Configuration method, equipment and medium of hydrogen production system coupled with wind energy and solar energy

Abstract

The embodiment of the invention particularly relates to a configuration method of a hydrogen production system coupling wind energy and solar energy, equipment and a medium. According to the method, on the basis of constraint information, external environment parameter information, hydrogen demand quantity information and real-time consumed power of an electrolytic cell module at each moment in a future preset time length, a multi-target genetic algorithm is adopted to solve a target function; the configuration installed capacity of the power generation module, the configuration upper limit load capacity of the energy storage module and the configuration rated power of the energy storage module are obtained. The solved configuration installed capacity of the power generation module, the configuration upper limit charge capacity of the energy storage module and the configuration rated power of the energy storage module not only can ensure the electrolytic power requirement of the electrolytic tank corresponding to the hydrogen demand quantity information, but also can ensure that the total construction cost of the hydrogen production system is lower; and when the power generation module and the energy storage module jointly supply electrolytic power to the electrolytic bath, the electric quantity loss is smaller.

Description

Technical Field

[0001] Multiple embodiments of this specification relate to the technical field of system configuration, and specifically to a configuration method, equipment, and medium for a hydrogen production system coupled with wind energy and solar energy. Background Art

[0002] In recent years, the demand for energy in countries around the world has continued to rise, and energy consumption has continued to increase. However, the reserves of traditional fossil energy are decreasing, and the contradiction between insufficient energy supply capacity and strong energy demand continues to intensify. At the same time, the problem of global warming caused by the burning of fossil energy is also becoming increasingly serious. As the main consumer of fossil energy, the heavy chemical industry's carbon emissions and carbon-containing byproducts in its production process are not conducive to the realization of green and low-carbon goals.

[0003] Existing methanol and methane production technologies rely heavily on raw materials such as natural gas and coal, which results in a large amount of carbon emissions during the production process, which is not conducive to the realization of green and low-carbon goals. In order to solve the carbon emission problem, renewable energy can be introduced into the production process. However, the inherent randomness and fluctuation of renewable energy will affect its power generation, thus having a negative impact on the production process.

[0004] In order to achieve the goal of green and low-carbon production, there is currently an improved methane and methanol production method, in which external hydrogen is introduced to reduce the carbon content in the coal chemical process. In order to ensure that the introduced hydrogen does not cause carbon emissions, renewable energy can be used to generate electricity, and then water electrolysis can be used to produce hydrogen to ensure that the hydrogen used in the coal chemical process is green hydrogen. In addition, the byproduct oxygen produced by water electrolysis is also used in the coal processing process, and water-coal slurry gasification is carried out together with the raw coal to achieve the production of synthesis gas with carbon monoxide and hydrogen as the main components. This processing technology itself has the advantages of stable combustion and low pollution emissions. Compared with traditional methods, it is more energy-saving and environmentally friendly, and the production process effectively utilizes the byproducts of water electrolysis to produce hydrogen, avoiding waste of resources. However, due to environmental factors, the power generation of renewable energy fluctuates, so it is impossible to always ensure that the power generation is equal to the power required for electrolysis. Therefore, an additional energy storage module is required under this method to store the excess power generated by the power generation module, or when the power generated by the power generation module is not enough for the electrolyzer to perform electrolysis, the excess power stored is used to power the electrolyzer for electrolysis. There is a large gap in the initial construction costs required for renewable energy power generation modules with different installed capacities and energy storage modules with different upper load limits and different rated powers; in addition, when renewable energy power generation modules with different installed capacities and energy storage modules with different upper load limits and different rated powers are jointly used to supply power to the electrolysis module, the amount of resource abandonment caused is also different. Therefore, before applying this method to produce methane and methanol, it is necessary to effectively configure the installed capacity of the renewable energy power generation module and the upper load limit and rated power of the energy storage module. Summary of the invention

[0005] The embodiments of this specification provide a configuration method, device, and medium for a hydrogen production system that couples wind energy and solar energy.

[0006] The technical solution is as follows:

[0007] In the first aspect, the embodiments of this specification provide a configuration method for a hydrogen production system coupled with wind energy and solar energy, wherein the hydrogen production system includes a power generation module, an energy storage module, and an electrolyzer module, wherein the power generation module is connected to the energy storage module and the electrolyzer module respectively, and the energy storage module is also connected to the electrolyzer module, wherein the power generation module is used to generate electric energy for electrolysis in the electrolyzer, and the energy storage module is used to store excess electric energy generated by the power generation module, and the energy storage module is also used to use the excess electric energy stored in the electrolyzer to power electrolysis when the electric energy generated by the power generation module is insufficient for electrolysis in the electrolyzer, and the configuration method includes:

[0008] Obtain the external environment parameter information and hydrogen demand information at each moment within the future preset time length;

[0009] Based on the hydrogen demand information at each moment within the future preset time length, determine the real-time power consumption of the electrolyzer module at each moment within the future preset time length;

[0010] Establish an objective function with the total system construction cost and resource abandonment rate as optimization targets;

[0011] Obtain constraint information, and use a multi-objective genetic algorithm to solve the objective function based on the constraint information and the external environmental parameter information, hydrogen demand information, and real-time power consumption of the electrolyzer module at each moment within a preset time length in the future, so as to obtain the configured installed capacity of the power generation module, the configured upper limit load of the energy storage module, and the configured rated power of the energy storage module;

[0012] The constraint information includes:

[0013] At each moment within a preset time length in the future, the maximum power supply of the system obtained by the power generation power of the power generation module, the real-time charge of the energy storage module, the time interval between the current moment and the next moment, and the configured rated power of the energy storage module is greater than or equal to the real-time power consumption of the electrolyzer module;

[0014] At each moment within a preset time period in the future, the real-time charge of the energy storage module is less than or equal to the configured upper limit charge;

[0015] At each moment within a preset time period in the future, the real-time charging and discharging power of the energy storage module is less than or equal to the configured rated power;

[0016] The total construction cost of the system includes the construction cost of the power generation module and the construction cost of the energy storage module. The construction cost of the power generation module is obtained based on the configured installed capacity of the power generation module, and the construction cost of the energy storage module is obtained based on the configured upper limit load and the configured rated power of the energy storage module.

[0017] The resource abandonment rate is calculated based on the configured installed capacity, the external environmental parameter information at each moment within a future preset time length, the real-time charge of the energy storage module at each moment within a future preset time length, and the real-time power consumption of the electrolyzer module.

[0018] As a preferred solution, the power generation module includes a wind power generation unit and a solar power generation unit, and the configured installed capacity includes the installed capacity of the wind power generation unit and the installed capacity of the solar power generation unit;

[0019] The construction cost of the power generation module includes the construction cost of the wind power generation unit and the construction cost of the solar power generation unit;

[0020] The construction cost of the wind power generation unit is obtained based on the installed capacity of the wind power generation unit;

[0021] The solar power generation unit construction cost is obtained based on the installed capacity of the solar power generation unit.

[0022] As a preferred solution, the external environment parameter information includes wind speed information and solar radiation information;

[0023] The power generation power of the power generation module is the sum of the power generation power of the wind power generation unit and the power generation power of the solar power generation unit;

[0024] The power generation power of the wind power generation unit is calculated based on wind speed information and installed capacity of the wind power generation unit;

[0025] The power generation power of the solar power generation unit is calculated based on solar irradiation information and the installed capacity of the solar power generation unit.

[0026] As a preferred solution, the real-time power consumption of the electrolyzer module at each moment within the future preset time length is equal to the electrolysis power required by the electrolyzer module to generate the hydrogen demand at that moment.

[0027] As a preferred solution, the calculation formula for the resource abandonment rate is:

[0028]

[0029] Among them, L represents the resource abandonment rate, P loss Indicates the amount of resource abandonment, P use represents the total amount of power generation, T represents the total number of moments within the preset time length in the future, and P W(i) represents the power generation of the wind power generation unit at the i-th moment in the future, ρ W Represents the energy conversion efficiency of the wind power generation unit, P P (i) represents the power generation of the solar power generation unit at the i-th moment in the future, ρ P Represents the energy conversion efficiency of the solar power generation unit, P EL (i) represents the real-time power consumption of the electrolyzer module at the future i-th moment, Y(i) represents the time interval between the future i-th moment and the i+1-th moment, α represents the energy conversion efficiency of the energy storage module, E B (i+1) represents the real-time charge of the energy storage module at the future i+1th moment, E B (i) represents the real-time charge of the energy storage module at the i-th moment in the future. The resource abandonment amount is calculated for the moment when the power generation power of all power generation modules within a preset time length in the future is greater than the real-time power consumption of the electrolyzer module.

[0030] As a preferred solution:

[0031] P W (i) = f(S i )*P W ;

[0032] P P (i) = X(T i )*P P ;

[0033] Among them, S i represents the wind speed at the i-th moment in the future, T i represents the solar radiation at the i-th moment in the future, f(·) represents the wind speed energy efficiency conversion ratio function, X(·) represents the solar radiation energy efficiency conversion ratio function, P W represents the installed capacity of wind power generation unit, P P Indicates the installed capacity of solar power generation units.

[0034] As a preferred solution, a wind speed energy efficiency conversion ratio function is constructed, including:

[0035] Acquire a first data set, wherein the first data set includes a plurality of first data subsets, each of which includes power generation data of a wind power generation unit under different wind speed environmental conditions at an installed capacity of a corresponding wind power generation unit;

[0036] Constructing a first multiple regression function, wherein the independent variables of the first multiple regression function are wind speed and installed capacity of wind power generation units, and the dependent variable of the first multiple regression function is wind speed energy efficiency conversion ratio;

[0037] The first multivariate regression function is solved based on the first data set to construct a wind speed energy efficiency conversion ratio function.

[0038] As a preferred solution, a solar energy efficiency conversion ratio function is constructed, including:

[0039] Acquire a second data set, wherein the second data set includes a plurality of second data subsets, each of which includes power generation data of a solar power generation unit under different solar irradiation environment conditions at the installed capacity of the corresponding solar power generation unit;

[0040] constructing a second multiple regression function, wherein the independent variables of the second multiple regression function are solar irradiation and installed capacity of solar power generation units, and the dependent variable of the second multiple regression function is solar energy efficiency conversion ratio;

[0041] The second multivariate regression function is solved based on the second data set to construct a solar energy efficiency conversion ratio function.

[0042] In a second aspect, an embodiment of the present specification provides an electronic device, comprising a processor and a memory; the processor is connected to the memory; the memory is used to store executable program code; the processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to execute the steps described in the first aspect of the above embodiment.

[0043] In a third aspect, an embodiment of this specification provides a computer storage medium, wherein the computer storage medium stores a plurality of instructions, wherein the instructions are suitable for being loaded by a processor and executing the steps described in the first aspect of the above embodiment.

[0044] The beneficial effects brought by the technical solutions provided by some embodiments of this specification include at least:

[0045] Based on the constraint information and the external environmental parameter information at each moment within the preset time length in the future, the hydrogen demand information, and the real-time power consumption of the electrolyzer module, a multi-objective genetic algorithm is used to solve the objective function to obtain the configured installed capacity of the power generation module, the configured upper limit load of the energy storage module, and the configured rated power of the energy storage module. The solved configured installed capacity of the power generation module, the configured upper limit load of the energy storage module, and the configured rated power of the energy storage module can not only ensure the electrolysis power requirements of the electrolyzer corresponding to the hydrogen demand information, but also ensure that the total construction cost of the hydrogen production system is lower, and the power loss is smaller when the power generation module and the energy storage module jointly supply the electrolysis power of the electrolyzer. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0047] Figure 1 It is a flow chart of a configuration method of a hydrogen production system coupled with wind energy and solar energy provided in an embodiment of this specification.

[0048] Figure 2 It is a structural schematic diagram of a configuration system of a hydrogen production system coupled with wind energy and solar energy provided in an embodiment of this specification.

[0049] Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of this specification. DETAILED DESCRIPTION

[0050] The technical solutions in the embodiments of this specification will be described clearly and completely below in conjunction with the drawings in the embodiments of this specification.

[0051] The terms "first", "second", "third", etc. in the description and claims of this specification and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0052] The following description provides examples and does not limit the scope, applicability or examples set forth in the claims. Changes may be made to the functions and arrangements of the elements described without departing from the scope of the present specification. Various processes or components may be appropriately omitted, substituted or added to each example. For example, the described method may be performed in an order different from the order described, and various steps may be added, omitted or combined. In addition, features described with respect to some examples may be combined in other examples.

[0053] Before explaining the configuration method of the hydrogen production system coupled with wind energy and solar energy through multiple embodiments of this specification, the methanol and methane production technology is first explained:

[0054] Methanol preparation technology:

[0055] Methanol production is generally carried out using natural gas and coal as raw materials.

[0056] The process of natural gas to methanol is as follows: natural gas and steam undergo a conversion reaction to generate a mixed gas with hydrogen, carbon monoxide and carbon dioxide as the main components; then a methanol synthesis reaction is carried out, and carbon monoxide, carbon dioxide and hydrogen generate methanol under specific temperature and pressure conditions. The reaction process is as follows:

[0057] CO2+3H2→CH3OH+H2O

[0058] C0+2H2→CH3OH

[0059] The coal-to-methanol process is as follows: first, the raw coal is converted into coal gas through a gasification process, and then the sulfur dioxide and hydrogen sulfide in the coal gas are removed. At this time, the main components of the mixed gas are carbon monoxide, carbon dioxide and hydrogen. At this time, carbon monoxide and hydrogen react to synthesize methane, and then the methane vapor is converted into methanol.

[0060] Methane production technology:

[0061] Methane production generally uses coal as raw material, which reacts with oxygen and water vapor under high temperature and high pressure conditions to obtain synthesis gas. The main components of synthesis gas are carbon monoxide, hydrogen, carbon dioxide, hydrogen sulfide and other gases. After the synthesis gas is purified and impurities are removed, the carbon monoxide and hydrogen in the synthesis gas react under high temperature and high pressure conditions to obtain methane.

[0062] In order to achieve green and low-carbon production goals, there is currently an improved methane and methanol production system, which includes a power generation and hydrogen production part and a coal chemical part.

[0063] The power generation and hydrogen production part (i.e., the hydrogen production system involved in multiple embodiments of this specification) includes a renewable energy power generation module, an energy storage module, and an electrolyzer module. The electricity generated by the renewable energy power generation module is used for electrolysis and hydrogen production in the electrolyzer module, and the renewable energy power generation module also generates electric energy for transmission with the energy storage module. The renewable energy power generation module, the energy storage module, and the electrolyzer module are connected by a power electronic converter. The renewable energy power generation module can be a combination of wind and solar power generation units, a wind power generation unit, or a solar power generation unit. The electrolyzer module adopts a proton exchange membrane electrolyzer, and the electrolyzer module is respectively connected to the renewable energy power generation module and the energy storage module. When the power generated by the renewable energy power generation module is insufficient, the energy storage module supplements the power; when the power generated by the renewable energy power generation module is excessive, the energy storage module stores the excess power, thereby ensuring a long-term and stable supply of hydrogen and oxygen.

[0064] The coal chemical industry includes a raw gas preparation module, an air separation module, a raw gas purification module, a C0 / H2 cryogenic separation module, a methanol synthesis module, and a methane preparation module. The air separation module is used to collect oxygen from the electrolyzer module and oxygen separated from the air. The raw gas preparation module is used to make the coal raw material and the oxygen from the air separation module undergo a water-coal slurry gasification reaction to obtain a raw gas whose main components are carbon monoxide and hydrogen. The raw gas purification unit is used to remove impurities and desulfurize the raw gas to obtain synthesis gas. The C0 / H2 cryogenic separation module is used to separate carbon monoxide and hydrogen in the synthesis gas. The methanol synthesis module is used to synthesize methanol based on the synthesis gas from the raw gas purification module. The methane preparation module is used to prepare methane based on the synthesis gas from the raw gas purification module. Among them, the methanol synthesis module includes a synthesis gas compression link, a circulating gas recovery link, and a hydrogen recovery link; the methane preparation module includes a high-temperature methanation link and an LNG refrigeration link. The air separation module includes an air compression link, a cooling link, and a distillation link.

[0065] The workflow of the production system is as follows:

[0066] The power generation module generates electricity to generate electricity and provides electricity for the electrolyzer module to electrolyze water to produce oxygen and hydrogen. The oxygen from the electrolyzer module passes through the air separation module and is then gasified with the coal raw material in the raw gas preparation link through water-coal slurry to obtain raw gas. The raw gas is removed from impurities through the raw gas purification module to obtain synthesis gas. The synthesis gas is used for the extraction of carbon monoxide and hydrogen in the C0 / H2 cryogenic separation module, methanol synthesis in the methanol synthesis module, and methane preparation in the methane preparation module. The hydrogen extracted from the C0 / H2 cryogenic separation module and the hydrogen obtained by electrolysis of water are used together for methanol synthesis and methane preparation, and the carbon monoxide obtained from the C0 / H2 cryogenic separation module is used to obtain acetic acid. The synthesis gas passes through the methanol synthesis module to obtain crude methanol, in which the unused synthesis gas and hydrogen are recovered. The synthesis gas passes through the methane preparation link to obtain liquid natural gas.

[0067] Reference Figure 1 As shown, Figure 1 A flow chart of a configuration method of a hydrogen production system coupled with wind energy and solar energy provided in an embodiment of this specification, wherein the hydrogen production system comprises a power generation module, an energy storage module, and an electrolyzer module, wherein the power generation module is respectively connected to the energy storage module and the electrolyzer module, and the energy storage module is also connected to the electrolyzer module, wherein the power generation module is used to generate electric energy for electrolysis in the electrolyzer, and the energy storage module is used to store excess electric energy generated by the power generation module, and the energy storage module is also used to power the electrolyzer for electrolysis using the excess electric energy stored when the electric energy generated by the power generation module is insufficient for electrolysis in the electrolyzer, wherein the configuration method may at least comprise the following steps:

[0068] Step 102: Obtain external environmental parameter information and hydrogen demand information at each moment within a preset time length in the future;

[0069] Step 104: based on the hydrogen demand information at each moment within the future preset time length, determine the real-time power consumption of the electrolyzer module at each moment within the future preset time length;

[0070] Step 106: Establish an objective function with the total system construction cost and resource abandonment rate as optimization targets, wherein the objective function aims to minimize the sum of the normalized total system construction cost and the normalized resource abandonment rate;

[0071] Step 108: Obtain constraint information, and use a multi-objective genetic algorithm to solve the objective function based on the constraint information and the external environmental parameter information, hydrogen demand information, and real-time power consumption of the electrolyzer module at each moment within a preset time length in the future, so as to obtain the configured installed capacity of the power generation module, the configured upper limit load of the energy storage module, and the configured rated power of the energy storage module;

[0072] The constraint information includes:

[0073] Constraint 1: At each moment within a preset time length in the future, the maximum power supply of the system obtained by the power generation power of the power generation module, the real-time charge of the energy storage module, the time interval between the current moment and the next moment, and the configured rated power of the energy storage module is greater than or equal to the real-time power consumption of the electrolyzer module;

[0074] Constraint 2: At each moment within a preset time period in the future, the real-time charge of the energy storage module is less than or equal to the configured upper limit charge;

[0075] Constraint 3: At each moment within a preset time period in the future, the real-time charging and discharging power of the energy storage module is less than or equal to the configured rated power;

[0076] The total construction cost of the system includes the construction cost of the power generation module and the construction cost of the energy storage module. The construction cost of the power generation module is obtained based on the configured installed capacity of the power generation module, and the construction cost of the energy storage module is obtained based on the configured upper limit load and the configured rated power of the energy storage module.

[0077] The resource abandonment rate is calculated based on the configured installed capacity, the external environmental parameter information at each moment within a future preset time length, the real-time charge of the energy storage module at each moment within a future preset time length, and the real-time power consumption of the electrolyzer module.

[0078] Specifically, the maximum power supply power of the system is obtained from the power generation power of the power generation module, the real-time charge of the energy storage module, the time interval between the current moment and the next moment, and the configured rated power of the energy storage module, including:

[0079] Based on the real-time charge of the energy storage module and the time interval between the current moment and the next moment, obtain the first maximum output power of the energy storage module;

[0080] Based on the first maximum output power of the energy storage module and the configured rated power of the energy storage module, obtaining the second maximum output power of the energy storage module;

[0081] Based on the power generation power of the power generation module and the second maximum output power of the energy storage module, the maximum power supply power of the system is obtained.

[0082] More specifically, obtaining the second maximum output power of the energy storage module based on the first maximum output power of the energy storage module and the configured rated power of the energy storage module includes:

[0083] When the first maximum output power is greater than the configured rated power, the configured rated power is used as the second maximum output power;

[0084] When the first maximum output power is less than the configured rated power, the first maximum output power is used as the second maximum output power.

[0085] More specifically, the maximum power supply power of the system is obtained based on the power generation power of the power generation module and the second maximum output power of the energy storage module, specifically by summing the power generation power of the power generation module and the second maximum output power of the energy storage module to obtain the maximum power supply power of the system.

[0086] For constraint 1, several examples are given to illustrate:

[0087] Example 1: Assume that the time interval between the current moment and the next moment is 1 hour, and assume that at the current moment, the power generation power of the power generation module is 5kw, the real-time power consumption of the electrolyzer module is 20kw, the real-time charge of the energy storage module is 10kwh, and the configured rated power of the energy storage module is 10kw. At this time, the maximum power supply power of the system obtained by the power generation power of the power generation module, the real-time charge of the energy storage module, the time interval between the current moment and the next moment, and the configured rated power of the energy storage module is 15kw, which is less than the real-time power consumption of the electrolyzer module of 20kw.

[0088] Example 2: Assume that the time interval between the current moment and the next moment is 1 hour, and assume that at the current moment, the power generation power of the power generation module is 10kw, the real-time power consumption of the electrolyzer module is 20kw, the real-time charge of the energy storage module is 10kwh, and the configured rated power of the energy storage module is 10kw. At this time, the maximum power supply power of the system obtained by the power generation power of the power generation module, the real-time charge of the energy storage module, the time interval between the current moment and the next moment, and the configured rated power of the energy storage module is 20kw, which is equal to the real-time power consumption of the electrolyzer module of 20kw.

[0089] Example 3: Assume that the time interval between the current moment and the next moment is 1 hour, and assume that at the current moment, the power generation power of the power generation module is 15kw, the real-time power consumption of the electrolyzer module is 20kw, the real-time charge of the energy storage module is 10kwh, and the configured rated power of the energy storage module is 10kw. At this time, the maximum power supply power of the system obtained by the power generation power of the power generation module, the real-time charge of the energy storage module, the time interval between the current moment and the next moment, and the configured rated power of the energy storage module is 25kw, which is greater than the real-time power consumption of the electrolyzer module of 20kw.

[0090] That is, the conditions described in Example 2 and Example 3 should be met during the solution process.

[0091] It should be noted that when considering the energy conversion efficiency of the power generation module, the energy conversion efficiency must also be considered in the calculation process of the maximum power supply power. Taking Example 2 as an example, assuming that the energy conversion efficiency of the power generation module is 0.9, the maximum power supply power of the system is 19kw, which is less than the real-time power consumption of the electrolyzer module of 20kw (Note: The same is true when considering the energy conversion efficiency of the energy storage module, which will not be elaborated here).

[0092] Based on the constraint information and the external environmental parameter information at each moment within the preset time length in the future, the hydrogen demand information, and the real-time power consumption of the electrolyzer module, a multi-objective genetic algorithm is used to solve the objective function to obtain the configured installed capacity of the power generation module, the configured upper limit load of the energy storage module, and the configured rated power of the energy storage module. The solved configured installed capacity of the power generation module, the configured upper limit load of the energy storage module, and the configured rated power of the energy storage module can not only ensure the electrolysis power requirements of the electrolyzer corresponding to the hydrogen demand information, but also ensure that the total construction cost of the hydrogen production system is lower, and the power loss is smaller when the power generation module and the energy storage module jointly supply the electrolysis power of the electrolyzer.

[0093] Based on the above constraint information and the external environment parameter information and hydrogen demand information at each moment within the future preset time length, the NSGA-II algorithm is used to solve the objective function. The specific steps are as follows:

[0094] Initialize the population, set the initial population size to N, the crossover probability and mutation probability to θ and μ respectively, and set the maximum number of iterations to max_N;

[0095] Randomly generate the initial population so that it is randomly distributed in the entire solution space;

[0096] Fast non-dominated sorting: Calculate the number of dominated solutions and the number of dominated solutions for each solution according to the objective function, and perform Pareto ranking until all solutions are divided;

[0097] Crowding calculation and sorting: For the two objective functions, the crowding degree of each Pareto level solution is calculated, and then the crowding degree is summed and sorted;

[0098] Generate a generation of population through selection, crossover and mutation: Use binary tournament method to implement selection operation, randomly select N / 2 solutions from all solutions and compare fitness values, select the one with the best fitness value to enter the next population, repeat this step many times until a new solution space with a population of N is obtained; use simulated binary method to implement crossover operation; use polynomial mutation method to implement mutation operation;

[0099] Merge the first generation population with the initial population;

[0100] Perform fast non-dominated sorting on the merged population, calculate the crowding degree of the solutions in each non-dominated layer, and select appropriate solutions to form a new parent population based on the non-dominated relationship and the crowding degree results of each solution;

[0101] Generate a new subpopulation according to the corresponding steps and methods above;

[0102] Merge the new parent population and child population, and select the appropriate solution based on the objective function value of each solution after the merger;

[0103] Compare whether the number of iterations reaches the maximum number of iterations max_N. If so, output the result. If less than the maximum number of iterations, repeat the above steps until the number of iterations meets the maximum number of iterations.

[0104] It should be noted that the above steps are only conventional methods of multi-objective genetic algorithm, so they will not be described in detail.

[0105] In one embodiment of the present specification, the power generation module includes a wind power generation unit and a solar power generation unit, and the configured installed capacity includes the installed capacity of the wind power generation unit and the installed capacity of the solar power generation unit;

[0106] The construction cost of the power generation module includes the construction cost of the wind power generation unit and the construction cost of the solar power generation unit;

[0107] The construction cost of the wind power generation unit is obtained based on the installed capacity of the wind power generation unit;

[0108] The solar power generation unit construction cost is obtained based on the installed capacity of the solar power generation unit.

[0109] It is understandable that the unit installed capacity construction cost of the wind power generation unit can be obtained in advance, and the construction cost of the wind power generation unit can be obtained based on the unit installed capacity construction cost and the installed capacity of the wind power generation unit. The same is true for the calculation of the construction cost of the solar power generation unit, which will not be elaborated.

[0110] It should be noted that, for the construction cost of energy storage modules, the cost calculation formula obtained in advance can be used for calculation, and the configuration upper limit load and configuration rated power can be substituted into the cost calculation formula to calculate the construction cost of the energy storage module. And the configuration upper limit load, configuration rated power and energy storage module construction cost should all be positively correlated. That is, the higher the configuration upper limit load, the higher the energy storage module construction cost, and the higher the configuration rated power, the higher the energy storage module construction cost.

[0111] In one embodiment of the present specification, the external environment parameter information includes wind speed information and solar radiation information;

[0112] The power generation power of the power generation module is the sum of the power generation power of the wind power generation unit and the power generation power of the solar power generation unit;

[0113] The power generation power of the wind power generation unit is calculated based on wind speed information and installed capacity of the wind power generation unit;

[0114] The power generation power of the solar power generation unit is calculated based on solar irradiation information and the installed capacity of the solar power generation unit.

[0115] It is understandable that the installed capacity of a wind power generation unit is the power that can be generated by the wind power generation unit under standard conditions, and the power that can be generated by the wind power generation unit varies with wind speed. Therefore, in this embodiment, the power generation of the wind power generation unit is calculated based on wind speed information and the installed capacity of the wind power generation unit. The calculation of the power generation of the solar power generation unit is similar and will not be described in detail. The specific calculation method will be described in detail in the corresponding embodiments below.

[0116] In one embodiment of the present specification, the real-time power consumption of the electrolyzer module at each moment within the future preset time length is equal to the electrolysis power required by the electrolyzer module to generate the hydrogen demand at that moment.

[0117] Therefore, it can be understood that after obtaining the hydrogen demand information at each moment within the future preset time length, the real-time power consumption of the electrolyzer module at each moment within the future preset time length will also be determined.

[0118] It should be noted here that the external environmental parameter information and hydrogen demand information at each moment within a preset time length in the future can be obtained based on historical data and through model prediction, such as a neural network model.

[0119] In one embodiment of the present specification, the resource abandonment rate is calculated as follows:

[0120]

[0121] Among them, L represents the resource abandonment rate, P loss Indicates the amount of resource abandonment, P use represents the total amount of power generation, T represents the total number of moments within the preset time length in the future, and P W (i) represents the power generation of the wind power generation unit at the i-th moment in the future, ρ W Represents the energy conversion efficiency of the wind power generation unit, P P (i) represents the power generation of the solar power generation unit at the i-th moment in the future, ρ P Represents the energy conversion efficiency of the solar power generation unit, P EL (i) represents the real-time power consumption of the electrolyzer module at the future i-th moment, Y(i) represents the time interval between the future i-th moment and the i+1-th moment (note: because there is a unit conversion between power and electricity, it needs to be multiplied by the time interval), α represents the energy conversion efficiency of the energy storage module, E B (i+1) represents the real-time charge of the energy storage module at the future i+1th moment, E B (i) represents the real-time charge of the energy storage module at the i-th moment in the future. The resource abandonment amount is calculated for the moment when the power generation power of all power generation modules within the preset time length in the future is greater than the real-time power consumption of the electrolyzer module, that is, for the resource abandonment amount P loss When performing calculations, the data at the moment when the power generation of the power generation module is less than the real-time power consumption of the electrolyzer module is not taken into account, because in this case the generated electricity is consumed and there is no resource abandonment.

[0122] It is understandable that when the power generation is greater than the real-time power consumption of the electrolyzer module, the excess power will be stored in the energy storage module first. When the energy storage module is supplying excess power for a second time, there is a certain energy conversion efficiency and it cannot achieve 100% utilization. For example, it stores 100kwh of electricity. When it supplies this part of electricity to the electrolyzer module, it may only be able to transmit 98kwh of electricity. 2kwh may be lost during the transmission process. Therefore, the parameter α is set in the above formula. The same is true for wind power generation units and solar power generation units. Therefore, ρ is also set respectively. W , PIt is also understandable that if the energy storage module reaches full charge, the excess power will be directly discarded.

[0123] In one embodiment of the present specification:

[0124] P W (i) = f(S i )*P W ;

[0125] P P (i) = X(T i )*P P ;

[0126] Among them, S i represents the wind speed at the i-th moment in the future, T i represents the solar radiation at the i-th moment in the future, f(·) represents the wind speed energy efficiency conversion ratio function, X(·) represents the solar radiation energy efficiency conversion ratio function, P W represents the installed capacity of wind power generation unit, P P Indicates the installed capacity of solar power generation units.

[0127] In one embodiment of the present specification, constructing a wind speed energy efficiency conversion ratio function includes:

[0128] Acquire a first data set, wherein the first data set includes a plurality of first data subsets, each of which includes power generation data of a wind power generation unit under different wind speed environmental conditions at an installed capacity of a corresponding wind power generation unit;

[0129] Constructing a first multiple regression function, wherein the independent variables of the first multiple regression function are wind speed and installed capacity of wind power generation units, and the dependent variable of the first multiple regression function is wind speed energy efficiency conversion ratio;

[0130] The first multivariate regression function is solved based on the first data set to construct a wind speed energy efficiency conversion ratio function.

[0131] In one embodiment of the present specification, constructing a solar energy efficiency conversion ratio function includes:

[0132] Acquire a second data set, wherein the second data set includes a plurality of second data subsets, each of which includes power generation data of a solar power generation unit under different solar irradiation environment conditions at the installed capacity of the corresponding solar power generation unit;

[0133] constructing a second multiple regression function, wherein the independent variables of the second multiple regression function are solar irradiation and installed capacity of solar power generation units, and the dependent variable of the second multiple regression function is solar energy efficiency conversion ratio;

[0134] The second multivariate regression function is solved based on the second data set to construct a solar energy efficiency conversion ratio function.

[0135] It should be noted that the multiple regression function is a statistical model used to describe the relationship between two or more independent variables (explanatory variables) and a dependent variable (response variable). In mathematical expression, the multiple regression function model includes the multiple linear regression function model and the multiple nonlinear regression function model, among which the multiple linear regression function model can be written in the form of the following equation:

[0136] Y=β0+β1X1+β2X2+...+β n X n +Φ,

[0137] Among them, Y is the dependent variable, which represents the variable we want to predict or explain; X1, X2, ..., X n are independent variables, which are explanatory variables that affect the dependent variable; β0 is the intercept, which is the expected value of the dependent variable when all independent variables are 0; β1, β2, ..., β n is the coefficient of each independent variable, which indicates the expected change in the dependent variable when the corresponding independent variable changes by one unit; Φ is the error term, which indicates the random variation that the model cannot explain.

[0138] In multiple regression, our goal is to find the best coefficients β1, β2, ..., β n In order to be able to accurately predict the dependent variable.

[0139] Therefore, the first multiple regression function is taken as an example for explanation. The first multiple regression function is as follows:

[0140] B=β0+β1S+β2P+Φ,

[0141] Among them, B represents the wind speed energy efficiency conversion ratio; S represents the wind speed; P represents the installed capacity of the wind power generation unit; Φ represents the error term; β0 is the intercept; β1 is the coefficient corresponding to the wind speed; β2 is the coefficient corresponding to the installed capacity of the wind power generation unit.

[0142] Therefore, the first multivariate regression function can be solved based on the first data set to construct a wind speed energy efficiency conversion ratio function.

[0143] The least squares method is usually used to estimate the coefficients of the multivariate linear regression function model.

[0144] Of course, if there is no obvious linear relationship between the independent variables and the dependent variables, a multivariate nonlinear regression function model is needed. The multivariate nonlinear regression function model is similar to the above-mentioned multivariate linear regression function model. The difference is that it allows the relationship between the independent variables and the dependent variables to be expressed by a nonlinear equation, which means that the relationship between one or more independent variables and the dependent variable in the function model is not linear, but follows a nonlinear function, which can be but is not limited to any of the exponential functions, logarithmic functions, and power functions.

[0145] When establishing the multivariate regression function, the corresponding multivariate regression function model can be directly selected according to the actual situation, or the multivariate linear regression function model and the multivariate nonlinear regression function model can be used to solve the function respectively, so as to obtain a wind speed energy efficiency conversion proportional function whose proportional solution is more in line with the actual situation.

[0146] The solution of the multivariate nonlinear regression function model is usually more complicated than the linear model because it involves nonlinear optimization problems. In practical applications, computer algorithms such as the Newton-Raphson method, gradient descent method, genetic algorithm, etc. are usually used to estimate the model parameters.

[0147] As for the second multiple regression function, its solution process is the same as that of the first multiple regression function, so no further details are given. It should also be noted that, similarly, the cost calculation formula of the above energy storage module can also be obtained by solving the multiple regression function.

[0148] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0149] See next Figure 2 , Figure 2 A schematic structural diagram of a configuration system 200 for a hydrogen production system coupled with wind energy and solar energy provided in an embodiment of this specification is shown.

[0150] The configuration system 200 may include at least:

[0151] An acquisition module 201 is used to acquire external environment parameter information and hydrogen demand information at each moment within a preset time length in the future;

[0152] Determination module 202, based on the hydrogen demand information at each moment within the future preset time length, determines the real-time power consumption of the electrolyzer module at each moment within the future preset time length;

[0153] Establishing module 203, establishing an objective function with the total system construction cost and resource abandonment rate as optimization targets;

[0154] The solution module 204 obtains the constraint information, and uses a multi-objective genetic algorithm to solve the objective function based on the constraint information and the external environmental parameter information, hydrogen demand information, and real-time power consumption of the electrolyzer module at each moment within a preset time length in the future, so as to obtain the configured installed capacity of the power generation module, the configured upper limit load of the energy storage module, and the configured rated power of the energy storage module.

[0155] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the configuration system embodiment, since it is basically similar to the configuration method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the configuration method embodiment.

[0156] See also Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of this specification is shown.

[0157] like Figure 3 As shown, the electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 305 , and at least one communication bus 302 .

[0158] The communication bus 302 may be used to realize the connection and communication among the above-mentioned components.

[0159] The user interface 303 may include buttons, and the optional user interface may also include a standard wired interface or a wireless interface.

[0160] The network interface 304 may include, but is not limited to, a Bluetooth module, an NFC module, a Wi-Fi module, etc.

[0161] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts within the entire electronic device 300, and executes various functions and processes data of the electronic device 300 by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Optionally, the processor 301 can be implemented in at least one hardware form of DSP, FPGA, and PLC. The processor 301 can integrate one or a combination of CPU, GPU, modem, etc. Among them, the CPU mainly processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301, and it can be implemented separately through a chip.

[0162] Among them, the memory 305 may include RAM or ROM. Optionally, the memory 305 includes a non-transitory computer-readable medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above various method embodiments, etc. The memory 305 may also be at least one storage device located away from the aforementioned processor 301. The memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module, and a configuration application. The processor 301 can be used to call the configuration program stored in the memory 305 and execute the steps of the configuration method mentioned in the above-mentioned embodiment.

[0163] The embodiments of this specification also provide a computer-readable storage medium, which stores instructions, and when the instructions are executed on a computer or a processor, the computer or the processor executes one or more steps in the above configuration method embodiments. If the component modules of the above electronic device are implemented in the form of software functional units and sold or used as independent products, they can be stored in the computer-readable storage medium.

[0164] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of this specification is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (Digital Subscriber Line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server, data center, etc. that contains one or more available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital versatile disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0165] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other media that can store program codes. In the absence of conflict, the technical features in this embodiment and the implementation scheme can be combined arbitrarily.

[0166] The embodiments described above are merely preferred embodiments of this specification and are not intended to limit the scope of this specification. Without departing from the design spirit of this specification, various modifications and improvements made to the technical solutions of this specification by ordinary technicians in this field should fall within the scope of protection determined by the claims of this specification.

Claims

1. A configuration method for a hydrogen production system coupled with wind energy and solar energy, wherein the hydrogen production system comprises a power generation module, an energy storage module, and an electrolyzer module, wherein the power generation module is connected to the energy storage module and the electrolyzer module respectively, and the energy storage module is also connected to the electrolyzer module, wherein the power generation module is used to generate electric energy for electrolysis in the electrolyzer, and the energy storage module is used to store excess electric energy generated by the power generation module, and the energy storage module is also used to use the excess electric energy stored in the power generation module to power the electrolyzer for electrolysis when the electric energy generated by the power generation module is insufficient for electrolysis in the electrolyzer, wherein the power generation module comprises: Configuration methods include: Obtain the external environment parameter information and hydrogen demand information at each moment within the future preset time length; Based on the hydrogen demand information at each moment within the future preset time length, determine the real-time power consumption of the electrolyzer module at each moment within the future preset time length; Establish an objective function with the total system construction cost and resource abandonment rate as optimization targets; Obtain constraint information, and use a multi-objective genetic algorithm to solve the objective function based on the constraint information and the external environmental parameter information, hydrogen demand information, and real-time power consumption of the electrolyzer module at each moment within a preset time length in the future, so as to obtain the configured installed capacity of the power generation module, the configured upper limit load of the energy storage module, and the configured rated power of the energy storage module; The constraint information includes: At each moment within a preset time length in the future, the maximum power supply of the system obtained by the power generation power of the power generation module, the real-time charge of the energy storage module, the time interval between the current moment and the next moment, and the configured rated power of the energy storage module is greater than or equal to the real-time power consumption of the electrolyzer module; At each moment within a preset time period in the future, the real-time charge of the energy storage module is less than or equal to the configured upper limit charge; At each moment within a preset time period in the future, the real-time charging and discharging power of the energy storage module is less than or equal to the configured rated power; The total construction cost of the system includes the construction cost of the power generation module and the construction cost of the energy storage module. The construction cost of the power generation module is obtained based on the configured installed capacity of the power generation module, and the construction cost of the energy storage module is obtained based on the configured upper limit load and the configured rated power of the energy storage module. The resource abandonment rate is calculated based on the configured installed capacity, the external environmental parameter information at each moment within a future preset time length, the real-time charge of the energy storage module at each moment within a future preset time length, and the real-time power consumption of the electrolyzer module.

2. The configuration method of the hydrogen production system coupled with wind energy and solar energy according to claim 1 is characterized in that: The power generation module includes a wind power generation unit and a solar power generation unit, and the configured installed capacity includes the installed capacity of the wind power generation unit and the installed capacity of the solar power generation unit; The construction cost of the power generation module includes the construction cost of the wind power generation unit and the construction cost of the solar power generation unit; The construction cost of the wind power generation unit is obtained based on the installed capacity of the wind power generation unit; The solar power generation unit construction cost is obtained based on the installed capacity of the solar power generation unit.

3. The configuration method of the hydrogen production system coupled with wind energy and solar energy according to claim 2 is characterized in that: The external environment parameter information includes wind speed information and solar radiation information; The power generation power of the power generation module is the sum of the power generation power of the wind power generation unit and the power generation power of the solar power generation unit; The power generation power of the wind power generation unit is calculated based on wind speed information and installed capacity of the wind power generation unit; The power generation power of the solar power generation unit is calculated based on solar irradiation information and the installed capacity of the solar power generation unit.

4. The configuration method of the hydrogen production system coupled with wind energy and solar energy according to claim 3 is characterized in that: The real-time power consumption of the electrolyzer module at each moment within the future preset time length is equal to the electrolysis power required by the electrolyzer module to generate the hydrogen demand at that moment.

5. The configuration method of the hydrogen production system coupled with wind energy and solar energy according to claim 3 is characterized in that: The calculation formula of the resource abandonment rate is: Among them, L represents the resource abandonment rate, P loss Indicates the amount of resource abandonment, P use represents the total amount of power generation, T represents the total number of moments within the preset time length in the future, and P W (i) represents the power generation of the wind power generation unit at the i-th moment in the future, ρ W Represents the energy conversion efficiency of the wind power generation unit, P P (i) represents the power generation of the solar power generation unit at the i-th moment in the future, ρ P Represents the energy conversion efficiency of the solar power generation unit, P EL (i) represents the real-time power consumption of the electrolyzer module at the future i-th moment, Y(i) represents the time interval between the future i-th moment and the i+1-th moment, α represents the energy conversion efficiency of the energy storage module, E B (i+1) represents the real-time charge of the energy storage module at the future i+1th moment, E B (i) represents the real-time charge of the energy storage module at the i-th moment in the future. The resource abandonment amount is calculated for the moment when the power generation power of all power generation modules within a preset time length in the future is greater than the real-time power consumption of the electrolyzer module.

6. The configuration method of the hydrogen production system coupled with wind energy and solar energy according to claim 5 is characterized in that: P W (i)=f(S i )*P W ; P P (i)=X(T i )*P P ; Among them, S i represents the wind speed at the i-th moment in the future, T i represents the solar radiation at the i-th moment in the future, f(·) represents the wind speed energy efficiency conversion ratio function, X(·) represents the solar radiation energy efficiency conversion ratio function, P W represents the installed capacity of wind power generation unit, P P Indicates the installed capacity of solar power generation units.

7. The configuration method of the hydrogen production system coupled with wind energy and solar energy according to claim 6, characterized in that: Construct the wind speed energy efficiency conversion ratio function, including: Acquire a first data set, wherein the first data set includes a plurality of first data subsets, each of which includes power generation data of a wind power generation unit under different wind speed environmental conditions at an installed capacity of a corresponding wind power generation unit; Constructing a first multiple regression function, wherein the independent variables of the first multiple regression function are wind speed and installed capacity of wind power generation units, and the dependent variable of the first multiple regression function is wind speed energy efficiency conversion ratio; The first multivariate regression function is solved based on the first data set to construct a wind speed energy efficiency conversion ratio function.

8. The configuration method of the hydrogen production system coupled with wind energy and solar energy according to claim 6, characterized in that: Construct a solar energy efficiency conversion ratio function, including: Acquire a second data set, wherein the second data set includes a plurality of second data subsets, each of which includes power generation data of a solar power generation unit under different solar irradiation environment conditions at the installed capacity of the corresponding solar power generation unit; constructing a second multiple regression function, wherein the independent variables of the second multiple regression function are solar irradiation and installed capacity of solar power generation units, and the dependent variable of the second multiple regression function is solar energy efficiency conversion ratio; The second multivariate regression function is solved based on the second data set to construct a solar energy efficiency conversion ratio function.

9. An electronic device, characterized in that: including a processor and a memory; The processor is connected to the memory; The memory is used to store executable program code; The processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to execute the method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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