Capacity configuration method of off-grid hydrogen-electricity hybrid energy storage system

Abstract

The invention relates to the technical field of energy, in particular to a capacity configuration method of an off-grid hydrogen-electricity hybrid energy storage system. The capacity configuration method of the system comprises the following steps: 1, establishing a mathematical function of the off-grid hydrogen-electricity hybrid energy storage system; 2, establishing a target optimization function by taking the lowest total cost of the system as an economical efficiency target and taking the maximum self-power generation rate and the minimum power abandoning rate as operation targets of the hydrogen-electricity coupling direct-current micro-grid system; 3, establishing a capacity configuration constraint function by taking system power balance, thermodynamic balance, grid-connected interaction power balance, equipment capacity upper limit and equipment power upper and lower limits as constraint conditions; and 4, establishing a capacity configuration optimization model of the system based on the mathematical function, the target optimization function and the capacity configuration constraint function of the off-grid hydrogen-electricity hybrid energy storage system, and solving through an NSGA-II algorithm to obtain an optimal capacity configuration scheme. The economical efficiency, stability and efficiency of system operation are considered at the same time, and reasonable capacity configuration of the system is achieved.

Description

Technical Field

[0001] The present invention relates to the field of energy technology, and in particular to a capacity configuration method for an off-grid hydrogen-electric hybrid energy storage system. Background Art

[0002] The off-grid hydrogen-electric hybrid energy storage system has demonstrated significant potential by combining the advantages of electric energy storage and hydrogen energy storage. In addition, the off-grid hydrogen-electric hybrid energy storage system has strong flexibility and independence. When faced with extreme weather events such as typhoons and earthquakes, the off-grid hydrogen-electric hybrid energy storage system can quickly disconnect from the main power grid and operate independently.

[0003] The existing off-grid hydrogen-electric hybrid energy storage system has the defect of incomplete consideration of comprehensive capacity configuration. If only the economy of system operation is considered, the stability and efficiency of the system itself during off-grid operation will be ignored; if only the power supply stability and reliability of the system during off-grid operation are optimized, it will affect the overall economy of the system.

[0004] Therefore, it is necessary to design an optimized configuration of hybrid energy storage capacity for off-grid hydrogen-electric hybrid energy storage systems, which can achieve the best balance in hydrogen-electric energy storage capacity, comprehensively consider the capacity ratio of batteries and hydrogen energy storage, and formulate a reasonable capacity configuration strategy. Summary of the invention

[0005] In order to overcome the above problems, the purpose of the present invention is to provide a capacity configuration method for an off-grid hydrogen-electric hybrid energy storage system, while taking into account the economy, stability and efficiency of the system operation, to achieve a reasonable capacity configuration of the off-grid hydrogen-electric hybrid energy storage system.

[0006] To achieve the above-mentioned purpose, the present invention provides a capacity configuration method for an off-grid hydrogen-electric hybrid energy storage system, which is characterized by comprising the steps of:

[0007] (1) Establishing a mathematical function of an off-grid hydrogen-electric hybrid energy storage system: The off-grid hydrogen-electric hybrid energy storage system includes three types of energy storage subsystems, namely, an electric energy storage system, a hydrogen energy storage system, and a hot water tank energy storage system. The mathematical function of the off-grid hydrogen-electric hybrid energy storage system is established based on the charging and discharging characteristics of the three types of energy storage subsystems. The mathematical function of the off-grid hydrogen-electric hybrid energy storage system is used to characterize the charging and discharging power, real-time power, and energy storage capacity of each energy storage subsystem.

[0008] (2) Taking the lowest total system cost as the economic goal, and taking the maximum self-generation rate and the minimum power abandonment rate as the operation goals of the hydrogen-electricity coupled DC microgrid system, an objective optimization function is established;

[0009] (3) Establish a capacity configuration constraint function based on system power balance, thermal balance, grid-connected interactive power balance, equipment capacity upper limit, and equipment power upper and lower limits as constraints;

[0010] (4) Based on the mathematical function, target optimization function and capacity configuration constraint function of the off-grid hydrogen-electric hybrid energy storage system, a capacity configuration optimization model of the off-grid hydrogen-electric hybrid energy storage system is established. The capacity configuration optimization model of the off-grid hydrogen-electric hybrid energy storage system is solved by the NSGA-II algorithm to obtain the Pareto frontier solution. The obtained Pareto solutions are sorted, and the optimal capacity configuration scheme of the off-grid hydrogen-electric hybrid energy storage system is finally obtained by comparing the distance between each possible solution and the ideal optimal solution and the worst solution.

[0011] As a preferred embodiment, the electric energy storage system in step (1) includes a photovoltaic power generation unit, a wind power generation unit, a battery unit and a lithium battery, the hydrogen energy storage system includes a hydrogen storage tank unit, and the hot water tank energy storage system includes a hot water tank unit.

[0012] As a preferred embodiment, the process of establishing the mathematical function of the off-grid hydrogen-electric hybrid energy storage system in step (1) is as follows: based on the charging and discharging characteristics of the photovoltaic power generation unit, the wind power generation unit, the battery unit, the lithium battery, the hydrogen storage tank unit, and the hot water storage tank unit, respectively establish a photovoltaic power generation mathematical function, a wind power generation mathematical function, a battery mathematical function, a lithium battery mathematical function, a hydrogen storage tank mathematical function, and a hot water storage tank mathematical function, and the photovoltaic power generation mathematical function, the wind power generation mathematical function, the battery mathematical function, the lithium battery mathematical function, the hydrogen storage tank mathematical function, and the hot water storage tank mathematical function are used to respectively correspond to and characterize the charging and discharging power, real-time power, and energy storage capacity of each energy storage unit.

[0013] As a preferred solution, the photovoltaic power generation mathematical function, wind power generation mathematical function, battery mathematical function, lithium battery mathematical function, hydrogen storage tank mathematical function, and hot water storage tank mathematical function are respectively:

[0014] 1.1. The mathematical function of photovoltaic power generation is shown in formula (1):

[0015]

[0016] In formula (1), P pv is the steady-state power of the photovoltaic power generation system, P STC is the installed capacity of photovoltaic power generation system, I G The standard rated irradiance is 1000W / m 2 ,T G is the standard rated temperature of 25°C, I and T are the actual working radiation intensity and temperature of the system, P0 is the power value under the standard rated state, k is the power temperature coefficient, which is 0.0045;

[0017] 1.2. The mathematical function of wind power generation is shown in formula (2):

[0018]

[0019] In formula (2), P WT (v) is the wind turbine power generation under wind speed v, v in is the cut-in wind speed, v cut is the cut-out wind speed, v G is the rated wind speed, P WTC is the rated output power of the wind turbine, δ(v) is the function of wind speed, taking quadratic form;

[0020] 1.3. The mathematical function of the battery is shown in formula (3);

[0021]

[0022] In formula (3), SOC(t) is the battery state of charge at time t, 0.8≥SOC≥0.2, P cha , P dis are the battery charging and discharging power, η cha , η dis are the battery charge and discharge efficiency, Q bat is the battery capacity;

[0023] 1.4. The mathematical function of lithium battery is shown in formula (4);

[0024]

[0025] P t bat N is the battery charge and discharge efficiency, positive for charging and negative for discharging; cycle is the cycle life of the battery.

[0026] 1.5. The mathematical model of the hydrogen storage tank is shown in formula (5) and formula (6);

[0027] When charging, the hydrogen storage tank model is shown in formula (5):

[0028] SOC HT (t) = SOC HT (t-1)+η EL (P g (t)-P L(t) / η inv )ρ (5)

[0029] In formula (5), P g (t) is the sum of photovoltaic and wind power generation at time t, P L(t) is the power load at time t, η invis the efficiency of the inverter, SOC HT (t) is the remaining hydrogen volume in the hydrogen tank at time t, ρ is the amount of hydrogen that can be generated per kilowatt-hour of electricity, η EL The charging efficiency of the water electrolysis hydrogen production system;

[0030] During discharge, the hydrogen storage tank model is shown in formula (6):

[0031] SOC HT (t) = SOC HT (t-1)-η FC (P L (t) / η inv -P g(t) ) / η (6)

[0032] In formula (6), SOC HT (t) is the remaining hydrogen volume in the hydrogen tank at time t, P L(t) is the power load at time t, P g (t) is the sum of photovoltaic and wind power generation at time t, η represents the amount of electricity generated per cubic meter of hydrogen, η inv is the efficiency of the inverter, η FC is the discharge efficiency of the fuel cell;

[0033] 1.6. The mathematical model of the hot water storage tank is shown in formula (7):

[0034]

[0035] In formula (3), tw t Indicates the water temperature of the hot water tank; V t load is the heat water consumption during the heat load period t, M ttk is the volume of the hot water tank, p t boil is the heating power of the electric boiler in period t, a1 and a2 are the heat transfer powers of the electric boiler and the fuel cell respectively. T is the ambient temperature, m water P is the calculation coefficient of thermal power to water temperature. t thermel is the thermal power of the fuel cell.

[0036] As a preferred solution, in step (2), the multi-objective optimization function F includes a system total cost function F1, a system self-generation rate function F2, and a system power abandonment rate function F3;

[0037] The multi-objective optimization function F is shown in formula (8):

[0038] F={min(F1,F3),max(F2)} (8)

[0039] The total system cost function F1 includes the one-time investment cost function C cap , equipment replacement cost function C rep , system maintenance function C mat , the system operation cost function C in off-grid mode co_off and the system operation cost function C of the grid-connected mode co on ;

[0040] One-time investment cost function C cap As shown in formula (9):

[0041]

[0042] In formula (9), C cap is the one-time investment cost, C cap_wt , C cap_pv , C cap_bat , C cap_bl , C cap_ele , C cap_tank , C cap_fc , C cap_ttk They are the purchase costs of wind turbines, photovoltaic panels, batteries, electric boilers, water electrolysis hydrogen production systems, hydrogen storage tanks, fuel cells, and hot water storage tanks. wt , k pv , k bl , k ele , k fc are the unit power prices of fans, photovoltaic panels, electric boilers, water electrolysis hydrogen production systems, and fuel cells, respectively. tank , k ttk are the unit mass prices of hydrogen storage tank and hot water storage tank, respectively, bat P is the unit capacity cost of the battery. wt , P pv , P ele , P fc , P bl They are the installed capacity of wind turbines and photovoltaics, the rated power of the water electrolysis hydrogen production system and fuel cells, and the rated heating power of the electric boiler. bat 、M tank 、M ttk They are the rated capacities of the electric energy storage, hydrogen energy storage, and hot water storage tanks;

[0043] Equipment replacement function C rep As shown in formula (10): including the replacement cost C of the battery as shown in formula (11) rep_bat , as shown in formula (12), the replacement cost C of the water electrolysis hydrogen production system rep_el , as shown in formula (13), the replacement cost of the fuel cell C rep_fc :

[0044]

[0045] C rep =C rep_el +C rep_bat +C rep_fc (10)

[0046] In formulas (10), (11), (12), and (13), C rep_bat is the replacement cost of the battery, Δsoh a is the annual soh change of the battery, soh max 、soh min is the initial soh of the battery and the soh when it reaches ELO; C rep_el , C rep_fc are the replacement costs of the water electrolysis hydrogen production system and the fuel cell, ΔV ela is the annual voltage rise of the water electrolysis hydrogen production system, ΔV fca is the annual voltage attenuation of the water electrolysis hydrogen production system, V eol_el 、V eol_fc It is the voltage value when the water electrolysis hydrogen production system and the fuel cell reach EOL;

[0047] System maintenance function C mat As shown in formula (14):

[0048] C mat =0.1*C cap (14)

[0049] In formula (14), C cap is the one-time investment cost in formula (9); C mat System maintenance costs;

[0050] The system operation cost function includes the system operation cost function C of the off-grid mode co_off and the system operation cost function C of the grid-connected mode co_on ; The system operation cost function model is shown in formula (15) and formula (16):

[0051]

[0052] In formula (15) and formula (16), C co_off , C co_on They represent the operating costs of off-grid and grid-connected operation, C gass , C gas are the selling price and purchasing price of hydrogen, m t gass 、m t gasare the sales and purchase volumes of hydrogen at time t, c t e represents the electricity purchase price of the upper power grid at time t, P t ex represents the interaction power between the microgrid and the upper grid at time t;

[0053] The total cost function F1 of the system is as follows:

[0054] F1=C cap +C rep +C mat +C co_off +C co_on (17)

[0055] The system's self-generation rate function F2 is as shown in formula (18):

[0056]

[0057] In formula (18), P t grid_buy is the amount of electricity purchased from the upper power grid at time t, P load_t is the load required on the load side at time t;

[0058] The system's power abandonment rate function F3 is as shown in formula (19):

[0059]

[0060] In formula (19), P HS,max , P bat,max is the power output of the hydrogen storage tank and the battery at time t, P WT (t), P PV (t) is the output power of wind power and photovoltaic power at time t, P L (t) is the load at time t.

[0061] As a preferred solution, in step (3), the function of the constraint condition is expressed as:

[0062] In the grid-connected mode, the system power balance constraint function is as shown in formula (20):

[0063]

[0064] In off-grid mode, the system power balance constraint function is as shown in formula (21):

[0065]

[0066] In formula (20) and formula (21), is the output power of the photovoltaic system, is the output power of the wind system, is the battery output power, is the fuel cell output power, For this moment, the load power, P t el is the output power of the water electrolysis hydrogen production system, P t boiler is the output power of the electric boiler;

[0067] The system thermodynamic balance constraint function is as shown in formula (22):

[0068]

[0069] In formula (22), a1 and a1 are the electric heating efficiency of the electric boiler and the heat recovery rate of the fuel cell, P t tload is the system heat load demand at time t;

[0070] The water temperature constraint function of the hot water storage tank is as shown in formula (23): 50≤tw t ≤70(23)

[0071] The interactive power constraint function in the grid-connected mode is as follows:

[0072]

[0073] In formula (24), It is the upper limit of power exchange with the upper power grid when the system is connected to the grid; is the transmission power between the system and the upper power grid at time t when the system is connected to the grid;

[0074] The upper and lower limit constraint functions of equipment capacity are as shown in formula (25):

[0075]

[0076] The upper and lower limit constraint functions of equipment power are as shown in formulas (26) and (27):

[0077]

[0078]

[0079] In formula (26), P bat_rated is the rated power of the battery, P el_rated is the rated power of the electrolytic cell, P fc_rated is the fuel cell rated power, P boli_rated is the rated power of the electric boiler, β is the overload coefficient of the electrolyzer; in formula (27), when the photovoltaic power output is excessive and cannot be absorbed, the output will be reduced by cutting off or exiting the MPPT mode to achieve power balance, P tpvi It is the ideal output of the photovoltaic module in MPPT mode at time t.

[0080] As a preferred solution, in step (4), the optimal capacity configuration scheme of the off-grid hydrogen-electric hybrid energy storage system includes wind and solar power, battery power, electrolyzer power, fuel cell power, and hydrogen quality in the hydrogen storage tank.

[0081] As a preferred solution, in step (3), the process of the NSGA-II algorithm is as follows: first, the control parameters of the NSGA-II algorithm are input, including the population size (N) and the maximum number of iterations, Gen max Then, the capacity allocation parameter Ri is selected as the initial population of the NSGA-II algorithm. The capacity allocation parameter Ri includes the scale of wind and solar power generation, the capacity of the heat storage tank, the power of the electric boiler, the capacity of the electrolyzer, the hydrogen energy storage capacity, and the fuel cell capacity. The capacity allocation parameter Ri is input into the capacity configuration optimization model of the off-grid hydrogen-electric hybrid energy storage system, the model is solved, and the Pareto frontier solution is obtained.

[0082] Compared with the traditional ones, the present invention has the following advantages: the present invention first establishes the mathematical function of the off-grid hydrogen-electric hybrid energy storage system based on the charging and discharging characteristics of the energy storage subsystem of the off-grid hydrogen-electric hybrid energy storage system, and the established mathematical function of the off-grid hydrogen-electric hybrid energy storage system is used to characterize the charging and discharging power, real-time power and energy storage capacity of each energy storage subsystem; then, based on the system operation strategy, a multi-dimensional target optimization function is established in two different scenarios of grid-connected and off-grid, with the lowest total system cost as the economic goal, and the maximum self-generation rate and the minimum abandonment rate as the operation goals of the hydrogen-electric coupled DC microgrid system; then, a capacity configuration constraint function is established with the system power balance, thermal balance, grid-connected interactive power balance, and equipment capacity upper limit as constraints; finally, a capacity configuration optimization model of the off-grid hydrogen-electric hybrid energy storage system is established based on the mathematical function of the off-grid hydrogen-electric hybrid energy storage system, the target optimization function, and the capacity configuration constraint function, and the optimal capacity configuration scheme is obtained by solving the capacity configuration optimization model. Compared with the traditional surplus electricity hydrogen production mode, the capacity configuration method of the present invention can effectively balance consumption and energy efficiency and improve the overall efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 This is the operation topology diagram of the off-grid hydrogen-electric hybrid energy storage system;

[0084] Figure 2 This is the operation strategy diagram of the off-grid hydrogen-electric hybrid energy storage system in grid-connected mode;

[0085] Figure 3 This is an operation strategy diagram of the off-grid hydrogen-electric hybrid energy storage system in off-grid mode;

[0086] Figure 4 A capacity configuration flow chart for an off-grid hydrogen-electric hybrid energy storage system;

[0087] Figure 5 This is a data diagram of light intensity in Cixi, Ningbo under normal weather conditions in Example 1;

[0088] Figure 6 This is a wind speed data diagram of Cixi, Ningbo under normal weather conditions in Example 1;

[0089] Figure 7 This is a graph of electricity load data in Cixi, Ningbo under normal weather conditions in Example 1;

[0090] Figure 8 This is the electricity price information diagram of Ningbo Cixi under normal weather conditions in Example 1;

[0091] Fig. 9 This is a data graph of light intensity in Cixi, Ningbo under extreme weather conditions in Example 2. DETAILED DESCRIPTION

[0092] In order to better understand the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific examples.

[0093] Example 1: Capacity configuration of off-grid hydrogen-electric hybrid energy storage system in Cixi, Ningbo under grid-connected mode

[0094] In grid-connected mode, the off-grid hydrogen-electric hybrid energy storage system can extract historical data of normal weather conditions in Cixi, Ningbo for one year. The average annual sunshine hours in Cixi City are 2038 hours, and the annual sunshine percentage is 47%. The annual average temperature is 16.0℃, with the highest in July, averaging 28.2℃, and the lowest in January, averaging 3.8℃. The wind is mainly from the east throughout the year, with an annual average wind speed of 3 meters per second and an average number of strong wind days of 9.6 days per year. There are many tropical storms in summer and autumn. Wind, solar and load data are as follows: Figure 5 , Figure 6 , Figure 7 and Figure 8 shown.

[0095] Combination Figure 4 As shown, in the grid-connected mode, the capacity configuration method of the off-grid hydrogen-electric hybrid energy storage system in Cixi City, Ningbo, includes the following steps:

[0096] (1) Establish mathematical functions for off-grid hydrogen-electric hybrid energy storage systems

[0097] Combination Figure 1As shown, the off-grid hydrogen-electric hybrid energy storage system includes three types of energy storage subsystems, namely, electric energy storage system, hydrogen energy storage system and hot water tank energy storage system. More specifically, the off-grid hydrogen-electric hybrid energy storage system includes photovoltaic power generation unit, wind power generation unit, battery unit, lithium battery, hydrogen storage tank unit, hot water tank unit. This embodiment has carried out detailed mathematical functions for each unit. By establishing the mathematical functions of each unit, the operating characteristics, energy conversion process and power output characteristics of the system can be accurately described. These mathematical functions provide basic data and scientific basis for the overall design and capacity configuration of the system.

[0098] 1.1. The mathematical function of photovoltaic power generation is shown in formula (1): The steady-state power of the mathematical function of photovoltaic power generation is related to factors such as natural light irradiance and ambient temperature when the inclination angle of the photovoltaic panel is constant.

[0099]

[0100] In formula (1), P pv is the steady-state power of the photovoltaic power generation system, P STC is the installed capacity of photovoltaic power generation system, I G The standard rated irradiance is 1000W / m 2 ,T G is the standard rated temperature of 25°C, I and T are the actual working radiation intensity and temperature of the system, P0 is the power value under the standard rated state, k is the power temperature coefficient, which is 0.0045;

[0101] 1.2. The mathematical function of wind power generation is shown in formula (2): Wind power generation adopts a piecewise function output model, that is, the working state is divided into four sections according to the actual wind speed.

[0102]

[0103] In formula (2), P WT (v) is the wind turbine power generation under wind speed v, v in is the cut-in wind speed, v cut is the cut-out wind speed, v G is the rated wind speed, P WTC is the rated output power of the wind turbine, δ(v) is the function of wind speed, taking quadratic form;

[0104] 1.3. The mathematical function of the battery is shown in formula (3). The mathematical function of the battery is represented by the battery state of charge SOC. The heat load is the actual water load, and the unit is the mass of water used. Therefore, the water temperature can be selected as the measurement standard for the heat energy flow.

[0105]

[0106] In formula (3), SOC(t) is the battery state of charge at time t, 0.8≥SOC≥0.2, P cha , P dis are the battery charging and discharging power, η cha , η dis are the battery charge and discharge efficiency, Q bat is the battery capacity;

[0107] 1.4. The mathematical function of lithium battery is shown in formula (4); lithium battery uses battery health status soh to evaluate and manage the life of lithium battery.

[0108]

[0109] P t bat N is the battery charge and discharge efficiency, positive for charging and negative for discharging; cycle is the cycle life of the battery.

[0110] 1.5. The mathematical model of the hydrogen storage tank is shown in formula (5) and formula (6). The mathematical model of the hydrogen storage tank is that the real-time hydrogen mass in the hydrogen storage tank should be the sum of the amount generated by the water electrolysis hydrogen production system and the amount consumed by the fuel cell.

[0111] When charging, the hydrogen storage tank model is shown in formula (5):

[0112] SOC HT (t) = SOC HT (t-1)+η EL (P g (t)-P L(t) / η inv )ρ (5)

[0113] In formula (5), P g (t) is the sum of photovoltaic and wind power generation at time t, P L(t) is the power load at time t, η inv is the efficiency of the inverter, SOC HT (t) is the remaining hydrogen volume in the hydrogen tank at time t, ρ is the amount of hydrogen that can be generated per kilowatt-hour of electricity, η EL The charging efficiency of the water electrolysis hydrogen production system;

[0114] During discharge, the hydrogen storage tank model is shown in formula (6):

[0115] SOC HT (t) = SOC HT (t-1)-η FC (P L (t) / η inv -P g(t) ) / η(6)

[0116] In formula (6), SOC HT (t) is the remaining hydrogen volume in the hydrogen tank at time t, P L(t) is the power load at time t, P g (t) is the sum of photovoltaic and wind power generation at time t, η represents the amount of electricity generated per cubic meter of hydrogen, η inv is the efficiency of the inverter, η FC is the discharge efficiency of the fuel cell;

[0117] 1.6. The mathematical model of the hot water storage tank is shown in formula (7): The heat load of the hot water storage tank is the actual water load, and the unit is the mass of water used. Therefore, the water temperature twt can be selected as the measurement standard for the heat energy flow.

[0118]

[0119] In formula (7), tw t Indicates the water temperature of the hot water tank; V t load is the heat water consumption during the heat load period t, M ttk is the volume of the hot water tank, p t boil is the heating power of the electric boiler in period t, a1 and a2 are the heat transfer powers of the electric boiler and the fuel cell respectively. T is the ambient temperature, m water P is the calculation coefficient of thermal power to water temperature. t thermel is the thermal power of the fuel cell.

[0120] (2) Based on the analysis of the operation strategy of the off-grid hydrogen-electric hybrid energy storage system, the economic goal is to minimize the total system cost, and the operation goals of the hydrogen-electric coupled DC microgrid system are to maximize the self-generation rate and minimize the power abandonment rate, and an objective optimization function is established.

[0121] Analysis and combination of operation strategies of off-grid hydrogen-electric hybrid energy storage system Figure 2 and Figure 3As shown, when the system is connected to the grid, the time-of-use electricity price of the grid is considered. When there is a surplus of energy, hydrogen is produced first to meet the hydrogen load demand and ensure the hydrogen storage level of the system; according to the current electricity price level, when energy is insufficient and the electricity price is at a low point, priority is given to purchasing electricity from the grid and considering battery discharge to meet the load demand. This is because there is a large energy loss in the "electricity-gas-electricity" closed loop process. In this way, the operating efficiency of the system is reduced, and the fuel cell can only start working under limited conditions; but when the electricity price is not at a low point, the energy storage system is given priority to supply power, which can ensure the economy of grid-connected operation. When the system is off-grid, the power supply stability of the system is considered. When the electricity generated by photovoltaic and wind power exceeds the power demand, the electrolysis device will convert the excess electricity into hydrogen by electrolyzing water and charge the battery. On the contrary, when the net load power of the system is less than 0, the power storage unit and the fuel cell unit begin to discharge, which has met the load demand of the system. If the load demand difference is too large and cannot be fully met, consider removing an appropriate amount of low-priority loads and increasing the input power of wind and solar.

[0122] The multi-objective optimization function F includes the system total cost function F1, the system self-generation rate function F2, and the system power abandonment rate function F3;

[0123] The multi-objective optimization function F is shown in formula (8):

[0124] F={min(F1,F3),max(F2)} (8)

[0125] 2.1. The total system cost function F1 includes the primary investment cost function C cap , equipment replacement cost function C rep , system maintenance function C mat , the system operation cost function C in off-grid mode co_off and the system operation cost function C of the grid-connected mode co_on ; The system total cost model F1 is as follows:

[0126] F1=C cap +C rep +C mat +C co_off +C co_on (17)

[0127] Among them, the one-time investment cost function C cap As shown in formula (9):

[0128]

[0129] In formula (9), C cap is the one-time investment cost function, C cap_wt , C cap_pv , Ccap_bat , C cap_bl , C cap_ele , C cap_tank , C cap_fc , C cap_ttk They are the purchase costs of wind turbines, photovoltaic panels, batteries, electric boilers, water electrolysis hydrogen production systems, hydrogen storage tanks, fuel cells, and hot water storage tanks. wt , k pv , k bl , k ele , k fc are the unit power prices of fans, photovoltaic panels, electric boilers, water electrolysis hydrogen production systems, and fuel cells, respectively. tank , k ttk are the unit mass prices of hydrogen storage tank and hot water storage tank, respectively, bat P is the unit capacity cost of the battery. wt , P pv , P ele , P fc , P bl They are the installed capacity of wind turbines and photovoltaics, the rated power of the water electrolysis hydrogen production system and fuel cells, and the rated heating power of the electric boiler. bat 、M tank 、M ttk They are the rated capacities of the electric energy storage, hydrogen energy storage, and hot water storage tanks;

[0130] Equipment replacement function C rep As shown in formula (10): including the replacement cost C of the battery as shown in formula (11) rep_bat , as shown in formula (12), the replacement cost C of the water electrolysis hydrogen production system rep_el , as shown in formula (13), the replacement cost of the fuel cell C rep_fc :

[0131]

[0132] C rep =C rep_el +C rep_bat +C rep_fc (10)

[0133] In formulas (10), (11), (12), and (13), C rep_bat is the replacement cost of the battery, Δsoh a is the annual soh change of the battery, soh max 、soh min is the initial soh of the battery and the soh when it reaches ELO; C rep_el , C rep_fc are the replacement costs of the water electrolysis hydrogen production system and the fuel cell, ΔVela is the annual voltage rise of the water electrolysis hydrogen production system, ΔV fca is the annual voltage attenuation of the water electrolysis hydrogen production system, V eol_el 、V eol_fc It is the voltage value when the water electrolysis hydrogen production system and the fuel cell reach EOL;

[0134] System maintenance function C mat As shown in formula (14):

[0135] C mat =0.1*C cap (14)

[0136] In formula (14), C cap is the one-time investment cost in formula (8); C mat System maintenance costs;

[0137] The system operation cost function includes the system operation cost function C of the off-grid mode co_off and the system operation cost function C of the grid-connected mode co_on ; The system operation cost function model is shown in formula (15) and formula (16):

[0138]

[0139] In formula (14) and formula (15), C co_off , C co_on They represent the operating costs of off-grid and grid-connected operation, C gass , C gas are the selling price and purchasing price of hydrogen, m t gass 、m t gas are the sales and purchase volumes of hydrogen at time t, c t e represents the electricity purchase price of the upper power grid at time t, P t ex It represents the interaction power between the microgrid and the upper grid at time t.

[0140] 2.2. The system's self-generation rate function F2 is as shown in formula (18):

[0141]

[0142] In formula (18), P t grid_buy is the amount of electricity purchased from the upper power grid at time t, P load_t is the load required on the load side at time t;

[0143] 2.3. The system power abandonment rate function F3 is as shown in formula (19):

[0144]

[0145] In formula (19), P HS,max , P bat,max is the power output of the hydrogen storage tank and the battery at time t, P WT (t), P PV (t) is the output power of wind power and photovoltaic power at time t, P L (t) is the load at time t.

[0146] (3) Taking system power balance, thermal balance, grid-connected interactive power balance, and equipment capacity upper limit as constraints, a capacity configuration constraint function is established:

[0147] In the grid-connected mode, the system power balance constraint function is as shown in formula (20):

[0148]

[0149] In off-grid mode, the system power balance constraint function is as shown in formula (21):

[0150]

[0151] In formula (20) and formula (21), is the output power of the photovoltaic system, is the output power of the wind system, is the battery output power, Output power for fuel cells This is the load power at this moment, P t el is the output power of the water electrolysis hydrogen production system, P t boiler is the output power of the electric boiler;

[0152] The system thermodynamic balance constraint function is as shown in formula (22):

[0153]

[0154] In formula (22), a1 and a1 are the electric heating efficiency of the electric boiler and the heat recovery rate of the fuel cell, P t tload is the system heat load demand at time t;

[0155] The water temperature constraint function of the hot water storage tank is as shown in formula (23):

[0156] 50≤tw t ≤70 (23)

[0157] The interactive power constraint function in the grid-connected mode is as shown in formula (24):

[0158]

[0159] It is the upper limit of power exchange with the upper power grid when the system is connected to the grid; is the transmission power between the system and the upper power grid at time t after the system is connected to the grid;

[0160] The upper and lower limit constraint functions of equipment capacity are as shown in formula (25):

[0161]

[0162] The equipment should operate within its rated operating range. In particular, when the photovoltaic power output is excessive and cannot be absorbed, the output will be reduced by cutting off or exiting the MPPT mode to achieve power balance. Therefore, the upper and lower limit constraint functions of the equipment power are set, such as formula (26) and formula (27):

[0163]

[0164]

[0165] In formula (26), P bat_rated is the rated power of the battery, P el_rated is the rated power of the electrolyzer, P fc_rated is the fuel cell rated power, P boli_rated is the rated power of the electric boiler, β is the overload coefficient of the electrolyzer; in formula (27), when the photovoltaic power output is excessive and cannot be absorbed, the output will be reduced by cutting off or exiting the MPPT mode to achieve power balance, P t pvi It is the ideal output of the photovoltaic module in MPPT mode at time t.

[0166] (4) Based on the mathematical function, target optimization function and capacity configuration constraint function of the off-grid hydrogen-electric hybrid energy storage system, a capacity configuration optimization model of the off-grid hydrogen-electric hybrid energy storage system is established. The capacity configuration optimization model of the off-grid hydrogen-electric hybrid energy storage system is solved by the NSGA-II algorithm to obtain the Pareto frontier solution. The obtained Pareto solutions are sorted, and the optimal capacity configuration scheme of the off-grid hydrogen-electric hybrid energy storage system is finally obtained by comparing the distance between each possible solution and the ideal optimal solution and the worst solution.

[0167] The process of NSGA-II algorithm is as follows: first, input the control parameters of NSGA-II algorithm, including population size (N) and maximum number of iterations, Gen maxThen, the capacity allocation parameter Ri is selected as the initial population of the NSGA-II algorithm. The capacity allocation parameter Ri includes the scale of wind and solar power generation, the capacity of the heat storage tank, the power of the electric boiler, the capacity of the electrolyzer, the hydrogen energy storage capacity, and the fuel cell capacity. The capacity allocation parameter Ri is input into the capacity configuration optimization model of the off-grid hydrogen-electric hybrid energy storage system, and the model is solved to obtain the Pareto frontier solution. The specific NSGA-II algorithm process is:

[0168] Step 1: Input the control parameters of the NSGA-II algorithm, including the population size (N) and the maximum number of iterations, Gen max .

[0169] Step 2: Initialize the population and set Gen = 1. Randomly select N groups of integer arrays (Ri) as the initial population of the NSGA-II algorithm. Each array represents a set of upper-level decision variables, such as wind and solar power generation scale (x1), heat storage tank capacity (x2), electric boiler power (x3), electrolyzer capacity (x4), hydrogen energy storage capacity (x5), and fuel cell capacity (x6).

[0170] Step 3: Input the capacity allocation parameters (Ri) of the individuals in the population into the simplified optimization model. Solve the model by combining meteorological data, load data and wind power data.

[0171] Step 4: Calculate the optimization target of each individual in the group. Perform non-dominated ranking and crowding calculations to obtain the ranking values ​​and crowding of all individuals.

[0172] Step 5: Determine the current individual size. If the population size is equal to N, go to step 6. Otherwise, go to step 7.

[0173] Step 6: Use selection, crossover, and mutation operations to create an offspring population of size N / 2. Merge the offspring population with the parent population to form a new combined population of size N+N / 2. Return to step 3.

[0174] Step 7: Select N individuals from the population based on rank and crowding. These individuals form a new population. The optimization process continues, and if the number of iterations (Gen) exceeds the maximum allowed number of iterations (Gen max ), the optimization method ends. The Pareto frontier is output and Gen is incremented by 1. The process returns to step 6.

[0175] Through this solution process, the proposed off-grid optimization model can be effectively solved. After performing the above optimization calculations, a set of Pareto frontier solutions are obtained, each of which represents a different trade-off between system performance criteria. Through further multi-criteria target selection, the most appropriate solution is determined. The optimization results are shown in Table 1.

[0176] Table 1 Capacity configuration of off-grid hydrogen-electric hybrid energy storage system in Ningbo Cixi City under grid-connected mode

[0177] Wind / kW 400 / 4058.05 Battery / kWh 5670.31 Electrolyzer / kW 396.35 Fuel cell / kW 239.80 Hydrogen storage tank / Kg 390.00

[0178] Example 2: Capacity configuration of the off-grid hydrogen-electric hybrid energy storage system in Ningbo Cixi in off-grid mode

[0179] Under extreme weather conditions, the output of photovoltaic and wind power accounts for a relatively low proportion. At the same time, the planning time cycle is different from normal times, and needs to be considered separately. That is, the capacity of the equipment mainly involved in off-grid energy support is obtained through the configuration under extreme weather conditions, and the optimized configuration results of the remaining equipment are obtained in the normal condition model. In this example, the requirement of 168 hours of off-grid operation under extreme weather is proposed. In the off-grid mode, the off-grid hydrogen-electric hybrid energy storage system can extract the historical extreme weather data of Ningbo Cixi for one year. The extraction of extreme weather data shows that the wind and solar resources are low for 7 consecutive days, resulting in insufficient system energy. The results of extreme weather extraction are as follows: Fig. 9 shown.

[0180] In the off-grid mode, the capacity configuration method of the off-grid hydrogen-electric hybrid energy storage system in Ningbo Cixi is basically the same as that in Example 1, except that the system total cost function F1 adopts the system operation cost function C in the off-grid mode. co_off , and the system power balance constraint function adopts the system power balance constraint function in the off-grid mode. The capacity configuration of the off-grid hydrogen-electric hybrid energy storage system in Ningbo Cixi in the off-grid mode is shown in Table 2:

[0181] Table 2 Capacity configuration of the off-grid hydrogen-electric hybrid energy storage system in Ningbo Cixi in off-grid mode

[0182] Wind / kW 400 / 4058.05 Battery / kWh 5887.11 Electrolyzer / kW 396.35 Fuel cell / kW 239.80 Hydrogen storage tank / Kg 390.00

[0183] By comparing the capacity configuration results of the off-grid hydrogen-electric hybrid energy storage system of Example 1 and Example 2, it can be seen that the capacity configuration results in the two cases are very similar, which shows that the capacity configuration method of the off-grid hydrogen-electric hybrid energy storage system using the present invention has good robustness and stability, and can maintain the stability and reliability of the system under normal operation and extreme weather. The capacity configuration method of the off-grid hydrogen-electric hybrid energy storage system has good adaptability, can cope with challenges under different operating modes such as power grid failures, maintenance and extreme weather, and fully considers the economy and self-sufficiency of the off-grid hydrogen-electric hybrid energy storage system. In the grid-connected state, the model achieves long-term economic benefits at the lowest cost, while in the off-grid state, the self-sufficiency and balance of the system are ensured by maximizing the self-generation rate and minimizing the power abandonment rate. The similarity of the results further proves the comprehensiveness of the optimization strategy. Whether in grid-connected or off-grid conditions, the capacity configuration method of the off-grid hydrogen-electric hybrid energy storage system can effectively guarantee the system performance, demonstrating its versatility and practical value.

Claims

1. A capacity configuration method for an off-grid hydrogen-electric hybrid energy storage system, characterized in that: Includes steps: (1) Establishing a mathematical function of an off-grid hydrogen-electric hybrid energy storage system: The off-grid hydrogen-electric hybrid energy storage system includes three types of energy storage subsystems, namely, an electric energy storage system, a hydrogen energy storage system, and a hot water tank energy storage system. The mathematical function of the off-grid hydrogen-electric hybrid energy storage system is established based on the charging and discharging characteristics of the three types of energy storage subsystems. The mathematical function of the off-grid hydrogen-electric hybrid energy storage system is used to characterize the charging and discharging power, real-time power, and energy storage capacity of each energy storage subsystem. (2) Taking the lowest total system cost as the economic goal, and taking the maximum self-generation rate and the minimum power abandonment rate as the operation goals of the hydrogen-electricity coupled DC microgrid system, an objective optimization function is established; (3) Establish a capacity configuration constraint function based on system power balance, thermal balance, grid-connected interactive power balance, equipment capacity upper limit, and equipment power upper and lower limits as constraints; (4) Based on the mathematical function, target optimization function and capacity configuration constraint function of the off-grid hydrogen-electric hybrid energy storage system, a capacity configuration optimization model of the off-grid hydrogen-electric hybrid energy storage system is established. The capacity configuration optimization model of the off-grid hydrogen-electric hybrid energy storage system is solved by the NSGA-II algorithm to obtain the Pareto frontier solution. The obtained Pareto solutions are sorted, and the optimal capacity configuration scheme of the off-grid hydrogen-electric hybrid energy storage system is finally obtained by comparing the distance between each possible solution and the ideal optimal solution and the worst solution.

2. The capacity configuration method of the off-grid hydrogen-electric hybrid energy storage system according to claim 1, characterized in that: In step (1), the electric energy storage system includes a photovoltaic power generation unit, a wind power generation unit, a battery unit and a lithium battery, the hydrogen energy storage system includes a hydrogen storage tank unit, and the hot water tank energy storage system includes a hot water tank unit.

3. The capacity configuration method of the off-grid hydrogen-electric hybrid energy storage system according to claim 2 is characterized in that: The process of establishing the mathematical function of the off-grid hydrogen-electric hybrid energy storage system in the step (1) is as follows: based on the charge and discharge characteristics of the photovoltaic power generation unit, the wind power generation unit, the battery unit, the lithium battery, the hydrogen storage tank unit, and the hot water storage tank unit, respectively establish a photovoltaic power generation mathematical function, a wind power generation mathematical function, a battery mathematical function, a lithium battery mathematical function, a hydrogen storage tank mathematical function, and a hot water storage tank mathematical function, and the photovoltaic power generation mathematical function, the wind power generation mathematical function, the battery mathematical function, the lithium battery mathematical function, the hydrogen storage tank mathematical function, and the hot water storage tank mathematical function are used to respectively correspond to and characterize the charge and discharge power, real-time power, and energy storage capacity of each energy storage unit.

4. The capacity configuration method of the off-grid hydrogen-electric hybrid energy storage system according to claim 3 is characterized in that: The mathematical functions of photovoltaic power generation, wind power generation, battery, lithium battery, hydrogen storage tank and hot water storage tank are respectively: 1.

1. The mathematical function of photovoltaic power generation is shown in formula (1): In formula (1), P pv is the steady-state power of the photovoltaic power generation system, P STC is the installed capacity of photovoltaic power generation system, I G The standard rated irradiance is 1000W / m 2 ,T G is the standard rated temperature of 25°C, I and T are the actual working radiation intensity and temperature of the system, P0 is the power value under the standard rated state, k is the power temperature coefficient, which is 0.0045; 1.

2. The mathematical function of wind power generation is shown in formula (2): In formula (2), P WT (v) is the wind turbine power generation under wind speed v, v in is the cut-in wind speed, v cut is the cut-out wind speed, v G is the rated wind speed, P WTC is the rated output power of the wind turbine, δ(v) is the function of wind speed, taking quadratic form; 1.

3. The mathematical function of the battery is shown in formula (3); In formula (3), SOC(t) is the battery state of charge at time t, 0.8≥SOC≥0.2, P cha , P dis are the battery charging and discharging power, η cha , η dis are the battery charge and discharge efficiency, Q bat is the battery capacity; 1.

4. The mathematical function of lithium battery is shown in formula (4); P t bat N is the battery charge and discharge efficiency, positive for charging and negative for discharging; cycle is the cycle life of the battery; 1.

5. The mathematical model of the hydrogen storage tank is shown in formula (5) and formula (6); When charging, the hydrogen storage tank model is shown in formula (5): SOCIETY HT (t)=SOC HT (t-1)+η EL (P g (t)-P L(t) / η inv )ρ (5) In formula (5), P g (t) is the sum of photovoltaic and wind power generation at time t, P L(t) is the power load at time t, η inv is the efficiency of the inverter, SOC HT (t) is the remaining hydrogen volume in the hydrogen tank at time t, ρ is the amount of hydrogen that can be generated per kilowatt-hour of electricity, η EL The charging efficiency of the water electrolysis hydrogen production system; During discharge, the hydrogen storage tank model is shown in formula (6): SOCIETY HT (t)=SOC HT (t-1)-η FC (P L (t) / η inv -P g(t) ) / η (6) In formula (6), SOC HT (t) is the remaining hydrogen volume in the hydrogen tank at time t, P L(t) is the power load at time t, P g (t) is the sum of photovoltaic and wind power generation at time t, η represents the amount of electricity generated per cubic meter of hydrogen, η inv is the efficiency of the inverter, η FC is the discharge efficiency of the fuel cell; 1.

6. The mathematical model of the hot water storage tank is shown in formula (7): In formula (7), tw t Indicates the water temperature of the hot water tank; V t load is the heat water consumption in the heat load time period t, M ttk is the volume of the hot water tank, p t boil is the heating power of the electric boiler in period t, a1 and a2 are the heat transfer powers of the electric boiler and the fuel cell respectively; T is the ambient temperature, m water P is the calculation coefficient of thermal power to water temperature; t thermel is the thermal power of the fuel cell.

5. The capacity configuration method of the off-grid hydrogen-electric hybrid energy storage system according to claim 1, characterized in that: In the step (2), the multi-objective optimization function F includes a system total cost function F1, a system self-generation rate function F2, and a system power abandonment rate function F3; The multi-objective optimization function F is shown in formula (8): F={min(F1,F3),max(F2)} (8) The total system cost function F1 includes the one-time investment cost function C cap , equipment replacement cost function C rep , system maintenance function C mat , the system operation cost function C in off-grid mode co_off and the system operation cost function C of the grid-connected mode co_on ; One-time investment cost function C cap As shown in formula (9): In formula (9), C cap is the one-time investment cost, C cap_wt , C cap_pv , C cap_bat , C cap_bl , C cap_ele , C cap_tank , C cap_fc , C cap_ttk are the purchase costs of wind turbines, photovoltaic panels, batteries, electric boilers, water electrolysis hydrogen production systems, hydrogen storage tanks, fuel cells, and hot water storage tanks; k wt , k pv , k bl , k ele , k fc are the unit power prices of fans, photovoltaic panels, electric boilers, water electrolysis hydrogen production systems, and fuel cells, respectively. tank , k ttk are the unit mass prices of hydrogen storage tank and hot water storage tank, respectively, bat is the unit capacity cost of the battery; P wt , P pv , P ele , P fc , P bl are the installed capacity of wind turbines and photovoltaics, the rated power of the water electrolysis hydrogen production system and fuel cells, and the rated heating power of the electric boiler; P bat 、M tank 、M ttk They are the rated capacities of the electric energy storage, hydrogen energy storage, and hot water storage tanks; Equipment replacement function C rep As shown in formula (10): including the replacement cost C of the battery as shown in formula (11) rep_bat , as shown in formula (12), the replacement cost C of the water electrolysis hydrogen production system rep_el , as shown in formula (13), the replacement cost of the fuel cell C rep_fc : C rep =C rep_el +C rep_bat +C rep_fc (10) In formulas (10), (11), (12), and (13), C rep_bat is the replacement cost of the battery, Δsoh a is the annual soh change of the battery, soh max 、soh min is the initial soh of the battery and the soh when it reaches ELO; C rep_el , C rep_fc are the replacement costs of the water electrolysis hydrogen production system and the fuel cell, ΔV ela is the annual voltage rise of the water electrolysis hydrogen production system, ΔV fca is the annual voltage attenuation of the water electrolysis hydrogen production system, V eol_el 、V eol_fc It is the voltage value when the water electrolysis hydrogen production system and the fuel cell reach EOL; System maintenance function C mat As shown in formula (14): C mat =0.1*C cap (14) In formula (14), C cap is the one-time investment cost in formula (9); C mat System maintenance costs; The system operation cost function includes the system operation cost function C of the off-grid mode co_off and the system operation cost function C of the grid-connected mode co_on ; The system operation cost function model is shown in formula (15) and formula (16): In formula (15) and formula (16), C co_off , C co_on They represent the operating costs of off-grid and grid-connected operation, C gass , C gas are the selling price and purchasing price of hydrogen, m t gass 、m t gas are the sales and purchase volumes of hydrogen at time t, c t e represents the electricity purchase price of the upper power grid at time t, P t ex represents the interaction power between the microgrid and the upper grid at time t; The total cost function F1 of the system is as follows: F1=C cap +C rep +C mat +C co_off +C co_on (17) The system's self-generation rate function F2 is as shown in formula (18): In formula (18), P t grid_buy is the amount of electricity purchased from the upper power grid at time t, P load_t is the load required on the load side at time t; The system's power abandonment rate function F3 is as shown in formula (19): In formula (19), P HS,max , P bat,max is the power output of the hydrogen storage tank and the battery at time t, P WT (t), P PV (t) is the output power of wind power and photovoltaic power at time t, P L (t) is the load at time t.

6. The capacity configuration method of the off-grid hydrogen-electric hybrid energy storage system according to claim 1, characterized in that: In step (3), the function of the constraint condition is expressed as: In the grid-connected mode, the system power balance constraint function is as shown in formula (20): In off-grid mode, the system power balance constraint function is as shown in formula (21): In formula (20) and formula (21), is the output power of the photovoltaic system, is the output power of the wind system, is the battery output power, Output power for fuel cells For this moment, the load power, P t el is the output power of the water electrolysis hydrogen production system, P t boiler is the output power of the electric boiler; The system thermodynamic balance constraint function is as shown in formula (22): In formula (22), a1 and a1 are the electric heating efficiency of the electric boiler and the heat recovery rate of the fuel cell, P t tload is the system heat load demand at time t; The water temperature constraint function of the hot water storage tank is as shown in formula (23): 50≤tw t ≤70(23) The interactive power constraint function in the grid-connected mode is as shown in formula (24): In formula (24), It is the upper limit of power exchange with the upper power grid when the system is connected to the grid; is the transmission power between the system and the upper power grid at time t when the system is connected to the grid; The upper and lower limit constraint functions of equipment capacity are as shown in formula (25): The upper and lower limit constraint functions of equipment power are as shown in formulas (26) and (27): In formula (26), P bat_rated is the rated power of the battery, P el_rated is the rated power of the electrolyzer, P fc_rated is the fuel cell rated power, P boli_rated is the rated power of the electric boiler, β is the overload coefficient of the electrolyzer; in formula (27), when the photovoltaic power output is excessive and cannot be absorbed, the output will be reduced by cutting off or exiting the MPPT mode to achieve power balance, P t pvi It is the ideal output of the photovoltaic module in MPPT mode at time t.

7. The capacity configuration method of the off-grid hydrogen-electric hybrid energy storage system according to claim 1, characterized in that: In step (4), the optimal capacity configuration scheme of the off-grid hydrogen-electric hybrid energy storage system includes wind and solar power, battery power, electrolyzer power, fuel cell power, and hydrogen quality in the hydrogen storage tank.

8. The capacity configuration method of the off-grid hydrogen-electric hybrid energy storage system according to claim 1, characterized in that: In step (3), the process of the NSGA-II algorithm is as follows: first, the control parameters of the NSGA-II algorithm are input, including the population size (N) and the maximum number of iterations, Gen max Then, the capacity allocation parameter Ri is selected as the initial population of the NSGA-II algorithm. The capacity allocation parameter Ri includes the scale of wind and solar power generation, the capacity of the heat storage tank, the power of the electric boiler, the capacity of the electrolyzer, the hydrogen energy storage capacity, and the fuel cell capacity. The capacity allocation parameter Ri is input into the capacity configuration optimization model of the off-grid hydrogen-electric hybrid energy storage system, the model is solved, and the Pareto frontier solution is obtained.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the capacity configuration method of the off-grid hydrogen-electric hybrid energy storage system as described in any one of claims 1 to 8 is implemented.

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

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