = w × v i + c1 × rand() × (p best，i ) + c2 × rand() × (g best - x i ) x i = v i + x i where v i is the velocity of the particle at that time, x i is the position of the particle at that time, rand() is a random function, p best is the best position, c1 is the self-learning factor of the particle, c2 is the swarm learning factor of the particle, and w is the inertia weight.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the real-time power-based wind power hydrogen production regulation method according to any one of claims 1-4.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the real-time power-based wind power hydrogen production regulation method according to any one of claims 1-4.

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