Processing method of integrated energy system, electronic device and storage medium

Abstract

Embodiments of the present application provide a kind of integrated energy system processing method, electronic equipment and storage medium.The method comprises: obtaining initial vector;Under the constraint of initial vector, integrated energy system simulation model is run, and fitness value is obtained;Fitness value includes system reliability, energy cost and photovoltaic waste rate;When fitness value does not satisfy genetic termination condition, initial vector is processed using genetic algorithm, and candidate vector is obtained, candidate vector is used to replace initial vector, and the step of continuing to determine fitness value is carried out;In the case where fitness value satisfies genetic termination condition, the initial vector that satisfies genetic termination condition is used as target vector;Target vector includes target photovoltaic array rated power, target electrolytic cell rated power, target fuel cell rated power, target hydrogen storage tank capacity and target collector area.The method improves the reliability of integrated energy system, reduces energy cost, and improves the utilization rate of photovoltaic power generation.

Description

Technical Field

[0001] This application relates to the energy field, and more particularly to a processing method, electronic device, and storage medium for an integrated energy system. Background Technology

[0002] An integrated energy system is a system that combines electrical energy, hydrogen energy, and thermal energy, enabling coordinated planning, optimized operation, collaborative management, interactive response, and mutual support among multiple energy subsystems.

[0003] In related technologies, energy devices in integrated energy systems are set to operate according to fixed reference parameters. For example, photovoltaic arrays operate at reference rated power, and fuel cells operate at reference rated power, resulting in low overall efficiency of the integrated energy system. Summary of the Invention

[0004] This application provides a processing method, electronic device, and storage medium for an integrated energy system, which improves the reliability of the integrated energy system, reduces energy costs, increases the utilization rate of photovoltaic power generation, and effectively improves the overall efficiency of the integrated energy system.

[0005] In a first aspect, embodiments of this application provide a method for processing an integrated energy system, comprising: obtaining an initial vector; the initial vector including the rated power of a photovoltaic array, the rated power of an electrolyzer, the rated power of a fuel cell, the capacity of a hydrogen storage tank, and the area of ​​a solar collector; running an integrated energy system simulation model under the constraints of the initial vector to obtain a fitness value corresponding to the initial vector; the fitness value including system reliability, energy cost, and photovoltaic waste rate; if the fitness value does not meet the genetic termination condition, processing the initial vector using a genetic algorithm based on the fitness value to obtain a candidate vector; replacing the initial vector with the candidate vector and continuing to execute the step of running the integrated energy system simulation model under the constraints of the initial vector; if the fitness value meets the genetic termination condition, using the initial vector that meets the genetic termination condition as the target vector; the target vector including the target rated power of the photovoltaic array, the target rated power of the electrolyzer, the target rated power of the fuel cell, the target capacity of the hydrogen storage tank, and the target area of ​​the solar collector.

[0006] Secondly, embodiments of this application provide a processing apparatus for an integrated energy system, comprising:

[0007] The acquisition module is used to acquire the initial vector; the initial vector includes the rated power of the photovoltaic array, the rated power of the electrolyzer, the rated power of the fuel cell, the capacity of the hydrogen storage tank, and the area of ​​the solar collector;

[0008] The simulation module is used to run a comprehensive energy system simulation model under the constraints of the initial vector to obtain the fitness value corresponding to the initial vector; the fitness value includes system reliability, energy cost and photovoltaic waste rate;

[0009] The optimization module is used to process the initial vector using a genetic algorithm based on the fitness value to obtain candidate vectors when the fitness value does not meet the genetic termination condition.

[0010] The iterative module is used to replace the initial vector with a candidate vector and continue executing the steps of running the integrated energy system simulation model under the constraints of the initial vector;

[0011] The processing module is used to take the initial vector that meets the genetic termination condition as the target vector when the fitness value meets the genetic termination condition. The target vector includes the target photovoltaic array rated power, the target electrolyzer rated power, the target fuel cell rated power, the target hydrogen storage tank capacity, and the target solar collector area.

[0012] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor;

[0013] The memory stores instructions that the computer executes;

[0014] The processor executes computer execution instructions stored in memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0015] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0016] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0017] The integrated energy system processing method, electronic device, storage medium, and program product provided in this application embodiment, in the above-mentioned integrated energy system processing method, the initial vector includes the rated power of the photovoltaic array, the rated power of the electrolyzer, the rated power of the fuel cell, the capacity of the hydrogen storage tank, and the area of ​​the solar collector. Under the constraints of the initial vector, the integrated energy system simulation model is run to obtain the fitness corresponding to the initial vector. If the fitness does not meet the genetic termination condition, the initial vector is processed by a genetic algorithm based on the fitness to obtain candidate vectors. The candidate vectors are used to replace the initial vector. This process is repeated multiple times until the fitness corresponding to the initial vector meets the genetic termination condition. The initial vector that meets the genetic termination condition is taken as the target vector, thereby determining the target rated power of the photovoltaic array, the target rated power of the electrolyzer, the target rated power of the fuel cell, the target capacity of the hydrogen storage tank, and the target area of ​​the solar collector. This improves the reliability of the integrated energy system, reduces energy costs, and improves the utilization rate of photovoltaic power generation. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0019] Figure 1 Flowchart of the processing method for the integrated energy system provided in this application Figure 1 ;

[0020] Figure 2 A schematic diagram of the integrated energy system provided in this application;

[0021] Figure 3 Flowchart of the processing method for the integrated energy system provided in this application Figure 2 ;

[0022] Figure 4 Flowchart of the processing method for the integrated energy system provided in this application Figure 3 ;

[0023] Figure 5 A schematic diagram of the processing device for the integrated energy system provided in this application;

[0024] Figure 6 A schematic diagram of the structure of the electronic device provided in this application.

[0025] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0026] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0027] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0028] Figure 1 Flowchart of the processing method for the integrated energy system provided in this application Figure 1 ,like Figure 1 As shown, the method includes:

[0029] S101. Obtain the initial vector; the initial vector includes the rated power of the photovoltaic array, the rated power of the electrolyzer, the rated power of the fuel cell, the capacity of the hydrogen storage tank, and the area of ​​the solar collector.

[0030] Among them, the rated power of the photovoltaic array is the maximum power that the photovoltaic array can output, which can be used to evaluate the power generation capacity of the photovoltaic array; the rated power of the electrolyzer is the maximum power that the electrolyzer can output, which can be used to evaluate the electrolysis capacity of the electrolyzer; the rated power of the fuel cell is the maximum power that the fuel cell can output, which can be used to evaluate the power generation capacity of the fuel cell; the hydrogen storage tank capacity is the maximum capacity of hydrogen that the hydrogen storage tank can store, which determines the functional regulation capability of the integrated energy network system; and the collector area is the maximum effective area of ​​sunlight projected onto the collector, which is an important parameter for evaluating the performance of the solar thermal system, determining the system capacity, and selecting the appropriate type.

[0031] Specifically, the initial vector can be represented as ;in, It is the rated power of the photovoltaic array, It is the rated power of the electrolytic cell, It is the rated power of the fuel cell, It refers to the capacity of the hydrogen storage tank. It refers to the area of ​​the solar collector.

[0032] The electronic device can randomly generate multiple photovoltaic array rated power, multiple electrolyzer rated power, multiple fuel cell rated power, multiple hydrogen storage tank capacity, and multiple solar collector area. Based on the randomly generated multiple photovoltaic array rated power, multiple electrolyzer rated power, multiple fuel cell rated power, multiple hydrogen storage tank capacity, and multiple solar collector area, multiple initial vectors are formed.

[0033] S102. Run the integrated energy system simulation model under the constraints of the initial vector to obtain the fitness value corresponding to the initial vector; the fitness value includes system reliability, energy cost and photovoltaic waste rate.

[0034] Among them, the integrated energy system simulation model is obtained by simulating the integrated energy system; specifically, such as Figure 2 As shown, the solar-hydrogen power system includes a photovoltaic array that provides renewable electricity to the load. Excess electricity generated by the photovoltaic array powers an electrolyzer to produce hydrogen. The fuel cell combines hydrogen and oxygen to generate electricity for power supply. The hydrogen produced by the electrolyzer is stored in a hydrogen storage tank and can be used by the fuel cell. When the power generation of the photovoltaic array is insufficient to meet the power demand, the fuel cell operates and can absorb hydrogen from the hydrogen storage tank to generate electricity. The electrolyzer and fuel cell can be implemented using proton exchange membrane technology.

[0035] Since fuel cells generate heat during operation, some of this heat can be generated through coolant exchange to provide hot water. Thus, a solar-hydrogen cogeneration system is formed on the basis of the solar-hydrogen power system. The solar-thermal system heats the water in the storage tank through a solar collector.

[0036] The integrated energy system in this application embodiment combines a solar-hydrogen cogeneration system and a solar-thermal system. When solar radiation is insufficient, the photovoltaic array's electrical output is insufficient, and the thermal output of the thermal system is also insufficient. At this time, the energy of the fuel cell can be used to meet the insufficient power supply of the photovoltaic array. At the same time, the heat generated by the operation of the fuel cell can be recovered in the cogeneration system, thereby making up for the insufficiency of the solar collector. The heat of the fuel cell is recovered through a heat exchanger, and the cold load (the heat recovered from the fuel cell) is transferred to the water tank of the thermal system through the heat exchanger to provide hot water to the water tank.

[0037] The fitness values ​​include system reliability, energy cost, and photovoltaic waste rate. System reliability reflects the overall reliability of the integrated energy system for power supply and heating. Energy cost is the cost required to operate the integrated energy system. Photovoltaic waste rate represents the ratio between the power generation provided by the photovoltaic array that is not involved in the operation of the integrated energy system and the power generation provided by the photovoltaic array.

[0038] Specifically, the electronic device inputs the initial vector into the integrated energy system simulation model so that the integrated energy system simulation model runs under the constraints of the initial vector, and obtains the system reliability, energy cost and photovoltaic waste rate after the simulation is completed.

[0039] S103. If the fitness value does not meet the genetic termination condition, the initial vector is processed using a genetic algorithm based on the fitness value to obtain candidate vectors.

[0040] The genetic termination condition can be that the number of iterations (the number of times processed by the genetic algorithm) corresponding to the initial vector reaches a preset number, the fitness value corresponding to the initial vector converges, or other termination conditions.

[0041] Genetic algorithms are heuristic search algorithms based on the principles of natural selection and genetics. They transform the problem-solving process into a process similar to the crossover and mutation of chromosomes in biological evolution.

[0042] In genetic algorithms, fitness value can be used as a key indicator to evaluate the quality of an individual (initial vector). The higher the fitness value, the greater the probability that the initial vector will be selected during the evolution process, thus having more opportunities to reproduce offspring and gradually approach the optimal solution.

[0043] Specifically, the electronic device uses a genetic algorithm to process the initial vector based on the fitness value corresponding to the initial vector to obtain candidate vectors.

[0044] In practical applications, there can be multiple initial vectors, which can be regarded as an initial population; there can also be multiple candidate vectors, which can be regarded as a candidate population. That is, it can be understood that the electronic device uses a genetic algorithm to process the initial population based on the fitness value of the initial vectors to obtain the candidate population.

[0045] S104. Replace the initial vector with a candidate vector and continue to execute the steps of running the integrated energy system simulation model under the constraints of the initial vector.

[0046] Specifically, after the electronic device obtains the candidate vector, it replaces the initial vector with the candidate vector and continues to execute S102. After determining the fitness value corresponding to the initial vector (the candidate vector obtained in the previous iteration), it then judges whether the genetic termination condition is met. If the genetic termination condition is not met, the initial vector (the candidate vector obtained in the previous iteration) is processed again by the genetic algorithm. This process is repeated multiple times.

[0047] S105. If the fitness value satisfies the genetic termination condition, the initial vector that satisfies the genetic termination condition shall be used as the target vector. The target vector includes the target photovoltaic array rated power, the target electrolyzer rated power, the target fuel cell rated power, the target hydrogen storage tank capacity, and the target solar collector area.

[0048] Specifically, the electronic device determines whether the initial vector satisfies the genetic termination condition. If the initial vector satisfies the genetic termination condition, the initial vector that satisfies the genetic termination condition is taken as the target vector.

[0049] For example, an electronic device randomly generates an initial vector x0, and an initial population A0 includes multiple initial vectors x0. Under the constraints of the initial vector x0, a comprehensive energy system simulation model is run to obtain the fitness value f0 corresponding to the initial vector x0. Based on the fitness value f0, it is determined whether the genetic termination condition is met. If not, based on the initial vector x0 and the corresponding fitness value f0, a genetic algorithm is used to process the initial population A0 to obtain a candidate population A1, which includes multiple candidate vectors x1. The initial vector x0 is replaced by the candidate vector x1 (the initial population A0 is replaced by the candidate population A1), and the comprehensive energy system simulation model is run under the constraints of the initial vector x1 (candidate vector x1) to obtain the fitness value f1 corresponding to the initial vector x1. Based on the fitness value f1, it is determined whether the genetic termination condition is met. If not, the genetic algorithm is executed again, and this process is repeated multiple times until an initial vector xn is obtained. The fitness value fn of the initial vector xn satisfies the genetic termination condition, and the initial vector xn is used as the target vector.

[0050] The target vector is obtained, which determines the rated power of the photovoltaic array, the rated power of the electrolyzer, the rated power of the fuel cell, the capacity of the hydrogen storage tank, and the area of ​​the solar collector in the integrated energy system. This results in the highest system reliability, the lowest energy cost, and the lowest photovoltaic waste rate of the integrated energy system, thereby improving the reliability of the integrated energy system, reducing energy costs, and increasing the utilization rate of photovoltaic power generation.

[0051] In the aforementioned integrated energy system processing method, the initial vector includes the rated power of the photovoltaic array, the rated power of the electrolyzer, the rated power of the fuel cell, the capacity of the hydrogen storage tank, and the area of ​​the solar collector. Under the constraints of the initial vector, the integrated energy system simulation model is run to obtain the fitness corresponding to the initial vector. If the fitness does not meet the genetic termination condition, a genetic algorithm is used to process the initial vector based on the fitness to obtain candidate vectors. These candidate vectors replace the initial vector, and this process is repeated multiple times until the fitness corresponding to the initial vector meets the genetic termination condition. The initial vector that meets the genetic termination condition is then used as the target vector, thereby determining the target rated power of the photovoltaic array, the target rated power of the electrolyzer, the target rated power of the fuel cell, the target capacity of the hydrogen storage tank, and the target area of ​​the solar collector. This improves the reliability of the integrated energy system, reduces energy costs, and increases the utilization rate of photovoltaic power generation.

[0052] In some embodiments, obtaining an initial vector includes: obtaining a first constraint condition for the rated power of the photovoltaic array, a second constraint condition for the rated power of the electrolyzer, a third constraint condition for the rated power of the fuel cell, a fourth constraint condition for the capacity of the hydrogen storage tank, and a fifth constraint condition for the area of ​​the solar collector; and generating an initial vector under the constraints of the first, second, third, fourth, and fifth constraints.

[0053] Specifically, the first constraint condition represents the range to which the rated power of the photovoltaic array belongs. Similarly, the second, third, fourth, and fifth constraints each represent the range to which their respective parameters belong.

[0054] For example, the first constraint is shown in formula (1).

[0055] (1)

[0056] The second constraint is shown in formula (2).

[0057] (2)

[0058] The third constraint is shown in formula (3).

[0059] (3)

[0060] The fourth constraint is shown in formula (4).

[0061] (4)

[0062] The fifth constraint is shown in formula (5).

[0063] (5)

[0064] in, It is the rated power of the photovoltaic array, It is the rated power of the electrolytic cell, It is the rated power of the fuel cell, It refers to the capacity of the hydrogen storage tank. It refers to the area of ​​the solar collector.

[0065] In practical applications, the maximum rated power of the photovoltaic array, the maximum rated power of the electrolyzer, the maximum rated power of the fuel cell, the maximum capacity of the hydrogen storage tank, and the maximum area of ​​the solar collector can also be set according to the actual situation.

[0066] In the above embodiments, under the first constraint, the rated power of the photovoltaic array is randomly generated; under the second constraint, the rated power of the electrolyzer is randomly generated; under the third constraint, the rated power of the fuel cell is randomly generated; under the fourth constraint, the capacity of the hydrogen storage tank is randomly generated; and under the fifth constraint, the area of ​​the solar collector is randomly generated. Then, an initial vector is formed based on the generated rated power of the photovoltaic array, rated power of the electrolyzer, rated power of the fuel cell, capacity of the hydrogen storage tank, and area of ​​the solar collector, thereby improving the richness and flexibility of the initial vector.

[0067] In some embodiments, the integrated energy system simulation model includes: a combined heat and power (CHP) simulation model, a thermal energy simulation model, and an economic simulation model; running the integrated energy system simulation model under the constraints of an initial vector to obtain the fitness value corresponding to the initial vector includes:

[0068] For each initial vector, a comprehensive energy system simulation model is run under the constraints of the initial vector. The photovoltaic waste rate and power reliability corresponding to the initial vector are obtained through the cogeneration simulation model, the thermal reliability corresponding to the initial vector is obtained through the thermal energy simulation model, and the energy cost corresponding to the initial vector is obtained through the economic simulation model. The system reliability corresponding to the initial vector is determined based on the power reliability and thermal reliability.

[0069] Specifically, for each initial vector, a comprehensive energy system simulation model is run under the constraints of that initial vector. The cogeneration simulation model outputs the photovoltaic waste rate and power reliability corresponding to the initial vector. The cogeneration simulation model also obtains the cooling load, which is the heat recovered from the fuel cell. The cooling load is input into the thermal simulation model, which obtains the thermal reliability corresponding to the initial vector. The product between the power reliability and the thermal reliability is calculated to obtain the system reliability.

[0070] Obtain initial costs, maintenance costs, equipment replacement costs, and equipment operating costs. Determine energy output costs using cogeneration simulation models and thermal energy simulation models. Calculate energy costs based on these initial costs, maintenance costs, equipment replacement costs, equipment operating costs, and energy output costs.

[0071] In the above embodiments, a comprehensive energy system simulation model is run under the constraints of the initial vector. Through the cogeneration simulation model, thermal energy simulation model, and economic simulation model, the system reliability, energy cost, and photovoltaic waste rate are determined. This allows for subsequent optimization of the rated power of the photovoltaic array, the rated power of the electrolyzer, the rated power of the fuel cell, the hydrogen storage tank capacity, and the collector area based on the system reliability, energy cost, and photovoltaic waste rate. This improves the reliability of the comprehensive energy system, reduces energy costs, and increases the utilization rate of photovoltaic power generation.

[0072] In some embodiments, a comprehensive energy system simulation model is run under the constraints of a given initial vector. The photovoltaic waste rate and power reliability corresponding to the given initial vector are obtained through a combined heat and power (CHP) simulation model; the thermal reliability corresponding to the given initial vector is obtained through a thermal energy simulation model; and the energy cost corresponding to the given initial vector is obtained through an economic simulation model, including:

[0073] The cogeneration simulation model is run under the constraints of the initial vector to obtain the output power of the photovoltaic array, the cooling load of the fuel cell, the power reliability and the power shortage demand. The photovoltaic waste rate is determined based on the preset power demand power, the output power of the photovoltaic array, the rated power of the fuel cell and the rated power of the electrolyzer included in the initial vector.

[0074] The thermal simulation model is run under the constraints of the initial vector and the fuel cell cold load to obtain the thermal reliability and gap thermal energy corresponding to the initial vector.

[0075] By inputting the power demand gap and heat energy gap into the economic simulation model, the energy cost corresponding to the initial vector is obtained.

[0076] Specifically, in the cogeneration simulation model, the output power of the photovoltaic array can be determined according to formulas (6) and (7).

[0077] (6)

[0078] (7)

[0079] in, It refers to the conversion efficiency of the photovoltaic array. This is the reference efficiency of the photovoltaic array. It refers to the efficiency of the auxiliary components of the photovoltaic array. It is the temperature coefficient of the photovoltaic array. It is the ambient temperature. It is the total incident irradiance. This refers to the ambient temperature at the standard rated battery operating temperature. It is the incident irradiance at the standard rated battery operating temperature. This is the reference temperature for the photovoltaic array. This is the rated power of the photovoltaic array. It is the output power of the photovoltaic array.

[0080] To reduce manufacturing costs, the electrolyzer is set to operate at low pressure; the mass flow rate of hydrogen supplied to the electrolyzer can be calculated according to formula (8).

[0081] (8)

[0082] in, It is the mass flow rate of hydrogen supplied to the electrolyzer. It is the input power of the electrolytic cell. It is the high calorific value of hydrogen. It refers to the conversion efficiency of the electrolytic cell.

[0083] The mass flow rate of hydrogen flowing into the fuel cell is shown in Equation (9).

[0084] (9)

[0085] in, It is the mass flow rate of hydrogen flowing into the fuel cell. It refers to the number of cells in the fuel cell. It is the current of the fuel cell. It is Faraday's constant. It is the hydrogen utilization coefficient.

[0086] For a given fuel cell power The energy conversion efficiency of the fuel cell is shown in formula (10).

[0087] , (10)

[0088] in, It refers to the energy conversion efficiency of the fuel cell. It is the mass flow rate of hydrogen flowing into the fuel cell. It is the high calorific value of hydrogen. It refers to the power of the fuel cell.

[0089] The amount of heat generated when the fuel cell operates at fuel cell power is determined by formula (11).

[0090] (11)

[0091] in, It is the heat generated by the fuel cell. It refers to the power of the fuel cell. It is the hydrogen utilization coefficient. It refers to the energy conversion efficiency of a fuel cell.

[0092] The heat generated by the fuel cell is partially absorbed by the inside of the fuel cell to evaporate the generated water, partially carried away by the additional air and hydrogen flow, partially carried away by the heat through convection on the outer surface of the fuel cell, and part of the remaining heat, namely the fuel cell cold load, is recovered through the heat exchanger. The fuel cell cold load can be 60% to 70% of the heat generated by the fuel cell. For example, the fuel cell cold load is calculated according to formula (12).

[0093] (12)

[0094] in, It is the heat generated by the fuel cell. It is the cold load of the fuel cell.

[0095] The combined heat and power (CHP) simulation model, simulating year-round operation, determines the mass of hydrogen stored in the hydrogen storage tank at any given time t, based on the current hydrogen mass flow rate into the fuel cell, the current hydrogen mass flow rate supplied by the electrolyzer, and the hydrogen mass at the previous time. It is worth noting that the electrolyzer and fuel cell do not operate simultaneously.

[0096] The cogeneration simulation model simulates year-round operation. For all moments throughout the year, the number of moments when the output power of the cogeneration simulation model meets the preset power demand is obtained. The ratio between the number of moments when the preset power demand is met and the total number of moments throughout the year is used as the power reliability.

[0097] For any time t in a year, the power demand shortfall can be determined based on the output power and preset power demand of the cogeneration simulation model at time t.

[0098] For any time t in the year, the output power of the photovoltaic array and the preset power demand at time t are obtained according to the cogeneration simulation model. If the output power of the photovoltaic array can meet the preset power demand, the fuel cell will not run, and the excess output power of the photovoltaic array will enter the electrolyzer. If the excess output power of the photovoltaic array is less than or equal to the rated power of the electrolyzer, the excess output power of the photovoltaic array will be fully utilized by the electrolyzer. If the excess output power of the photovoltaic array is greater than the rated power of the electrolyzer, the excess output power of the photovoltaic array will be wasted. If the output power of the photovoltaic array cannot meet the preset power demand, the fuel cell will run, and the power of the fuel cell corresponding to the power demand not met by the output power of the photovoltaic array will not exceed the rated power of the fuel cell. Therefore, the photovoltaic waste rate can be calculated according to formula (13).

[0099] (13)

[0100] in, It's the photovoltaic waste rate. It is the output power of the photovoltaic array. It is a preset power demand. This is the rated power of the electrolytic cell.

[0101] For the combined heat and power simulation model, it is also necessary to determine the hydrogen storage status in the hydrogen storage tank; the change in the hydrogen mass in the hydrogen storage tank is based on formula (14).

[0102] (14)

[0103] in, It represents the mass of hydrogen in the hydrogen storage tank at any time t throughout the year. It is any time t-1 in the whole year. It is the mass flow rate of hydrogen supplied to the electrolyzer. It is the mass flow rate of hydrogen flowing into the fuel cell; where, The maximum mass of the hydrogen storage tank corresponding to the hydrogen storage tank capacity included in the initial vector is less than the maximum mass of the hydrogen storage tank. .

[0104] The maximum mass of the hydrogen storage tank is calculated according to formula (15).

[0105] (15)

[0106] in, This is the maximum mass of the hydrogen storage tank. It refers to the hydrogen storage tank capacity included in the initial vector.

[0107] When t=1, This is the initial mass of the hydrogen storage tank, which can be denoted as... The initial mass can be a set value; at the end of the year, the mass of hydrogen in the storage tank is equal to that initial mass, which helps to wait for a more accurate cost and photovoltaic waste rate.

[0108] Based on the above process, the cogeneration simulation model operates under the constraints of the photovoltaic array rated power, electrolyzer rated power, fuel cell rated power, and hydrogen storage tank capacity included in the initial vector, and obtains the fuel cell cold load, power reliability, shortfall power demand, and photovoltaic waste rate.

[0109] The fuel cell cold load is input into the thermal simulation model. The thermal simulation model is run under the constraints of the collector area and fuel cell cold load included in the initial vector to obtain the thermal reliability and gap thermal energy corresponding to the initial vector.

[0110] refer to Figure 2 The diagram shows the structure of the heat exchanger, water storage tank, and solar collector. The thermal simulation model operates based on the following constraints.

[0111] The water storage tank is a multi-node system comprising five water tank nodes. Water tank node 1 contains cold water, and water tank node 5 contains hot water. A thermal simulation model simulates year-round operation and can calculate the water temperature at each water tank node at all times (t). The flow rate mass of water tank node 5 flowing into the solar collector is... The temperature is Therefore, the relationship shown in formulas (16) and (17) exists.

[0112] (16)

[0113] (17)

[0114] That is, the temperature of water tank node 5 It is equal to the input temperature of the solar collector. ; Input flow quality of water tank node 2 Equal to the flow rate and mass of the solar collector Temperature of water tank node 2 equal to the output temperature of the solar collector. .

[0115] The output temperature of the solar collector is shown in formula (18).

[0116] (18)

[0117] in, It is the output temperature of the solar collector. It is the total incident irradiance. It refers to the thermal efficiency of the solar collector. It is the collector area, and it is the mass flow rate of the circulating water in the collector. It is the specific heat capacity of water. The input temperature of the solar collector; the flow rate and mass of the solar collector. Equal to 25 In other words, the area of ​​the solar collector determines the flow rate of the solar collector, which in turn affects the output temperature of the solar collector and the temperature of the water tank nodes.

[0118] Water tank node 5 is filled with cold water, and hot water is drawn from water tank node 1 to the point of use; hot water is required to be supplied on demand, and the required hot water temperature is set at 40℃. Therefore, the heat demand corresponding to the hot water demand is... As shown in formula (19).

[0119] (19)

[0120] in, It is the demand for calories. This is the hot water demand when the required temperature is 40℃. It is the temperature of the cold water; It is the specific heat capacity of water.

[0121] If the temperature at node 1 of the water tank is less than 40℃, then the mass flow rate of the hot water from the storage tank to the required hot water is: At this time, heat demand Not fully satisfied; mass flow rate of cold water entering water tank node 5 This equals the mass flow rate of hot water from node 1 of the water tank to the required flow rate. ,Right now If the temperature at water tank node 1 is higher than 40°C, the hot water flowing from the storage tank to the user's side mixes with some cold water to reach 40°C, thus:

[0122] .

[0123] Wherein, the temperature of water tank node 1 is equal to the cold side inlet temperature of the heat exchanger, that is... The cold side outlet temperature of the heat exchanger It is equal to the temperature of the water flowing from the heat exchanger to node 1 of the water tank.

[0124] Heat exchanger As shown in formula (20).

[0125] (20)

[0126] in, It is the heat from the heat exchanger. It's the efficiency of the fuel cell. for and The minimum value, This refers to the inlet temperature on the hot side of the heat exchanger. This refers to the cold-side inlet temperature of the heat exchanger. , , It is the hot-side mass flow rate of the exchanger. It is the cold-side mass flow rate of the exchanger.

[0127] The cold-side outlet temperature of the exchanger is shown in formula (21).

[0128] (twenty one)

[0129] in, It is the cold-side outlet temperature of the heat exchanger. It is the heat from the heat exchanger. It is the cold-side mass flow rate of the exchanger. It is the specific heat capacity of water. The cold-side inlet temperature of the exchanger.

[0130] The outlet temperature of the heat exchanger on the hot side is shown in formula (22).

[0131] (twenty two)

[0132] in, It is the hot-side outlet temperature of the heat exchanger. It is the heat from the heat exchanger. It is the hot-side mass flow rate of the exchanger. It is the specific heat capacity of water. This refers to the inlet temperature on the hot side of the exchanger.

[0133] The outflow direction of each water tank node in the water storage tank is equal to the inflow flow rate of that water tank node.

[0134] The economic simulation model determines the operating cost based on the power shortage and heat shortage, which is the cost required to operate non-renewable energy equipment. The economic simulation model obtains the equipment maintenance cost, equipment replacement cost, initial cost, total output cost and residual cost, and calculates the energy cost, as shown in formula (23).

[0135] (twenty three)

[0136] in, It's the cost of energy. It is the initial cost. It is the cost of equipment maintenance. It is the cost of equipment replacement. It is the operating cost (determined based on the electricity demand gap and the heat energy gap). It is the remaining cost, it is Total output cost.

[0137] In the above embodiments, a comprehensive energy system simulation model is run under the constraints of the initial vector. Through the cogeneration simulation model, thermal energy simulation model, and economic simulation model, the system reliability, energy cost, and photovoltaic waste rate are determined. This allows for subsequent optimization of the rated power of the photovoltaic array, the rated power of the electrolyzer, the rated power of the fuel cell, the hydrogen storage tank capacity, and the collector area based on the system reliability, energy cost, and photovoltaic waste rate. This improves the reliability of the comprehensive energy system, reduces energy costs, and increases the utilization rate of photovoltaic power generation.

[0138] In some embodiments, a genetic algorithm is used to process the initial vector based on the fitness value to obtain candidate vectors, including: selecting a dominant vector from the initial vector based on the fitness value; and performing crossover and mutation processing on the dominant vector to obtain candidate vectors.

[0139] Among them, the advantage vector is a better initial vector determined based on the fitness value.

[0140] In some embodiments, selecting an advantage vector from the initial vector based on the fitness value includes: selecting an advantage vector from the initial vector with the goal of achieving the highest system reliability, lowest energy cost, and lowest photovoltaic waste rate corresponding to the initial vector.

[0141] With the goal of achieving the highest system reliability, lowest energy cost, and lowest photovoltaic waste rate, a dominant vector is selected from the initial vectors. For each initial vector, a reliability value can be determined based on system reliability, a cost value based on energy cost, and a waste value based on photovoltaic waste rate. The reliability value, cost value, and waste value are then weighted and summed to obtain the target value of the initial vector. The initial vector with the higher target value is selected as the dominant vector. By aiming for the highest system reliability, lowest energy cost, and lowest photovoltaic waste rate, target vectors with high system reliability, low energy cost, and low photovoltaic waste rate can be gradually determined, thus improving the quality of the target vectors.

[0142] In some embodiments, roulette wheel selection, tournament selection, etc., can also be used to select dominant vectors from the initial vectors, so as to ensure that the initial vectors with better fitness values ​​have a greater chance of being selected as dominant vectors.

[0143] After selecting the dominant vector, the dominant vector is used as the parent. The parent is paired and new individuals are generated through crossover operations (such as single-point crossover, multi-point crossover, uniform crossover, etc.). These new individuals inherit some features of the parent. Mutation operations are performed on the new individuals, such as randomly changing some feature values ​​of the individuals with a certain probability, in order to increase the diversity of the individuals and thus obtain candidate vectors.

[0144] It should be noted that the above describes one process of using a genetic algorithm to process the initial vector and obtain candidate vectors. In this embodiment, the above process will iterate multiple times until the genetic termination condition is met. After multiple iterations, the candidate vector that meets the genetic termination condition is used as the target vector. The target vector is the vector with the highest reliability, the lowest energy cost, and the lowest photovoltaic waste rate.

[0145] In the above embodiments, the initial vector is processed by a genetic algorithm. In this process, with the goals of maximizing system reliability, minimizing energy costs, and minimizing photovoltaic waste rate, the optimal candidate vector is gradually obtained. Through multi-objective optimization, the operating efficiency of the integrated energy system can be improved.

[0146] Figure 3 A schematic diagram of the processing flow of the integrated energy system provided in this application. Figure 2 ,like Figure 3 As shown, in this embodiment... Figure 1 Based on the embodiments, the processing of the integrated energy system is described in detail, and the method includes:

[0147] S301, the first constraint condition for obtaining the rated power of the photovoltaic array, the second constraint condition for the rated power of the electrolyzer, the third constraint condition for the rated power of the fuel cell, the fourth constraint condition for the capacity of the hydrogen storage tank, and the fifth constraint condition for the area of ​​the solar collector.

[0148] S302. Under the constraints of the first, second, third, fourth, and fifth constraints, generate an initial vector; the initial vector includes the rated power of the photovoltaic array, the rated power of the electrolyzer, the rated power of the fuel cell, the capacity of the hydrogen storage tank, and the area of ​​the solar collector.

[0149] S303. For each initial vector, run the cogeneration simulation model under the constraints of the initial vector to obtain the output power of the photovoltaic array, the cooling load of the fuel cell, the power reliability and the power shortage demand.

[0150] S304. Determine the photovoltaic waste rate based on the preset power demand, photovoltaic array output power, and electrolytic cell rated power.

[0151] S305. Run the thermal simulation model under the constraints of the initial vector and the fuel cell cold load to obtain the thermal reliability and gap thermal energy corresponding to the initial vector.

[0152] S306. Input the power shortage demand and heat shortage energy into the economic simulation model to obtain the energy cost corresponding to the initial vector.

[0153] S307. Determine the system reliability corresponding to the initial vector based on electrical reliability and thermal reliability;

[0154] S308. With the goal of achieving the highest system reliability, lowest energy cost, and lowest photovoltaic waste rate corresponding to the initial vector, select the dominant vector from the initial vector; perform crossover and mutation processing based on the dominant vector to obtain candidate vectors;

[0155] S309. If the fitness value does not meet the genetic termination condition, the initial vector is processed using a genetic algorithm based on the fitness value to obtain candidate vectors.

[0156] S310, Replace the initial vector with the candidate vector, and continue executing S303;

[0157] S311. If the fitness value satisfies the genetic termination condition, the initial vector that satisfies the genetic termination condition shall be used as the target vector. The target vector includes the target photovoltaic array rated power, the target electrolyzer rated power, the target fuel cell rated power, the target hydrogen storage tank capacity, and the target solar collector area.

[0158] In some embodiments, such as Figure 4 As shown, multiple initial vectors are randomly generated, including the rated power of the photovoltaic array, the rated power of the electrolyzer, the rated power of the fuel cell, the capacity of the hydrogen storage tank, and the area of ​​the solar collector. The initial vectors are input into the integrated energy system simulation model to obtain the fitness value of the initial vectors. Based on the fitness value, it is determined whether the initial vectors meet the genetic termination condition. If the initial vectors do not meet the genetic termination condition, a dominant vector is selected from the initial vectors based on the fitness value, and the dominant vectors are subjected to crossover and mutation to obtain candidate vectors. The candidate vectors are used to replace the initial vectors, and the process of inputting the initial vectors into the integrated energy system simulation model to obtain the fitness value of the initial vectors continues. If the initial vectors meet the genetic termination condition, the initial vectors that meet the genetic termination condition are used as the target vectors to obtain the target rated power of the photovoltaic array, the target rated power of the electrolyzer, the target rated power of the fuel cell, the target capacity of the hydrogen storage tank, and the target area of ​​the solar collector.

[0159] In the aforementioned integrated energy system processing method, the initial vector includes the rated power of the photovoltaic array, the rated power of the electrolyzer, the rated power of the fuel cell, the capacity of the hydrogen storage tank, and the area of ​​the solar collector. Under the constraints of the initial vector, the integrated energy system simulation model is run to obtain the fitness corresponding to the initial vector. If the fitness does not meet the genetic termination condition, a genetic algorithm is used to process the initial vector based on the fitness to obtain candidate vectors. These candidate vectors replace the initial vector, and this process is repeated multiple times until the fitness corresponding to the initial vector meets the genetic termination condition. The initial vector that meets the genetic termination condition is then used as the target vector, thereby determining the target rated power of the photovoltaic array, the target rated power of the electrolyzer, the target rated power of the fuel cell, the target capacity of the hydrogen storage tank, and the target area of ​​the solar collector. This improves the reliability of the integrated energy system, reduces energy costs, and increases the utilization rate of photovoltaic power generation.

[0160] Figure 5 A schematic diagram of the processing device of the integrated energy system provided in this application is shown below. Figure 5 As shown, the processing device 50 of the integrated energy system provided in this embodiment includes:

[0161] The acquisition module 501 is used to acquire the initial vector; the initial vector includes the rated power of the photovoltaic array, the rated power of the electrolyzer, the rated power of the fuel cell, the capacity of the hydrogen storage tank, and the area of ​​the solar collector;

[0162] Simulation module 502 is used to run a comprehensive energy system simulation model under the constraints of the initial vector to obtain the fitness value corresponding to the initial vector; the fitness value includes system reliability, energy cost and photovoltaic waste rate;

[0163] The optimization module 503 is used to process the initial vector using a genetic algorithm based on the fitness value to obtain candidate vectors when the fitness value does not meet the genetic termination condition.

[0164] Iteration module 504 is used to replace the initial vector with a candidate vector and continue to execute the steps of running the integrated energy system simulation model under the constraints of the initial vector;

[0165] The processing module 505 is used to take the initial vector that meets the genetic termination condition as the target vector when the fitness value meets the genetic termination condition; the target vector includes the target photovoltaic array rated power, the target electrolyzer rated power, the target fuel cell rated power, the target hydrogen storage tank capacity, and the target solar collector area.

[0166] In one possible implementation, the acquisition module 501 is further configured to acquire a first constraint condition for the rated power of the photovoltaic array, a second constraint condition for the rated power of the electrolyzer, a third constraint condition for the rated power of the fuel cell, a fourth constraint condition for the capacity of the hydrogen storage tank, and a fifth constraint condition for the area of ​​the solar collector; and generate an initial vector under the constraints of the first, second, third, fourth, and fifth constraints.

[0167] In one possible implementation, the integrated energy system simulation model includes: a combined heat and power simulation model, a thermal energy simulation model, and an economic simulation model;

[0168] Simulation module 502 is used to run a comprehensive energy system simulation model for each initial vector under the constraints of the initial vector. It obtains the photovoltaic waste rate and power reliability corresponding to the initial vector through the cogeneration simulation model, the thermal reliability corresponding to the initial vector through the thermal energy simulation model, and the energy cost corresponding to the initial vector through the economic simulation model. Based on the power reliability and thermal reliability, it determines the system reliability corresponding to the initial vector.

[0169] In one possible implementation, simulation module 502 is used to run a cogeneration simulation model under the constraints of the initial vector to obtain the output power of the photovoltaic array, the cooling load of the fuel cell, the power reliability, and the shortfall power demand; determine the photovoltaic waste rate based on the preset power demand, the output power of the photovoltaic array, and the rated power of the electrolyzer; run a thermal energy simulation model under the constraints of the initial vector and the cooling load of the fuel cell to obtain the thermal reliability and the shortfall thermal energy corresponding to the initial vector; and input the shortfall power demand and the shortfall thermal energy into the economic simulation model to obtain the energy cost corresponding to the initial vector.

[0170] In one possible implementation, the optimization module 503 is used to select a dominant vector from the initial vectors based on the fitness value; and to perform crossover and mutation processing on the dominant vectors to obtain candidate vectors.

[0171] In one possible implementation, optimization module 503 is used to select an advantageous vector from the initial vector with the goal of maximizing system reliability, minimizing energy costs, and minimizing photovoltaic waste rate.

[0172] The processing device of the integrated energy system provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0173] Figure 6 A schematic diagram of the structure of the electronic device provided in this application. Figure 6As shown, the electronic device 60 provided in this embodiment includes at least one processor 601 and a memory 602. Optionally, the device 60 further includes a communication component 603. The processor 601, memory 602, and communication component 603 are connected via a bus 604.

[0174] In a specific implementation, at least one processor 601 executes computer execution instructions stored in memory 602, causing at least one processor 601 to perform the above-described method.

[0175] The specific implementation process of processor 601 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0176] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0177] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0178] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0179] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0180] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0181] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0182] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0183] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0184] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0185] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0186] If a function is implemented as 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 this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause an electronic device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0187] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0188] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A processing method for an integrated energy system, characterized in that, include: Obtain an initial vector; the initial vector includes the rated power of the photovoltaic array, the rated power of the electrolyzer, the rated power of the fuel cell, the capacity of the hydrogen storage tank, and the area of ​​the solar collector; The integrated energy system simulation model is run under the constraints of the initial vector to obtain the fitness value corresponding to the initial vector; the fitness value includes system reliability, energy cost, and photovoltaic waste rate. If the fitness value does not meet the genetic termination condition, the initial vector is processed using a genetic algorithm based on the fitness value to obtain candidate vectors; The candidate vector is used to replace the initial vector, and the step of running the integrated energy system simulation model under the constraints of the initial vector is continued. If the fitness value satisfies the genetic termination condition, the initial vector that satisfies the genetic termination condition will be used as the target vector; the target vector includes the target photovoltaic array rated power, the target electrolyzer rated power, the target fuel cell rated power, the target hydrogen storage tank capacity, and the target solar collector area.

2. The method according to claim 1, characterized in that, The process of obtaining the initial vector includes: The first constraint condition for obtaining the rated power of the photovoltaic array, the second constraint condition for the rated power of the electrolyzer, the third constraint condition for the rated power of the fuel cell, the fourth constraint condition for the capacity of the hydrogen storage tank, and the fifth constraint condition for the area of ​​the solar collector. An initial vector is generated under the constraints of the first constraint, the second constraint, the third constraint, the fourth constraint, and the fifth constraint.

3. The method according to claim 1, characterized in that, The integrated energy system simulation model includes: a combined heat and power simulation model, a thermal energy simulation model, and an economic simulation model; The process of running the integrated energy system simulation model under the constraints of the initial vector to obtain the fitness value corresponding to the initial vector includes: For each initial vector, a comprehensive energy system simulation model is run under the constraints of the initial vector. The photovoltaic waste rate and power reliability corresponding to the initial vector are obtained through the cogeneration simulation model, the thermal reliability corresponding to the initial vector is obtained through the thermal energy simulation model, and the energy cost corresponding to the initial vector is obtained through the economic simulation model. The system reliability corresponding to the initial vector is determined based on the electrical reliability and the thermal reliability.

4. The method according to claim 3, characterized in that, The process of running a comprehensive energy system simulation model under the constraints of a given initial vector, obtaining the photovoltaic waste rate and power reliability corresponding to the given initial vector through the cogeneration simulation model, obtaining the thermal reliability corresponding to the given initial vector through the thermal energy simulation model, and obtaining the energy cost corresponding to the given initial vector through the economic simulation model, includes: The cogeneration simulation model is run under the constraints of the initial vector to obtain the output power of the photovoltaic array, the cooling load of the fuel cell, the power reliability, and the power shortage demand. The photovoltaic waste rate is determined based on the preset power demand, the output power of the photovoltaic array, and the rated power of the electrolytic cell. The thermal simulation model is run under the constraints of the initial vector and the fuel cell cold load to obtain the thermal reliability and notched thermal energy corresponding to the initial vector. The energy shortage demand and the thermal energy shortage are input into the economic simulation model to obtain the energy cost corresponding to the initial vector.

5. The method according to claim 1, characterized in that, The process of processing the initial vector using a genetic algorithm based on the fitness value to obtain candidate vectors includes: Based on the fitness value, a dominant vector is selected from the initial vectors; Based on the dominant vector, crossover and mutation processes are performed to obtain candidate vectors.

6. The method according to claim 5, characterized in that, The step of selecting an advantage vector from the initial vector based on the fitness value includes: With the objectives of achieving the highest system reliability, the lowest energy cost, and the lowest photovoltaic waste rate, an advantageous vector is selected from the initial vector.

7. A processing device for an integrated energy system, characterized in that, include: An acquisition module is used to acquire an initial vector; the initial vector includes the rated power of the photovoltaic array, the rated power of the electrolyzer, the rated power of the fuel cell, the capacity of the hydrogen storage tank, and the area of ​​the solar collector; The simulation module is used to run a comprehensive energy system simulation model under the constraints of the initial vector to obtain the fitness value corresponding to the initial vector; the fitness value includes system reliability, energy cost, and photovoltaic waste rate; An optimization module is used to process the initial vector using a genetic algorithm based on the fitness value to obtain candidate vectors when the fitness value does not meet the genetic termination condition. An iterative module is used to replace the initial vector with the candidate vector and continue to execute the step of running the integrated energy system simulation model under the constraints of the initial vector; The processing module is configured to, when the fitness value satisfies the genetic termination condition, take the initial vector that satisfies the genetic termination condition as the target vector; the target vector includes the target photovoltaic array rated power, the target electrolyzer rated power, the target fuel cell rated power, the target hydrogen storage tank capacity, and the target solar collector area.

8. An electronic device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-6.

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