Electrolytic hydrogen production optimal capacity configuration method

Abstract

The application provides an electrolytic hydrogen production optimal capacity configuration method, comprising the following steps: constructing an economic scheduling model of an electrolytic hydrogen system according to coupling constraints of the electrolytic hydrogen system; decomposing the economic scheduling model of the electrolytic hydrogen system into a power system operation model and a hydrogen energy system operation model by using an optimality condition decomposition algorithm; calculating carbon emissions of the power system operation model and the hydrogen energy system operation model; and determining electrolytic hydrogen production capacity configuration for minimizing the economic scheduling model of the electrolytic hydrogen system based on the carbon emissions and the golden section method. The application establishes a joint economic scheduling model of an electrolytic hydrogen system and decomposes and coordinates the joint economic scheduling model by using an optimality condition decomposition method, and determines electrolytic hydrogen production optimal capacity configuration by using the golden section method, thereby providing theoretical guidance for behavior decision-making for reducing carbon emissions of an electrolytic hydrogen system.

Description

Technical Field

[0001] This invention belongs to the field of integrated energy technology. Background Technology

[0002] As important secondary energy sources, the production of electricity and hydrogen generates significant carbon emissions. On the one hand, the power system's capacity to absorb renewable energy still needs improvement, with thermal power generation remaining the dominant mode of power generation, leading to substantial carbon emissions. On the other hand, current hydrogen production still relies on fossil fuel reforming and industrial byproducts, both of which are accompanied by high levels of carbon emissions. Therefore, reducing carbon emissions from electricity and hydrogen production is an urgent issue.

[0003] In recent years, the development of hydrogen electrolysis technology has provided a new solution for reducing carbon emissions from power systems and hydrogen energy systems. However, excessive hydrogen electrolysis will lead to increased carbon emissions from the power system: the energy structure of the power system is based on fossil fuels, and excessive hydrogen electrolysis may lead to the startup of high-carbon-emission thermal power units, thereby increasing carbon emissions from the hydrogen electrolysis system. Therefore, how to determine the capacity of hydrogen electrolysis that minimizes carbon emissions from the hydrogen electrolysis system remains to be studied. Summary of the Invention

[0004] The present invention aims to at least partially solve one of the technical problems in the related art.

[0005] Therefore, the purpose of this invention is to propose an optimal capacity configuration method for electrolytic hydrogen production, which is used to determine the capacity of electrolytic hydrogen production that can minimize carbon emissions from the electrolytic hydrogen production system.

[0006] To achieve the above objectives, a first aspect of the present invention provides a method for optimal capacity configuration in hydrogen production by electrolysis, comprising:

[0007] Based on the coupling constraints of the electric-hydrogen system, an economic scheduling model for the electric-hydrogen system is constructed.

[0008] The optimality condition decomposition algorithm is used to decompose the economic dispatch model of the electric-hydrogen system into a power system operation model and a hydrogen energy system operation model.

[0009] Calculate the carbon emissions of the power system operation model and the hydrogen energy system operation model, and determine the electrolysis hydrogen production capacity configuration that minimizes the economic dispatch model of the electric hydrogen system based on the golden section method according to the carbon emissions.

[0010] In addition, the optimal capacity configuration method for electrolytic hydrogen production according to the above embodiments of the present invention may also have the following additional technical features:

[0011] Furthermore, in one embodiment of the present invention, the step of constructing an economic dispatch model for the electric-hydrogen system based on the coupling constraints of the electric-hydrogen system includes:

[0012] Construct the objective function of the economic dispatch model for the electric-hydrogen system:

[0013]

[0014] The objective function mainly consists of two parts, the first part being the power system operating cost C. E The second part is the operating cost C of the hydrogen energy system. H ;Φ T It is a set of time periods; Φ E It is a collection of thermal power units; Φ H It is a collection of fossil fuel reformings; and These are the power generation of thermal power units and the hydrogen production from fossil fuel reforming, respectively. It is the cost coefficient of thermal power units; It is the cost coefficient for fossil fuel reforming;

[0015] The electro-hydrogen coupling constraint is as follows:

[0016]

[0017] in, It is hydrogen produced by electrolysis. It refers to the electrical energy consumed in the electrolysis of hydrogen production; HHV is the higher calorific value of hydrogen. It refers to the conversion efficiency of the electrolytic hydrogen production unit.

[0018] Furthermore, in one embodiment of the present invention, the step of decomposing the economic dispatch model of the electric-hydrogen system into a power system operation model and a hydrogen energy system operation model using an optimality condition decomposition algorithm includes:

[0019] Construct the objective function for the power system operation model:

[0020]

[0021] in, and These are the dual variables of the coupling constraint in electrolytic hydrogen production and the hydrogen production capacity of the electrolytic hydrogen production unit, respectively.

[0022] The node power balance constraints are as follows:

[0023]

[0024] in, and Φ m These are the sets of thermal power units, renewable energy sources, electrolytic hydrogen production units, and nodes connected to node m. It is the output of renewable energy; It is the electrical energy consumed in the electrolysis of hydrogen production; It is the electrical load of node m; It is the transmission power of line mn;

[0025] Among them, the power flow constraints of the power grid are:

[0026]

[0027] Where, θ m,t and θ n,t It is the phase angle between nodes m and n; This refers to the transmission capacity of the power transmission line mn;

[0028] Among them, the constraints for thermal power generation are:

[0029]

[0030] in, and These are the upper and lower limits of the output of thermal power units;

[0031] Among them, the constraints for renewable energy are:

[0032]

[0033] in, It is the predicted power of renewable energy;

[0034] The constraints for hydrogen production via electrolysis are as follows:

[0035]

[0036] in, It refers to the installed capacity of hydrogen production via electrolysis;

[0037] The boundary information constraints are as follows:

[0038]

[0039] in, It is the dual variable of the electro-hydrogen coupling constraint.

[0040] Furthermore, in one embodiment of the present invention, the step of decomposing the economic dispatch model of the electric-hydrogen system into a power system operation model and a hydrogen energy system operation model using an optimality condition decomposition algorithm includes:

[0041] Construct the objective function for the hydrogen energy system operation model:

[0042]

[0043] in, and These are the dual variables of the electro-hydrogen coupling constraint and the power consumption of the electrolysis hydrogen production unit, respectively.

[0044] The hydrogen balance constraint at the nodes is as follows:

[0045]

[0046] in, and These are the collections of fossil fuel reforming and electrolytic hydrogen production connected to node m; Ω I (mn) = m and Ω O (mn) = m are the sets of pipes with m as the input node and m as the output node, respectively; and These are the input and output hydrogen flow rates of pipe m and n, respectively. It is hydrogen produced by electrolysis; It is the hydrogen load at node m.

[0047] The pipeline flow constraint is as follows:

[0048]

[0049] Where, Φ L It is a collection of pipes; f mn,t This refers to the hydrogen flow rate in pipe mn; p m,t S is the hydrogen pressure at node m; mn It is a constant determined by the length, diameter, and temperature of the pipe mn; sgn(p m,t ,p n,t ) is a symbolic function representing the direction of hydrogen flow in pipe mn.

[0050] Among them, the constraints for hydrogen production from fossil fuel reforming are:

[0051]

[0052] in, and These are the upper and lower limits for hydrogen production from fossil fuel reforming.

[0053] The hydrogen pressure constraint is as follows:

[0054]

[0055] Where, p m,max and p m,min These are the upper and lower limits of the hydrogen pressure at node m.

[0056] The pipeline storage constraints are as follows:

[0057]

[0058]

[0059] Among them, F mn,t It is the amount of hydrogen stored in pipe mn; μ mn It is a constant determined by the length, diameter, and temperature of the hydrogen pipeline mn.

[0060] Furthermore, in one embodiment of the present invention, the step of decomposing the economic dispatch model of the electric-hydrogen system into a power system operation model and a hydrogen energy system operation model using an optimality condition decomposition algorithm includes:

[0061] The initial value of the installed capacity for electrolytic hydrogen production is set to 0. The sub-problems of the power system and the hydrogen energy system are optimized respectively, and the Lagrange multipliers are initialized.

[0062] Information is exchanged and boundary information is updated between the power system and the hydrogen energy system.

[0063] Based on the updated boundary information, the sub-problems of the power system and the hydrogen energy system are optimized respectively;

[0064] The algorithm is terminated if the boundary information meets the convergence condition; otherwise, the iteration continues.

[0065] Furthermore, in one embodiment of the present invention, determining the electrolysis hydrogen production capacity configuration that minimizes the economic dispatch model of the electro-hydrogen system based on the carbon emissions using the golden ratio method includes:

[0066] Initialize the electrolysis hydrogen production ratio of the electro-hydrogen system and set the convergence conditions;

[0067] The golden section method is used to select two electrolysis hydrogen production ratio values ​​within a given interval. If the difference between the two ratios is less than the convergence condition, the value is directly output.

[0068] If the difference between the two ratios is not less than the convergence condition, calculate the total carbon emissions of the electrolytic hydrogen production system under different electrolysis hydrogen production ratios and compare their magnitudes. Based on the results, assign values ​​to the endpoints of the interval to further narrow the interval of the electrolysis hydrogen production ratio and conduct a new round of iteration.

[0069] To achieve the above objectives, a second aspect of the present invention provides an optimal capacity configuration device for electrolytic hydrogen production, comprising the following modules:

[0070] The module is used to construct an economic scheduling model for the electric-hydrogen system based on the coupling constraints of the electric-hydrogen system.

[0071] The decomposition module is used to decompose the economic dispatch model of the electric-hydrogen system into an electric system operation model and a hydrogen energy system operation model using the optimal condition decomposition algorithm.

[0072] The calculation module is used to calculate the carbon emissions of the power system operation model and the hydrogen energy system operation model, and to determine the electrolysis hydrogen production capacity configuration that minimizes the economic dispatch model of the electric hydrogen system based on the golden section method according to the carbon emissions.

[0073] To achieve the above objectives, a third aspect of the present invention provides a computer device, characterized in that it includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements an optimal capacity configuration method for electrolytic hydrogen production as described above.

[0074] To achieve the above objectives, a fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements an optimal capacity configuration method for electrolytic hydrogen production as described above.

[0075] The proposed method for optimal capacity configuration of electrolytic hydrogen production in this invention first constructs an economic scheduling model of the electrolytic hydrogen system, considering the coupling constraints of the electrolytic hydrogen system; then, it uses an optimality condition decomposition method to decompose and coordinate the electrolytic hydrogen system; finally, it uses the golden section method to determine the electrolytic hydrogen production capacity configuration that minimizes the carbon emissions of the electrolytic hydrogen system; and it provides a simulation method for electrolytic hydrogen production capacity configuration that minimizes the carbon emissions of the electrolytic hydrogen system, providing theoretical guidance for behavioral decisions to reduce the carbon emissions of the electrolytic hydrogen system. Attached Figure Description

[0076] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0077] Figure 1 This is a schematic flowchart of an optimal capacity configuration method for electrolytic hydrogen production provided in an embodiment of the present invention.

[0078] Figure 2 The flowchart illustrates a simulation method for optimal capacity configuration of electrolytic hydrogen production based on collaborative optimization of an electro-hydrogen system, provided in an embodiment of the present invention.

[0079] Figure 3 This is a schematic flowchart of an optimal capacity configuration method for electrolytic hydrogen production provided in an embodiment of the present invention. Detailed Implementation

[0080] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0081] The optimal capacity configuration method for hydrogen production by electrolysis according to an embodiment of the present invention is described below with reference to the accompanying drawings.

[0082] Example 1

[0083] Figure 1 This is a schematic flowchart of an optimal capacity configuration method for electrolytic hydrogen production provided in an embodiment of the present invention.

[0084] like Figure 1 As shown, the optimal capacity configuration method for hydrogen production by electrolysis includes the following steps:

[0085] S101: Construct an economic scheduling model for the electric-hydrogen system based on the coupling constraints of the electric-hydrogen system;

[0086] S102: The optimal condition decomposition algorithm is used to decompose the economic dispatch model of the electric-hydrogen system into a power system operation model and a hydrogen energy system operation model.

[0087] S103: Calculate the carbon emissions of the power system operation model and the hydrogen energy system operation model, and determine the electrolysis hydrogen production capacity configuration of the minimum economic dispatch model of the electric hydrogen system based on the golden section method according to the carbon emissions.

[0088] Furthermore, in one embodiment of the present invention, an economic dispatch model for the electric-hydrogen system is constructed based on the coupling constraints of the electric-hydrogen system, including:

[0089] Construct the objective function of the economic dispatch model for the electric-hydrogen system:

[0090]

[0091] The objective function mainly consists of two parts, the first part being the power system operating cost C. E The second part is the operating cost C of the hydrogen energy system. H ;Φ T It is a set of time periods; Φ E It is a collection of thermal power units; Φ H It is a collection of fossil fuel reformings; and These are the power generation of thermal power units and the hydrogen production from fossil fuel reforming, respectively. It is the cost coefficient of thermal power units; It is the cost coefficient for fossil fuel reforming;

[0092] The electro-hydrogen coupling constraint is as follows:

[0093]

[0094] in, It is hydrogen produced by electrolysis. It refers to the electrical energy consumed in the electrolysis of hydrogen production; HHV is the higher calorific value of hydrogen. It refers to the conversion efficiency of the electrolytic hydrogen production unit.

[0095] Furthermore, in one embodiment of the present invention, an optimality condition decomposition algorithm is used to decompose the economic dispatch model of the electric-hydrogen system into a power system operation model and a hydrogen energy system operation model, including:

[0096] Construct the objective function for the power system operation model:

[0097]

[0098] in, and These are the dual variables of the coupling constraint in electrolytic hydrogen production and the hydrogen production capacity of the electrolytic hydrogen production unit, respectively.

[0099] The node power balance constraints are as follows:

[0100]

[0101] in, and Φ m These are the sets of thermal power units, renewable energy sources, electrolytic hydrogen production units, and nodes connected to node m. It is the output of renewable energy; It is the electrical energy consumed in the electrolysis of hydrogen production; It is the electrical load of node m; It is the transmission power of line mn;

[0102] Among them, the power flow constraints of the power grid are:

[0103]

[0104] Where, θ m,t and θ n,t It is the phase angle between nodes m and n; This refers to the transmission capacity of the power transmission line mn;

[0105] Among them, the constraints for thermal power generation are:

[0106]

[0107] in, and These are the upper and lower limits of the output of thermal power units;

[0108] Among them, the constraints for renewable energy are:

[0109]

[0110] in, It is the predicted power of renewable energy;

[0111] The constraints for hydrogen production via electrolysis are as follows:

[0112]

[0113] in, It refers to the installed capacity of hydrogen production via electrolysis;

[0114] The boundary information constraints are as follows:

[0115]

[0116] in, It is the dual variable of the electro-hydrogen coupling constraint.

[0117] Furthermore, in one embodiment of the present invention, an optimality condition decomposition algorithm is used to decompose the economic dispatch model of the electric-hydrogen system into a power system operation model and a hydrogen energy system operation model, including:

[0118] Construct the objective function for the hydrogen energy system operation model:

[0119]

[0120] in, and These are the dual variables of the electro-hydrogen coupling constraint and the power consumption of the electrolysis hydrogen production unit, respectively.

[0121] The hydrogen balance constraint at the nodes is as follows:

[0122]

[0123] in, and These are the collections of fossil fuel reforming and electrolytic hydrogen production connected to node m; Ω I (mn) = m and Ω O (mn) = m are the sets of pipes with m as the input node and m as the output node, respectively; and These are the input and output hydrogen flow rates of pipe m and n, respectively. It is hydrogen produced by electrolysis; It is the hydrogen load at node m.

[0124] The pipeline flow constraint is as follows:

[0125]

[0126] Where, Φ L It is a collection of pipes; f mn,t This refers to the hydrogen flow rate in pipe mn; p m,tS is the hydrogen pressure at node m; mn It is a constant determined by the length, diameter, and temperature of the pipe mn; sgn(p m,t ,p n,t ) is a symbolic function representing the direction of hydrogen flow in pipe mn.

[0127] Among them, the constraints for hydrogen production from fossil fuel reforming are:

[0128]

[0129] in, and These are the upper and lower limits for hydrogen production from fossil fuel reforming.

[0130] The hydrogen pressure constraint is as follows:

[0131]

[0132] Where, p m,max and p m,min These are the upper and lower limits of the hydrogen pressure at node m.

[0133] The pipeline storage constraints are as follows:

[0134]

[0135]

[0136] Among them, F mn,t It is the amount of hydrogen stored in pipe mn; μ mn It is a constant determined by the length, diameter, and temperature of the hydrogen pipeline mn.

[0137] Furthermore, in one embodiment of the present invention, an optimality condition decomposition algorithm is used to decompose the economic dispatch model of the electric-hydrogen system into a power system operation model and a hydrogen energy system operation model, including:

[0138] The initial value of the installed capacity for electrolytic hydrogen production is set to 0. The sub-problems of the power system and the hydrogen energy system are optimized respectively, and the Lagrange multipliers are initialized.

[0139] Information is exchanged between the power system and the hydrogen energy system to update boundary information;

[0140] Based on the updated boundary information, the sub-problems of the power system and the hydrogen energy system are optimized respectively;

[0141] The algorithm is terminated if the boundary information meets the convergence condition; otherwise, the iteration continues.

[0142] Furthermore, in one embodiment of the present invention, determining the electrolysis hydrogen production capacity configuration of the economic dispatch model for minimizing carbon emissions based on the golden ratio method includes:

[0143] Initialize the electrolysis hydrogen production ratio of the electro-hydrogen system and set the convergence conditions;

[0144] The golden section method is used to select two electrolysis hydrogen production ratio values ​​within a given interval. If the difference between the two ratios is less than the convergence condition, the value is directly output.

[0145] If the difference between the two ratios is not less than the convergence condition, calculate the total carbon emissions of the hydrogen electrolysis system under different hydrogen electrolysis ratios and compare their magnitudes. Based on the results, assign values ​​to the endpoints of the interval to further narrow the interval of the hydrogen electrolysis ratio and carry out a new round of iteration.

[0146] Example 2

[0147] Figure 2 This invention proposes a simulation method for optimal capacity configuration of electrolytic hydrogen production based on the collaborative optimization of an electro-hydrogen system, comprising:

[0148] 1) Taking into account the physical connection between the power system and the hydrogen system as well as the power flow constraints of the topology, an economic dispatch model for the electric hydrogen system is established, and the energy conversion process of the electrolysis hydrogen production device is taken as the coupling constraint of the electric hydrogen system.

[0149] 1-1) Construct an objective function for the operating costs of the power system and the hydrogen system, as shown in the following expression:

[0150] min C E +C H

[0151] In the expression C E The specific expression for the operating cost of the power system is as follows:

[0152]

[0153] Where, Φ T It is a set of time periods; Φ E It is a collection of thermal power units; This refers to the power generation of thermal power units. It is the cost coefficient of thermal power units.

[0154] In the expression C H The cost of operating a hydrogen energy system is expressed as follows:

[0155]

[0156] Where, Φ T It is a set of time periods; Φ H It is a collection of fossil fuel reformings; This refers to the amount of hydrogen produced from fossil fuel reforming; It is the cost coefficient for fossil fuel reforming.

[0157] 1-2) Treating the energy conversion process of the electrolysis hydrogen production unit as a coupling constraint of the electro-hydrogen system, the expression is as follows:

[0158]

[0159] in, It is hydrogen produced by electrolysis. It refers to the electrical energy consumed in the electrolysis of hydrogen production; HHV is the higher calorific value of hydrogen. It refers to the conversion efficiency of the electrolytic hydrogen production unit.

[0160] 2) The optimal condition decomposition algorithm is used to decompose and coordinate the economic dispatch model of the electric hydrogen system to obtain the power system operation model.

[0161] 2-1) The objective function for constructing the power system operation model is as follows:

[0162]

[0163] in, and These are the dual variables of the electrolytic hydrogen production coupling constraint and the hydrogen production capacity of the electrolytic hydrogen production device, respectively.

[0164] 2-2) Construct the constraints of the power system, the expressions of which are as follows:

[0165] 2-2-1) Nodal power balance constraints

[0166]

[0167] in, and Φ m These are the sets of thermal power units, renewable energy sources, electrolytic hydrogen production units, and nodes connected to node m. It is the output of renewable energy; It is the electrical energy consumed in the electrolysis of hydrogen production; It is the electrical load of node m; It is the transmission power of line mn.

[0168] 2-2-2) Power Flow Constraints

[0169]

[0170] Where, θ m,t and θ n,t It is the phase angle between nodes m and n; It is the transmission capacity of the power transmission line mn.

[0171] 2-2-3) Constraints on thermal power generation

[0172]

[0173] in, and These are the upper and lower limits of the output of thermal power units.

[0174] 2-2-4) Renewable Energy Constraints

[0175]

[0176] in, It is the predicted power of renewable energy.

[0177] 2-2-5) Phase Angle Constraint

[0178]

[0179] Where, θ m,max and θ m,min These are the upper and lower limits of the phase angle at node m.

[0180] 2-2-6) Constraints on Electrolytic Hydrogen Production

[0181]

[0182] in, It refers to the installed capacity of hydrogen production via electrolysis.

[0183] 2-2-7) Boundary Information Constraints

[0184]

[0185] in, It is a Lagrange multiplier constrained by electro-hydrogen coupling.

[0186] 3) The optimal condition decomposition algorithm is used to decompose and coordinate the economic dispatch model of the hydrogen-electric system to obtain the hydrogen energy system operation model.

[0187] 3-1) The objective function for constructing the hydrogen energy system operation model is as follows:

[0188]

[0189] in, and These are the dual variables of the electro-hydrogen coupling constraint and the power consumption of the electrolysis hydrogen production unit, respectively.

[0190] 3-2) Construct the constraints for the hydrogen energy system, the expressions of which are as follows:

[0191] 3-2-1) Node Hydrogen Balance Constraint

[0192]

[0193] in, and These are the collections of fossil fuel reforming and electrolytic hydrogen production connected to node m; Ω I (mn) = m and Ω O (mn) = m are the sets of pipes with m as the input node and m as the output node, respectively; and These are the input and output hydrogen flow rates of pipe m and n, respectively. It is hydrogen produced by electrolysis; It is the hydrogen load at node m.

[0194] 3-2-2) Pipeline flow constraints

[0195]

[0196] Where, Φ L It is a collection of pipes; f mn,t This refers to the hydrogen flow rate in pipe mn; p m,t S is the hydrogen pressure at node m; mn It is a constant determined by the length, diameter, and temperature of the pipe mn; sgn(p m,t ,p n,t ) is a symbolic function representing the direction of hydrogen flow in pipe mn.

[0197] 3-2-3) Fossil fuel conversion constraints

[0198]

[0199] in, and These are the upper and lower limits for hydrogen production from fossil fuel reforming.

[0200] 3-2-4) Hydrogen pressure constraint

[0201]

[0202] Where, p m,max and p m,min These are the upper and lower limits of the hydrogen pressure at node m.

[0203] 3-2-5) Pipeline storage constraints

[0204]

[0205] Among them, F mn,t It is the amount of hydrogen stored in pipe mn; μ mnIt is a constant determined by the length, diameter, and temperature of the hydrogen pipeline mn.

[0206] 4) Solve the coordinated dispatch model of the power system and the hydrogen energy system, including:

[0207] 4-1) Set the initial value of the electrolytic hydrogen production capacity to 0, optimize the sub-problems of the power system and hydrogen energy system respectively, and initialize the Lagrange multipliers.

[0208] 4-2) Information exchange between the power system and the hydrogen energy system;

[0209] 4-3) Based on the updated boundary information, the power system and the hydrogen energy system optimize the sub-problems respectively;

[0210] 4-4) Determine the convergence condition. If the convergence condition is met, terminate the algorithm. If the convergence condition is not met, continue iterating and return to step 4-2).

[0211] 5) Determine the electrolysis hydrogen production capacity configuration that minimizes carbon emissions from the electro-hydrogen system using the golden ratio method, including:

[0212] 5-1) Initialize the electrolysis hydrogen production ratio of the electro-hydrogen system and set the convergence conditions;

[0213] 5-2) Use the golden section method to select two electrolysis hydrogen production ratio values ​​within a given interval. If the difference between the two ratios is less than the convergence condition, output directly; otherwise, go to step 5-3).

[0214] 5-3) Calculate the total carbon emissions of the hydrogen electrolysis system under different hydrogen electrolysis ratios and compare their magnitudes. Based on the results, assign values ​​to the endpoints of the interval to further narrow the interval of hydrogen electrolysis ratios, and then proceed to step 5-2) for a new round of iteration.

[0215] By applying the optimal condition decomposition method to the electro-hydrogen system, the decomposition and coordination of the power system and the hydrogen energy system are finally realized, and the carbon emission of the power system and the hydrogen energy system is obtained. Based on the carbon emission results of the electro-hydrogen system, the optimal capacity configuration of the electrolytic hydrogen production device is determined iteratively using the golden section method, thereby minimizing the carbon emission of the electro-hydrogen system.

[0216] The proposed method for optimal capacity configuration of electrolytic hydrogen production in this invention first constructs an economic scheduling model of the electrolytic hydrogen system, considering the coupling constraints of the electrolytic hydrogen system; then, it uses an optimality condition decomposition method to decompose and coordinate the electrolytic hydrogen system; finally, it uses the golden section method to determine the electrolytic hydrogen production capacity configuration that minimizes the carbon emissions of the electrolytic hydrogen system; and it provides a simulation method for electrolytic hydrogen production capacity configuration that minimizes the carbon emissions of the electrolytic hydrogen system, providing theoretical guidance for behavioral decisions to reduce the carbon emissions of the electrolytic hydrogen system.

[0217] To achieve the above embodiments, the present invention also proposes an optimal capacity configuration device for electrolytic hydrogen production.

[0218] Figure 3 This is a schematic diagram of an electrolytic hydrogen production device with optimal capacity configuration provided in an embodiment of the present invention.

[0219] like Figure 3 As shown, the optimal capacity configuration device for electrolytic hydrogen production includes: a construction module 100, a decomposition module 200, and a calculation module 300, wherein...

[0220] The module is used to construct an economic scheduling model for the electric-hydrogen system based on the coupling constraints of the electric-hydrogen system.

[0221] The decomposition module is used to decompose the economic dispatch model of the electric-hydrogen system into an electric system operation model and a hydrogen energy system operation model using the optimal condition decomposition algorithm.

[0222] The calculation module is used to calculate the carbon emissions of the power system operation model and the hydrogen energy system operation model, and to determine the electrolysis hydrogen production capacity configuration of the economic dispatch model of the electric hydrogen system based on the golden ratio method to minimize the carbon emissions.

[0223] To achieve the above objectives, a third aspect of the present invention provides a computer device, characterized in that it includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the optimal capacity configuration method for electrolytic hydrogen production as described above.

[0224] To achieve the above objectives, a fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements the optimal capacity configuration method for electrolytic hydrogen production as described above.

[0225] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0226] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0227] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for optimal capacity configuration in hydrogen production by electrolysis, characterized in that, Includes the following steps: Based on the coupling constraints of the electric-hydrogen system, an economic scheduling model for the electric-hydrogen system is constructed. The optimality condition decomposition algorithm is used to decompose the economic dispatch model of the electric-hydrogen system into a power system operation model and a hydrogen energy system operation model. The carbon emissions of the power system operation model and the hydrogen energy system operation model are calculated. Based on the carbon emissions, the electrolysis hydrogen production capacity configuration of the economic dispatch model of the electric hydrogen system is determined using the golden section method to minimize the capacity. Specifically, the electrolysis hydrogen production ratio of the electric hydrogen system is initialized, and convergence conditions are set. Using the golden section method, two electrolysis hydrogen production ratio values ​​are selected within a given interval. If the difference between the two ratios is less than the convergence condition, the value is directly output. If the difference is not less than the convergence condition, the total carbon emissions of the electric hydrogen system under different electrolysis hydrogen production ratios are calculated and compared. Based on the results, interval endpoints are assigned to further narrow the interval of the electrolysis hydrogen production ratio, and a new round of iteration is performed.

2. The method according to claim 1, characterized in that, The construction of an economic dispatch model for the electric-hydrogen system based on the coupling constraints of the electric-hydrogen system includes: Construct the objective function of the economic dispatch model for the electric-hydrogen system: ， The objective function mainly consists of two parts, the first part being the power system operating cost. The second part is the operating cost of the hydrogen energy system. ; It is a set of time periods; It is a collection of thermal power units; It is a collection of fossil fuel reformings; and These are the power generation of thermal power units and the hydrogen production from fossil fuel reforming, respectively. It is the cost coefficient of thermal power units; It is the cost coefficient for fossil fuel reforming; The electro-hydrogen coupling constraint is as follows: ， in, It is hydrogen produced by electrolysis. It is the electrical energy consumed in the electrolysis of hydrogen production. It is the high calorific value of hydrogen. It refers to the conversion efficiency of the electrolytic hydrogen production unit.

3. The method according to claim 1, characterized in that, The optimal condition decomposition algorithm is used to decompose the economic dispatch model of the electric-hydrogen system into a power system operation model and a hydrogen energy system operation model, including: Construct the objective function for the power system operation model: ， in, and These are the dual variables of the coupling constraint in electrolytic hydrogen production and the hydrogen production capacity of the electrolytic hydrogen production unit, respectively. For time periods; It is a collection of thermal power units; It is the cost coefficient of thermal power units; This refers to the power generation of thermal power units. It is the high calorific value of hydrogen. It refers to the conversion efficiency of the electrolytic hydrogen production unit; The node power balance constraints are as follows: ， in, , , and These are the sets of thermal power units, renewable energy sources, electrolytic hydrogen production units, and nodes connected to node m. It is the output of renewable energy; It is the electrical energy consumed in the electrolysis of hydrogen production; It is the electrical load of node m; It is the transmission power of line mn; Among them, the power flow constraints of the power grid are: ， in, and It is the phase angle between nodes m and n; It is the transmission capacity of transmission line mn; Among them, the constraints for thermal power generation are: ， in, and These are the upper and lower limits of the output of thermal power units; Among them, the constraints for renewable energy are: in, It is the predicted power of renewable energy; Among them, the constraints for hydrogen production by electrolysis are: in, It refers to the installed capacity of hydrogen production via electrolysis; The boundary information constraints are as follows: in, It is the dual variable of the electro-hydrogen coupling constraint.

4. The method according to claim 1, characterized in that, The optimal condition decomposition algorithm is used to decompose the economic dispatch model of the electric-hydrogen system into a power system operation model and a hydrogen energy system operation model, including: Construct the objective function for the hydrogen energy system operation model: ， in, and These are the dual variables of the electro-hydrogen coupling constraint and the power consumption of the electrolysis hydrogen production unit, respectively. It is the cost coefficient for fossil fuel reforming; For time periods; This refers to the amount of hydrogen produced from fossil fuel reforming; It is a collection of fossil fuel reformings; It is a collection of thermal power units; It has the high calorific value of hydrogen; It refers to the conversion efficiency of the electrolytic hydrogen production unit; The hydrogen balance constraint at the nodes is as follows: ， in, and These are the collections of fossil fuel reforming and electrolytic hydrogen production connected to node m; and These are sets of pipes with m as both the input and output nodes; and These are the input and output hydrogen flow rates of pipe m and n, respectively. It is hydrogen produced by electrolysis; The hydrogen load at node m; The pipeline flow constraint is as follows: ， in, It is a collection of pipes; This is the hydrogen flow rate in pipe mn; It is the hydrogen pressure at node m; It is a constant determined by the length, diameter, and temperature of the pipe mn; It is a symbolic function representing the direction of hydrogen flow in pipe mn; Among them, the constraints for hydrogen production from fossil fuel reforming are: ， in, and These are the upper and lower limits for hydrogen production from fossil fuel reforming; The hydrogen pressure constraint is as follows: ， in, and These are the upper and lower limits of the hydrogen pressure at node m; The pipeline storage constraints are as follows: ， ， in, This refers to the amount of hydrogen stored in pipe mn; It is a constant determined by the length, diameter, and temperature of the hydrogen pipeline mn.

5. The method according to claim 1, characterized in that, The optimal condition decomposition algorithm is used to decompose the economic dispatch model of the electric-hydrogen system into a power system operation model and a hydrogen energy system operation model, including: The initial value of the installed capacity for electrolytic hydrogen production is set to 0. The sub-problems of the power system and the hydrogen energy system are optimized respectively, and the Lagrange multipliers are initialized. Information is exchanged and boundary information is updated between the power system and the hydrogen energy system. Based on the updated boundary information, the sub-problems of the power system and the hydrogen energy system are optimized respectively; The algorithm is terminated if the boundary information meets the convergence condition; otherwise, the iteration continues.

6. An optimal capacity configuration device for electrolytic hydrogen production, characterized in that, Includes the following modules: The module is used to construct an economic scheduling model for the electric-hydrogen system based on the coupling constraints of the electric-hydrogen system. The decomposition module is used to decompose the economic dispatch model of the electric-hydrogen system into a power system operation model and a hydrogen energy system operation model using an optimal condition decomposition algorithm. The calculation module is used to calculate the carbon emissions of the power system operation model and the hydrogen energy system operation model. Based on the carbon emissions, it determines the electrolysis hydrogen production capacity configuration of the economic dispatch model of the electric-hydrogen system to minimize the electrolysis hydrogen production capacity. Specifically, it initializes the electrolysis hydrogen production ratio of the electric-hydrogen system and sets convergence conditions. Using the golden section method, it selects two electrolysis hydrogen production ratio values ​​within a given interval. If the difference between the two ratios is less than the convergence condition, it outputs the value directly. If the difference between the two ratios is not less than the convergence condition, it calculates and compares the total carbon emissions of the electric-hydrogen system under different electrolysis hydrogen production ratios. Based on the results, it assigns values ​​to the interval endpoints to further narrow the interval of the electrolysis hydrogen production ratio and performs a new round of iteration.

7. A computer device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the optimal capacity configuration method for electrolytic hydrogen production as described in any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the optimal capacity configuration method for electrolytic hydrogen production as described in any one of claims 1-5.

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