A structural optimization method and device for complementary energy system

Abstract

The present invention provides a method and device for optimizing the structure of a complementary energy system, the method comprising: obtaining the load power demand of the complementary energy system; establishing a first output power model of a photovoltaic power generation unit in a photovoltaic power generation subsystem and a second output power model of an energy storage power generation unit in an energy storage power generation subsystem; constructing an objective function model of the complementary energy system based on the structural parameters of the complementary energy system and taking the total system cost as the target; determining the structural parameter range corresponding to the structural parameter based on the load power demand, the first output power model and the second output power model; calculating the optimal solution of the objective function model within the structural parameter range, and determining the structural design scheme of the complementary energy system based on the target structural parameters corresponding to the optimal solution. Thus, the economic maximization operation of the complementary energy system is achieved while meeting the user's load demand, the cost of the complementary energy system is reduced, and the comprehensive economic performance of the system is improved.

Description

Technical Field

[0001] The present invention relates to the field of new energy technology, and in particular to a structure optimization method and device for a complementary energy system. Background Art

[0002] Photovoltaic power generation has been fully developed and utilized due to its advantages of high efficiency, cleanliness and pollution-free. However, there is still a lot of room for improvement in the technology and economic benefits of photovoltaic power stations. Since the large-scale grid connection of renewable energy power can easily cause grid fluctuations, the load instructions assigned to photovoltaic power stations often change. The frequently fluctuating load instructions increase the difficulty of operation and maintenance and the cost of power generation of photovoltaic power stations, and the power generation and load instructions are usually not balanced. Therefore, combining energy storage power generation such as hydrogen storage tanks or heat storage tanks with photovoltaic power stations to form a complementary energy system can improve the operational flexibility of photovoltaic power stations and achieve the dual goals of maximizing the economy of photovoltaic full-load power generation and flexible storage and utilization of surplus electricity.

[0003] However, the existing structural design schemes of complementary energy systems often only focus on meeting user load requirements and lack consideration of economic performance. There is generally a problem of high system cost. Therefore, how to optimize the structure of the complementary energy system to reduce costs and improve the comprehensive economic performance of the system while meeting user load requirements has become an urgent problem to be solved. Summary of the invention

[0004] In view of this, an embodiment of the present invention provides a method and device for optimizing the structure of a complementary energy system, so as to overcome the problems of high cost and poor comprehensive economic performance of the complementary energy system structure design scheme in the prior art.

[0005] According to a first aspect, an embodiment of the present invention provides a method for optimizing the structure of a complementary energy system, wherein the complementary energy system comprises: a photovoltaic power generation subsystem and an energy storage power generation subsystem, and the method comprises:

[0006] Obtaining load power demand of the complementary energy system;

[0007] Establishing a first output power model of a photovoltaic power generation unit in the photovoltaic power generation subsystem and a second output power model of an energy storage power generation unit in the energy storage power generation subsystem;

[0008] Based on the structural parameters of the complementary energy system, an objective function model of the complementary energy system is constructed with the total system cost as the target;

[0009] Determining a structural parameter range corresponding to the structural parameter based on the load power demand, the first output power model, and the second output power model;

[0010] Within the range of the structural parameters, the optimal solution of the objective function model is calculated, and the structural design scheme of the complementary energy system is determined based on the target structural parameters corresponding to the optimal solution.

[0011] Optionally, the step of establishing a first output power model of a photovoltaic power generation unit in the photovoltaic power generation subsystem includes:

[0012] Based on the property parameters of the photovoltaic array in the photovoltaic power generation unit, a third power output model of the photovoltaic array is established;

[0013] The first output power model is established based on the attribute parameters of the inverter and the third power output model.

[0014] Optionally, the power generation energy stored in the energy storage and power generation unit is hydrogen, and the energy storage and power generation unit is composed of an electrolyzer, a hydrogen storage tank and a fuel cell. The second output power model of the energy storage and power generation unit in the energy storage and power generation subsystem is established, including:

[0015] Based on the property parameters of the electrolytic cell, establishing a fourth power output model of the electrolytic cell;

[0016] Based on the property parameters of the hydrogen storage tank, establishing an energy storage model of the hydrogen storage tank;

[0017] The second output power model is established based on the fourth power output model, the energy storage model and the property parameters of the fuel cell.

[0018] Optionally, the structural parameters include: the number of photovoltaic arrays, the area occupied by the photovoltaic arrays, the number of electrolyzers, the number of fuel cells, and the number of inverters, and determining the structural parameter range corresponding to the structural parameters based on the load power demand, the first output power model, and the second output power model includes:

[0019] Determining a selection range of the number of photovoltaic arrays based on the load power demand and the area occupied by the photovoltaic array;

[0020] Based on the selection range of the number of photovoltaic arrays, the number of electrolyzers, the number of fuel cells and the number of inverters corresponding to different photovoltaic arrays are determined.

[0021] Optionally, the objective function model of the complementary energy system is expressed by the following formula:

[0022]

[0023] Among them, Min.TNPC represents the total system cost, i represents the number of the equipment group in the system, and TNPC irepresents the cost of the i-th equipment group, N is the number of photovoltaic arrays, C capital is the initial investment cost, C replacement is the replacement cost, C maintenance is the maintenance and repair cost, and the time unit is 1 year; R is the system usage time, ir is the real interest rate based on the nominal interest rate and the annual inflation rate; y and L represent the replacement times and service life of each device in the system, respectively.

[0024] Optionally, calculating the optimal solution of the objective function model within the structural parameter range includes:

[0025] Within the range of the structural parameters, the objective function model is solved by using a quantum emperor penguin optimization algorithm to obtain a system cost calculation value corresponding to the objective function model under different structural parameters;

[0026] An optimal solution for the objective function model is determined based on the calculated value of the system cost.

[0027] Optionally, determining the optimal solution of the objective function model based on the system cost calculation value includes:

[0028] Sorting the system cost calculation values ​​corresponding to different structural parameters to determine the minimum system cost value;

[0029] The minimum system cost value and its corresponding target structure parameter are determined as the optimal solution of the target function model.

[0030] According to a second aspect, an embodiment of the present invention provides a structure optimization device for a complementary energy system, wherein the complementary energy system comprises: a photovoltaic power generation subsystem and an energy storage power generation subsystem, and the device comprises:

[0031] An acquisition module, used for acquiring a load power demand of the complementary energy system;

[0032] A first processing module, used to establish a first output power model of the photovoltaic power generation unit in the photovoltaic power generation subsystem and a second output power model of the energy storage power generation unit in the energy storage power generation subsystem;

[0033] A second processing module is used to construct an objective function model of the complementary energy system based on the structural parameters of the complementary energy system and taking the total system cost as the target;

[0034] A third processing module, configured to determine a structural parameter range corresponding to the structural parameter based on the load power demand, the first output power model and the second output power model;

[0035] The fourth processing module is used to calculate the optimal solution of the objective function model within the range of the structural parameters, and determine the structural design scheme of the complementary energy system based on the target structural parameters corresponding to the optimal solution.

[0036] According to the third aspect, an embodiment of the present invention provides an electronic device, comprising: a memory and a processor, the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method described in the first aspect and any one of its optional embodiments by executing the computer instructions.

[0037] According to the fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method described in the first aspect or any optional implementation manner of the first aspect.

[0038] The technical solution of the present invention has the following advantages:

[0039] The structural optimization method and device of the complementary energy system provided by the embodiment of the present invention obtain the load power demand of the complementary energy system; establish the first output power model of the photovoltaic power generation unit in the photovoltaic power generation subsystem and the second output power model of the energy storage power generation unit in the energy storage power generation subsystem; based on the structural parameters of the complementary energy system, construct the objective function model of the complementary energy system with the total system cost as the target; based on the load power demand, the first output power model and the second output power model, determine the structural parameter range corresponding to the structural parameter; within the structural parameter range, calculate the optimal solution of the objective function model, and determine the structural design scheme of the complementary energy system based on the target structural parameters corresponding to the optimal solution. Thus, by using the power output model corresponding to photovoltaic power generation and energy storage power generation to determine the structural parameter selection range of the complementary energy system that meets the load power demand, and by solving the objective function model with the total system cost as the target, determine the structural design scheme of the complementary energy system, thereby realizing the economic maximization operation of the complementary energy system while meeting the user's load demand, reducing the cost of the complementary energy system, and improving the comprehensive economic performance of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1A flowchart of a method for optimizing the structure of a complementary energy system according to an embodiment of the present invention;

[0042] Figure 2 A schematic diagram of a complementary energy system according to an embodiment of the present invention;

[0043] Figure 3 A schematic diagram of the structure of a complementary energy system structure optimization device according to an embodiment of the present invention;

[0044] Figure 4 FIG. 4 is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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 those skilled in the art without creative work are within the scope of protection of the present invention.

[0046] The technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0047] Photovoltaic power generation has been fully developed and utilized due to its advantages of high efficiency, cleanliness and pollution-free. However, there is still a lot of room for improvement in the technology and economic benefits of photovoltaic power stations. Since the large-scale grid connection of renewable energy power can easily cause grid fluctuations, the load instructions assigned to photovoltaic power stations often change. The frequently fluctuating load instructions increase the difficulty of operation and maintenance and the cost of power generation of photovoltaic power stations, and the power generation and load instructions are usually not balanced. Therefore, combining energy storage power generation such as hydrogen storage tanks or heat storage tanks with photovoltaic power stations to form a complementary energy system can improve the operational flexibility of photovoltaic power stations and achieve the dual goals of maximizing the economy of photovoltaic full-load power generation and flexible storage and utilization of surplus electricity.

[0048] However, the existing structural design schemes of complementary energy systems often only focus on meeting user load requirements and lack consideration of economic performance. There is generally a problem of high system cost. Therefore, how to optimize the structure of the complementary energy system to reduce costs and improve the comprehensive economic performance of the system while meeting user load requirements has become an urgent problem to be solved.

[0049] Based on the above problems, an embodiment of the present invention provides a method for optimizing the structure of a complementary energy system, the complementary energy system comprising: a photovoltaic power generation subsystem and an energy storage power generation subsystem. When there is surplus power generation in the photovoltaic power generation subsystem, the surplus power generation is converted into a first power generation energy source for storage by the above energy storage power generation subsystem. When the power generation of the photovoltaic power generation subsystem is insufficient, the energy storage power generation subsystem uses the stored first power generation energy source to generate electricity. It should be noted that in the embodiment of the present invention, the first power generation energy source stored in the energy storage power generation subsystem is hydrogen as an example, and the energy storage power generation unit is composed of an electrolyzer, a hydrogen storage tank and a fuel cell. In practical applications, the first power generation energy source can also be thermal energy, which can be used to store electrical energy and can be converted into electrical energy, and the present invention is not limited to this.

[0050] like Figure 1 As shown, the structural optimization method of the complementary energy system specifically includes the following steps:

[0051] Step S101: Obtain the load power demand of the complementary energy system.

[0052] The load power demand is the load power value required by the user side of the complementary energy system, that is, the output power requirement of the complementary energy system.

[0053] Step S102: establishing a first output power model of a photovoltaic power generation unit in a photovoltaic power generation subsystem and a second output power model of an energy storage power generation unit in an energy storage power generation subsystem.

[0054] Among them, the photovoltaic power generation unit is a photovoltaic array, also known as photovoltaic panels, which converts solar energy into electrical energy, and then supplies it to the load side after being boosted by an inverter. The energy storage power generation unit is composed of an electrolyzer, a hydrogen storage tank and a fuel cell. Hydrogen is extracted from water through the electrolysis process of the electrolyzer in the electrolyzer and stored in the hydrogen storage tank. The stored hydrogen is burned in the fuel cell to generate electricity for external supply. When the photovoltaic power generation unit generates excess electricity, the remaining electricity can be used to extract hydrogen from the electrolyzer of the energy storage power generation unit and store it in the hydrogen storage tank. When the photovoltaic power generation unit generates insufficient electricity, the hydrogen stored in the hydrogen storage tank is used to generate electricity to supplement the insufficient electricity generation, thereby achieving energy complementarity, that is, ensuring the load power demand on the user side, and being able to reasonably use photovoltaic energy, avoid energy waste, and improve energy utilization.

[0055] Step S103: Based on the structural parameters of the complementary energy system, an objective function model of the complementary energy system is constructed with the total system cost as the target.

[0056] Specifically, the above structural parameters include: the number of photovoltaic arrays, the area occupied by the photovoltaic arrays, the number of electrolyzers, the number of fuel cells and the number of inverters.

[0057] Step S104: determining a structural parameter range corresponding to the structural parameter based on the load power demand, the first output power model and the second output power model.

[0058] Specifically, the above step S104 determines the number selection range of photovoltaic arrays based on the load power demand and the area occupied by the photovoltaic arrays; based on the number selection range of photovoltaic arrays, determines the number of electrolyzers, the number of fuel cells and the number of inverters corresponding to different photovoltaic arrays.

[0059] Among them, in order to ensure the user's electricity demand, the occupied area and total number of photovoltaic arrays of different specifications of the above-mentioned photovoltaic power generation units need to meet certain requirements. The smaller the area, the more photovoltaic arrays are required, and vice versa.

[0060] Step S105: calculating the optimal solution of the objective function model within the range of structural parameters, and determining the structural design scheme of the complementary energy system based on the target structural parameters corresponding to the optimal solution.

[0061] Among them, the optimal solution indicates that the total system cost of the complementary energy system is the lowest. When the total system cost is the lowest, the corresponding structural parameters are used to carry out the structural design of the complementary energy system, which can meet the load power demand of the user side while ensuring the maximization of economic performance.

[0062] By executing the above steps, the structural optimization method of the complementary energy system provided by the embodiment of the present invention determines the structural parameter selection range of the complementary energy system that meets the load power demand by utilizing the power output model corresponding to photovoltaic power generation and energy storage power generation, and determines the structural design scheme of the complementary energy system by solving the objective function model with the total system cost as the target, thereby realizing the economic maximization operation of the complementary energy system while meeting the user's load demand, reducing the cost of the complementary energy system, and improving the comprehensive economic performance of the system.

[0063] Specifically, in one embodiment, the first output power model of the photovoltaic power generation unit in the photovoltaic power generation subsystem is established in the above step S102, which specifically includes the following steps:

[0064] Step S201: establishing a third power output model of the photovoltaic array based on the attribute parameters of the photovoltaic array in the photovoltaic power generation unit.

[0065] Specifically, the third power output model of the photovoltaic array can calculate the output power of the photovoltaic panel according to the solar irradiance, the ambient temperature and the efficiency of the photovoltaic array:

[0066] P pv (t) = A pv ·η pvI(t) (1)

[0067] Among them, P PV is the output power of the photovoltaic array, A PV is the area occupied by the photovoltaic array, η pv is the instantaneous efficiency of the photovoltaic array, and I is the available solar irradiance on the slope. PV , A PV , η pv , I can be obtained from the power plant operation data, and the specific calculation method will not be described here.

[0068] Among them, the instantaneous efficiency of the photovoltaic array can be expressed as:

[0069]

[0070] Among them, η pv is the instantaneous efficiency of the photovoltaic array, η r is the reference efficiency of the photovoltaic array, η t is the photovoltaic power tracking efficiency, β is the gain thermal coefficient, T a is the ambient temperature, T r is the reference thermal temperature of the photovoltaic cell, I is the available solar irradiance on the slope, and NOCT is the nominal operating temperature of the photovoltaic cell. Specifically, β∈(0.004-0.006), the gain thermal coefficient β=0.005, and the ambient temperature T a =24℃, the reference thermal temperature of the photovoltaic cell T r and nominal operating temperature NOCT, photovoltaic panel reference efficiency η r , Photovoltaic power tracking efficiency η t It can be provided by the on-site centralized control center set up by the complementary energy system, and the detailed data will not be repeated here.

[0071] Step S202: establishing a first output power model based on the attribute parameters of the inverter and the third power output model.

[0072] Specifically, the volt-generated power is supplied to the load side after being boosted by the inverter. The third power output model, i.e., the power injected by the inverter to the load, is obtained according to the efficiency of the inverter:

[0073] P inv-load =(P FC-inv +P ren-inv )·η inv (3)

[0074] Among them, P inv-load is the output power of the inverter, η inv is the conversion efficiency of the inverter, P FC-inv is the power input from the energy storage power generation unit to the inverter, P ren-invThe power input to the inverter by the photovoltaic power generation unit.

[0075] Specifically, in one embodiment, the second output power model of the energy storage power generation unit in the energy storage power generation subsystem is established in the above step S102, which specifically includes the following steps:

[0076] Step S203: establishing a fourth power output model of the electrolytic cell based on the property parameters of the electrolytic cell.

[0077] Specifically, the fourth power output model of the electrolyzer, that is, the output power of the electrolyzer is:

[0078] P el-tan k =P ren-el ·η el (4)

[0079] Among them, P el-tan k is the output power of the electrolyzer, η el is the efficiency of the electrolyzer, P ren-el It is the energy fed into the electrolyser by photovoltaic cells and biowaste.

[0080] Step S204: establishing an energy storage model of the hydrogen storage tank based on the property parameters of the hydrogen storage tank.

[0081] Specifically, the energy storage model of the hydrogen storage tank at time t is:

[0082] E tan k (t) = E tan k (t-1)+P el-tan k (t)·Δt-P tan k-FC (t)·Δt·η storage (5)

[0083] Among them, E tan k (t) is the energy stored in the hydrogen storage tank at time t, E tan k (t-1) is the energy stored in the hydrogen storage tank at time t-1, P el-tan k (t) is the power input from the electrolyzer to the energy storage tank at time t, P tan k-FC (t) is the power input from the hydrogen storage tank to the fuel cell at time t, Δt= is the time step, η storage is the efficiency of the hydrogen storage tank. For example, Δt=1h, η storage =95%.

[0084] Step S205: establishing a second output power model based on the fourth power output model, the energy storage model and the property parameters of the fuel cell.

[0085] Specifically, the second output power model, i.e., the output power model of the fuel cell, is:

[0086] PFC-inv =P tan k-FC ·η FC (6)

[0087] Among them, P FC-inv is the output power of the fuel cell, P tan k-FC is the power input from the hydrogen storage tank to the fuel cell, η FC The efficiency of the fuel cell.

[0088] Specifically, in one embodiment, the most important purpose of the complementary energy system composed of photovoltaic and hydrogen storage tanks is to increase the reliability of load supply and reduce the cost of power generation. The system economic indicators include the area and number of photovoltaic arrays, the number of electrolyzers, the number of hydrogen fuel cells, and the number of inverters. The objective function model of the complementary energy system, i.e., the photovoltaic-hydrogen storage tank economic objective function, is expressed by the following formula (7):

[0089]

[0090] Among them, Min.TNPC represents the total system cost, i represents the number of the equipment group in the system, and TNPC i represents the cost of the i-th equipment group, N is the number of photovoltaic arrays, C capital is the initial investment cost, C replacement is the replacement cost, C maintenance is the maintenance and repair cost, and the time unit is 1 year; R is the system usage time, ir is the real interest rate based on the nominal interest rate and the annual inflation rate; y and L represent the replacement times and service life of each device in the system, respectively.

[0091] Specifically, in one embodiment, in the above step S105, calculating the optimal solution of the objective function model within the structural parameter range specifically includes the following steps:

[0092] Step S501: Within the range of structural parameters, the objective function model is solved using the quantum emperor penguin optimization algorithm to obtain the system cost calculation value corresponding to the objective function model under different structural parameters.

[0093] Step S502: Determine the optimal solution of the objective function model based on the calculated value of the system cost.

[0094] Specifically, the above step S502 specifically determines the minimum system cost value by sorting the system cost calculation values ​​corresponding to different structural parameters; and determines the minimum system cost value and its corresponding target structural parameter as the optimal solution of the objective function model.

[0095] Specifically, in an embodiment of the present invention, a quantum emperor penguin optimization algorithm is introduced to optimize the comprehensive economic performance indicators of the complementary energy system.

[0096] The Emperor Penguin Optimization Algorithm (EPO algorithm for short) is a new type of swarm intelligence algorithm. The EPO algorithm simulates the behavior of emperor penguins looking for the highest temperature point in the group to find the best point. The emperor penguins will constantly change their positions and move to the optimal point under the guidance of the best individuals. The Quantum Emperor Penguin Optimization Algorithm (QEPO algorithm for short) is improved on the basis of EPO and combined with quantum wave functions, aiming to improve the algorithm's optimization accuracy and convergence speed.

[0097] In a group of emperor penguins, the individual at the highest temperature is the best individual. After determining the distance between the individual and the best individual, the penguin individual will move towards the best individual and re-determine the position of the best individual. The temperature distribution of the group around T1 is calculated as follows:

[0098]

[0099] in, k is the current iteration number, Max iteration is the maximum number of iterations.

[0100] After determining that all emperor penguin individuals are within the temperature boundary, calculate the distance between the emperor penguin individual and the optimal individual, and the emperor penguin individual updates its position vector based on the optimal individual:

[0101]

[0102]

[0103]

[0104] Where γ, η, u, ζ∈(0, 1); α is the contraction and expansion factor of the quantum rule, T is the total number of iterations of the algorithm, and t is the current number of iterations; X i is the position vector of the ith particle, xpbest i is the optimal position of particle i, X gbest It is the global optimal solution.

[0105] In order to avoid collisions between adjacent individuals in the group, use and Vector parameter characterization:

[0106]

[0107]

[0108]

[0109] in, is the position vector of the optimal individual; is the position vector of the individual; is the distance between the individual and the optimal individual; Rand∈[0,1], M=2 is the motion parameter to avoid collision between adjacent individuals and maintain distance, P grid (Accuracy) represents the absolute value between the optimal individual position and other individual positions.

[0110] Update the position vector of the emperor penguin individual according to the position of the current optimal individual. The update formula is as follows:

[0111]

[0112] in, is the current optimal individual position, is the position of the previous optimal individual, is the distance between the individual and the optimal individual, Parameter vector to prevent individual collisions. The above process is the working principle of the quantum emperor penguin algorithm. The specific solution process of the above objective function model can be solved by referring to the above content and the solution method of the quantum emperor penguin algorithm in the prior art, which will not be repeated here. After the optimization process is completed, the position information of the optimal individual is output. The optimal individual is the individual with the lowest total system cost of the above complementary energy. The position information of the optimal individual is the structural design scheme of the complementary energy system, which specifically includes: the number of photovoltaic arrays, the area occupied by the photovoltaic arrays, the number of electrolytic cells, the number of fuel cells, and the number of inverters, etc.

[0113] For example, in an embodiment of the present invention, the complementary energy system structure framework based on the optimization of the quantum emperor penguin algorithm is as follows: Figure 2 As shown. When there is surplus photovoltaic power generation, hydrogen energy is obtained by electrolyzing water through the fuel cell and stored in the hydrogen storage tank. When the weather is bad and the sunlight is insufficient, the hydrogen energy in the storage tank is converted into electrical energy to supply the load side to ensure the power demand of the load side.

[0114] Therefore, by combining hydrogen storage technology with photovoltaic power generation, the operating flexibility of photovoltaic power stations is efficiently improved; by proposing comprehensive economic indicators covering power generation costs, equipment costs and operation and maintenance costs, support is provided for the economic maximization of photovoltaic-hydrogen storage tank energy systems; by using the quantum emperor penguin algorithm to automatically solve the objective function of the energy system, the intelligence and professionalism of photovoltaic power generation are improved.

[0115] By executing the above steps, the structural optimization method of the complementary energy system provided by the embodiment of the present invention determines the structural parameter selection range of the complementary energy system that meets the load power demand by utilizing the power output model corresponding to photovoltaic power generation and energy storage power generation, and determines the structural design scheme of the complementary energy system by solving the objective function model with the total system cost as the target, thereby realizing the economic maximization operation of the complementary energy system while meeting the user's load demand, reducing the cost of the complementary energy system, and improving the comprehensive economic performance of the system.

[0116] The embodiment of the present invention also provides a structure optimization device for a complementary energy system, such as Figure 3 As shown, the structural optimization device of the complementary energy system includes:

[0117] The acquisition module 101 is used to acquire the load power demand of the complementary energy system. For details, please refer to the relevant description of step S101 in the above method embodiment, which will not be repeated here.

[0118] The first processing module 102 is used to establish a first output power model of the photovoltaic power generation unit in the photovoltaic power generation subsystem and a second output power model of the energy storage power generation unit in the energy storage power generation subsystem. For details, please refer to the relevant description of step S102 in the above method embodiment, which will not be repeated here.

[0119] The second processing module 103 is used to construct an objective function model of the complementary energy system based on the structural parameters of the complementary energy system and taking the total system cost as the target. For details, please refer to the relevant description of step S103 in the above method embodiment, which will not be repeated here.

[0120] The third processing module 104 is used to determine the structural parameter range corresponding to the structural parameter based on the load power demand, the first output power model and the second output power model. For details, please refer to the relevant description of step S104 in the above method embodiment, which will not be repeated here.

[0121] The fourth processing module 105 is used to calculate the optimal solution of the objective function model within the structural parameter range, and determine the structural design scheme of the complementary energy system based on the target structural parameters corresponding to the optimal solution. For details, please refer to the relevant description of step S105 in the above method embodiment, which will not be repeated here.

[0122] The complementary energy system structure optimization device provided in the embodiment of the present invention is used to execute the complementary energy system structure optimization method provided in the above embodiment. Its implementation method and principle are the same. For details, please refer to the relevant description of the above method embodiment and will not be repeated here.

[0123] Through the coordinated cooperation of the above-mentioned components, the structural optimization device of the complementary energy system provided by the embodiment of the present invention determines the structural parameter selection range of the complementary energy system that meets the load power demand by utilizing the power output model corresponding to photovoltaic power generation and energy storage power generation, and determines the structural design scheme of the complementary energy system by solving the objective function model with the total system cost as the target, thereby realizing the economic maximization operation of the complementary energy system while meeting the user's load demand, reducing the cost of the complementary energy system, and improving the comprehensive economic performance of the system.

[0124] The embodiment of the present invention further provides an electronic device, such as Figure 4 As shown, the electronic device includes: a processor 901 and a memory 902, wherein the processor 901 and the memory 902 can be connected via a bus or other means. Figure 4 The example of connecting through bus is taken in the following.

[0125] The processor 901 may be a central processing unit (CPU). The processor 901 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips.

[0126] The memory 902 is a non-transitory computer-readable storage medium that can be used to store non-transitory software programs, non-transitory computer executable programs and modules, such as program instructions / modules corresponding to the methods in the above method embodiments. The processor 901 executes various functional applications and data processing of the processor by running the non-transitory software programs, instructions and modules stored in the memory 902, that is, implementing the methods in the above method embodiments.

[0127] The memory 902 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required by at least one function; the data storage area may store data created by the processor 901, etc. In addition, the memory 902 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 902 may optionally include a memory remotely arranged relative to the processor 901, and these remote memories may be connected to the processor 901 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0128] One or more modules are stored in the memory 902 , and when executed by the processor 901 , the method in the above method embodiment is executed.

[0129] The specific details of the above electronic device can be understood by referring to the corresponding related descriptions and effects in the above embodiments, and will not be repeated here.

[0130] 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 implemented program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD), etc.; the storage medium can also include a combination of the above-mentioned types of memory.

[0131] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A structural optimization method for a complementary energy system, characterized in that: The complementary energy system comprises: a photovoltaic power generation subsystem and an energy storage power generation subsystem, and the method comprises: Obtaining load power demand of the complementary energy system; Establishing a first output power model of a photovoltaic power generation unit in the photovoltaic power generation subsystem and a second output power model of an energy storage power generation unit in the energy storage power generation subsystem; Based on the structural parameters of the complementary energy system, an objective function model of the complementary energy system is constructed with the total system cost as the target; Determining a structural parameter range corresponding to the structural parameter based on the load power demand, the first output power model, and the second output power model; Within the range of the structural parameters, calculating the optimal solution of the objective function model, and determining the structural design scheme of the complementary energy system based on the target structural parameters corresponding to the optimal solution; The step of establishing the first output power model of the photovoltaic power generation unit in the photovoltaic power generation subsystem includes: establishing a third power output model of the photovoltaic array based on the attribute parameters of the photovoltaic array in the photovoltaic power generation unit; and establishing the first output power model based on the attribute parameters of the inverter and the third power output model. The energy source for power generation stored in the energy storage and power generation unit is hydrogen, and the energy storage and power generation unit is composed of an electrolyzer, a hydrogen storage tank and a fuel cell. The second output power model of the energy storage and power generation unit in the energy storage and power generation subsystem is established, including: establishing a fourth power output model of the electrolyzer based on the property parameters of the electrolyzer; establishing an energy storage model of the hydrogen storage tank based on the property parameters of the hydrogen storage tank; and establishing the second output power model based on the fourth power output model, the energy storage model and the property parameters of the fuel cell. The objective function model of the complementary energy system is expressed by the following formula: Among them, Min.TNPC represents the total system cost, i represents the number of the equipment group in the system, and TNPC i represents the cost of the i-th equipment group, N is the number of photovoltaic arrays, C capital is the initial investment cost, C replacement is the replacement cost, C maintenance is the maintenance and repair cost, and the time unit is 1 year; R is the system usage time, ir is the real interest rate based on the nominal interest rate and the annual inflation rate; y and L represent the replacement times and service life of each device in the system, respectively.

2. The method according to claim 1, characterized in that: The structural parameters include: the number of photovoltaic arrays, the area occupied by the photovoltaic arrays, the number of electrolyzers, the number of fuel cells, and the number of inverters. The determining of the structural parameter range corresponding to the structural parameters based on the load power demand, the first output power model, and the second output power model includes: Determining a selection range of the number of photovoltaic arrays based on the load power demand and the area occupied by the photovoltaic array; Based on the selection range of the number of photovoltaic arrays, the number of electrolyzers, the number of fuel cells and the number of inverters corresponding to different photovoltaic arrays are determined.

3. The method according to claim 1, characterized in that: The step of calculating the optimal solution of the objective function model within the range of the structural parameters comprises: Within the range of the structural parameters, the objective function model is solved by using a quantum emperor penguin optimization algorithm to obtain a system cost calculation value corresponding to the objective function model under different structural parameters; An optimal solution for the objective function model is determined based on the calculated value of the system cost.

4. The method according to claim 3, characterized in that The determining the optimal solution of the objective function model based on the system cost calculation value includes: Sorting the system cost calculation values ​​corresponding to different structural parameters to determine the minimum system cost value; The minimum system cost value and its corresponding target structure parameter are determined as the optimal solution of the target function model.

5. A structural optimization device for a complementary energy system, characterized in that: The complementary energy system comprises: a photovoltaic power generation subsystem and an energy storage power generation subsystem, and the device comprises: An acquisition module, used for acquiring a load power demand of the complementary energy system; A first processing module, used to establish a first output power model of the photovoltaic power generation unit in the photovoltaic power generation subsystem and a second output power model of the energy storage power generation unit in the energy storage power generation subsystem; A second processing module is used to construct an objective function model of the complementary energy system based on the structural parameters of the complementary energy system and taking the total system cost as the target; A third processing module, configured to determine a structural parameter range corresponding to the structural parameter based on the load power demand, the first output power model and the second output power model; A fourth processing module, used to calculate the optimal solution of the objective function model within the range of the structural parameters, and determine the structural design scheme of the complementary energy system based on the target structural parameters corresponding to the optimal solution; The first processing module is specifically used to: establish a third power output model of the photovoltaic array based on the attribute parameters of the photovoltaic array in the photovoltaic power generation unit; establish the first output power model based on the attribute parameters of the inverter and the third power output model; The energy source for power generation stored in the energy storage power generation unit is hydrogen. The energy storage power generation unit is composed of an electrolyzer, a hydrogen storage tank and a fuel cell. The first processing module is further used to: establish a fourth power output model of the electrolyzer based on the property parameters of the electrolyzer; establish an energy storage model of the hydrogen storage tank based on the property parameters of the hydrogen storage tank; establish the second output power model based on the fourth power output model, the energy storage model and the property parameters of the fuel cell; The objective function model of the complementary energy system is expressed by the following formula: Among them, Min.TNPC represents the total system cost, i represents the number of the equipment group in the system, and TNPC i represents the cost of the i-th equipment group, N is the number of photovoltaic arrays, C capital is the initial investment cost, C replacement is the replacement cost, C maintenance is the maintenance and repair cost, and the time unit is 1 year; R is the system usage time, ir is the real interest rate based on the nominal interest rate and the annual inflation rate; y and L represent the replacement times and service life of each device in the system, respectively.

6. An electronic device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 4 by executing the computer instructions.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method according to any one of claims 1 to 4.

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