Hydrogen-based near-zero carbon emission integrated energy system and its operation optimization method

Abstract

The present invention discloses a hydrogen-based near-zero carbon emission integrated energy system and its operation optimization method. Photovoltaic and wind turbine generator sets are responsible for supplying electrical loads. When there is excess electricity, the excess electricity load inputs direct current into an electrolyzer to electrolyze water to produce hydrogen, which is then stored in a hydrogen storage tank. When there is insufficient electricity, the hydrogen storage tank provides hydrogen to a fuel cell, which generates electricity to meet the electrical load demand. A heat storage device provides heat to the electrolyzer. The hydrogen produced by the electrolyzer releases heat during compression, which is recovered and stored by the heat storage device. The fuel cell releases heat during electricity generation, which is recovered and stored by the heat storage device. An absorption chiller absorbs heat energy from the heat storage device for cooling operations. A heat pump draws electricity from the photovoltaic and wind turbine generator sets to generate heat or cold energy. This system has the advantages of a zero-carbon economy, promoting the consumption of renewable energy, peak-load shifting, and cross-seasonal energy storage scheduling.

Description

Technical Field

[0001] The present invention relates to the field of integrated energy technology, and in particular to a hydrogen-based near-zero carbon emission integrated energy system and an operation optimization method thereof. Background Art

[0002] The statements in this section merely mention background art related to the present invention and do not necessarily constitute prior art.

[0003] Currently, the primary energy source for integrated energy systems is still fossil fuels, which emit large amounts of carbon dioxide during combined heat and power generation. While measures such as carbon capture and carbon trading have reduced CO2 emissions to some extent, they still cannot fundamentally address the problem. Furthermore, the absorption rate of renewable clean energy is a major constraint on the development of the energy system. The phenomenon of curtailing wind and solar power wastes energy and correspondingly increases power generation costs, seriously affecting indicators such as energy utilization and economic efficiency.

[0004] As energy consumption intensifies, finding new energy sources has become a crucial task. Hydrogen, one of the most promising energy sources today, is widely available, produces virtually no pollution, has high conversion efficiency, and has a wide range of applications. As a crucial transitional energy source in this energy transition, hydrogen, through the energy coupling of hydrogen and electricity and the "production, storage, and use" of hydrogen, can achieve long-term balance between the power generation and load sides of integrated energy systems. Therefore, optimizing the operation of hydrogen-based integrated energy systems is of great research significance. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a hydrogen-based near-zero carbon emission integrated energy system and its operation optimization method. This system offers the advantages of a zero-carbon economy, promoting renewable energy consumption, peak load shifting, and cross-seasonal energy storage scheduling. This system is a near-zero carbon emission integrated energy system.

[0006] In a first aspect, the present invention provides a hydrogen-based near-zero carbon emission integrated energy system;

[0007] A hydrogen-based, near-zero carbon emission integrated energy system, including: photovoltaic generators, wind turbines, electrolyzers, hydrogen storage tanks, fuel cells, heat pumps, absorption chillers, and thermal storage devices;

[0008] The photovoltaic generator set and wind turbine generator set are responsible for supplying the electrical load. When there is excess electricity, the excess electricity load inputs direct current to the electrolyzer to electrolyze water to produce hydrogen, and the hydrogen is stored in the hydrogen storage tank. When there is insufficient electricity, the hydrogen storage tank provides hydrogen to the fuel cell, and the fuel cell generates electricity to meet the electrical load demand.

[0009] The heat storage device provides heat for the electrolyzer; the hydrogen produced by the electrolyzer releases heat during the compression process, and the heat storage device recovers and stores the heat released by the compressed hydrogen; the fuel cell releases heat during the generation of electricity, and the heat storage device recovers and stores the heat released by the generated electricity;

[0010] Absorption chillers absorb heat energy from a heat storage device to perform cooling operations;

[0011] Heat pumps draw electricity from photovoltaic generators and wind turbines to generate heat or cold energy.

[0012] In a second aspect, the present invention provides an operation optimization method for a hydrogen-based near-zero carbon emission integrated energy system;

[0013] The operation optimization method of hydrogen-based near-zero carbon emission integrated energy system includes:

[0014] Obtain weather data, load data, equipment parameters, and energy cost data;

[0015] Get the energy flow demand per hour;

[0016] Constructing a mathematical model of a hydrogen-based near-zero carbon emission integrated energy system; the mathematical model of the hydrogen-based near-zero carbon emission integrated energy system includes: an electrolyzer mathematical model, a fuel cell mathematical model, an absorption chiller mathematical model, and a heat pump mathematical model;

[0017] Construct the objective function and constraints; solve the objective function to obtain the input and output values ​​of each device.

[0018] Compared with the prior art, the present invention has the following beneficial effects:

[0019] The hydrogen-based "near-zero carbon" integrated energy system and its optimized operation method achieve a "near-zero carbon" design while increasing the system's renewable energy absorption rate; increasing the system's thermal management to achieve energy recycling, while using seasonal hydrogen storage to achieve a higher system energy utilization rate throughout the year. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0021] Figure 1 This is a system structure diagram of Example 1;

[0022] Figure 2 This is a flow chart of the method of Example 2. DETAILED DESCRIPTION

[0023] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0024] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0025] In the absence of conflict, the embodiments of the present invention and the features thereof may be combined with each other.

[0026] All data in this embodiment is obtained in compliance with laws and regulations and based on the consent of the user, and is used legally.

[0027] Example 1

[0028] This embodiment provides a hydrogen-based near-zero carbon emission integrated energy system;

[0029] like Figure 1 As shown, the hydrogen-based near-zero carbon emission integrated energy system includes: photovoltaic generators, wind turbines, electrolyzers, hydrogen storage tanks, fuel cells, heat pumps, absorption chillers and heat storage devices;

[0030] The photovoltaic generator set and wind turbine generator set are responsible for supplying the electrical load. When there is excess electricity, the excess electricity load inputs direct current to the electrolyzer to electrolyze water to produce hydrogen, and the hydrogen is stored in the hydrogen storage tank. When there is insufficient electricity, the hydrogen storage tank provides hydrogen to the fuel cell, and the fuel cell generates electricity to meet the electrical load demand.

[0031] The heat storage device provides heat for the electrolyzer; the hydrogen produced by the electrolyzer releases heat during the compression process, and the heat storage device recovers and stores the heat released by the compressed hydrogen; the fuel cell releases heat during the generation of electricity, and the heat storage device recovers and stores the heat released by the generated electricity;

[0032] Absorption chillers absorb heat energy from a heat storage device to perform cooling operations;

[0033] Heat pumps draw electricity from photovoltaic generators and wind turbines to generate heat or cold energy.

[0034] It should be understood that by providing energy to the electrolyzer through the heat storage device, electricity consumption is reduced while improving the efficiency of hydrogen production.

[0035] Example 2

[0036] This embodiment provides an operation optimization method for a hydrogen-based near-zero carbon emission integrated energy system;

[0037] like Figure 2 As shown in FIG, the operation optimization method of the hydrogen-based near-zero carbon emission integrated energy system includes:

[0038] S201: Acquire weather data, load data, equipment parameters, and energy cost data;

[0039] S202: Obtaining energy flow demand per hour;

[0040] S203: Constructing a mathematical model of a hydrogen-based near-zero carbon emission integrated energy system; the mathematical model of the hydrogen-based near-zero carbon emission integrated energy system includes: an electrolyzer mathematical model, a fuel cell mathematical model, an absorption chiller mathematical model, and a heat pump mathematical model;

[0041] S204: Construct an objective function and constraint conditions; solve the objective function to obtain input values ​​and output values ​​of each device.

[0042] The method further includes: S205: determining whether the optimized scheduling time t is equal to a set value, if so, ending the process; if not, adding one to t, updating the energy storage device, and returning to S202.

[0043] t is 8760 hours.

[0044] Among them, 8760 hours = 365 days * 24 hours.

[0045] The energy storage equipment includes: a hydrogen storage tank and a heat storage device.

[0046] Furthermore, the weather parameters include: solar radiation, wind speed and direction, etc. of the weather forecast.

[0047] Furthermore, the load data includes: user's predicted demand data;

[0048] The user's predicted demand data includes: electricity load data, cooling load data, heating load data and hydrogen load data.

[0049] Furthermore, the equipment parameters include: refrigerator COP, heat pump COP, capacity of each device, fuel cell efficiency, electrolyzer temperature and pressure, etc.

[0050] Furthermore, the energy cost data includes: the price of hydrogen.

[0051] Furthermore, the S202: obtaining the energy flow demand every hour; the energy flow demand refers to the load demand of cooling, heating, electricity, and hydrogen.

[0052] Furthermore, the mathematical model of the S203 electrolytic cell specifically refers to:

[0053] The hydrogen production rate of the electrolyzer is related to the current:

[0054]

[0055] in, is the hydrogen production rate of the electrolyzer; I cell is the current of the electrolytic cell; P is the pressure of the electrolytic cell.

[0056] The temperature of the electrolyzer is related to the heat energy flow and the power input to the electrolyzer:

[0057] T elz =T elz (Q elz ,P elz );

[0058] Among them, T elz Indicates the working temperature of the electrolytic cell, Q elz Indicates the heat delivered by the heat storage device to the electrolytic cell; P elz Indicates the input power of the electrolyzer.

[0059] Electrolyzer efficiency:

[0060]

[0061] Where η E is the efficiency of the electrolyzer; HHV of H2 represents the higher heating value of hydrogen; C E is the energy consumption of the electrolyzer;

[0062] The reaction in the electrolytic cell requires both electrical and thermal energy:

[0063] H2O→H2(g)+1 / 2O2(g)

[0064] Furthermore, the S203 fuel cell mathematical model specifically refers to:

[0065] Heat value Q fc :

[0066] Q fc =η he P fc

[0067] Among them, Qfc is the heating power of the fuel cell; η he is the fuel cell heat-to-power ratio;

[0068] Furthermore, the mathematical model of the absorption chiller in step S203 specifically refers to:

[0069] Cooling capacity Q c,ac :

[0070] Q c,ac =COP ac Q h,ac

[0071] Among them, COP ac is the efficiency of the absorption chiller; Q h,ac The heat input to the absorption chiller.

[0072] Furthermore, the S203 heat pump mathematical model specifically refers to:

[0073] Heating capacity Q h,hp :

[0074] Q h,hp =COP h,hp P hp ;

[0075] Cooling capacity Q c,hp :

[0076] Q c,hp =COP c,hp P hp ;

[0077] Among them, COP c,hp is the heat pump cooling efficiency, COP h,hp is the heating efficiency of the heat pump; P hp Electrical energy input for the heat pump.

[0078] Furthermore, the step S203 of constructing a mathematical model of a hydrogen-based near-zero carbon emission integrated energy system further includes:

[0079] Constructing a balance equation; the balance equation includes: an electric energy balance equation, a thermal energy balance equation, a cold energy balance equation and a hydrogen energy balance equation.

[0080] Furthermore, the electric energy balance equation refers to:

[0081] P pv +P wt -P elz -P hp +P fc =P L

[0082] Among them, Ppv is the photovoltaic power generation; P wt is wind power generation; P elz is the power consumption of the electrolytic cell; P hp is the heat pump power input; P fc is the power generation of the fuel cell; P L For electrical load.

[0083] Furthermore, the thermal energy balance equation refers to:

[0084]

[0085] Among them, Q fc Generating heat for fuel cells, Q h,hp The heat pump generates heat; Q h,Hs Heat released for compressing hydrogen; Q elz The heat supply from the heat storage device to the electrolyzer; Q h,ac Heat input to the absorption chiller; is the heating efficiency; is the heating power; is the heat release efficiency; is the heat release power; Q h For heat load.

[0086] Furthermore, the cold energy balance equation refers to:

[0087] Q c,hp +Q c,ac =Q c

[0088] Q c,hp is the cooling capacity of the heat pump; Q c,ac Generates heat for the absorption refrigeration unit; Q c For cooling load.

[0089] Furthermore, the hydrogen energy balance equation refers to:

[0090]

[0091] Among them, η loss P is the ratio of energy consumed in the process of compressing hydrogen to the energy lost as heat; elz Input power to the electrolyzer; Power for filling hydrogen storage tank; The hydrogen storage tank filling efficiency is Hydrogen storage and charging power for the season; It is the seasonal hydrogen storage and charging efficiency; The hydrogen release power for the hydrogen storage tank; is the hydrogen release efficiency of the hydrogen storage tank, It is the seasonal hydrogen storage and release power; is the seasonal hydrogen storage and release efficiency; H l is hydrogen loading.

[0092] Furthermore, the S204: constructing an objective function and constraint conditions;

[0093] Among them, the objective function is a scheduling model with the minimum operating cost as the optimization goal:

[0094]

[0095] The operating costs include: equipment operating costs, hydrogen sales costs, and penalty costs for curtailed solar and wind power.

[0096] Among them, the constraints include: hydrogen storage constraints, heat storage constraints and equipment output constraints.

[0097] The hydrogen storage constraint conditions are:

[0098] Seasonal hydrogen storage enables the charging and release of hydrogen between typical days, and hydrogen storage enables the charging and release of hydrogen within a day. The operating constraints of seasonal hydrogen storage are as follows:

[0099]

[0100] Formula (2) limits the maximum amount of hydrogen charged and released each time and the maximum hydrogen storage capacity. Wherein, shs is the abbreviation of Seasonal Hydrogen Storage; is the charging / discharging power of shs at time t in scenario s; 1 means that at time t in scenario s, shs is in the charging / releasing state; v shs is the power capacity ratio of shs; Cap shs The maximum installation capacity of shs.

[0101]

[0102] Formula (3) is a typical day in different seasons. There is only one state in shs, charging or releasing.

[0103]

[0104]

[0105]

[0106]

[0107] In formulas (4)-(6), C is the remaining capacity of the hydrogen storage tank. The initial value of C is half of the installed capacity on the first typical day, and on other typical days it is the accumulation of the charge and discharge power of the previous season after deducting the self-discharge energy loss.

[0108] in, is the remaining capacity on the first typical day; is the remaining capacity at time t in scenario s; is the self-release efficiency of shs; is the charging efficiency of shs; is the release efficiency of shs; ω(s) is the probability of the scenario of s. Formula (6) stipulates that the sum of the probabilities of the s scenarios is 1.

[0109] The heat storage constraint condition refers to:

[0110]

[0111]

[0112]

[0113]

[0114] is the charging power of the heat storage device at time t in scenario s;

[0115] is the heat release power of the heat storage device at time t under scenario s;

[0116] is the maximum heating power of the heat storage device;

[0117] is the maximum heat release power of the heat storage device;

[0118] A value of 1 indicates that the heat storage device is in the charging state at time t in scenario s;

[0119] A value of 1 indicates that the heat storage device is in the heat release state at time t in scenario s;

[0120] Formula (8) limits the maximum power of each heat charging and heat dissipation, and heat charging and heat dissipation cannot occur at the same time;

[0121] In formulas (9)-(11), E is the remaining capacity of the heat storage device;

[0122] Formula (9) is the upper and lower limits of the heat storage device capacity;

[0123] is the self-release efficiency of the heat storage device;

[0124] is the charging efficiency of the heat storage device;

[0125] is the heat release efficiency of the heat storage device;

[0126] Formula (10) represents the remaining capacity of the heat storage device at time t.

[0127] The equipment output constraint conditions refer to:

[0128]

[0129] Equation (12) represents the rated power constraints of each device in operation, and θ represents various devices including: heat pump, electrolyzer, fuel cell, absorption chiller, photovoltaic, and wind power. Indicates the minimum operating power of the device; Indicates the operating power of each device; Indicates the maximum operating power of each device

[0130]

[0131] Formula (13) represents the climbing constraint of each device during operation, and R is the climbing efficiency.

[0132]

[0133] A value of 1 indicates that the electrolyzer / fuel cell is working at time t in scenario s, and Equation (14) indicates that the electrolyzer and fuel cell cannot work at the same time.

[0134] Furthermore, the objective function is solved to obtain the input value and output value of each device; the solution algorithm adopted is: NGSA-Ⅱ optimization algorithm.

[0135] Furthermore, the objective function is solved to obtain input values ​​and output values ​​of each device; the various devices here specifically include: heat pumps, electrolyzers, fuel cells, absorption refrigerators, photovoltaics, wind power, hydrogen storage devices, and heat storage devices.

[0136] The present invention provides energy for the electrolysis reaction by recycling heat in the system, thus reducing the power consumption of the electrolyzer; reduces the total energy consumption of refrigeration by coordinating the heat consumption of the absorption refrigerator and the power consumption of the heat pump; and achieves optimized scheduling throughout the year by balancing the long-term mismatch between the power generation side and the load side through cross-seasonal hydrogen storage. Figure 2As shown in the figure, in the optimization, the amount of hydrogen stored in the hydrogen tank, the energy stored in the heat storage device, and the cooling / heating capacity of the heat pump are selected as optimization variables, and the minimum operating cost is used as the objective function. According to the state of heat storage and the state of load, the heat currently supplied to the electrolyzer is constrained, and the energy stored in the heat storage device, the amount of hydrogen stored in the hydrogen tank, and the cooling / heating capacity of the heat pump are solved to control the operation of each device in the system.

[0137] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. An operation optimization method for a hydrogen-based near-zero carbon emission integrated energy system, characterized by: include: Obtain weather data, load data, equipment parameters, and energy cost data; Get the energy flow demand per hour; Construct a mathematical model of a hydrogen-based near-zero carbon emission integrated energy system; the mathematical model of the hydrogen-based near-zero carbon emission integrated energy system includes: an electrolyzer mathematical model, a fuel cell mathematical model, an absorption chiller mathematical model, a heat pump mathematical model, and also includes: Constructing balance equations; the balance equations include: an electrical energy balance equation, a thermal energy balance equation, a cold energy balance equation, and a hydrogen energy balance equation; The electric energy balance equation is: P pv +P wt -P elz -P hp +P fc =P L Among them, P pv is the photovoltaic power generation; P wt is wind power generation; P elz is the power consumption of the electrolytic cell; P hp is the heat pump power input; P fc is the power generation of the fuel cell; P L is the electrical load; The heat energy balance equation is: Among them, Q fc Generating heat for fuel cells, Q h,hp The heat pump generates heat; Q h,Hs Heat released for compressing hydrogen; Q elz The heat supply from the heat storage device to the electrolyzer; Q h,ac Heat input to the absorption chiller; is the heating efficiency; is the heating power; is the heat release efficiency; is the heat release power; Q h is the heat load; The cold energy balance equation is: Q c,hp +Q c,ac =Q c Q c,hp is the cooling capacity of the heat pump; Q c,ac Generates heat for absorption refrigeration; Q c is the cooling load; The hydrogen energy balance equation refers to: Among them, η loss P is the ratio of energy consumed in the process of compressing hydrogen to the energy lost as heat; elz Input power to the electrolyzer; Power for filling hydrogen storage tank; The hydrogen storage tank filling efficiency is Hydrogen storage and charging power for the season; It is the seasonal hydrogen storage and charging efficiency; The hydrogen release power for the hydrogen storage tank; is the hydrogen release efficiency of the hydrogen storage tank, It is the seasonal hydrogen storage and release power; is the seasonal hydrogen storage and release efficiency; H l is the hydrogen load; Construct the objective function and constraints; solve the objective function to obtain the input and output values ​​of each device; The hydrogen-based near-zero carbon emission integrated energy system includes: a photovoltaic generator set, a wind turbine generator set, an electrolyzer, a hydrogen storage tank, a fuel cell, a heat pump, an absorption refrigerator, and a heat storage device; The photovoltaic generator set and wind turbine generator set are responsible for supplying the electrical load. When there is excess electricity, the excess electricity load inputs direct current to the electrolyzer to electrolyze water to produce hydrogen, and the hydrogen is stored in the hydrogen storage tank. When there is insufficient electricity, the hydrogen storage tank provides hydrogen to the fuel cell, and the fuel cell generates electricity to meet the electrical load demand. The heat storage device provides heat for the electrolyzer; the hydrogen produced by the electrolyzer releases heat during the compression process, and the heat storage device recovers and stores the heat released by the compressed hydrogen; the fuel cell releases heat during the generation of electricity, and the heat storage device recovers and stores the heat released by the generated electricity; Absorption chillers absorb heat energy from a heat storage device to perform cooling operations; Heat pumps draw electricity from photovoltaic generators and wind turbines to generate heat or cold energy.

2. The operation optimization method of the hydrogen-based near-zero carbon emission integrated energy system according to claim 1 is characterized in that: The mathematical model of the electrolytic cell specifically refers to: The hydrogen production rate of the electrolyzer is related to the current: in, is the hydrogen production rate of the electrolyzer; I cell is the current of the electrolytic cell; P is the pressure of the electrolytic cell; The temperature of the electrolyzer is related to the heat energy flow and the power input to the electrolyzer: T elz =T elz (Q elz ,P elz ); Among them, T elz Indicates the working temperature of the electrolytic cell, Q elz Indicates the heat delivered by the heat storage device to the electrolytic cell; P elz Indicates the input power of the electrolyzer; Electrolyzer efficiency: Where η E is the efficiency of the electrolyzer; HHV of H2 represents the higher heating value of hydrogen; C E is the energy consumption of the electrolyzer; The reaction in the electrolytic cell requires both electrical and thermal energy: H2O→H2(g)+1 / 2O2(g).

3. The operation optimization method of the hydrogen-based near-zero carbon emission integrated energy system according to claim 1 is characterized in that: Fuel cell mathematical model, specifically refers to: Heat value Q fc : Q fc =η he P fc Among them, Q fc is the heating power of the fuel cell; η he is the fuel cell heat-to-power ratio; The mathematical model of absorption chiller refers to: Cooling capacity Q c,ac : Q c,ac =COP ac Q h,ac Among them, COP ac is the efficiency of the absorption chiller; Q h,ac Heat input to the absorption chiller; Heat pump mathematical model, specifically refers to: Heating capacity Q h,hp : Q h,hp =COP h,hp P hp ; Cooling capacity Q c,hp : Q c,hp =COP c,hp P hp ; Among them, COP c,hp is the heat pump cooling efficiency, COP h,hp is the heating efficiency of the heat pump; P hp Electrical energy input for the heat pump.

4. The operation optimization method of the hydrogen-based near-zero carbon emission integrated energy system according to claim 1 is characterized in that: Construct objective functions and constraints; Among them, the objective function is a scheduling model with the minimum operating cost as the optimization goal: The operating costs include: equipment operating costs, hydrogen sales costs, and penalty costs for curtailed solar and wind power.

5. The operation optimization method of the hydrogen-based near-zero carbon emission integrated energy system according to claim 1 is characterized in that: Constraints, including hydrogen storage constraints, heat storage constraints, and equipment output constraints; The hydrogen storage constraint conditions are: Seasonal hydrogen storage enables the charging and release of hydrogen between typical days, and hydrogen storage enables the charging and release of hydrogen within a day. The operating constraints of seasonal hydrogen storage are as follows: Formula (2) limits the maximum amount of hydrogen charging and releasing and the maximum hydrogen storage capacity each time; where shs is the abbreviation of Seasonal Hydrogen Storage; is the charging / discharging power of shs at time t in scenario s; 1 means that at time t in scenario s, shs is in the charging / releasing state; v shs is the power capacity ratio of shs; Cap shs is the maximum installation capacity of shs; Formula (3) shows typical days in different seasons. There is only one state in shs, charging or releasing; In formulas (4)-(6), C is the remaining capacity of the hydrogen storage tank. The initial value of C is half of the installed capacity on the first typical day, and on other typical days it is the accumulation of the charge and discharge power of the previous season after deducting the self-discharge energy loss; in, is the remaining capacity on the first typical day; is the remaining capacity at time t in scenario s; is the self-release efficiency of shs; is the charging efficiency of shs; is the release efficiency of shs; ω(s) is the probability of the scene of s; Formula (6) stipulates that the probability of the scene of s is 1; The heat storage constraint condition refers to: is the charging power of the heat storage device at time t in scenario s; is the heat release power of the heat storage device at time t under scenario s; is the maximum heating power of the heat storage device; is the maximum heat release power of the heat storage device; A value of 1 indicates that the heat storage device is in the charging state at time t in scenario s; A value of 1 indicates that the heat storage device is in the heat release state at time t in scenario s; Formula (8) limits the maximum power of each heat charging and heat dissipation, and heat charging and heat dissipation cannot occur at the same time; In formulas (9)-(11), E is the remaining capacity of the heat storage device; Formula (9) is the upper and lower limits of the heat storage device capacity; is the self-release efficiency of the heat storage device; is the charging efficiency of the heat storage device; is the heat release efficiency of the heat storage device; Formula (10) represents the remaining capacity of the heat storage device at time t; The equipment output constraint conditions refer to: Equation (12) represents the rated power constraints of each device in operation, θ represents various devices including: heat pump, electrolyzer, fuel cell, absorption chiller, photovoltaic, and wind power; Indicates the minimum operating power of the device; Indicates the operating power of each device; Indicates the maximum operating power of each device Formula (13) represents the climbing constraint of each device during operation, R is the climbing efficiency; A value of 1 indicates that the electrolyzer / fuel cell is working at time t in scenario s, and Equation (14) indicates that the electrolyzer and fuel cell cannot work at the same time.

6. The operation optimization method of the hydrogen-based near-zero carbon emission integrated energy system according to claim 1 is characterized in that: The objective function is solved to obtain the input value and output value of each device; the solution algorithm adopted is: NGSA-Ⅱ optimization algorithm.

7. The operation optimization method of the hydrogen-based near-zero carbon emission integrated energy system according to claim 1 is characterized in that: Solving the objective function to obtain input values ​​and output values ​​of each device; The various equipment here include: heat pumps, electrolyzers, fuel cells, absorption chillers, photovoltaics, wind power, hydrogen storage devices, and heat storage devices.

8. The method for optimizing the operation of a hydrogen-based near-zero carbon emission integrated energy system according to claim 1, wherein: The method further includes: determining whether the optimized scheduling time t is equal to a set value, and ending the process if so; and if not, incrementing t by one, updating the energy storage device, and returning to the step of obtaining the energy flow demand for each hour.

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