Optimal configuration and scheduling method and system for wind-solar hydrogen production and storage system matched with hydrogen demand

Abstract

The invention relates to an optimal configuration and scheduling method and system for a wind-solar hydrogen production and storage system matched with a hydrogen demand, and the method comprises the following steps: converting a configuration problem of the wind-solar hydrogen production and storage system into a double-layer optimization problem according to the demand matching of the wind-solar hydrogen production and storage system and a hydrogen end, initial hydrogen production system parameters, initial new energy power generation system parameters and initial hydrogen storage system parameters are set according to the hydrogen demand curve, and new energy configuration energy storage system parameters and hydrogen production electrolytic cell parameters are determined to serve as inputs for establishing a wind and light hydrogen production and storage system optimization model based on constraint conditions; the upper-layer model takes the minimum life cycle cost of the wind-solar hydrogen production and storage system as an optimization target, and the lower-layer model takes the optimal efficiency of the wind-solar hydrogen production and storage system as an optimization target; solving the double-layer optimization model by adopting a beetle antennae search algorithm to obtain the capacity optimal configuration and the whole life cycle minimum cost of the wind and light hydrogen production and storage system; and according to the hydrogen utilization load interval prediction result and the hydrogen storage capacity, the current-day hydrogen production electrolytic cell operation strategy is optimized.

Description

Technical Field

[0001] The present application relates to the technical field of new energy power generation and hydrogen energy joint development, and more specifically, to a method and system for optimizing the configuration and scheduling of a wind-solar hydrogen production and storage system that matches hydrogen demand. Background Art

[0002] In recent years, the use of wind power and photovoltaic power generation to produce green hydrogen has become an effective means to promote the consumption of new energy and promote deep decarbonization in the industrial and transportation sectors. However, the intermittent and volatile output of new energy leads to volatility in hydrogen production, which cannot meet the specific needs of hydrogen users. Relying on the power grid to ensure the stability of the hydrogen production power supply cannot ensure the environmental properties of green hydrogen.

[0003] Better matching of the demands for hydrogen such as synthetic ammonia, synthetic methanol, and hydrogen refueling stations is an important guarantee for increasing the proportion of green hydrogen substitution in the industrial and transportation fields and improving the utilization rate of large-scale hydrogen energy infrastructure such as pipeline hydrogen transportation. At present, the planning and production simulation of wind and solar hydrogen production systems are still mainly considered from the source end, with improving the utilization rate of new energy as the main optimization goal. Operation simulations are carried out for wind power, photovoltaic power generation, energy storage, and hydrogen production, lacking overall consideration of the matching of hydrogen production and hydrogen consumption demands, and unable to adapt to the construction of a green hydrogen energy supply system with consumption as the core.

[0004] Existing technologies, such as the Chinese patent with the patent number "CN115115185A", disclose a method for configuring the hydrogen production and storage capacity of a wind-hydrogen coupling system. The method includes the establishment of a mathematical model of wind power-hydrogen production-hydrogen storage-hydrogen supply. Based on the principle of optimal system yield, wind power + municipal electricity is used to jointly supply electricity to meet the needs of hydrogen users, and a hydrogen energy storage system is used to maximize the use of wind power to produce hydrogen, reduce hydrogen production costs, achieve effective hydrogen production and storage capacity configuration, and improve the economic efficiency of the wind-hydrogen system. Considering the best economic conditions for the wind-hydrogen system, a more reliable hydrogen production and storage system capacity configuration plan is obtained by simulating the wind-hydrogen joint operation model and combining it with the optimization model.

[0005] The problem with the above-mentioned existing technology is that this method uses wind power + city power to meet the needs of hydrogen users, relies on city power supply to smooth the volatility and intermittency of wind power output, improves the stability of system hydrogen supply, cannot ensure the environmental properties of green hydrogen, and is difficult to meet the requirements of green and low-carbon transformation of the hydrogen industry under the "dual carbon" goal. This method lacks the optimization of the operation of the hydrogen production and storage system according to the changes in downstream hydrogen demand to improve the operating efficiency of the equipment. Summary of the invention

[0006] In order to solve the above technical problems, the present invention proposes a method and system for optimizing the configuration and scheduling of a wind-solar hydrogen production and storage system that matches hydrogen demand.

[0007] The technical solution of the present invention is as follows:

[0008] The present invention proposes an optimization configuration and scheduling method for a wind-solar hydrogen production and storage system that matches hydrogen demand, comprising the following steps:

[0009] Step S1, according to the matching of the wind-solar hydrogen production and storage system with the demand of the hydrogen user, the configuration problem of the wind-solar hydrogen production and storage system is converted into a two-layer optimization problem, and the corresponding upper and lower layer optimization objectives and constraints are set;

[0010] Step S2, setting initial hydrogen production system parameters, initial new energy power generation system parameters, and initial hydrogen storage system parameters according to the hydrogen demand curve, and determining new energy configuration energy storage system parameters and hydrogen production electrolyzer parameters;

[0011] Step S3, based on the constraint conditions, a two-layer optimization model of the wind-solar hydrogen production and storage system is established, and the hydrogen demand, new energy configuration energy storage system parameters, hydrogen production electrolyzer parameters, initial hydrogen production system parameters, initial new energy power generation system parameters, and initial hydrogen storage system parameters are used as the input of the model. The upper model takes the minimum life cycle cost of the wind-solar hydrogen production and storage system as the optimization goal, and the lower model takes the optimal efficiency of the wind-solar hydrogen production and storage system as the optimization goal;

[0012] Step S4, using the beetle whisker search algorithm to solve the double-layer optimization model, and obtain the optimal capacity configuration and the minimum life cycle cost of the wind-solar hydrogen storage system;

[0013] Step S5, carry out the prediction of the hydrogen load range for the day, and optimize the operation strategy of the hydrogen production electrolyzer for the day according to the prediction result of the hydrogen load range and the hydrogen storage capacity.

[0014] As a preferred implementation, the configuration problem of the wind-solar hydrogen storage system is converted into a two-layer optimization problem, and corresponding optimization goals and constraints are set; the upper optimization goal is to minimize the system life cycle cost, and the constraint is the preset annual hydrogen balance; the lower optimization goal is to optimize the system operation efficiency, that is, the system power abandonment rate is minimized, the hydrogen abandonment rate is minimized, and the constraints are the preset annual power balance, the cumulative online power does not exceed the annual online power limit, and the hourly online power does not exceed the online power limit. .

[0015] As a preferred implementation, the initial hydrogen production system parameters, initial new energy power generation system parameters, and initial hydrogen storage system parameters are set according to the hydrogen demand curve, and the new energy configuration energy storage system parameters and hydrogen production electrolyzer parameters are determined; wherein the hydrogen demand curve is confirmed by the hydrogen user based on the actual annual hydrogen consumption measured in the previous year and the hydrogen consumption plan for this year.

[0016] As a preferred implementation manner, the initial hydrogen production system parameters, initial new energy power generation system parameters, and initial hydrogen storage system parameters are set according to the hydrogen demand curve to determine the new energy configuration energy storage system parameters and hydrogen production electrolyzer parameters; wherein the initial hydrogen production system parameters include: the number of electrolyzers, the hydrogen production system power, and the system operating power adjustment range; the initial new energy power generation system parameters include: wind power installed capacity and photovoltaic power generation installed capacity, wind power hourly power, photovoltaic power hourly power, new energy storage and grid-connected power and power upper limit; the initial hydrogen storage system parameters include: hydrogen storage volume, initial hydrogen storage capacity; the new energy configuration energy storage system parameters include: energy storage capacity ratio, duration, energy storage charging and discharging efficiency; the hydrogen production electrolyzer parameters include: electrolyzer single hydrogen production, electrolyzer rated power, electrolyzer operating power adjustment range.

[0017] As a preferred implementation, the two-layer optimization model of the wind-solar hydrogen production and storage system is established based on the constraint conditions, and the objective function of the upper model is:

[0018] The upper layer aims to minimize the system life cycle cost. The specific formula is:

[0019] F1=min(O sys );

[0020] In the formula, O sys is the system life cycle operating cost, including:

[0021] O sys =I sts +XM sys ;

[0022]

[0023] In the formula, I sys The initial investment for system construction includes investment in wind power and photovoltaic construction, investment in electrolyzer equipment, investment in electrochemical energy storage system and investment in hydrogen storage system; M sys is the annual operating cost of the system; X represents the operating life of the system; M maint The annual maintenance cost of the system includes the maintenance cost of wind power and photovoltaic power, the maintenance cost of electrolyzer, the maintenance cost of energy storage system and the maintenance cost of hydrogen storage system; is the cost of raw materials for hydrogen production by electrolyzer; elec For the income of grid-connected electricity;

[0024] The constraint condition of the upper model is to meet the annual hydrogen balance. The specific formula is:

[0025]

[0026] In the formula, is the amount of hydrogen supplied to the system at time i; is the amount of hydrogen produced by the electrolyzer at time i; is the net hydrogen storage at time i; is the amount of hydrogen required at the hydrogen-using end at time i; i = 1, 2, 3, ... 8760, which is a certain hour throughout the year.

[0027] As a preferred implementation, the two-layer optimization model of the wind-solar hydrogen production and storage system is established based on the constraint conditions, and the objective function of the lower model is:

[0028] The lower layer takes the optimal system operation efficiency as the optimization goal, and the specific formula is:

[0029]

[0030] In the formula, is the system power abandonment rate; is the system hydrogen abandonment rate;

[0031] The constraints of the lower model are the annual power balance; the cumulative online power does not exceed the annual online power limit; the hourly online power does not exceed the online power limit; hydrogen production and storage linkage: when the hydrogen storage scale reaches the set capacity, the hydrogen production end stops hydrogen production, and all new energy output is connected to the grid. The specific formula is:

[0032]

[0033] Where P ptg,i P is the grid-connected power of the new energy power generation system at time i; wind,i P is the installed grid-connected power of wind power at time i; solar,i P is the installed grid-connected power of photovoltaic power generation at time i; s,i The charging and discharging power of the energy storage system configured by the new energy at time i, P s,i Positive means that the energy storage system configured with new energy is in charging state; P is the power consumption of hydrogen production by the wind-solar hydrogen storage system at time i; ptg,max S is the upper limit of Internet access power at time i; ptg,i S is the accumulated online power consumption at time i; ptg,max The upper limit of the accumulated Internet power consumption; The hydrogen storage capacity of the wind-solar hydrogen storage system at time i-1; is the maximum hydrogen storage capacity of the wind-solar hydrogen storage system; i = 1, 2, 3, ... 8760, which is a certain hour in the whole year.

[0034] As a preferred implementation, the bilayer optimization model is solved by using the beetle whisker search algorithm, and the specific steps are as follows:

[0035] Input the initial system parameters of the wind-solar hydrogen storage system, and the optimization variable is the wind power installed capacity C wind , Photovoltaic installed capacity C solar, Number of hydrogen production electrolyzers N, Volume of hydrogen storage system

[0036] Initialize the parameters of the beetle whisker search algorithm, including the initial step size step (0) , step size adjustment ratio eta, initial beetle left and right whisker spacing d0, maximum number of iterations t max ;

[0037] Establish a normalized random vector with the right beetle's whisker facing the left beetle, and determine the positions x of the left and right beetles of the beetle l and x r , calculate the left and right whiskers x l and x r The corresponding optimization objective function value;

[0038] Randomly generate an initial solution vector x that satisfies the constraints (0) , substitute the optimization objective functions F1 and F2, and calculate the initial optimal solution

[0039] Update the position of the longhorn beetle x (t) 、The position of the left and right whiskers of the longicorn and Step length (t) And the distance between left and right whiskers Where t is the number of iterations;

[0040] Calculate the updated objective function value judge and size;

[0041] Let t = t + 1, and when the maximum number of iterations is reached, the optimization process ends and the current optimal solution x is output. best and F best .

[0042] As a preferred implementation, the specific steps of carrying out the daily hydrogen load interval prediction are as follows:

[0043] Obtain the hourly hydrogen load of hydrogen users on the same day for three consecutive years, and obtain the average hourly maximum value of the hydrogen load on the day for the previous three years. Average hourly minimum

[0044] Obtain the hourly hydrogen load of hydrogen users within the previous day, and obtain the hourly maximum value of hydrogen load on the previous day Hourly minimum

[0045] Based on the above data, the hydrogen load of the day was corrected and compared. The maximum value of the three values ​​is updated as the hourly maximum value of hydrogen load for the day.

[0046] contrast The minimum of the three values ​​is updated as the minimum hourly value of hydrogen load for the day.

[0047] As a preferred implementation, the operation strategy of the hydrogen production electrolyzer is optimized on the day according to the hydrogen load interval prediction result and the hydrogen storage capacity, and the specific steps are as follows:

[0048] Determine the status of the hydrogen storage system: If The hydrogen production electrolyzer does not start;

[0049] like Start up the hydrogen production electrolyzer;

[0050] Further judgement if The number of electrolytic cells in operation is Corresponding number of units;

[0051] like The number of electrolytic cells in operation is Corresponding number of units.

[0052] On the other hand, the present invention also provides an optimization configuration and dispatching system for a wind-solar hydrogen production and storage system that matches hydrogen demand, including:

[0053] The two-layer optimization model building module converts the configuration problem of the wind-solar hydrogen production and storage system into a two-layer optimization problem according to the matching of the wind-solar hydrogen production and storage system with the demand of the hydrogen user, and sets the corresponding upper and lower layer optimization objectives and constraints;

[0054] The parameter confirmation module sets the initial hydrogen production system parameters, the initial new energy power generation system parameters, and the initial hydrogen storage system parameters according to the hydrogen demand curve, and determines the new energy configuration energy storage system parameters and the hydrogen production electrolyzer parameters;

[0055] The simulation calculation module establishes a two-layer optimization model of the wind-solar hydrogen production and storage system based on constraint conditions, and takes hydrogen demand, new energy configuration energy storage system parameters, hydrogen production electrolyzer parameters, initial hydrogen production system parameters, initial new energy power generation system parameters, and initial hydrogen storage system parameters as the input of the model. The upper model takes the minimum life cycle cost of the wind-solar hydrogen production and storage system as the optimization goal, and the lower model takes the optimal efficiency of the wind-solar hydrogen production and storage system as the optimization goal;

[0056] The solution module uses the beetle whisker search algorithm to solve the double-layer optimization model and obtain the optimal capacity configuration and the minimum life cycle cost of the wind-solar hydrogen production and storage system; the daily hydrogen load range forecast is carried out, and the daily hydrogen production electrolyzer operation strategy is optimized based on the hydrogen load range forecast results and hydrogen storage capacity;

[0057] The prediction and optimization module conducts a daily hydrogen load range forecast and optimizes the daily hydrogen production electrolyzer operation strategy based on the hydrogen load range forecast results and hydrogen storage capacity.

[0058] The present invention has the following beneficial effects:

[0059] 1. The present invention takes matching hydrogen demand as the optimization goal, does not rely on the power supply from the power grid, takes the overall power transmission from the wind and solar power hydrogen production and storage project to the power grid as the constraint condition, gives full play to the regulation capabilities of hydrogen production, hydrogen storage and electrochemical energy storage, and solves the model by setting a double-layer optimization goal to obtain a reasonable new energy installed capacity, electrolyzer scale and hydrogen storage scale.

[0060] 2. The present invention adopts the bull's whisker search algorithm to solve the double-layer optimization model. Compared with the traditional genetic algorithm, the bull's whisker search algorithm has the advantages of fewer parameter settings, not easy to fall into the local optimal solution, high computational efficiency and fast convergence speed.

[0061] 3. Carry out daily hydrogen load range forecasting, and optimize the daily hydrogen production electrolyzer operation strategy based on the hydrogen load range forecasting results and hydrogen storage capacity, to achieve overall optimal configuration of the wind and solar hydrogen production and storage system based on hydrogen demand, improve the coupling degree between upstream green hydrogen production and downstream green hydrogen consumption, and promote green hydrogen consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application 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.

[0063] Figure 1 This is a schematic diagram of the method flow of Example 1;

[0064] Figure 2 This is a flow chart of the solution of the longicorn beetle whisker search algorithm of the present invention. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] It should be understood that the step numbers used in this document are only for convenience of description and are not intended to limit the order in which the steps are executed.

[0067] It should be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0068] The terms “include” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0069] The term "and / or" means and includes any and all possible combinations of one or more of the associated listed items.

[0070] Embodiment 1:

[0071] In order to make the purpose, technical solutions and advantages of the present invention more clear, the following will be combined with the specific embodiments of the present application and refer to the attached Figure 1 , clearly and completely describe the technical solution of the present invention.

[0072] In order to solve the problems of the prior art, the present invention provides an optimization configuration and scheduling method for a wind-solar hydrogen production and storage system that matches hydrogen demand, comprising the following steps:

[0073] Step S1, according to the matching of the wind-solar hydrogen production and storage system with the demand of the hydrogen user, the configuration problem of the wind-solar hydrogen production and storage system is converted into a two-layer optimization problem, and the corresponding upper and lower layer optimization objectives and constraints are set;

[0074] The configuration problem of the wind-solar hydrogen production and storage system is converted into a two-layer optimization problem, and corresponding optimization goals and constraints are set; among which, the upper-layer optimization goal is to minimize the system's full life cycle cost, and the constraint is the preset annual hydrogen balance; the lower-layer optimization goal is to optimize the system's operating efficiency, that is, the system's power abandonment rate and hydrogen abandonment rate are minimized, and the constraints are the preset annual power balance, the cumulative online power does not exceed the annual online power upper limit, and the hourly online power does not exceed the online power upper limit.

[0075] Step S2, setting initial hydrogen production system parameters, initial new energy power generation system parameters, and initial hydrogen storage system parameters according to the hydrogen demand curve, and determining new energy configuration energy storage system parameters and hydrogen production electrolyzer parameters;

[0076] The initial hydrogen production system parameters, initial new energy power generation system parameters, and initial hydrogen storage system parameters are set according to the hydrogen demand curve, and the new energy configuration energy storage system parameters and hydrogen production electrolyzer parameters are determined; wherein the hydrogen demand curve is confirmed by the hydrogen user based on the actual annual hydrogen consumption measured in the previous year and the hydrogen consumption plan for this year.

[0077] The initial hydrogen production system parameters, initial new energy power generation system parameters, and initial hydrogen storage system parameters are set according to the hydrogen demand curve to determine the new energy configuration energy storage system parameters and hydrogen production electrolyzer parameters; wherein the initial hydrogen production system parameters include: the number of electrolyzers, the hydrogen production system power, and the system operating power adjustment range; the initial new energy power generation system parameters include: wind power installed capacity and photovoltaic power generation installed capacity, wind power hourly power, photovoltaic power hourly power, new energy storage and grid-connected power and power upper limit; the initial hydrogen storage system parameters include: hydrogen storage volume, initial hydrogen storage capacity; the new energy configuration energy storage system parameters include: energy storage capacity ratio, duration, energy storage charging and discharging efficiency; the hydrogen production electrolyzer parameters include: electrolyzer single hydrogen production, electrolyzer rated power, and electrolyzer operating power adjustment range.

[0078] Step S3, based on the constraint conditions, a two-layer optimization model of the wind-solar hydrogen production and storage system is established, and the hydrogen demand, new energy configuration energy storage system parameters, hydrogen production electrolyzer parameters, initial hydrogen production system parameters, initial new energy power generation system parameters, and initial hydrogen storage system parameters are used as the input of the model. The upper model takes the minimum life cycle cost of the wind-solar hydrogen production and storage system as the optimization goal; the lower model takes the optimal efficiency of the wind-solar hydrogen production and storage system as the optimization goal;

[0079] The upper layer aims to minimize the system life cycle cost. The specific formula is:

[0080] F1=min(O sys );

[0081] In the formula, O sys is the system life cycle operating cost, including:

[0082] O sys =I sts +XM sys ;

[0083]

[0084] In the formula, I sys The initial investment for system construction includes investment in wind power and photovoltaic construction, investment in electrolyzer equipment, investment in electrochemical energy storage system and investment in hydrogen storage system; M sys is the annual operating cost of the system; X represents the operating life of the system; M maintThe annual maintenance cost of the system includes the maintenance cost of wind power and photovoltaic power, the maintenance cost of electrolyzer, the maintenance cost of energy storage system and the maintenance cost of hydrogen storage system; is the cost of raw materials for hydrogen production by electrolyzer; elec For the income of grid electricity.

[0085] The constraint condition of the upper model is to meet the annual hydrogen balance. The specific formula is:

[0086]

[0087] In the formula, is the amount of hydrogen supplied to the system at time i; is the amount of hydrogen produced by the electrolyzer at time i; is the hydrogen storage capacity of the hydrogen storage system at time i; is the amount of hydrogen required at the hydrogen-using end at time i; i = 1, 2, 3, ... 8760, which is a certain hour in the whole year;

[0088] The lower layer takes the optimal system operation efficiency as the optimization goal, and the specific formula is:

[0089]

[0090] In the formula, is the system power abandonment rate; is the system hydrogen abandonment rate.

[0091] The constraints of the lower model are the annual power balance; the cumulative online power does not exceed the annual online power limit; the hourly online power does not exceed the online power limit; hydrogen production and storage linkage: when the hydrogen storage scale reaches the set capacity, the hydrogen production end stops hydrogen production, and all new energy output is connected to the grid. The specific formula is:

[0092]

[0093] Where P ptg,i P is the grid-connected power of the new energy power generation system at time i; wind,i P is the installed grid-connected power of wind power at time i; solar,i P is the installed grid-connected power of photovoltaic power generation at time i; s,i The charging and discharging power of the energy storage system configured by the new energy at time i, P s,i Positive means that the energy storage system configured with new energy is in charging state; P is the power consumption of hydrogen production by the wind-solar hydrogen storage system at time i; ptg,max S is the upper limit of Internet access power at time i; ptg,i S is the accumulated online power consumption at time i; ptg,max The upper limit of the accumulated Internet power consumption; The hydrogen storage capacity of the wind-solar hydrogen storage system at time i-1; is the maximum hydrogen storage capacity of the wind-solar hydrogen storage system; i = 1, 2, 3, ... 8760, which is a certain hour in the whole year.

[0094] Step S4, using the beetle whisker search algorithm to solve the double-layer optimization model, and obtain the optimal capacity configuration and the minimum life cycle cost of the wind-solar hydrogen storage system.

[0095] Step S401: Input the initial system parameters of the wind-solar hydrogen storage system, and the optimization variable is the wind power installed capacity C wind , Photovoltaic installed capacity C solar , Number of hydrogen production electrolyzers N, Volume of hydrogen storage system

[0096] Step S402: Initialize the parameters of the beetle whisker search algorithm, including the initial step length step (0) , step size adjustment ratio eta, initial beetle left and right whisker spacing d0, maximum number of iterations t max ;

[0097] Step S403: Establish a normalized random vector that points the right beetle's whisker toward the left beetle, and determine the positions x of the left and right beetle's whiskers. l and x r , calculate the left and right whiskers x l and x r The corresponding optimization objective function value;

[0098] Step S404: Randomly generate an initial solution vector x that satisfies the constraints (0) , substitute the optimization objective functions F1 and F2, and calculate the initial optimal solution

[0099] Step S405: Update the position x of the longhorn beetle (t) 、The position of the left and right whiskers of the longicorn and Step length (t) And the distance between left and right whiskers Where t is the number of iterations;

[0100] Step S406: Calculate the updated objective function value judge and size;

[0101] Step S407: Let t = t + 1, determine whether the number of iterations t reaches the maximum number of iterations, if not, repeat steps S405 and S406; if reached, the optimization process ends and the current optimal solution x is output. best and F best .

[0102] Step S5, carry out the prediction of the hydrogen load range for the day, and optimize the operation strategy of the hydrogen production electrolyzer for the day according to the prediction result of the hydrogen load range and the hydrogen storage capacity.

[0103] The specific steps of optimizing the operation strategy of the hydrogen production electrolyzer on the day according to the hydrogen load range prediction results and hydrogen storage capacity are as follows:

[0104] Determine the status of the hydrogen storage system: If The hydrogen production electrolyzer does not start;

[0105] like Start up the hydrogen production electrolyzer;

[0106] Further judgement if The number of electrolytic cells in operation is Corresponding number of units;

[0107] like The number of electrolytic cells in operation is Corresponding number of units.

[0108] In this embodiment, the input conditions for the multi-objective optimization calculation of the wind-solar hydrogen production and storage system are set as follows:

[0109] The rated requirement for hydrogen end is 5000Nm 3 / h, the hydrogen demand range is 80% to 100%; the hydrogen production end is equipped with several 1000Nm 3 / h electrolyzer, the unit power consumption of hydrogen production is 5 kWh / Nm 3 The adjustment range of the electrolyzer is 30% to 110%; the proportion of new energy storage is 10%, the duration is 2 hours, and the energy storage charging and discharging efficiency is 0.9; the annual hydrogen demand is about 43.8 million Nm 3 , set the hydrogen storage tank capacity to 900,000 Nm 3 , the initial hydrogen storage capacity is 0. The annual hydrogen production capacity is about 220 million, the initial wind power installed capacity is set to 50,000 kilowatts, the annual utilization hours are 4,000 hours; the initial photovoltaic installed capacity is 40,000 kilowatts, the annual utilization hours are 1,400 hours, and the new energy power generation is about 256 million kilowatt-hours. The system operation cycle is 20 years.

[0110] The constraints are set as follows:

[0111] The annual on-grid electricity of the wind and solar hydrogen production and storage system shall not exceed 10% of the renewable energy power generation;

[0112] The hourly grid-connected power of the wind and solar hydrogen storage system shall not exceed 20% of the grid-connected power of renewable energy;

[0113] Data is input into the two-layer optimization model of the wind-solar hydrogen production and storage system and simulation calculations are carried out based on the above conditions. Iterative calculations are carried out according to the optimization objectives to minimize the life cycle cost of the wind-solar hydrogen production and storage system and optimize the operating efficiency (i.e., minimize the power abandonment rate and hydrogen abandonment rate). The optimal configuration results of the wind-solar hydrogen production and storage system are output, as shown in Table 1:

[0114] Table 1 Optimal results of the wind-solar hydrogen storage system configuration in this embodiment

[0115] project unit Numeric Wind power installed capacity 10,000 kilowatts 4.5 Photovoltaic power generation installed capacity 10,000 kilowatts 4.2 Hydrogen storage capacity <![CDATA[10,000 Nm 3 > 300 Number of hydrogen production electrolyzers tower 8 Power abandonment rate ％ 2.7 Hydrogen abandonment rate ％ 0.0 System life cycle cost Ten thousand yuan 249900

[0116] Embodiment 2:

[0117] This embodiment provides an optimization configuration and scheduling system for a wind-solar hydrogen production and storage system that matches hydrogen demand, including:

[0118] The two-layer optimization model building module converts the configuration problem of the wind-solar hydrogen production and storage system into a two-layer optimization problem according to the matching of the wind-solar hydrogen production and storage system with the demand of the hydrogen user, and sets the corresponding upper and lower layer optimization objectives and constraints;

[0119] The parameter confirmation module sets the initial hydrogen production system parameters, the initial new energy power generation system parameters, and the initial hydrogen storage system parameters according to the hydrogen demand curve, and determines the new energy configuration energy storage system parameters and the hydrogen production electrolyzer parameters;

[0120] The simulation calculation module establishes a two-layer optimization model of the wind-solar hydrogen production and storage system based on constraint conditions, and takes hydrogen demand, new energy configuration energy storage system parameters, hydrogen production electrolyzer parameters, initial hydrogen production system parameters, initial new energy power generation system parameters, and initial hydrogen storage system parameters as the input of the model. The upper model takes the minimum life cycle cost of the wind-solar hydrogen production and storage system as the optimization goal, and the lower model takes the optimal efficiency of the wind-solar hydrogen production and storage system as the optimization goal;

[0121] The solution module uses the beetle whisker search algorithm to solve the double-layer optimization model and obtain the optimal capacity configuration and the minimum life cycle cost of the wind-solar hydrogen production and storage system; the daily hydrogen load range forecast is carried out, and the daily hydrogen production electrolyzer operation strategy is optimized based on the hydrogen load range forecast results and hydrogen storage capacity;

[0122] The prediction and optimization module conducts a daily hydrogen load range forecast and optimizes the daily hydrogen production electrolyzer operation strategy based on the hydrogen load range forecast results and hydrogen storage capacity.

[0123] In the embodiments of the present application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. Among them, A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c can be represented by: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, c can be single or multiple.

[0124] Those of ordinary skill in the art will appreciate that the various units and algorithm steps described in the embodiments disclosed herein can be implemented in a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0125] 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.

[0126] In several embodiments provided in the present application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes 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: U disk, mobile hard disk, read-only memory (Read-Only Memory; hereinafter referred to as: ROM), random access memory (Random Access Memory; hereinafter referred to as: RAM), disk or optical disk, and other media that can store program codes.

[0127] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for optimizing the configuration and scheduling of a wind-solar hydrogen production and storage system to match hydrogen demand, characterized in that: The following steps are involved: Step S1, according to the matching of the wind-solar hydrogen production and storage system with the demand of the hydrogen user, the configuration problem of the wind-solar hydrogen production and storage system is converted into a two-layer optimization problem, and the corresponding upper and lower layer optimization objectives and constraints are set; Step S2, setting initial hydrogen production system parameters, initial new energy power generation system parameters, and initial hydrogen storage system parameters according to the hydrogen demand curve, and determining new energy configuration energy storage system parameters and hydrogen production electrolyzer parameters; Step S3, based on the constraint conditions, a two-layer optimization model of the wind-solar hydrogen production and storage system is established, and the hydrogen demand, new energy configuration energy storage system parameters, hydrogen production electrolyzer parameters, initial hydrogen production system parameters, initial new energy power generation system parameters, and initial hydrogen storage system parameters are used as the input of the model. The upper model takes the minimum life cycle cost of the wind-solar hydrogen production and storage system as the optimization goal, and the lower model takes the optimal efficiency of the wind-solar hydrogen production and storage system as the optimization goal; Step S4, using the beetle whisker search algorithm to solve the double-layer optimization model, and obtain the optimal capacity configuration and the minimum life cycle cost of the wind-solar hydrogen storage system; Step S5, carry out the prediction of the hydrogen load range for the day, and optimize the operation strategy of the hydrogen production electrolyzer for the day according to the prediction result of the hydrogen load range and the hydrogen storage capacity.

2. The method for optimizing configuration and scheduling of a wind-solar hydrogen production and storage system to match hydrogen demand according to claim 1, characterized in that: The configuration problem of the wind-solar hydrogen production and storage system is converted into a two-layer optimization problem, and corresponding optimization goals and constraints are set; among which, the upper-layer optimization goal is to minimize the system's full life cycle cost, and the constraint is the preset annual hydrogen balance; the lower-layer optimization goal is to optimize the system's operating efficiency, that is, the system's power abandonment rate and hydrogen abandonment rate are minimized, and the constraints are the preset annual power balance, the cumulative online power does not exceed the annual online power upper limit, and the hourly online power does not exceed the online power upper limit.

3. The method for optimizing configuration and scheduling of a wind-solar hydrogen production and storage system to match hydrogen demand according to claim 1, characterized in that: The initial hydrogen production system parameters, initial new energy power generation system parameters, and initial hydrogen storage system parameters are set according to the hydrogen demand curve, and the new energy configuration energy storage system parameters and hydrogen production electrolyzer parameters are determined; wherein the hydrogen demand curve is confirmed by the hydrogen user based on the actual annual hydrogen consumption measured in the previous year and the hydrogen consumption plan for this year.

4. The method for optimizing configuration and scheduling of a wind-solar hydrogen production and storage system to match hydrogen demand according to claim 1, characterized in that: The initial hydrogen production system parameters, initial new energy power generation system parameters, and initial hydrogen storage system parameters are set according to the hydrogen demand curve to determine the new energy configuration energy storage system parameters and hydrogen production electrolyzer parameters; wherein the initial hydrogen production system parameters include: the number of electrolyzers, the hydrogen production system power, and the system operating power adjustment range; the initial new energy power generation system parameters include: wind power installed capacity and photovoltaic power generation installed capacity, wind power hourly power, photovoltaic power hourly power, new energy storage and grid-connected power and power upper limit; the initial hydrogen storage system parameters include: hydrogen storage volume, initial hydrogen storage capacity; the new energy configuration energy storage system parameters include: energy storage capacity ratio, duration, energy storage charging and discharging efficiency; the hydrogen production electrolyzer parameters include: electrolyzer single hydrogen production, electrolyzer rated power, and electrolyzer operating power adjustment range.

5. The method for optimizing configuration and scheduling of a wind-solar hydrogen production and storage system to match hydrogen demand according to claim 1, characterized in that: The double-layer optimization model of the wind-solar hydrogen storage system is established based on the constraint conditions, and the objective function of the upper model is: The upper layer aims to minimize the system life cycle cost. The specific formula is: F1=min(O sys ); In the formula, O sys is the system life cycle operating cost, including: O sys =I sys +XM sys ; In the formula, I sys The initial investment for system construction includes investment in wind power and photovoltaic construction, investment in electrolyzer equipment, investment in electrochemical energy storage system and investment in hydrogen storage system; M sys is the annual operating cost of the system; X represents the operating life of the system; M maint The annual maintenance cost of the system includes the maintenance cost of wind power and photovoltaic power, the maintenance cost of electrolyzer, the maintenance cost of energy storage system and the maintenance cost of hydrogen storage system; is the cost of raw materials for hydrogen production by electrolyzer; elec For the income of grid-connected electricity; The constraint condition of the upper model is to meet the annual hydrogen balance. The specific formula is: In the formula, is the amount of hydrogen supplied to the system at time i; is the amount of hydrogen produced by the electrolyzer at time i; is the net hydrogen storage at time i; is the amount of hydrogen required at the hydrogen-using end at time i; i = 1, 2, 3, ... 8760, which is a certain hour throughout the year.

6. The method for optimizing configuration and scheduling of a wind-solar hydrogen production and storage system to match hydrogen demand according to claim 1, characterized in that: The two-layer optimization model of the wind-solar hydrogen storage system is established based on the constraint conditions, and the objective function of the lower model is: The lower layer takes the optimal system operation efficiency as the optimization goal, and the specific formula is: In the formula, is the system power abandonment rate; is the system hydrogen abandonment rate; The lower model constraint is the annual power balance; The cumulative on-grid power shall not exceed the annual on-grid power limit; the on-grid power per hour shall not exceed the on-grid power limit; hydrogen production and storage linkage: when the hydrogen storage scale reaches the set capacity, the hydrogen production end stops producing hydrogen, and all new energy output is connected to the grid. The specific formula is: Where P ptg,i P is the grid-connected power of the new energy power generation system at time i; wind,i P is the installed grid-connected power of wind power at time i; solar,i P is the installed grid-connected power of photovoltaic power generation at time i; s,i The charging and discharging power of the energy storage system configured by the new energy at time i, P s,i Positive means that the energy storage system configured with new energy is in charging state; P is the power consumption of hydrogen production by the wind-solar hydrogen storage system at time i; ptg,max is the upper limit of Internet access power at time i; S ptg,i S is the accumulated online power consumption at time i; ptg,max The upper limit of the accumulated Internet power consumption; The hydrogen storage capacity of the wind-solar hydrogen storage system at time i-1; is the maximum hydrogen storage capacity of the wind-solar hydrogen storage system; i = 1, 2, 3, ... 8760, which is a certain hour in the whole year.

7. The method for optimizing configuration and scheduling of a wind-solar hydrogen production and storage system to match hydrogen demand according to claim 1, characterized in that: The bilayer optimization model is solved by using the beetle whisker search algorithm, and the specific steps are as follows: Input the initial system parameters of the wind-solar hydrogen storage system, and the optimization variable is the wind power installed capacity C wind , Photovoltaic installed capacity C solar , Number of hydrogen production electrolyzers N, Volume of hydrogen storage system Initialize the parameters of the beetle whisker search algorithm, including the initial step size step (0) , step size adjustment ratio eta, initial beetle left and right whisker spacing d0, maximum number of iterations t max ; Establish a normalized random vector with the right beetle's whisker facing the left beetle, and determine the positions x of the left and right beetles of the beetle l and x r , calculate the left and right whiskers x l and x r The corresponding optimization objective function value; Randomly generate an initial solution vector x that satisfies the constraints (0) , substitute the optimization objective functions F1 and F2, and calculate the initial optimal solution Update the position of the longhorn beetle x (t) 、The position of the left and right whiskers of the longicorn and Step length (t) And the distance between left and right whiskers Where t is the number of iterations; Calculate the updated objective function value judge and size; Let t = t + 1, and when the maximum number of iterations is reached, the optimization process ends and the current optimal solution x is output. best and F best .

8. The method for optimizing configuration and scheduling of a wind-solar hydrogen production and storage system to match hydrogen demand according to claim 1, characterized in that: The specific steps of carrying out the daily hydrogen load range prediction are as follows: Obtain the hourly hydrogen load of hydrogen users on the same day for three consecutive years, and obtain the average hourly maximum value of the hydrogen load on the day for the previous three years. Average hourly minimum Obtain the hourly hydrogen load of hydrogen users within the previous day, and obtain the hourly maximum value of hydrogen load on the previous day Hourly minimum Based on the above data, the hydrogen load of the day was corrected and compared. The maximum value of the three values ​​is updated as the hourly maximum value of hydrogen load for the day. contrast The minimum of the three values ​​is updated as the minimum hourly value of hydrogen load for the day.

9. The method for optimizing configuration and scheduling of a wind-solar hydrogen production and storage system to match hydrogen demand according to claim 1, characterized in that: The specific steps of optimizing the operation strategy of the hydrogen production electrolyzer on the day according to the hydrogen load range prediction results and hydrogen storage capacity are as follows: Determine the status of the hydrogen storage system: If The hydrogen production electrolyzer does not start; like Start up the hydrogen production electrolyzer; Further judgement if The number of electrolytic cells in operation is Corresponding number of units; like The number of electrolytic cells in operation is Corresponding number of units.

10. An optimization configuration and dispatching system for wind and solar hydrogen production and storage systems that matches hydrogen demand, characterized in that: include: The two-layer optimization model building module converts the configuration problem of the wind-solar hydrogen production and storage system into a two-layer optimization problem according to the matching of the wind-solar hydrogen production and storage system with the demand of the hydrogen user, and sets the corresponding upper and lower layer optimization objectives and constraints; The parameter confirmation module sets the initial hydrogen production system parameters, the initial new energy power generation system parameters, and the initial hydrogen storage system parameters according to the hydrogen demand curve, and determines the new energy configuration energy storage system parameters and the hydrogen production electrolyzer parameters; The simulation calculation module establishes a two-layer optimization model of the wind-solar hydrogen production and storage system based on constraint conditions, and takes hydrogen demand, new energy configuration energy storage system parameters, hydrogen production electrolyzer parameters, initial hydrogen production system parameters, initial new energy power generation system parameters, and initial hydrogen storage system parameters as the input of the model. The upper model takes the minimum life cycle cost of the wind-solar hydrogen production and storage system as the optimization goal, and the lower model takes the optimal efficiency of the wind-solar hydrogen production and storage system as the optimization goal; The solution module uses the beetle whisker search algorithm to solve the double-layer optimization model and obtain the optimal capacity configuration and the minimum life cycle cost of the wind-solar hydrogen production and storage system; the daily hydrogen load range forecast is carried out, and the daily hydrogen production electrolyzer operation strategy is optimized based on the hydrogen load range forecast results and hydrogen storage capacity; The prediction and optimization module conducts a daily hydrogen load range forecast and optimizes the daily hydrogen production electrolyzer operation strategy based on the hydrogen load range forecast results and hydrogen storage capacity.

Images