Capacity optimization method and system for a multi-energy flow coupling system based on an efficient electrohydrogen catalyst

Abstract

This invention provides a method and system for optimizing the capacity of a multi-energy flow coupled system based on an efficient electrohydrogen catalyst. [Solution] A method for optimizing the capacity of a multi-energy flow coupled system based on an efficient electrohydrogen catalyst, comprising the steps of: constructing high-resolution models after processing a transition metal catalyst by defect engineering and interface engineering; constructing a multi-energy flow coupled model using energy storage equipment based on the constructed high-resolution models, creating a multi-energy flow coupled collaborative optimization structure with constraints of reserve, carbon emissions, renewable energy allocation criteria and real-time balance of electricity, heat, and hydrogen supply and demand power, and targeting minimizing total annual costs; and acquiring operating data and cost data, inputting them into the multi-energy flow coupled collaborative optimization structure, solving it, and outputting an optimal capacity configuration strategy.

Description

[Technical Field]

[0001] (Cross-reference of related applications) This invention claims priority to the Chinese patent application filed with the China National Intellectual Property Administration on April 1, 2025, with application number 202510396758.X, and titled "Method and System for Optimizing the Capacity of a Multi-Energy Flow Coupled System Based on an Efficient Electro-Hydrogen Catalyst," the entirety of which is incorporated into this invention by reference for all purposes and constitutes a part of this invention.

[0002] The present invention relates to the technical field of planning high-ratio new energy power systems, and more particularly to a method and system for optimizing the capacity of a multi-energy flow coupled system based on an efficient electro-hydrogen catalyst. [Background technology]

[0003] The description in this section merely provides background information related to the present invention and does not necessarily constitute prior art.

[0004] Currently, the global energy system still relies heavily on fossil fuels, and the greenhouse gases emitted from their combustion have a serious impact on the environment and climate. Against this backdrop, renewable energy sources such as wind and solar energy are rapidly developing. However, with the rapid increase in renewable energy generation capacity and grid connection capacity, grid transport capacity is facing significant challenges, and problems such as wind and solar power depletion and declining utilization rates of new energy sources are becoming more serious. Hydrogen energy is attracting attention as an energy carrier due to its advantages such as flexibility, high energy density, abundant supply sources, and the ability to be stored for long periods and transported between regions. To achieve effective collaboration between hydrogen energy and existing power systems (electro-hydrogen coupling), those skilled in the art have proposed the concept of a multi-energy flow coupling system.

[0005] However, existing electro-hydrogen bonding technologies, such as water electrolyzers and hydrogen fuel cells, still rely primarily on precious metal catalysts (e.g., platinum-based and iridium-based catalysts) that are scarce, expensive, and have undesirable electrocatalytic efficiency. Furthermore, existing multi-energy flow coupling systems fail to fully demonstrate the flexibility of electro-hydrogen bonding technologies in their modeling processes, thus failing to fully utilize their potential to solve the problems of fume and light elimination. As a result, the above technical bottlenecks limit the deep integration of hydrogen energy with existing power systems. Therefore, improving the catalytic efficiency of existing electro-hydrogen bonding technologies, performing high-resolution modeling of electro-hydrogen bonding technologies to fully demonstrate their flexibility, and realizing efficient collaborative planning for multi-energy flow coupling systems are urgent issues that need to be addressed. [Overview of the project]

[0006] To solve the above problems, this invention proposes a method and system for optimizing the capacity of a multi-energy flow coupling system based on an efficient electrohydrogen catalyst, which involves incorporating defect engineering and interface engineering to obtain an electrohydrogen coupling technology with efficient catalytic performance, constructing a high-resolution model, constructing a multi-energy flow coupling model based on the model, and creating a multi-energy flow coupling cooperative optimization structure. This invention improves the catalytic efficiency of the electrohydrogen coupling technology and realizes deep integration of hydrogen energy with existing power systems.

[0007] To achieve the above objectives, the present invention employs the following technical solution.

[0008] In the first aspect, the present invention provides a step of obtaining a composite catalyst by treating a transition metal catalyst with defect engineering and interface engineering, The steps include using the aforementioned composite catalyst in a water electrolytic cell and a hydrogen fuel cell, and constructing high-resolution models of the water electrolytic cell and the hydrogen fuel cell, respectively. Based on high-resolution models of water electrolyzers and hydrogen fuel cells, a multi-energy flow coupling model is constructed using energy storage equipment. The constraints include reserve, carbon emissions, renewable energy allocation criteria, and the real-time balance of electricity, heat, and hydrogen supply and demand, with the goal of minimizing total annual costs, and a multi-energy flow coupling collaborative optimization structure is created. The process involves acquiring operational data and cost data, inputting them into a multi-energy flow coupled collaborative optimization structure, solving the problem, and outputting an optimal capacity configuration strategy. This invention provides a method for optimizing the capacity of a multi-energy flow coupled system based on an efficient electrohydrogen catalyst, including the provision of efficient electrohydrogen catalysts.

[0009] In a further technical solution, the defect engineering incorporates an irregular structure into the complete lattice of the transition metal catalyst, the defect engineering includes three-dimensional defects: vacancy defects, helical dislocations, and stacking faults, and the interface engineering causes a multilayer porous heterogeneous heterostructure to be formed in the transition metal catalyst by chemical vapor deposition.

[0010] In a further technical solution, the high-resolution model of the water electrolytic cell is a model of the output characteristics of the water electrolytic cell, and specifically,

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[0011] In a further technical solution, the high-precision model of the hydrogen fuel cell is an output characteristic model of the hydrogen fuel cell, and specifically,

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[0012] Further technical proposals involve constructing a multi-energy flow coupled model based on high-resolution models of water electrolyzers and hydrogen fuel cells, using energy storage equipment. Specifically, this model includes renewable energy models, hydrogen storage container models, thermal storage tank models, electric storage equipment models, electric heating device models, and compressor models.

[0013] In further technical proposals, the minimum total annual cost is calculated by subtracting grid sales revenue from the sum of investment costs, operation and maintenance costs, grid electricity purchase costs, and penalty costs.

[0014] Further technical solutions include an alkaline water electrolytic cell, a proton exchange membrane water electrolytic cell, and a solid oxide water electrolytic cell, and the hydrogen fuel cell includes an alkaline hydrogen fuel cell, a proton exchange membrane hydrogen fuel cell, a solid oxide hydrogen fuel cell, and a molten carbonate hydrogen fuel cell.

[0015] In a second aspect, the present invention provides a catalyst efficiency improvement module configured to obtain a composite catalyst by treating a transition metal catalyst with defect engineering and interface engineering, An electro-hydrogen coupling model construction module is configured to use the aforementioned composite catalyst in a water electrolytic cell and a hydrogen fuel cell, and to construct high-resolution models of the water electrolytic cell and the hydrogen fuel cell, respectively. A multi-energy flow coupled collaborative optimization structure creation module is configured to create a multi-energy flow coupled collaborative optimization structure based on high-resolution models of water electrolyzers and hydrogen fuel cells, using energy storage equipment to construct a multi-energy flow coupled model, with constraints of reserve, carbon emissions, renewable energy allocation criteria, and real-time balance of electricity, heat, and hydrogen supply and demand power, aiming to minimize total annual costs. A strategy output module is configured to acquire operating data and cost data, input them into a multi-energy flow coupled collaborative optimization structure, solve the problem, and output an optimal capacity configuration strategy. This invention provides a capacity optimization system for multi-energy flow coupled systems based on efficient electrohydrogen catalysts, including the provision of an efficient electrohydrogen catalyst-based system.

[0016] Compared to the prior art, the present invention has the following advantages and beneficial effects.

[0017] 1. The present invention constructs high-resolution models of water electrolyzers and hydrogen fuel cells that not only reflect the output characteristics of electrohydrogen bonding technology but also fully demonstrate its flexibility. By examining the cooperative complementary relationship between these models and the variability and unpredictability of renewable resources such as wind and solar power, the invention aims to maximize the use of renewable energy, reduce the rate of wasted wind and solar power, and fully realize the function and potential of hydrogen energy as an energy carrier.

[0018] 2. The present invention provides a water electrolytic cell and hydrogen fuel cell with efficient catalytic performance by obtaining a transition metal catalyst that is competitive in terms of both cost and catalytic performance by combining defect engineering and interface engineering with two types of transition metal catalysts, Fe and Ni, which have abundant storage capacity and are environmentally friendly. This provides technical support for the efficient conversion and storage of electricity generated from new energy sources. By using the improved Fe-Ni composite catalyst in the water electrolytic cell and hydrogen fuel cell, the output performance of the electro-hydrogen bonding technology is greatly improved, the conversion efficiency of electricity-hydrogen and hydrogen-electricity is significantly improved, and an electro-hydrogen bonding technology with efficient catalytic performance is obtained, laying a solid foundation for the deep integration of hydrogen energy with existing power systems.

[0019] 3. The multi-energy flow coupled cooperative optimization structure created by the present invention integrates multiple electro-hydrogen bonding technologies with efficient catalytic performance, comprehensively coordinating three different types of energy—electricity, heat, and hydrogen—and multiple energy conversion and storage devices. This efficiently meets the user's diverse energy needs, such as electricity, thermal energy, and hydrogen energy, achieving stable functionality with very high cost-effectiveness and environmental benefits. Importantly, the method proposed by the present invention clarifies the optimal combination and type selection of electro-hydrogen conversion devices under different operating conditions, providing precise guidance for energy scheduling and equipment configuration in different scenarios.

[0020] The accompanying drawings, which constitute part of the present invention, are used to better understand the present invention. Schematic embodiments and descriptions of the present invention are for interpretation purposes only and do not limit the present invention. [Brief explanation of the drawing]

[0021] [Figure 1] This is a logical structural diagram of the capacity optimization method for a multi-energy flow coupled system based on an efficient electrohydrogen catalyst according to the present invention. [Figure 2] This is a structural diagram of the comprehensive energy system of the present invention. [Modes for carrying out the invention]

[0022] The following detailed descriptions are all illustrative and intended to further illustrate the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those generally understood by those skilled in the art.

[0023] Examples and features of the present invention can be combined with each other, provided that no contradiction arises.

[0024] Example 1 As shown in Figure 1, this embodiment proposes a method for optimizing the capacity of a multi-energy flow coupled system based on an efficient electrohydrogen catalyst, and specifically employs the following technical approach.

[0025] S1. Technology to improve the catalytic efficiency of energy conversion equipment (water electrolytic cells and hydrogen fuel cells). Renewable energy drives a water electrolytic cell to decompose water into high-purity hydrogen and oxygen gases, converting the energy of renewable energy into chemical energy. Subsequently, a hydrogen fuel cell uses the hydrogen and oxygen gases to undergo an electrochemical reaction, synthesizing water again and releasing electrical energy, thus achieving a further conversion of chemical energy into electrical energy in the hydrogen gas. This process is completely independent of fossil fuels and effectively avoids the carbon emission problems of conventional energy conversion, so the renewable energy-water-hydrogen energy system provides an important technological pathway to promote the transition of existing energy systems to a low-carbon state.

[0026] On the other hand, the processes of hydrogen generation by water electrolysis cells and electricity generation by hydrogen fuel cells both depend on four types of electrode electrochemical reactions that occur on the surface of the catalyst, and are specifically as shown in the following equation.

[0027] Hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in acidic electrolytes: [ka] Hydrogen evolution (HER) and oxygen evolution (OER) reactions in alkaline electrolytes: [ka] Hydrogen oxidation reaction (HOR) and oxygen reduction reaction (ORR) in acidic electrolytes: [ka] Hydrogen oxidation (HOR) and oxygen reduction (ORR) reactions in alkaline electrolytes: [ka]

[0028] To effectively catalyze the four types of electrochemical reactions, it is necessary to overcome high energy barriers. Taking the water splitting reaction in a water electrolytic cell as an example, under ideal conditions, the Gibbs free energy of the water splitting reaction is 237.2 kJ / mol. -1 The driving potential is 1.23V. However, in the actual reaction process, due to factors such as ohmic resistance, concentration difference resistance, and activation resistance, the reaction requires an additional potential to break the HO covalent bond in the water molecule and drive the reaction to occur.

[0029] Furthermore, an analysis of these three resistances reveals that ohmic resistance primarily stems from obstructions to electron transport by the cathode and anode materials and external conductors, as well as obstructions to ion transport by the electrolyte. This problem can be effectively addressed by improving the conductivity of the electrode materials and electrolyte, or by reducing the distance between the two plates.

[0030] Concentration difference resistance can be reduced by increasing the pressure of the gaseous reactants or the concentration of the liquid electrolyte. Therefore, while ohmic resistance and concentration difference resistance are mainly determined by the selection of electrode material and electrolyte, as well as the operating conditions of the equipment, more than 60% of the energy barrier of an electrochemical reaction originates from activation resistance. Thus, the catalytic performance of the catalyst is particularly important in driving the kinetic process of an electrochemical reaction.

[0031] However, the catalysts currently commonly used in electrohydrogen bonding technology are mainly precious metals such as platinum group metals and iridium-based metals. These precious metals are scarce and expensive, severely limiting the large-scale adoption and commercialization of electrohydrogen bonding technology. Obtaining a catalyst that is cost-effective and can effectively reduce the activation energy of the reaction is a crucial challenge for the development of electrohydrogen bonding technology.

[0032] In this embodiment, a transition metal catalyst is processed using a combination of defect engineering and interface engineering to obtain a composite catalyst, thereby obtaining a transition metal catalyst that is competitive in both cost and catalytic performance. This results in a water electrolytic cell and a hydrogen fuel cell with efficient catalytic performance, providing technical support for the efficient conversion and storage of renewable energy. Here, the transition metal catalysts are two types of transition metal catalysts, Fe and Ni, which are abundant in storage capacity and environmentally friendly.

[0033] This process is as follows:

[0034] First, defect engineering optimizes the electron distribution within Fe and Ni by intentionally introducing disordered structures into the complete Fe and Ni lattices, thereby disrupting the long-periodity of the matrix. In this example, defect engineering disrupts the electron distribution within the Fe and Ni lattices by using a combination of three-dimensional defects: vacancies, screw dislocations, and stacking faults. Specifically, vacancies are point defects, screw dislocations are line defects, and stacking faults are planar defects. By incorporating these three-dimensional defects, additional band alignment between the catalyst and reactants is effectively induced, reducing resistance to electron transfer and facilitating the movement and transport of electrons and charges during the electrochemical reaction. Furthermore, the incorporation of three-dimensional defects shifts the d-band centers of Fe and Ni, changing the position of the center of gravity of the electron energy of the d-orbitals. This promotes the interaction between the catalyst's d-orbitals and the reactant's electron orbitals, facilitating the formation of new bonds, altering the bond energy of key intermediates, and contributing to the adsorption and desorption of reaction intermediates. Additionally, the combined use of three-dimensional defects significantly reduces the band gap of the Fe and Ni electrocatalyst, lowering the energy barrier when electrons transition from the valence band to the conduction band. This allows electrons in the Fe and Ni catalyst's d-orbitals to participate more readily in electrode reactions, improving electron conduction efficiency and accelerating the dynamic process of the electrochemical reaction. Finally, defect incorporation alters the lattice structure of Fe and Ni, exposing more active sites, increasing the density of active sites, and effectively improving the intrinsic activity of the transition metal catalyst.

[0035] Next, the electrocatalytic activity of the Fe and Ni transition metal catalysts is improved by incorporating defects in three dimensions. In this embodiment, interface engineering is incorporated on top of defect engineering to further optimize the catalytic performance of the electrohydrogen bonding technology from a different angle. In this embodiment, interface engineering involves transporting defect-engineered Fe and Ni precursors to the base surface along with N2 by chemical vapor deposition (CVD), and promoting the decomposition and deposition of the Fe and Ni precursors on the base surface at a high temperature of nearly 1000°C, further forming a multilayer porous Fe-Ni heterogeneous structure (HS).

[0036] Both Fe and Ni possess unfilled d-electron orbitals and unpaired electrons, resulting in high electron density. This allows them to interact with the electron clouds of reactants or key reaction intermediates, providing ample electron sites for forming coordinate bonds, optimizing adsorption and desorption energies during the reaction process, and promoting electron flow between reactants and products. More importantly, differences in band arrangement and electronegativity between the different crystalline phases of Fe and Ni induce electron modulation on the surface of the Fe-Ni heterostructure, leading to significant electron effects. Furthermore, the atomic orbitals of Fe and Ni overlap and collide with each other during heterointerface formation, mutually filling bonded and antibonded states to form interfacial bonds, inevitably affecting the local electron arrangement. Simultaneously, because the lattice constants of Fe and Ni do not perfectly match, lattice strain occurs at the heterointerface during pseudo-growth of the crystal, directly interfering with the geometric structure and coordination environment of the active site. As described above, the electronic effects, interfacial bonding, lattice strain, and synergistic effects of interfacial engineering each optimize the electron arrangement of the active site and the Fermi level of the catalyst to different degrees, increasing the specific surface area of ​​the catalyst, significantly improving the internal activity and conductivity of the transition metal catalyst, and increasing the density of the active site.

[0037] Finally, in this embodiment, to avoid the dissolution and aggregation of the active component due to electrolyte reactions in acidic / alkaline electrolytes on the surface of the Fe-Ni heterostructure, which would lead to catalyst deactivation and shortened lifespan, this embodiment effectively prevents oxidative corrosion of the Fe-Ni composite catalyst in strong acidic or strong alkaline environments by covering the surface of the Fe-Ni heterostructure with a carbon material coating using a solvothermal synthesis method, thereby ensuring high activity and stability of the Fe-Ni heterostructure and extending its lifespan.

[0038] S2. Use the above composite catalyst in a water electrolytic cell and a hydrogen fuel cell, and construct high-resolution models of the water electrolytic cell and the hydrogen fuel cell, respectively. By using the improved Fe-Ni composite catalyst in water electrolytic cells and hydrogen fuel cells, the output performance of electro-hydrogen bonding technology is significantly improved, the conversion efficiency of electricity-hydrogen and hydrogen-electricity is greatly enhanced, and electro-hydrogen bonding technology with efficient catalytic performance is obtained.

[0039] First, the output characteristic model of the water electrolysis cell is as shown in the following equation.

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[0041] Next, the power characteristic model for a hydrogen fuel cell is as shown in the following equation.

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[0043] Furthermore, this embodiment fully demonstrates the flexibility of the water electrolytic cell and the hydrogen fuel cell, specifically as shown in the following equation.

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[0047] In this embodiment, there are three types of water electrolyzers: alkaline water electrolyzer (AEL), proton exchange membrane water electrolyzer (PEMEL), and solid oxide water electrolyzer (SOEL). There are four types of hydrogen fuel cells: alkaline hydrogen fuel cell (AFC), proton exchange membrane hydrogen fuel cell (PEMFC), solid oxide hydrogen fuel cell (SOFC), and molten carbonate hydrogen fuel cell (MCFC).

[0048] As described above, this embodiment constructs an output characteristic model and a flexibility representation model of the electro-hydrogen bonding technology, and the electro-hydrogen conversion efficiency in the model.

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[0049] S3, Construction of a multi-energy flow coupled collaborative optimization structure To ensure the efficient operation of a multi-energy flow coupling system and to fully realize the cooperative effects between dissimilar energy sources, the system needs to include multiple types of energy storage technologies and other energy conversion technologies to ensure the operational stability and reliability of the energy supply of the multi-energy flow coupling system. Accordingly, this embodiment constructs a multi-energy flow coupling model with energy storage equipment based on the high-definition model of the electro-hydrogen coupling technology, and creates a multi-energy flow coupling cooperative optimization structure with the goal of minimizing total annual costs, while being constrained by reserves, carbon emissions, renewable energy allocation criteria, and the real-time balance of electricity, heat, and hydrogen supply and demand power.

[0050] In this embodiment, renewable energy includes wind energy and light energy, and is specifically modeled as follows.

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[0051] As shown in Figure 2, in order to ensure the reliability of a multi-energy flow coupled system, it is necessary to integrate various energy storage devices into the system, such as hydrogen storage vessels (HSVs), thermal storage tanks (TSTs), and battery energy storage devices (BES), to respond to the variability of renewable energy, to fully utilize their regulatory functions, to ensure supply and demand balance at any given time, to stabilize the system output, and to further improve the system's robustness when faced with power load perturbations.

[0052] Hydrogen storage container model:

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[0053] Heat storage tank model:

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[0054] Electrical storage equipment models:

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[0055] At the same time, the electrical storage equipment needs to provide instantaneous reserve power, which is modeled as follows:

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[0056] Furthermore, in order to ensure that the multi-energy flow coupling system can maintain a balance between supply and demand even when the need for heat load increases in winter, the present invention incorporates an electric heating device into the system, and the model is as follows.

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[0057] Furthermore, when hydrogen gas generated in a water electrolysis cell enters a hydrogen storage container, in order to maximize the storage density of the hydrogen gas within a limited volume, the hydrogen storage container needs to compress the hydrogen gas. Therefore, the present invention provides a compressor model and explains this process in detail.

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[0059] Furthermore, the optimal capacity of each energy conversion device and energy storage device must satisfy the following constraints.

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[0060] In this embodiment, as shown in Figure 1, the model must satisfy the following constraints in order to achieve ordered complementary coupling between different energies in the system and efficient cooperative operation between each device.

[0061] Real-time balance of electricity, heat, and hydrogen supply and demand:

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[0062] Reserve constraint: [Math] wherein, [Math] represents the load reserve capacity, [Math] respectively represent the prediction errors of the wind power equipment unit and the solar power equipment unit.

[0063] Carbon emission constraint: [Math]

[0064] wherein, e Grid represents the carbon emission coefficient, A EM represents the maximum allowable value of carbon emission, S EM represents the carbon emission target deficit.

[0065] Renewable energy allocation criterion: [Math] [Math] However, Π RPS This represents the renewable energy allocation standard, S RE This represents the shortfall in the renewable energy allocation criteria.

[0066] In this embodiment, the goal is to minimize the total annual cost (TAC), which includes the investment cost of each type of equipment, operation and maintenance costs, grid electricity purchase costs, and penalty costs. At the same time, in this embodiment, revenue from selling electricity to the grid is used as the source of revenue, specifically as follows:

[0067]

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[0068] The formula for calculating the Capital Recovery Factor (CRF) is as follows:

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[0069] The cost of purchasing electricity and the revenue from selling electricity are as follows:

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[0070] Penalty cost:

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[0071] S4, Output of Optimal Capacity Configuration Strategy Operating data and cost data are acquired, input into a multi-energy flow coupled collaborative optimization structure, solved, and an optimal capacity configuration strategy is output.

[0072] The system acquires time-of-day electricity purchase prices and time-of-day electricity prices in the optimization area, as well as operating and cost data for wind power equipment units, solar power generation equipment units, different types of water electrolyzers and hydrogen fuel cells, compressors, and electric heating devices, as input parameters for a multi-energy flow coupled collaborative optimization structure. This data is then solved using a commercially available solver to obtain a scheme for the optimal capacity configuration and type selection combinations for each type of equipment unit, providing model support for subsequent real-time scheduling of the equipment units. During the scheduling phase, dynamic parameters such as fluctuations in wind and solar resources on the power source side, the storage status of electricity, heat, and hydrogen on the energy storage side, and changes in the load needs for electricity, heat, and hydrogen on the load side are monitored in real time. This helps energy aggregators formulate optimal scheduling plans and determine the optimal real-time output for each type of equipment unit and the optimal energy replenishment / release strategy for energy storage equipment, effectively addressing real-time uncertainties on the power source, storage, and load sides.

[0073] Example 2 This embodiment provides a capacity optimization system for a multi-energy flow coupled system based on an efficient electrohydrogen catalyst, and the system specifically provides: A catalyst efficiency improvement module configured to obtain a composite catalyst by processing a transition metal catalyst using defect engineering and interface engineering, An electro-hydrogen coupling model construction module is configured to use the aforementioned composite catalyst in a water electrolytic cell and a hydrogen fuel cell, and to construct high-resolution models of the water electrolytic cell and the hydrogen fuel cell, respectively. A multi-energy flow coupled collaborative optimization structure creation module is configured to create a multi-energy flow coupled collaborative optimization structure based on high-resolution models of water electrolyzers and hydrogen fuel cells, using energy storage equipment to construct a multi-energy flow coupled model, with constraints of reserve, carbon emissions, renewable energy allocation criteria, and real-time balance of electricity, heat, and hydrogen supply and demand power, aiming to minimize total annual costs. It includes a strategy output module configured to acquire operating data and cost data, input them into a multi-energy flow coupled collaborative optimization structure, solve the problem, and output an optimal capacity configuration strategy.

[0074] The specific implementation of the module in this embodiment will not be described in detail here, as it will refer to the steps of the capacity optimization method for a multi-energy flow coupled system based on an efficient electrohydrogen catalyst described in Example 1.

[0075] The above embodiments are merely illustrative of some embodiments of the present invention, and although the descriptions are specific and detailed, they should not be understood as limiting the scope of the invention. Those skilled in the art should note that all variations and improvements that can be made without departing from the concept of the present invention are all included within the scope of protection of the present invention. Accordingly, the scope of protection of the present invention should be in accordance with the appended claims.

Claims

1. A computer-based method for optimizing the capacity of an efficient electro-hydrogen catalyst-based multi-energy flow coupling system, A step of obtaining a composite catalyst by treating a transition metal catalyst with defect engineering and interface engineering, The steps include using the aforementioned composite catalyst in a water electrolytic cell and a hydrogen fuel cell, and constructing high-resolution models of the water electrolytic cell and the hydrogen fuel cell, respectively. Based on high-resolution models of water electrolyzers and hydrogen fuel cells, a multi-energy flow coupling model is constructed using energy storage equipment. The constraints include reserve, carbon emissions, renewable energy allocation criteria, and the real-time balance of electricity, heat, and hydrogen supply and demand, with the goal of minimizing total annual costs, and a multi-energy flow coupling collaborative optimization structure is created. The process involves taking operational data and cost data as input to a multi-energy flow coupled collaborative optimization structure, solving it, and outputting an optimal capacity configuration strategy. A method for optimizing the capacity of an efficient electrohydrogen catalyst-based multi-energy flow coupling system, characterized by including the following:

2. A method for optimizing the capacity of a multi-energy flow coupled system based on an efficient electrohydrogen catalyst according to claim 1, characterized in that the defect engineering incorporates an irregular structure into the complete lattice of the transition metal catalyst, the defect engineering includes three-dimensional defects: vacancy defects, helical dislocations, and stacking faults, and the interface engineering causes a multilayer porous heterogeneous heterostructure to be formed on the transition metal catalyst by chemical vapor deposition.

3. The high-resolution model of the aforementioned water electrolytic cell is a model of the output characteristics of the water electrolytic cell, and specifically, [Number 130] [Number 131] However, [Number 132] This represents the hourly driving power required for the nth type of water electrolysis cell. [Number 133] This represents the rated power of the nth type of water electrolysis cell. [Number 134] This represents the minimum operating limit for the nth type of water electrolysis cell, where n represents the type of water electrolysis cell. [Number 135] This represents the amount of hydrogen generated per hour by the nth type of water electrolysis cell. [Number 136] This represents the electricity-to-hydrogen conversion efficiency of the nth type of water electrolysis cell, LCVH. ２ A method for optimizing the capacity of a multi-energy flow coupled system based on an efficient electrohydrogen catalyst according to claim 1, characterized in that represents the lower heating value of hydrogen gas.

4. The aforementioned high-resolution model of the hydrogen fuel cell is a power characteristic model of the hydrogen fuel cell, and specifically, [Number 137] [Number 138] However, [Number 139] This represents the amount of electricity generated per hour by the m-th type of hydrogen fuel cell. [Number 140] This represents the hourly hydrogen consumption of the m-th type of hydrogen fuel cell. [Number 141] The value represents the hydrogen-to-electricity conversion efficiency of the m-th type of hydrogen fuel cell, where m represents the type of hydrogen fuel cell. [Number 142] This represents the amount of heat generated per hour by the m-th type of hydrogen fuel cell. [Number 143] This represents the heat conversion efficiency of the m-th type of hydrogen fuel cell. [Number 144] The method for optimizing the capacity of a multi-energy flow coupled system based on an efficient electrohydrogen catalyst according to claim 1, characterized in that represents the dissipation rate of the m-th type of hydrogen fuel cell.

5. A method for optimizing the capacity of an efficient electro-hydrogen catalyst-based multi-energy flow coupling system according to claim 1, characterized in that a multi-energy flow coupling model is constructed using energy storage equipment, specifically including a renewable energy model, a hydrogen storage container model, a heat storage tank model, an electric storage equipment model, an electric heating device model, and a compressor model, based on a high-resolution model of a water electrolytic cell and a high-resolution model of a hydrogen fuel cell.

6. The method for optimizing the capacity of a multi-energy flow coupled system based on an efficient electrohydrogen catalyst according to claim 1, characterized in that the minimum total annual cost is the sum of investment costs, operation and maintenance costs, grid electricity purchase costs, and penalty costs minus grid electricity sales revenue.

7. A method for optimizing the capacity of an efficient electrolytic hydrogen catalyst-based multi-energy flow coupling system according to claim 1, characterized in that the water electrolytic cell includes an alkaline water electrolytic cell, a proton exchange membrane water electrolytic cell, and a solid oxide water electrolytic cell, and the hydrogen fuel cell includes an alkaline hydrogen fuel cell, a proton exchange membrane hydrogen fuel cell, a solid oxide hydrogen fuel cell, and a molten carbonate hydrogen fuel cell.

8. A catalyst efficiency improvement module configured to obtain a composite catalyst by processing a transition metal catalyst using defect engineering and interface engineering, An electro-hydrogen coupling model construction module is configured to use the aforementioned composite catalyst in a water electrolytic cell and a hydrogen fuel cell, and to construct high-resolution models of the water electrolytic cell and the hydrogen fuel cell, respectively. A multi-energy flow coupled collaborative optimization structure creation module is configured to create a multi-energy flow coupled collaborative optimization structure based on high-resolution models of water electrolyzers and hydrogen fuel cells, using energy storage equipment to construct a multi-energy flow coupled model, with constraints of reserve, carbon emissions, renewable energy allocation criteria, and real-time balance of electricity, heat, and hydrogen supply and demand power, aiming to minimize total annual costs. A strategy output module is configured to acquire operating data and cost data, input them into a multi-energy flow coupled collaborative optimization structure, solve the problem, and output an optimal capacity configuration strategy. A capacity optimization system for a multi-energy flow coupling system based on an efficient electrohydrogen catalyst, characterized by including the following:

9. A computer-readable storage medium in which a program is stored, wherein when the program is executed by a processor, the steps of the capacity optimization method for a multi-energy flow coupling system based on an efficient electrohydrogen catalyst as described in any one of claims 1 to 7 are realized.

10. An electronic device comprising memory, a processor, and a program stored in the memory and executable in the processor, wherein when the processor executes the program, a step of the capacity optimization method for a multi-energy flow coupling system based on an efficient electrohydrogen catalyst as described in any one of claims 1 to 7 is realized.

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