Multi-energy flow coupling system capacity optimization method and system based on efficient electro-hydrogen catalysis

Abstract

The invention relates to a multi-energy flow coupling system capacity optimization method and system based on efficient electro-hydrogen catalysis, and belongs to the technical field of high-proportion new energy power system planning, and the method comprises the steps: processing a transition metal catalyst through defect engineering and interface engineering, and constructing refined models after processing; based on the constructed refined model, a multi-element energy flow coupling model is constructed in combination with energy storage equipment, and a multi-element energy flow coupling collaborative optimization framework is constructed by taking reserve, carbon emission and renewable energy quota standards and real-time balance of electricity, heat and hydrogen supply and demand power as constraint conditions and taking minimization of annual total cost as a target; and acquiring operation data and cost data, inputting the operation data and the cost data into the multi-element energy flow coupling collaborative optimization architecture, solving the operation data and the cost data, and outputting an optimal capacity configuration strategy. The catalytic efficiency of the electro-hydrogen coupling technology is improved, and deep fusion of hydrogen energy and an existing power system is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of high-proportion new energy power system planning, and in particular to a method and system for optimizing the capacity of a multi-energy flow coupling system based on efficient electric hydrogen catalysis. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] At present, the global energy system is still dominated by fossil energy, and the greenhouse gases emitted by its combustion pose a serious threat to the environment and climate. Against this background, renewable energy sources such as wind power and solar energy have developed rapidly. However, with the sharp increase in installed capacity and grid-connected capacity of renewable energy power generation, the grid's carrying capacity is facing huge challenges, while the problems of wind and solar power abandonment and reduced utilization of new energy are becoming more serious. Hydrogen energy has gradually become a highly-regarded energy carrier due to its flexibility, high energy density, abundant sources, long-term storage and cross-space transportation. In order to achieve effective synergy between hydrogen energy and the existing power system (electricity-hydrogen coupling), relevant technicians have proposed the concept of a multi-energy flow coupling system.

[0004] However, existing electric-hydrogen coupling technologies, such as water electrolyzers and hydrogen fuel cells, still rely mainly on noble metal catalysts (such as platinum-based catalysts and iridium-based catalysts). Such catalyst materials are scarce, expensive, and have poor electrocatalytic efficiency. In addition, the existing multi-energy flow coupling system fails to fully reflect the flexibility of electric-hydrogen coupling technology in the modeling process, and cannot fully tap the potential of electric-hydrogen coupling technology in solving the problems of wind and solar power abandonment. It can be seen that the above-mentioned technical bottlenecks restrict the deep integration of hydrogen energy with the existing power system. Therefore, how to improve the catalytic efficiency of the existing electric-hydrogen coupling technology, and at the same time carry out refined modeling of the electric-hydrogen coupling technology, fully reflect the flexibility of the electric-hydrogen coupling technology, and realize efficient collaborative planning of the multi-energy flow coupling system has become an urgent problem to be solved. Summary of the invention

[0005] In order to solve the above problems, the present invention proposes a capacity optimization method and system for a multi-energy flow coupling system based on efficient electric hydrogen catalysis. By introducing defect engineering and interface engineering, an electric hydrogen coupling technology with efficient catalytic performance is obtained; at the same time, a refined model is constructed, and a multi-energy flow coupling model is constructed based on this model, and a multi-energy flow coupling collaborative optimization architecture is built. The present invention improves the catalytic efficiency of the electric hydrogen coupling technology and realizes the deep integration of hydrogen energy with the existing power system.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for optimizing the capacity of a multi-energy flow coupling system based on efficient electric hydrogen catalysis, comprising: Defect engineering and interface engineering are used to treat transition metal catalysts to obtain composite catalysts; The composite catalyst is used in a water electrolysis cell and a hydrogen fuel cell, and refined models of the water electrolysis cell and the hydrogen fuel cell are constructed respectively; Based on the refined models of water electrolyzers and hydrogen fuel cells, a multi-energy flow coupling model is constructed in combination with energy storage equipment. With the constraints of reserves, carbon emissions, renewable energy quota standards, and real-time balance of electricity, heat, and hydrogen supply and demand, and the goal of minimizing the total annual cost, a multi-energy flow coupling collaborative optimization architecture is built; Obtain operation data and cost data, input them into the multi-energy flow coupling collaborative optimization framework and solve them, and output the optimal capacity configuration strategy.

[0007] A further technical solution is that the defect engineering introduces an irregular structure into the perfect lattice of the transition metal catalyst, and the defect engineering includes defects in three dimensions, namely: vacancy defects, screw dislocations, and stacking faults; the interface engineering is to use chemical vapor deposition to form a multi-layer porous heterogeneous heterogeneous structure of the transition metal catalyst.

[0008] In a further technical solution, the refined model of the water electrolysis cell is an output characteristic model of the water electrolysis cell, specifically: ; ;in, represents the hourly driving electric power required by the n-th water electrolysis cell; It represents the rated power of the nth water electrolysis cell; Indicates the minimum limit of the operation of the nth water electrolysis cell; n indicates the type of water electrolysis cell; represents the hourly hydrogen production of the nth water electrolysis cell; represents the electricity-to-hydrogen conversion efficiency of the nth water electrolyzer; Indicates the lower heating value of hydrogen.

[0009] In a further technical solution, the refined model of the hydrogen fuel cell is an output characteristic model of the hydrogen fuel cell, specifically: ; ;in, represents the hourly power generation of the mth hydrogen fuel cell; Indicates the hourly hydrogen consumption of the mth hydrogen fuel cell; represents the hydrogen-electricity conversion efficiency of the mth hydrogen fuel cell; m represents the type of hydrogen fuel cell; represents the hourly heat production of the mth hydrogen fuel cell; represents the thermal conversion efficiency of the mth hydrogen fuel cell; represents the dissipation rate of the mth hydrogen fuel cell.

[0010] A further technical solution is to construct a multi-element energy flow coupling model based on the refined models of water electrolyzers and hydrogen fuel cells combined with energy storage equipment, including: renewable energy model, hydrogen storage tank model, heat storage tank model, power storage equipment model, electric heating device model and compressor model.

[0011] According to a further technical solution, the minimized annual total cost is the sum of the investment cost, operation and maintenance cost, main grid electricity purchase cost and penalty cost minus the main grid electricity sales revenue.

[0012] According to a further technical solution, the water electrolysis cell includes: an alkaline water electrolysis cell, a proton exchange membrane water electrolysis cell and a solid oxide water electrolysis cell; 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.

[0013] In a second aspect, the present invention provides a capacity optimization system for a multi-energy flow coupling system based on high-efficiency electric hydrogen catalysis, comprising: The catalytic efficiency improvement module is configured to: process the transition metal catalyst by using defect engineering and interface engineering to obtain a composite catalyst; The electric-hydrogen coupling model building module is configured to: use the composite catalyst in a water electrolysis cell and a hydrogen fuel cell, and respectively build refined models of the water electrolysis cell and the hydrogen fuel cell; The module for building a multi-energy flow coupling collaborative optimization framework is configured as follows: Based on the refined models of water electrolysis cells and hydrogen fuel cells, a multi-energy flow coupling model is built in combination with energy storage equipment, and a multi-energy flow coupling collaborative optimization framework is built with the constraints of reserves, carbon emissions, renewable energy quota standards, and real-time balance of electricity, heat, and hydrogen supply and demand power, with the goal of minimizing the annual total cost; The strategy output module is configured to: obtain operation data and cost data, input and solve the multi-energy flow coupling collaborative optimization framework, and output the optimal capacity configuration strategy.

[0014] Compared with the prior art, the present invention has the following advantages and beneficial effects: 1. The present invention constructs a refined model of a water electrolyzer and a hydrogen fuel cell, which not only reflects the output characteristics of the electric-hydrogen coupling technology, but also fully demonstrates the flexibility of the electric-hydrogen coupling technology, and explores its synergistic and complementary relationship with the volatility and unpredictability of wind and solar renewable resources, so as to maximize the utilization of renewable energy, reduce the wind and solar power abandonment rate, and give full play to the function and potential of hydrogen energy as an energy carrier.

[0015] 2. The present invention combines defect engineering and interface engineering and applies them to two transition metal catalysts, Fe and Ni, which are abundant and environmentally friendly, to obtain transition metal catalysts that are competitive in terms of cost and catalytic performance to obtain water electrolysis cells and hydrogen fuel cells with high-efficiency catalytic performance, providing technical support for the efficient conversion and storage of new energy power generation. After the modified Fe-Ni composite catalyst is used in water electrolysis cells and hydrogen fuel cells, the output performance of the electric-hydrogen coupling technology has been greatly improved, and the conversion efficiency of electricity-hydrogen and hydrogen-electricity has been significantly improved, thereby obtaining an electric-hydrogen coupling technology with high-efficiency catalytic performance, laying a solid foundation for the deep integration of hydrogen energy with the existing power system.

[0016] 3. The multi-energy flow coupling collaborative optimization architecture built by the present invention integrates a variety of electric-hydrogen coupling technologies with high-efficiency catalytic performance, comprehensively coordinates three heterogeneous energy sources of electricity, heat and hydrogen, and a variety of energy conversion and storage equipment, and efficiently meets the user's diverse energy needs for electricity, heat and hydrogen, and realizes a stable function with great cost and environmental benefits. Importantly, the method proposed in the present invention clarifies the optimal combination and selection of electric-hydrogen conversion equipment under different working conditions, and provides precise guidance for energy scheduling and equipment configuration in different scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their description are used to explain the present invention but do not constitute a limitation of the present invention.

[0018] Figure 1 It is a logical structure diagram of the capacity optimization method of a multi-energy flow coupling system based on high-efficiency electric hydrogen catalysis in the present invention; Figure 2 It is a structural diagram of the comprehensive energy system of the present invention. DETAILED DESCRIPTION

[0019] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0020] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0021] Embodiment 1 like Figure 1 As shown, this embodiment proposes a capacity optimization method for a multi-energy flow coupling system based on efficient electric hydrogen catalysis, and specifically adopts the following technical solutions: S1. Technology for improving the catalytic efficiency of energy conversion equipment (water electrolyzers and hydrogen fuel cells).

[0022] Renewable energy drives the water electrolysis cell to decompose water into high-purity hydrogen and oxygen, converting the energy contained in renewable energy into chemical energy. Subsequently, the hydrogen fuel cell uses hydrogen and oxygen to undergo electrochemical reactions, resynthesizes water and releases electrical energy, thereby achieving further conversion of chemical energy in hydrogen into electrical energy. This process is completely independent of fossil fuels, effectively avoiding the carbon emission problem in traditional energy conversion. Therefore, the renewable energy-water-hydrogen energy system provides an important technical path for promoting the transformation of the existing energy system to a low-carbon one.

[0023] The process of producing hydrogen in water electrolysis cells and hydrogen fuel cells depends on four electrode electrochemical reactions occurring on the catalyst surface, as shown in the following formula: Hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in acidic electrolytes: ; Hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in alkaline electrolytes: ; Hydrogen oxidation reaction (HOR) and oxygen reduction reaction (ORR) in acidic electrolytes: ; Hydrogen oxidation reaction (HOR) and oxygen reduction reaction (ORR) in alkaline electrolytes: ; To effectively catalyze the four electrochemical reactions, it is necessary to overcome a high energy barrier. Taking the water splitting reaction in the water electrolysis cell as an example, under ideal conditions, the Gibbs free energy of the water splitting reaction becomes 237.2 kJ mol-1, and the driving potential is 1.23 V. However, in the actual reaction process, due to the existence of factors such as ohmic resistance, concentration difference resistance and activation resistance, the reaction requires additional potential to destroy the HO covalent bond in the water molecule to drive the reaction.

[0024] Further analysis of these three types of resistance shows that ohmic resistance mainly comes from the obstruction of the cathode and anode materials and external wires to the transmission of electron flow, and the obstruction of the electrolyte to the transmission of ion flow. This problem can be effectively addressed by improving the conductivity of the electrode material and electrolyte, or reducing the distance between the two plates. The concentration difference resistance can be reduced by increasing the pressure of the gas reactants or the concentration of the liquid electrolyte. Therefore, the ohmic resistance and concentration difference resistance mainly depend on the selection of the plate material and electrolyte and the equipment operating conditions, while more than 60% of the energy barrier in the electrochemical reaction comes from the activation resistance, which makes the catalytic performance of the catalyst particularly critical to the promotion of the electrochemical reaction kinetics process.

[0025] However, the catalysts commonly used in the current electric-hydrogen coupling technology are mostly noble metals, such as platinum group metals and iridium group metals. These noble metals are not only scarce but also expensive, which seriously restricts the large-scale promotion and commercialization of electric-hydrogen coupling technology. How to obtain a catalyst that is cost-effective and can effectively reduce the activation energy of the reaction has become an important challenge in the development of electric-hydrogen coupling technology.

[0026] In this embodiment, defect engineering and interface engineering are combined to process transition metal catalysts to obtain composite catalysts, and transition metal catalysts that are competitive in both cost and catalytic performance are obtained to obtain water electrolysis cells and hydrogen fuel cells with high catalytic performance, providing technical support for the efficient conversion and storage of new energy power generation, wherein the transition metal catalysts are two transition metal catalysts of Fe and Ni that are abundant in reserves and environmentally friendly.

[0027] The specific process is as follows: First, defect engineering breaks the long-range periodicity of its matrix by intentionally introducing irregular structures in the perfect lattice of Fe and Ni to optimize the electronic distribution state inside Fe and Ni. In this embodiment, defect engineering combines three dimensional defects: vacancies defects, screw dislocations, and stacking faults to disturb the distribution of electrons in Fe and Ni lattices. Specifically, vacancy defects belong to point defects, screw dislocations belong to line defects, and stacking faults belong to surface defects. By introducing these three dimensional defects, additional energy band alignment between catalysts and reactants is effectively induced, thereby reducing the resistance of electron transfer and promoting the transfer and transmission of electrons and charges during electrochemical reactions. At the same time, the introduction of three-dimensional defects causes the d-band centers of Fe and Ni to move, changes the position of the center of gravity of the d-orbital electron energy, promotes the interaction between the catalyst d-orbital and the reactant electron orbital, thereby making the formation of new bonds easier, and changes the binding energy of key intermediates, which is conducive to the adsorption and desorption of reaction intermediates. In addition, the combination of three-dimensional defects significantly reduces the band gap of Fe and Ni electrocatalysts, reduces the energy barrier of electrons jumping from the valence band to the conduction band, makes it easier for electrons in the d orbit of Fe and Ni catalysts to participate in the electrode reaction, improves the conduction efficiency of electrons, and promotes the kinetic process of electrochemical reactions. Finally, the introduction of defects changes the structure of Fe and Ni lattices, exposing more active sites, increasing the density of active sites, and effectively improving the intrinsic activity of transition metal catalysts.

[0028] Secondly, the introduction of three-dimensional defects improves the electrocatalytic activity of Fe and Ni transition metal catalysts respectively. In this embodiment, on the basis of defect engineering, interface engineering is introduced to further optimize the catalytic performance of the electric hydrogen coupling technology from different angles. In this embodiment, the interface engineering adopts chemical vapor deposition (CVD) to transport Fe and Ni precursors treated with defect engineering together with N2 to the substrate surface. The high temperature of nearly 1000°C promotes the decomposition and deposition of Fe and Ni precursors on the substrate surface, thereby forming a multi-layer porous Fe-Ni heterogeneous structure (HS).

[0029] Since both Fe and Ni have unfilled d electron orbitals and unpaired electrons, they have high electron density and can provide sufficient electron sites to interact with the electron cloud of reactants or key reaction intermediates and form coordination bonds with them, thereby optimizing the adsorption and desorption energy during the reaction and promoting the flow of electrons between reactants and products. More importantly, due to the differences in energy band arrangement and electronegativity between different crystal phases of Fe and Ni, electronic modulation on the surface of the Fe-Ni heterostructure is induced, forming a significant electronic effect; and the atomic orbitals of Fe and Ni will overlap and collide with each other when forming a heterogeneous interface, resulting in the mutual filling of bonding and anti-bonding states to form interface bonds, which inevitably affects the local arrangement of electrons; at the same time, since the lattice constants of Fe and Ni are not completely consistent, lattice strain will occur at the heterogeneous interface when the crystal is quasi-growing, directly interfering with the geometric structure and coordination environment of the active site. In summary, the electronic effects, interface bonding, lattice strain and synergistic effects caused by interface engineering have optimized the electronic arrangement of active sites and the Fermi level of the catalyst to varying degrees, increased the specific area of ​​the catalyst, significantly improved the intrinsic activity and conductivity of the transition metal catalyst, and increased the density of active sites.

[0030] Finally, in order to avoid electrolyte reactions on the surface of the Fe-Ni heterostructure in acid / alkaline electrolytes, which would cause the active components to be dissolved and agglomerated, thus passivating the catalyst and reducing its lifespan, this embodiment used a solvent thermal synthesis method to coat a layer of carbon material coating on the surface of the Fe-Ni heterostructure, thereby effectively preventing oxidative corrosion of the Fe-Ni composite catalyst in a strong acid or alkaline environment, ensuring the high activity and stability of the Fe-Ni heterostructure and extending its lifespan.

[0031] S2. Use the above composite catalyst in a water electrolysis cell and a hydrogen fuel cell, and construct detailed models of the water electrolysis cell and the hydrogen fuel cell, respectively.

[0032] After using the modified Fe-Ni composite catalyst in water electrolyzers and hydrogen fuel cells, the output performance of the electric-hydrogen coupling technology has been greatly improved, and the electricity-to-hydrogen and hydrogen-to-electricity conversion efficiencies have been significantly improved, thereby obtaining an electric-to-hydrogen coupling technology with high-efficiency catalytic performance.

[0033] First, the output characteristic model of the water electrolysis cell is shown as follows: ; In the formula, represents the hourly driving electric power required by the n-th water electrolysis cell; It represents the rated power of the nth water electrolysis cell; It represents the lowest limit of the operation of the nth water electrolysis cell; n represents the type of water electrolysis cell, and the present invention has a total of N types of water electrolysis cells.

[0034] ; In the formula, represents the hourly hydrogen production of the nth water electrolysis cell; represents the electricity-to-hydrogen conversion efficiency of the nth water electrolyzer; Indicates the lower heating value of hydrogen.

[0035] Secondly, the output characteristic model of the hydrogen fuel cell is shown as follows: ; In the formula, represents the hourly power generation of the mth hydrogen fuel cell; Indicates the hourly hydrogen consumption of the mth hydrogen fuel cell; represents the hydrogen-electricity conversion efficiency of the mth hydrogen fuel cell; m represents the type of hydrogen fuel cell, and there are M types of hydrogen fuel cells in total.

[0036] ; In the formula, represents the hourly heat production of the mth hydrogen fuel cell; represents the thermal conversion efficiency of the mth hydrogen fuel cell; represents the dissipation rate of the mth hydrogen fuel cell.

[0037] Next, this embodiment fully demonstrates the flexibility of the water electrolysis cell and the hydrogen fuel cell, as shown in the following formula: ; , ; In the formula, Represents a water electrolyzer or a hydrogen fuel cell t Online capacity at any given moment; Represents a water electrolyzer or a hydrogen fuel cellt The startup capacity at the moment; Represents a water electrolyzer or a hydrogen fuel cell t Shutdown capacity at the moment; Represents the total investment capacity of the water electrolyzer or hydrogen fuel cell; express N Water electrolysis cell and M A collection of hydrogen fuel cells.

[0038] ; In the formula, Represents a water electrolyzer or a hydrogen fuel cell t Real-time power consumption / production at all times; , They represent the lower and upper output limits of a water electrolyzer or a hydrogen fuel cell, respectively.

[0039] ; ; In the formula, , Respectively represent the startup ramp limit and shutdown ramp limit of the water electrolyzer or hydrogen fuel cell; , They represent the up-ramp limit and down-ramp limit of the water electrolyzer or hydrogen fuel cell respectively.

[0040] ; ; In the formula, , Respectively represent the minimum on time and minimum off time of the water electrolyzer or hydrogen fuel cell; T Indicates the total planning time.

[0041] In this embodiment, there are three types of water electrolyzers, namely: alkaline water electrolyzer (AEL), proton exchange membrane water electrolyzer (PEMEL) and solid oxide water electrolyzer (SOEL); there are four types of hydrogen fuel cells, namely: 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).

[0042] In summary, this embodiment constructs an output characteristic model of the electric-hydrogen coupling technology and a flexibility characterization model, which is reflected in the electric-hydrogen conversion efficiency and hydrogen-to-electricity conversion efficiency The significant improvement has effectively narrowed the efficiency differences between the three water electrolyzers and four hydrogen fuel cells, and further highlighted the differences in flexibility constraints such as minimum on / off time and climbing restrictions caused by factors such as operating temperature between different water electrolyzers and hydrogen fuel cells. Through an in-depth characterization of the flexibility differences between different devices, the present invention further proposes a strategy for equipment selection in different working scenarios, that is, based on the performance of various types of water electrolyzers and hydrogen fuel cells under different working conditions, their adaptability is evaluated, and the type of equipment that best matches their specific scenario is selected based on the flexibility requirements of the system. This selection process not only optimizes the equipment configuration and gives full play to the efficiency advantages of the electric-hydrogen coupling equipment, but also ensures the reliability and stability of the system under various operating conditions.

[0043] S3. Construction of multi-energy flow coupling collaborative optimization architecture.

[0044] In order to ensure the efficient operation of the multi-energy flow coupling system and give full play to the synergy between heterogeneous energy sources, the system also needs to include a variety of energy storage technologies and other energy conversion technologies to ensure the operational stability and energy supply reliability of the multi-energy flow coupling system. Therefore, this embodiment builds a multi-energy flow coupling model based on the refined model of the aforementioned electric hydrogen coupling technology combined with energy storage equipment, and uses reserves, carbon emissions, renewable energy quota standards, and real-time balance of electricity, heat, and hydrogen supply and demand power as constraints, with the goal of minimizing the annual total cost, to build a multi-energy flow coupling collaborative optimization architecture.

[0045] In this embodiment, renewable energy includes wind energy and solar energy, and the specific modeling method is as follows: ; ; In the formula, , Represent wind turbines and photovoltaic units respectively t Real-time output at all times; , They represent the capacity factors at the moment when the wind resources and photovoltaic resources in the optimized area are characterized; , , , , , They represent the total capacity, newly built capacity and existing capacity of wind turbines and photovoltaic units in the optimization area respectively.

[0046] like Figure 2 As shown in the figure, in order to ensure the reliability of the multi-energy flow coupling system, it is necessary to integrate a variety of energy storage devices into the system, such as hydrogen storage vessel (HSV), thermal storage tank (TST) and battery energy storage (BES), so as to better cope with the volatility of renewable energy, give full play to its regulatory role, ensure the balance of supply and demand at any time, stabilize the system output, and further enhance the robustness of the system in the face of source and load disturbances.

[0047] Hydrogen storage tank model: ; ; , ≥0; ; ; ; ; In the formula, , Respectively represent hydrogen storage tanks t The amount of hydrogen charged and discharged at each moment; , Respectively represent the maximum charging / discharging power and maximum hydrogen storage capacity of the hydrogen storage tank; , , They represent the hydrogen filling rate, hydrogen discharge rate and self-loss rate of the hydrogen storage tank respectively; Indicates hydrogen storage tank t The hydrogen storage status at each moment; Indicates a time interval.

[0048] Thermal storage tank model: ; ; ≥0, ≥0; ; ; ; ; In the formula, , Respectively represent heat storage tank t The heat charge and release at all times; , They represent the maximum charging / discharging power and the maximum heat storage capacity of the heat storage tank respectively; , , They represent the heat charging rate, heat releasing rate and self-loss rate of the heat storage tank respectively; Indicates heat storage tank t Heat storage state at the moment.

[0049] Energy storage equipment model: ; ; ≥0, ≥0; ; ; ; At the same time, the power storage equipment needs to provide spinning reserve, which is modeled as follows: ; ; ; In the formula, , Respectively represent power storage devices t The amount of charge and discharge at each moment; , Respectively represent the maximum charge / discharge power and maximum storage capacity of the power storage device; , , They represent the charging rate, discharging rate and self-loss rate of the power storage device respectively; Indicates power storage equipment t The state of charge at the moment; Indicates power storage equipment t Spinning reserve available at all times.

[0050] In addition, in order to ensure that the multi-energy flow coupling system can still maintain a supply-demand balance when the heat load demand is large in winter, the present invention introduces an electric heating device into the system, and its model is as follows: ; In the formula, Indicates electric heating device t Real-time output thermal power at all times; Indicates electric heating device t Power consumption at all times; Indicates the energy conversion efficiency of the electric heating device.

[0051] In addition, when the hydrogen generated by the water electrolysis cell enters the hydrogen storage tank, in order to maximize the storage density of hydrogen within a limited volume, the hydrogen storage tank needs to compress the hydrogen. Therefore, the present invention provides a compressor model to describe this process in detail: ; In the formula, express t The power consumption of the compressor at all times; express t The air intake volume of the compressor at any moment; represents the specific heat capacity of hydrogen at constant pressure; Indicates the operating temperature of the compressor; Indicates the working efficiency of the compressor; , Respectively represent the inlet pressure and outlet pressure of the compressor; r Represents the isentropic index of hydrogen.

[0052] In addition, the optimized capacity of each energy conversion device and energy storage device must meet the following constraints: ; In the formula, Indicates that the device is t Real-time output at all times; Indicates that the device is t Online power at all times; , , Respectively represent the total capacity, newly built capacity and existing capacity of the equipment; Represents the collection of all energy conversion devices and energy storage devices in a multi-energy flow coupling system.

[0053] In this embodiment, if Figure 1 As shown in the figure, in order to achieve orderly complementary coupling between heterogeneous energy sources and efficient coordinated operation between various devices in the system, the model still needs to meet the following constraints: Real-time balance of electricity, heat and hydrogen supply and demand: ; ; ; In the formula, , , Respectively t The electrical load, thermal load and hydrogen load at the moment; , Respectively t The amount of electricity purchased from the main grid and the amount of electricity sold to the main grid at all times.

[0054] Reserve constraints: ; In the formula, Indicates the load reserve capacity; , Represent the prediction errors of wind turbines and photovoltaic units respectively.

[0055] Carbon emission constraints: ; In the formula, represents the carbon emission factor; Indicates the maximum permissible value of carbon emissions; Indicates the shortfall in carbon emission targets.

[0056] Renewable Portfolio Standards: ; = ; In the formula, represents the Renewable Portfolio Standard; Indicates the Renewable Energy Portfolio Standard shortfall.

[0057] In this embodiment, the goal is to minimize the total annual cost (TAC). TAC covers the investment cost of various equipment, operation and maintenance cost, main grid electricity purchase cost, and penalty cost. At the same time, the income from selling electricity to the main grid is used as the source of income, which is specifically expressed as follows: ; = ; = ; = ; ; ; ; ; + + ; + + ; + + ; In the formula, Indicates the device x Unit investment cost; Indicates the device x Fixed operation and maintenance costs; Indicates the device x variable operating costs; Indicates the device x startup cost.

[0058] The calculation formula of capital recovery factor (CRF) is as follows: ; In the formula, r represents the discount rate; Represents the lifetime of the multi-element energy flow coupling system.

[0059] The electricity purchase cost and electricity sales revenue are as follows: ; ; In the formula, , They respectively represent the time-of-use electricity purchase and sales prices.

[0060] Penalty cost: ; In the formula, represents the carbon tax in the planning area; Represents the renewable energy quota standard shortfall penalty cost.

[0061] S4. Optimal capacity configuration strategy output Obtain operation data and cost data, input them into the multi-energy flow coupling collaborative optimization framework and solve them, and output the optimal capacity configuration strategy.

[0062] The operation and cost data of time-of-use purchase, electricity price, wind turbines, photovoltaic units, different types of water electrolyzers and hydrogen fuel cells, compressors and electric heating devices in the optimization area are obtained as input parameters of the multi-energy flow coupling collaborative optimization framework, and the optimal capacity configuration and combination selection scheme of various units are obtained by using commercial solvers to provide model support for the real-time scheduling of subsequent units. In the scheduling stage, by real-time monitoring of dynamic parameters such as the fluctuation of wind and solar resources on the source side, the storage status of electric and thermal hydrogen on the energy storage side, and the changes in the electric and thermal hydrogen load demand on the load side, energy aggregators are assisted in formulating the optimal scheduling plan, determining the optimal real-time output of various units and the optimal charging and discharging strategy of energy storage equipment, so as to effectively deal with the real-time uncertainty of the source, storage and load sides.

[0063] Embodiment 2 This embodiment provides a multi-energy flow coupling system capacity optimization system based on high-efficiency electric hydrogen catalysis, which specifically includes the following modules: The catalytic efficiency improvement module is configured to: process the transition metal catalyst by using defect engineering and interface engineering to obtain a composite catalyst; The electric-hydrogen coupling model building module is configured to: use the composite catalyst in a water electrolysis cell and a hydrogen fuel cell, and respectively build refined models of the water electrolysis cell and the hydrogen fuel cell; The module for building a multi-energy flow coupling collaborative optimization framework is configured as follows: Based on the refined models of water electrolysis cells and hydrogen fuel cells, a multi-energy flow coupling model is built in combination with energy storage equipment, and a multi-energy flow coupling collaborative optimization framework is built with the constraints of reserves, carbon emissions, renewable energy quota standards, and real-time balance of electricity, heat, and hydrogen supply and demand power, with the goal of minimizing the annual total cost; The strategy output module is configured to: obtain operation data and cost data, input and solve the multi-energy flow coupling collaborative optimization framework, and output the optimal capacity configuration strategy.

[0064] The implementation of the specific modules in this embodiment refers to the steps of a method for identifying the type of transmission line loss described in Embodiment 1, and will not be described in detail here.

[0065] The above-described embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the attached claims.

Claims

1. A capacity optimization method for a multi-energy flow coupling system based on efficient electro-hydrogen catalysis, characterized in that: include: Defect engineering and interface engineering are used to treat transition metal catalysts to obtain composite catalysts; The composite catalyst is used in a water electrolysis cell and a hydrogen fuel cell, and refined models of the water electrolysis cell and the hydrogen fuel cell are constructed respectively; Based on the refined models of water electrolyzers and hydrogen fuel cells, a multi-energy flow coupling model is constructed in combination with energy storage equipment. With the constraints of reserves, carbon emissions, renewable energy quota standards, and real-time balance of electricity, heat, and hydrogen supply and demand, and the goal of minimizing the total annual cost, a multi-energy flow coupling collaborative optimization architecture is built; The operation data and cost data are used as inputs of the multi-energy flow coupling collaborative optimization framework and solved to output the optimal capacity configuration strategy.

2. The method for optimizing the capacity of a multi-energy flow coupling system based on efficient electric hydrogen catalysis according to claim 1, characterized in that: The defect engineering introduces an irregular structure into the perfect lattice of the transition metal catalyst, and the defect engineering includes defects in three dimensions, namely: vacancy defects, screw dislocations, and stacking faults; the interface engineering uses chemical vapor deposition to form a multi-layer porous heterogeneous structure of the transition metal catalyst.

3. The method for optimizing the capacity of a multi-energy flow coupling system based on efficient electric hydrogen catalysis according to claim 1, characterized in that: The refined model of the water electrolysis cell is an output characteristic model of the water electrolysis cell, specifically: ; ;in, represents the hourly driving electric power required by the n-th water electrolysis cell; It represents the rated power of the nth water electrolysis cell; Indicates the minimum limit of the operation of the nth water electrolysis cell; n indicates the type of water electrolysis cell; represents the hourly hydrogen production of the nth water electrolysis cell; represents the electricity-to-hydrogen conversion efficiency of the nth water electrolyzer; Indicates the lower heating value of hydrogen.

4. The method for optimizing the capacity of a multi-energy flow coupling system based on efficient electric hydrogen catalysis according to claim 1, characterized in that: The refined model of the hydrogen fuel cell is an output characteristic model of the hydrogen fuel cell, specifically: ; ;in, represents the hourly power generation of the mth hydrogen fuel cell; Indicates the hourly hydrogen consumption of the mth hydrogen fuel cell; represents the hydrogen-electricity conversion efficiency of the mth hydrogen fuel cell; m represents the type of hydrogen fuel cell; represents the hourly heat production of the mth hydrogen fuel cell; represents the thermal conversion efficiency of the mth hydrogen fuel cell; represents the dissipation rate of the mth hydrogen fuel cell.

5. The method for optimizing the capacity of a multi-energy flow coupling system based on efficient electric hydrogen catalysis according to claim 1, characterized in that: Based on the refined models of water electrolyzers and hydrogen fuel cells, a multi-element energy flow coupling model is constructed in combination with energy storage equipment, including: renewable energy model, hydrogen storage tank model, heat storage tank model, power storage equipment model, electric heating device model and compressor model.

6. The method for optimizing the capacity of a multi-energy flow coupling system based on efficient electric hydrogen catalysis according to claim 1, characterized in that: The minimized annual total cost is the sum of investment cost, operation and maintenance cost, main grid electricity purchase cost and penalty cost minus the main grid electricity sales income.

7. The method for optimizing the capacity of a multi-energy flow coupling system based on efficient electric hydrogen catalysis according to claim 1, characterized in that: The water electrolysis cell includes: an alkaline water electrolysis cell, a proton exchange membrane water electrolysis cell and a solid oxide water electrolysis cell; 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. Capacity optimization system of multi-energy flow coupling system based on efficient electric hydrogen catalysis, characterized in that: include: The catalytic efficiency improvement module is configured to: process the transition metal catalyst by using defect engineering and interface engineering to obtain a composite catalyst; The electric-hydrogen coupling model building module is configured to: use the composite catalyst in a water electrolysis cell and a hydrogen fuel cell, and respectively build refined models of the water electrolysis cell and the hydrogen fuel cell; The module for building a multi-energy flow coupling collaborative optimization framework is configured as follows: Based on the refined models of water electrolysis cells and hydrogen fuel cells, a multi-energy flow coupling model is built in combination with energy storage equipment, and a multi-energy flow coupling collaborative optimization framework is built with the constraints of reserves, carbon emissions, renewable energy quota standards, and real-time balance of electricity, heat, and hydrogen supply and demand power, with the goal of minimizing the annual total cost; The strategy output module is configured to: obtain operation data and cost data, input and solve the multi-energy flow coupling collaborative optimization framework, and output the optimal capacity configuration strategy.

9. A computer-readable storage medium having a program stored thereon, characterized in that: When the program is executed by a processor, the steps in the method for optimizing the capacity of a multi-energy flow coupling system based on efficient electric hydrogen catalysis as described in any one of claims 1 to 7 are implemented.

10. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps in the capacity optimization method of a multi-energy flow coupling system based on efficient electric hydrogen catalysis as described in any one of claims 1 to 7 are implemented.

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