Prediction method and device for hydrogen energy production strategy, equipment and medium

Abstract

The invention provides a prediction method and device for a hydrogen energy production strategy, equipment and a medium. The method comprises the steps that the hydrogen demand quantity and the renewable energy source hydrogen production cost of each sub-region in a target region are calculated; inputting the hydrogen demand quantity of each sub-region and the hydrogen production cost of the renewable energy sources into a pre-constructed optimization model, and calculating the minimum total hydrogen production cost corresponding to the target region by taking the minimum total hydrogen production cost as a target; and performing model solving on the optimization model based on a mathematical optimization solver, and determining a hydrogen energy production strategy corresponding to the total hydrogen production minimum cost by using a linear programming method. Through the method and the device, the running path of hydrogen energy interconnection of each region is dynamically simulated, the hydrogen production cost of the target region is minimized through the generated hydrogen energy generation strategy, the accuracy of the generated hydrogen energy generation strategy is improved, and the simulation process and result are more credible.

Description

Technical Field

[0001] The present application relates to the technical field of energy systems, and in particular to a prediction method, device, equipment and medium for a hydrogen energy production strategy. Background Art

[0002] As an efficient zero-carbon energy, hydrogen will play a vital role in the transformation of energy structure and show great potential for future development. Hydrogen can replace fossil fuels in many industries, especially in those areas that are difficult to electrify, such as heavy industry, long-distance transportation and aviation, thereby significantly reducing greenhouse gas emissions. Among them, reducing the production cost of hydrogen is the key to promoting the large-scale development of the hydrogen energy industry.

[0003] At present, the optimization research on the electricity-hydrogen-carbon coupled energy system is mainly carried out through simulation calculations by constructing optimization models, aiming to seek the optimal solution that can maximize economic benefits and take into account environmental benefits under different scenarios and parameter conditions. However, there are certain limitations in the optimization layout of hydrogen energy based on electricity-hydrogen-carbon coupling. Since factors such as the cost, operating time and system efficiency of hydrogen production technology will continue to change with the development of society, economy and technology, existing research often uses fixed parameters or partially variable parameters for calculations, which affects the accuracy of its calculation results. Therefore, accurately predicting hydrogen production strategies to minimize hydrogen production costs has become an important technical problem that needs to be solved urgently. Summary of the invention

[0004] In view of this, the purpose of this application is to provide a prediction method, device, equipment and medium for hydrogen production strategy. By constructing a hydrogen optimization model, from the perspective of hydrogen production technology and production cost, the hydrogen production decisions of each region, inter-regional hydrogen scheduling and future hydrogen production structure are predicted. The hydrogen production cost of the target area is minimized through the generated hydrogen generation strategy, which improves the accuracy of the generated hydrogen generation strategy and makes the simulation process and results more credible.

[0005] In a first aspect, an embodiment of the present application provides a method for predicting a hydrogen production strategy, the method comprising:

[0006] Calculating the hydrogen demand of each sub-area within the target area based on the total hydrogen demand of the target area;

[0007] The cost of hydrogen production from renewable energy in each sub-region is calculated using the hydrogen levelized cost calculation formula;

[0008] The hydrogen demand and renewable energy hydrogen production cost of each sub-region are input into a pre-built optimization model, and the total hydrogen production minimum cost corresponding to the target region is calculated with the goal of minimizing the total hydrogen production cost; wherein the optimization model includes a hydrogen production cost minimization objective function and multiple constraints, and the hydrogen production cost minimization objective function is used to calculate the total hydrogen production minimum cost;

[0009] The optimization model is solved based on a mathematical optimization solver, and a hydrogen production strategy corresponding to the minimum total hydrogen production cost is determined using a linear programming method.

[0010] Furthermore, the step of calculating the hydrogen demand of each sub-region within the target region based on the total hydrogen demand of the target region includes:

[0011] For each sub-region, determine the hydrogen energy demand weight corresponding to the sub-region;

[0012] The hydrogen demand weight is multiplied by the total hydrogen demand of the target area to obtain the hydrogen demand of the sub-area.

[0013] Furthermore, the multiple constraints include renewable energy hydrogen production technology constraints, renewable energy hydrogen production proportion constraints, production-side carbon emission reduction constraints, transportation system constraints and supply and demand balance constraints.

[0014] Furthermore, the cost of renewable energy hydrogen production in each sub-region is calculated by the following formula:

[0015]

[0016] Among them, P i,v,t represents the renewable energy hydrogen production cost of the i-th sub-region through the v-th renewable energy hydrogen production technology in the t-th year; LHV is the lower heating value of hydrogen energy; η v,t is the efficiency of the hydrogen production technology system of the vth renewable energy in the tth year; r is the depreciation rate; a is the life cycle of the hydrogen production system; OPEX is the operating cost; CAPEX is the v,t is the fixed cost of hydrogen production technology using the vth renewable energy source in year t; τ v,t E is the number of transport hours of the vth renewable energy hydrogen production technology in year t; i,t is the renewable energy generation cost of the ith sub-region in year t.

[0017] Furthermore, the hydrogen production cost minimization objective function is expressed by the following formula:

[0018]

[0019] Among them, TC trepresents the total cost of hydrogen production in year t; i and j represent regions; k represents the mode of transportation of hydrogen; represents the hydrogen production in region i in year t; represents the unit hydrogen production cost of region i in year t; q i,j,k,t represents the amount of hydrogen transmitted from region i to region j through transmission mode k in year t; C trans represents the unit cost of hydrogen transportation; α t represents the proportion of renewable energy hydrogen production in hydrogen production in year t; v represents different renewable energy hydrogen production technologies; P′ t represents the cost of hydrogen production using traditional energy in year t.

[0020] In a second aspect, the embodiment of the present application further provides a prediction device for a hydrogen production strategy, the prediction device comprising:

[0021] A hydrogen demand calculation module, used to calculate the hydrogen demand of each sub-area within the target area based on the total hydrogen demand of the target area;

[0022] A hydrogen production cost calculation module is used to calculate the cost of hydrogen production from renewable energy in each sub-region using the hydrogen levelized cost calculation formula;

[0023] The total hydrogen production minimum cost calculation module is used to input the hydrogen demand of each sub-region and the cost of hydrogen production from renewable energy into a pre-built optimization model, and to calculate the total hydrogen production minimum cost corresponding to the target region with the goal of minimizing the total hydrogen production cost; wherein the optimization model includes a hydrogen production cost minimization objective function and multiple constraints, and the hydrogen production cost minimization objective function is used to calculate the total hydrogen production minimum cost;

[0024] The production strategy prediction module is used to solve the optimization model based on a mathematical optimization solver, and determine the hydrogen production strategy corresponding to the minimum total hydrogen production cost using a linear programming method.

[0025] Furthermore, when the hydrogen demand calculation module is used to calculate the hydrogen demand of each sub-area in the target area based on the total hydrogen demand of the target area, the hydrogen demand calculation module is also used to:

[0026] For each sub-region, determine the hydrogen energy demand weight corresponding to the sub-region;

[0027] The hydrogen demand weight is multiplied by the total hydrogen demand of the target area to obtain the hydrogen demand of the sub-area.

[0028] Furthermore, the multiple constraints include renewable energy hydrogen production technology constraints, renewable energy hydrogen production proportion constraints, production-side carbon emission reduction constraints, transportation system constraints and supply and demand balance constraints.

[0029] In a third aspect, an embodiment of the present application further provides an electronic device, comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the memory through the bus, and when the machine-readable instructions are executed by the processor, the steps of the prediction method for the hydrogen energy production strategy as described above are performed.

[0030] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the method for predicting the hydrogen production strategy as described above are executed.

[0031] The embodiments of the present application provide a prediction method, device, equipment and medium for a hydrogen production strategy. First, based on the total hydrogen demand in the target area, the hydrogen demand of each sub-area in the target area is calculated; then, the hydrogen levelized cost calculation formula is used to calculate the renewable energy hydrogen production cost of each sub-area; the hydrogen demand of each sub-area and the renewable energy hydrogen production cost are input into a pre-constructed optimization model, and the total hydrogen production minimum cost corresponding to the target area is calculated with the goal of minimizing the total hydrogen production cost; wherein the optimization model includes a hydrogen production cost minimization objective function and multiple constraints, and the hydrogen production cost minimization objective function is used to calculate the total hydrogen production minimum cost; finally, the optimization model is solved based on a mathematical optimization solver, and a hydrogen production strategy corresponding to the total hydrogen production minimum cost is determined using a linear programming method.

[0032] This application constructs an electricity-hydrogen-carbon coupled hydrogen energy optimization model, and studies the impact of changes in hydrogen production costs in each sub-region within the target area on hydrogen production decisions, taking into account technological equipment progress, electricity cost reduction, and cross-regional transmission of hydrogen energy. This optimization model takes into account the hydrogen production and transportation links, and combined with environmental and policy constraints, it can dynamically simulate the operation path of hydrogen energy interconnection in each region, and predict the hydrogen production decisions, inter-regional hydrogen energy scheduling, and future hydrogen energy production structure of each region from the perspective of hydrogen production technology and production costs. The generated hydrogen energy generation strategy is used to minimize the hydrogen production cost in the target area, improve the accuracy of the generated hydrogen energy generation strategy, and make the simulation process and results more credible. The impact of existing hydrogen energy industry policies on society, economy, environment, energy, etc. is fully simulated, and through scenario settings, the impact and effect of green development of the hydrogen energy industry in the medium and long term can be predicted. Not only can hydrogen energy production in each region be planned, but also cross-regional transportation planning of hydrogen energy can be planned, including transmission mode, transmission path, and transmission volume.

[0033] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0035] Figure 1 A flowchart of a method for predicting a hydrogen production strategy provided in an embodiment of the present application;

[0036] Figure 2 A schematic diagram of the structure of a prediction device for a hydrogen energy production strategy provided in an embodiment of the present application;

[0037] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0038] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application usually described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, each other embodiment obtained by those skilled in the art without making creative work belongs to the scope of protection of the present application.

[0039] First, the application scenarios to which the present application is applicable are introduced. The present application can be applied in the field of energy system technology.

[0040] Reducing the proportion of traditional fossil energy in energy utilization and vigorously developing low-carbon, clean renewable energy are the main directions of my country's energy transformation. As an efficient zero-carbon energy, hydrogen energy will play a huge role in the transformation of the energy structure and has great potential for future development. Hydrogen energy can replace fossil fuels in many industries, especially in areas that are difficult to electrify, such as heavy industry, long-distance transportation and aviation, thereby significantly reducing greenhouse gas emissions. At present, coal-to-hydrogen production is still the main source of hydrogen energy production, and green hydrogen accounts for only about 1%. This situation exposes some key problems facing the development of hydrogen energy: the high cost of hydrogen energy production, the core technology to be overcome, and the low proportion of green hydrogen. These problems not only limit the large-scale commercial application of hydrogen energy, but also affect its role in energy transformation. Among them, reducing the cost of hydrogen production is the top priority for promoting the large-scale development of the hydrogen energy industry. The high cost makes hydrogen energy uncompetitive in many application scenarios, especially when compared with traditional fossil fuels. With the continuous decline in the cost of renewable electricity in the future and the innovation of related equipment technology, green hydrogen will be more economically and environmentally beneficial than traditional hydrogen production methods. In addition, the continuous advancement of electrolyzer technology will further reduce the production cost of green hydrogen. These factors together will make green hydrogen occupy an increasingly important position in the future energy market.

[0041] Specifically, the prediction of future hydrogen demand is the basis for formulating a hydrogen development strategy. By establishing a scientific prediction model, we can accurately evaluate the hydrogen demand under different scenarios. On this basis, we can optimize and simulate the hydrogen production cost and production decision, find the optimal production path, reduce operating costs, and improve economic benefits. In addition, the multi-scenario simulation method can take into account various uncertainties and risk factors, providing comprehensive support for the healthy development of the hydrogen industry.

[0042] Therefore, in the context of energy transformation, it is necessary to study the development path and optimization strategy of the hydrogen energy industry. Regarding the optimization research of the hydrogen energy industry, the main consideration is the comprehensive system including electricity, heat, carbon, etc. In the process of energy structure transformation, what level of hydrogen energy demand will be reached in the future, how the cost of renewable water electrolysis hydrogen production will change, how much carbon emission reduction can be achieved by developing hydrogen energy, etc., are all key issues worthy of in-depth discussion in order to achieve low-carbon development of energy systems including hydrogen energy systems.

[0043] It has been found that at present, the optimization research on the electricity-hydrogen-carbon coupling energy system mainly simulates and calculates by constructing optimization models, aiming to seek the optimal solution that can maximize economic benefits and take into account environmental benefits under different scenarios and parameter conditions. However, there are certain limitations in the optimization layout of hydrogen energy based on electricity-hydrogen-carbon coupling. First, most of the research on hydrogen energy cost and demand is based on the national level, ignoring the differences in regional resources. Second, there are more significant regional characteristics in the production and demand of hydrogen energy, but few studies in the hydrogen energy industry chain consider the problem of hydrogen energy transmission, especially long-distance and large-scale cross-regional transmission, which means that the optimal allocation of resources cannot be achieved. Third, since factors such as the cost, operating time and system efficiency of hydrogen production technology will continue to change with the development of society, economy and technology, existing studies often use fixed parameters or partially variable parameters for calculation, which affects the accuracy of the calculation results. Fourth, the technical research on hydrogen production from renewable energy is single, and realistic problems such as competition and substitution between technologies are not considered. Therefore, accurately predicting hydrogen production strategies to minimize hydrogen production costs has become an important technical problem that needs to be solved urgently.

[0044] Based on this, the embodiment of the present application provides a method for predicting hydrogen production strategies. By constructing a hydrogen optimization model, the hydrogen production decisions of each region, inter-regional hydrogen scheduling and future hydrogen production structure are predicted from the perspective of hydrogen production technology and production costs. The hydrogen production cost of the target area is minimized through the generated hydrogen generation strategy, which improves the accuracy of the generated hydrogen generation strategy and makes the simulation process and results more credible.

[0045] See also Figure 1 , Figure 1 This is a flow chart of a method for predicting a hydrogen production strategy provided in an embodiment of the present application. Figure 1 As shown in , the prediction method provided in the embodiment of the present application includes:

[0046] S101, calculating the hydrogen demand of each sub-area in the target area based on the total hydrogen demand of the target area.

[0047] Here, the target area may be a region, and the sub-areas may be various cities in the region, which is not specifically limited in this application.

[0048] Regarding the above step S101, in specific implementation, the total hydrogen demand of the target area is first determined, and then the hydrogen demand of each sub-area in the target area is calculated based on the total hydrogen demand of the target area.

[0049] Specifically, with respect to the above step S101, the hydrogen demand of each sub-area in the target area is calculated based on the total hydrogen demand of the target area, including:

[0050] Step 1011, for each sub-region, determine the hydrogen energy demand weight corresponding to the sub-region.

[0051] In the above step 1011, when it is specifically implemented, for each sub-region in the target area, the hydrogen demand weight corresponding to the sub-region is determined. Here, as an embodiment, the hydrogen demand weight of each sub-region can be calculated using the entropy weight method according to the urbanization rate, secondary industry GDP and tertiary industry GDP of each sub-region.

[0052] Step 1012: multiply the hydrogen demand weight by the total hydrogen demand of the target area to obtain the hydrogen demand of the sub-area.

[0053] Regarding the above step 1012, in the specific implementation, for each sub-region, after the above step 1011 determines the hydrogen demand weight corresponding to the sub-region, the product of the hydrogen demand weight and the total hydrogen demand of the target region is used as the hydrogen demand of the sub-region. Specifically, the hydrogen demand of the sub-region is calculated by the following formula:

[0054] Q d,i =Q d ×λ i

[0055] Among them, Q d,i is the hydrogen demand of sub-region i, Q d is the total hydrogen demand in the target area, λ i is the hydrogen energy demand weight corresponding to sub-region i.

[0056] S102, using the hydrogen levelized cost calculation formula, calculate the cost of hydrogen production from renewable energy in each sub-region.

[0057] Regarding the above step S102, in specific implementation, the cost of hydrogen production from renewable energy in each sub-region is calculated using the hydrogen levelized cost calculation formula.

[0058] Specifically, with respect to the above step S102, the cost of producing hydrogen from renewable energy in each sub-region is calculated through the following steps:

[0059]

[0060] Among them, P i,v,trepresents the renewable energy hydrogen production cost (levelized cost of hydrogen, LCOH) of the i-th sub-region through the b-th renewable energy hydrogen production technology in the t-th year; LHV is the lower heating value of hydrogen energy; η v,t is the efficiency of the hydrogen production technology system of the vth renewable energy in the tth year; r is the depreciation rate; a is the life cycle of the hydrogen production system; OPEX is the operating cost, in (yuan / kWh); CAPEX v,t is the fixed cost of the vth renewable energy hydrogen production technology in year t, in (yuan / kWh); τ v,t E is the number of transport hours of the vth renewable energy hydrogen production technology in year t; i,t is the renewable energy power generation cost of the ith sub-region in the tth year, in (yuan / kWh).

[0061] S103, inputting the hydrogen demand of each sub-region and the cost of hydrogen production from renewable energy into a pre-built optimization model, taking minimizing the total cost of hydrogen production as the goal, and calculating the minimum total hydrogen production cost corresponding to the target region.

[0062] Here, the optimization model includes a hydrogen production cost minimization objective function and multiple constraints, and the hydrogen production cost minimization objective function is used to calculate the total minimum hydrogen production cost.

[0063] For the above step S103, in the specific implementation, the hydrogen demand of each sub-region obtained in step S101 and the renewable energy hydrogen production cost of each sub-region obtained in step S102 are input into the pre-built optimization model, and the total hydrogen production cost is minimized to calculate the minimum total hydrogen production cost corresponding to the target area. Specifically, according to the embodiment provided by the present application, the hydrogen production cost minimization objective function is expressed by the following formula:

[0064]

[0065] Among them, TC t represents the total cost of hydrogen production in year t; i and j represent regions. In the above formula, there are 7 regions. Since hydrogen energy transmission is carried out between regions, different letters are used to distinguish different regions; k represents the mode of transportation of hydrogen; represents the hydrogen production in region i in year t; represents the unit hydrogen production cost of region i in year t; q i,j,k,t represents the amount of hydrogen transmitted from region i to region j through transmission mode k in year t; C trans Represents the unit cost of hydrogen transportation.

[0066] α trepresents the proportion of renewable energy hydrogen production in hydrogen production in year t; v represents different renewable energy hydrogen production technologies; P′ t represents the cost of hydrogen production using traditional energy in year t.

[0067] According to the embodiments provided in the present application, the multiple constraints of the optimization model include renewable energy hydrogen production technology constraints, renewable energy hydrogen production proportion constraints, production-side carbon emission reduction constraints, transportation system constraints and supply and demand balance constraints.

[0068] In this way, by constraining the proportion of different production methods in future hydrogen production, the unit carbon emissions of hydrogen production, and other key parameters, combined with information provided by different institutions and referring to relevant research results, three possible change scenarios of the future hydrogen industry (production end) are set. For example, by constraining the proportion of hydrogen production from renewable energy, the transformation scenarios of hydrogen production structure in different years are simulated; by the competition and substitution of water electrolysis hydrogen production technology, the impact on the renewable energy hydrogen production structure under different technological developments is simulated; by constraining the unit carbon emissions of hydrogen energy at the production end, the impact on the hydrogen production structure under different carbon emission reduction efforts is reflected; by constraining the transmission system, the feasibility of inter-regional hydrogen transmission and the impact of transmission capacity on the transmission path are reflected. Each constraint condition is explained below:

[0069] Renewable energy hydrogen production technology constraints: With the development of water electrolysis hydrogen production technology, the proportion of proton exchange membrane water electrolysis hydrogen production in renewable energy hydrogen production will continue to change. Renewable energy hydrogen production technology constraints are expressed by the following formula:

[0070]

[0071] Among them, β min,t and β max,t They represent the minimum and maximum proportions of hydrogen produced by proton exchange membrane water electrolysis in renewable energy hydrogen production in year t respectively; represents the total amount of hydrogen produced by renewable energy in year t; It represents the total amount of hydrogen produced by proton exchange membrane water electrolysis in year t.

[0072] Renewable energy hydrogen production ratio constraint: With the continuous development of the hydrogen energy industry, the proportion of renewable energy hydrogen production in the future will not be lower than the current proportion, and will continue to rise, with a maximum of no more than 100%. The renewable energy hydrogen production ratio constraint is expressed by the following formula:

[0073]

[0074] Among them, α min,t and α max,t They represent the minimum and maximum proportion of hydrogen production from renewable energy in year t respectively; represents the total national hydrogen production in year t.

[0075] Production-side carbon reduction constraints: In response to the low-carbon transformation of energy, the average CO2 generated by each unit of hydrogen production is 2 Emissions must be controlled within a certain range. The carbon reduction constraint on the production side is expressed by the following formula:

[0076]

[0077] in, and They represent the minimum and maximum values ​​of the average carbon emissions from hydrogen production in year t, respectively; represents the average carbon emissions of hydrogen production using traditional hydrogen production technology in year t.

[0078] Transportation system constraints: The single transport capacity of different hydrogen transportation modes between regions is different, and the feasibility of hydrogen transportation between two regions must also be considered. With the continuous increase in the demand for hydrogen energy in the future, the transportation volume will also show an upward trend. Therefore, the transportation system constraints are expressed by the following formula:

[0079] q i,j,k,t ≤BE i,j,k ×V max_k,t ×n i,j,k,t

[0080] Among them, n i,j,k,t represents the number of times or pipelines that hydrogen is transmitted from supply area i to demand area j via transportation mode k in year t; BE i,j,k is a 0-1 variable, which is 1 if the supply area i can transport hydrogen to the demand area j through transportation mode k, otherwise it is 0; V max_k,t It represents the maximum single transport capacity of transport mode k in year t.

[0081]

[0082] Among them, Q d,t They represent the hydrogen demand in year t, ε t It represents the proportion of the total amount of hydrogen transported across regions in the total hydrogen demand in year t.

[0083] Supply and demand balance constraint: The sum of the total hydrogen production and net hydrogen input in each region should be greater than the hydrogen demand in the region. The supply and demand balance constraint is expressed by the following formula:

[0084]

[0085] Among them, Q s,i,t and Q s,j,t represent the hydrogen production of region i and region j in year t respectively; Q d,i,t and Qd,j,t They represent the hydrogen demand in region i and region j in year t respectively.

[0086] S104, solving the optimization model based on a mathematical optimization solver, and determining a hydrogen production strategy corresponding to the minimum total hydrogen production cost using a linear programming method.

[0087] Here, according to the embodiment provided in the present application, the hydrogen energy production strategy includes cost composition, regional hydrogen production, hydrogen production structure, cross-regional transportation volume and transportation route.

[0088] For the above step S104, in the specific implementation, the optimization model is solved based on the mathematical optimization solver, and the hydrogen production strategy corresponding to the minimum total hydrogen production cost can be determined by the linear programming method, and the hydrogen production cost of the target area can be minimized through the hydrogen generation strategy. In this way, not only can the hydrogen production in each region be planned, but also the cross-regional transportation planning of hydrogen energy can be planned, including the transmission mode, transmission path and transmission amount. Here, according to the embodiment provided by the present application, CPLEX in MATLAB is used as a mathematical optimization solver to solve the dynamic linear programming model.

[0089] Specifically, use CPLEX to solve a dynamic linear programming model with specific constraints and objective functions through the following steps:

[0090] The first step is to define the relevant parameters and variables of the model, such as the hydrogen demand in each region, the cost of electrolyzers, system efficiency, and transportation distance between regions; as well as decision variables such as the proportion of hydrogen production from renewable energy and PEM. Use the optimvar function to define decision variables, and you can specify the name, dimension, lower bound, and upper bound of the variable.

[0091] The second step is to construct the objective function of the linear programming problem. That is, the objective function with the minimum cost during the planning period, including the cost of hydrogen production, operation and maintenance, fixed cost, raw material cost and transportation cost. The purpose is to define it through MATLAB's Objective statement, and to obtain a decision-making plan that minimizes the total cost of the hydrogen energy system while satisfying all the constraints of the model.

[0092] The third step is to set constraints. These include renewable energy hydrogen production technology constraints, renewable energy hydrogen production ratio constraints, production-side carbon emission constraints, transportation system constraints, and supply-demand balance constraints. Each constraint condition is added to the optimization problem object using the Constraints property, and the functional relationship of each part is clarified to ensure that the optimal solution of the model can meet all restriction requirements.

[0093] The fourth step is to select a suitable solver. After the model is built, use a suitable solver to solve the problem. For linear programming problems, you can choose CPLEX and other suitable solvers, which have high efficiency and stability when dealing with linear programming problems.

[0094] The fifth step is to solve the model. Solve the model through the SOLVE command and call the CPLEX solver, which will calculate and solve according to the set model and output relevant results.

[0095] The prediction method of hydrogen production strategy provided in the embodiment of the present application first calculates the hydrogen demand of each sub-region within the target region based on the total hydrogen demand of the target region; then calculates the renewable energy hydrogen production cost of each sub-region based on the hydrogen demand of each sub-region; the renewable energy hydrogen production cost of each sub-region is input into a pre-constructed optimization model, and the total minimum hydrogen production cost corresponding to the target region is calculated with the goal of minimizing the total hydrogen production cost; wherein the optimization model includes a hydrogen production cost minimization objective function and multiple constraints, and the hydrogen production cost minimization objective function is used to calculate the total minimum hydrogen production cost; finally, the optimization model is solved based on a mathematical optimization solver, and the hydrogen production strategy corresponding to the total minimum hydrogen production cost is determined using a linear programming method.

[0096] This application constructs an electricity-hydrogen-carbon coupled hydrogen energy optimization model, and studies the impact of changes in hydrogen production costs in each sub-region within the target area on hydrogen production decisions, taking into account technological equipment progress, electricity cost reduction, and cross-regional transmission of hydrogen energy. This optimization model takes into account the hydrogen production and transportation links, and combined with environmental and policy constraints, it can dynamically simulate the operation path of hydrogen energy interconnection in each region, and predict the hydrogen production decisions, inter-regional hydrogen energy scheduling, and future hydrogen energy production structure of each region from the perspective of hydrogen production technology and production costs. The generated hydrogen energy generation strategy is used to minimize the hydrogen production cost in the target area, improve the accuracy of the generated hydrogen energy generation strategy, and make the simulation process and results more credible. The impact of existing hydrogen energy industry policies on society, economy, environment, energy, etc. is fully simulated, and through scenario settings, the impact and effect of green development of the hydrogen energy industry in the medium and long term can be predicted. Not only can hydrogen energy production in each region be planned, but also cross-regional transportation planning of hydrogen energy can be planned, including transmission mode, transmission path, and transmission volume.

[0097] Combined with the current hydrogen energy policy objectives, the potential for relevant technological development, the distribution characteristics of renewable energy, and cost trends, this paper combines the optimal layout of hydrogen energy with existing planning, explores the changes in hydrogen energy production, cross-regional transmission, and hydrogen energy production structure in various regions under the condition of changes in hydrogen production costs, and proposes a low-carbon, clean, and economically efficient hydrogen energy development layout plan. A systematic, comprehensive, scientific, reasonable, detailed, specific, and highly operational system optimization and overall planning of regional hydrogen energy production structures and transmission routes is carried out to provide decision-making references for breaking through the bottleneck of hydrogen energy industry development and building a long-distance, low-cost hydrogen energy transportation system.

[0098] See also Figure 2 , Figure 2 This is a schematic diagram of the structure of a prediction device for a hydrogen production strategy provided in an embodiment of the present application. Figure 2 As shown in , the prediction device 200 includes:

[0099] A hydrogen demand calculation module 201 is used to calculate the hydrogen demand of each sub-area in the target area based on the total hydrogen demand of the target area;

[0100] A hydrogen production cost calculation module 202 is used to calculate the cost of hydrogen production from renewable energy in each sub-region using a hydrogen levelized cost calculation formula;

[0101] The total hydrogen production minimum cost calculation module 203 is used to input the hydrogen demand of each sub-region and the cost of hydrogen production from renewable energy into a pre-built optimization model, and to calculate the total hydrogen production minimum cost corresponding to the target region with the goal of minimizing the total hydrogen production cost; wherein the optimization model includes a hydrogen production cost minimization objective function and multiple constraints, and the hydrogen production cost minimization objective function is used to calculate the total hydrogen production minimum cost;

[0102] The production strategy prediction module 204 is used to solve the optimization model based on a mathematical optimization solver, and determine the hydrogen production strategy corresponding to the minimum total hydrogen production cost using a linear programming method.

[0103] Furthermore, when the hydrogen demand calculation module 201 is used to calculate the hydrogen demand of each sub-area in the target area based on the total hydrogen demand of the target area, the hydrogen demand calculation module 201 is also used to:

[0104] For each sub-region, determine the hydrogen energy demand weight corresponding to the sub-region;

[0105] The hydrogen demand weight is multiplied by the total hydrogen demand of the target area to obtain the hydrogen demand of the sub-area.

[0106] Furthermore, the multiple constraints include renewable energy hydrogen production technology constraints, renewable energy hydrogen production proportion constraints, production-side carbon emission reduction constraints, transportation system constraints and supply and demand balance constraints.

[0107] Furthermore, the hydrogen production cost calculation module 202 is further used to calculate the renewable energy hydrogen production cost of each sub-region by the following formula:

[0108]

[0109] Among them, P i,v,t represents the renewable energy hydrogen production cost of the i-th sub-region through the v-th renewable energy hydrogen production technology in the t-th year; LHV is the lower heating value of hydrogen energy; η v,t is the efficiency of the hydrogen production technology system of the vth renewable energy in the tth year; r is the depreciation rate; a is the life cycle of the hydrogen production system; OPEX is the operating cost; CAPEX is the v,t is the fixed cost of hydrogen production technology using the vth renewable energy source in year t; τ v,t E is the number of transport hours of the vth renewable energy hydrogen production technology in year t; i,t is the renewable energy generation cost of the ith sub-region in year t.

[0110] Furthermore, the hydrogen production cost minimization objective function is expressed by the following formula:

[0111]

[0112] Among them, TC t represents the total cost of hydrogen production in year t; i and j represent regions; k represents the mode of transportation of hydrogen; represents the hydrogen production in region i in year t; represents the unit hydrogen production cost of region i in year t; q i,j,k,t represents the amount of hydrogen transmitted from region i to region j through transmission mode k in year t; C trans represents the unit cost of hydrogen transportation; α t represents the proportion of renewable energy hydrogen production in hydrogen production in year t; v represents different renewable energy hydrogen production technologies; P′ t represents the cost of hydrogen production using traditional energy in year t.

[0113] See also Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 3 As shown in , the electronic device 300 includes a processor 310 , a memory 320 and a bus 330 .

[0114] The memory 320 stores machine-readable instructions executable by the processor 310. When the electronic device 300 is running, the processor 310 communicates with the memory 320 via the bus 330. When the machine-readable instructions are executed by the processor 310, the above-mentioned Figure 1 The steps of the method for predicting the hydrogen energy production strategy in the method embodiment shown, and the specific implementation method can be found in the method embodiment, which will not be repeated here.

[0115] The present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the computer program can execute the above-mentioned Figure 1 The steps of the method for predicting the hydrogen energy production strategy in the method embodiment shown, and the specific implementation method can be found in the method embodiment, which will not be repeated here.

[0116] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0117] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0118] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0119] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0120] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application can essentially be embodied in the form of a software product, or in other words, the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0121] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the above-mentioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for predicting hydrogen production strategy, characterized in that: The prediction method comprises: Calculating the hydrogen demand of each sub-area within the target area based on the total hydrogen demand of the target area; The cost of hydrogen production from renewable energy in each sub-region is calculated using the hydrogen levelized cost calculation formula; The hydrogen demand and renewable energy hydrogen production cost of each sub-region are input into a pre-built optimization model, and the total hydrogen production minimum cost corresponding to the target region is calculated with the goal of minimizing the total hydrogen production cost; wherein the optimization model includes a hydrogen production cost minimization objective function and multiple constraints, and the hydrogen production cost minimization objective function is used to calculate the total hydrogen production minimum cost; The optimization model is solved based on a mathematical optimization solver, and a hydrogen production strategy corresponding to the minimum total hydrogen production cost is determined using a linear programming method.

2. The prediction method according to claim 1, characterized in that: The calculating of the hydrogen demand of each sub-area in the target area based on the total hydrogen demand of the target area includes: For each sub-region, determine the hydrogen energy demand weight corresponding to the sub-region; The hydrogen demand weight is multiplied by the total hydrogen demand of the target area to obtain the hydrogen demand of the sub-area.

3. The prediction method according to claim 1, characterized in that: The multiple constraints include renewable energy hydrogen production technology constraints, renewable energy hydrogen production proportion constraints, production-side carbon emission reduction constraints, transportation system constraints and supply and demand balance constraints.

4. The prediction method according to claim 1, characterized in that: The cost of renewable energy hydrogen production in each sub-region is calculated using the following formula: Among them, P i,v,t represents the renewable energy hydrogen production cost of the i-th sub-region through the v-th renewable energy hydrogen production technology in the t-th year; LHV is the lower heating value of hydrogen energy; η v,t is the efficiency of the hydrogen production technology system of the vth renewable energy in the tth year; r is the depreciation rate; a is the life cycle of the hydrogen production system; OPEX is the operating cost; CAPEX is the v,t is the fixed cost of hydrogen production technology using the vth renewable energy source in year t; τ v,t E is the number of transport hours of the vth renewable energy hydrogen production technology in year t; i,t is the renewable energy generation cost in the ith sub-region in year t.

5. The prediction method according to claim 4, characterized in that: The hydrogen production cost minimization objective function is expressed by the following formula: Among them, TC t represents the total cost of hydrogen production in year t; i and j represent regions; k represents the mode of transportation of hydrogen; represents the hydrogen production in region i in year t; represents the unit hydrogen production cost of region i in year t; q i,j,k,t represents the amount of hydrogen transmitted from region i to region j through transmission mode k in year t; C trans represents the unit cost of hydrogen transportation; α t represents the proportion of renewable energy hydrogen production in hydrogen production in year t; v represents different renewable energy hydrogen production technologies; P t ′ represents the cost of hydrogen production using traditional energy in year t.

6. A prediction device for hydrogen production strategy, characterized in that: The prediction device comprises: A hydrogen demand calculation module, used to calculate the hydrogen demand of each sub-area within the target area based on the total hydrogen demand of the target area; A hydrogen production cost calculation module is used to calculate the cost of hydrogen production from renewable energy in each sub-region using the hydrogen levelized cost calculation formula; The total hydrogen production minimum cost calculation module is used to input the hydrogen demand of each sub-region and the cost of hydrogen production from renewable energy into a pre-built optimization model, and to calculate the total hydrogen production minimum cost corresponding to the target region with the goal of minimizing the total hydrogen production cost; wherein the optimization model includes a hydrogen production cost minimization objective function and multiple constraints, and the hydrogen production cost minimization objective function is used to calculate the total hydrogen production minimum cost; The production strategy prediction module is used to solve the optimization model based on a mathematical optimization solver, and determine the hydrogen production strategy corresponding to the minimum total hydrogen production cost using a linear programming method.

7. The prediction device according to claim 6, characterized in that When the hydrogen demand calculation module is used to calculate the hydrogen demand of each sub-area in the target area based on the total hydrogen demand of the target area, the hydrogen demand calculation module is also used to: For each sub-region, determine the hydrogen energy demand weight corresponding to the sub-region; The hydrogen demand weight is multiplied by the total hydrogen demand of the target area to obtain the hydrogen demand of the sub-area.

8. The prediction device according to claim 6, characterized in that The multiple constraints include renewable energy hydrogen production technology constraints, renewable energy hydrogen production proportion constraints, production-side carbon emission reduction constraints, transportation system constraints and supply and demand balance constraints.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and the machine-readable instructions are executed by the processor to execute the steps of the method for predicting the hydrogen energy production strategy as described in any one of claims 1 to 5.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for predicting a hydrogen energy production strategy as claimed in any one of claims 1 to 5 are executed.

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