Multi-element hybrid energy storage system combined with hydrogen-doped combustion and capacity optimization configuration method

Abstract

The invention relates to the technical field of comprehensive energy systems, provides a multi-element hybrid energy storage system combined with hydrogen-doped combustion and a capacity configuration optimization method thereof, and establishes a distributed energy system containing ground source heat pump hydrogen-doped combustion based on the existing annual illumination intensity and wind speed data which are clustered into typical days through a K-means algorithm. The load module is used for providing power, heat supply and refrigeration loads for users; two targets of economy and carbon emission are selected, comprehensive constraint conditions are configured, the carbon emission is converted into a part of an economy target function, and the capacity of each link is configured to enable the economy to be optimal; and determining a global optimal configuration scheme according to the optimal configuration scheme by adopting an integer linear programming method. The system can solve the problems that in the prior art, a reasonable energy storage system optimization configuration scheme is lacked, and the economical efficiency and environmental protection performance of the system are not facilitated, fuel is saved, renewable energy sources are fully utilized, and flexible conversion and stable output between electricity and heat or cold and hydrogen are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of integrated energy systems, and particularly to a multi - energy hybrid energy storage system combined with hydrogen - doped combustion and an optimization method for its capacity configuration. Background Art

[0002] With the continuous growth of global energy demand and the improvement of environmental protection awareness, the development of low - carbon, green, and efficient energy systems has become a global consensus. In this context, the integrated energy system, as an advanced energy system integrating various energy forms and energy storage technologies, has gradually received attention. It can achieve the complementary advantages between different energies, improve energy utilization efficiency and system stability. However, there are still many problems in the existing integrated energy systems in terms of the optimal configuration of energy storage technologies, energy conversion, and utilization.

[0003] In terms of energy storage technology, the current integrated energy systems mostly adopt a single energy storage form, such as electrical energy storage, thermal energy storage, or hydrogen energy storage, often ignoring the synergistic effect between multiple energy storage forms. This single - energy - storage configuration method is difficult to achieve flexible scheduling when dealing with different load demands and meteorological conditions, resulting in low energy storage efficiency and increased system operation costs.

[0004] In terms of energy conversion and utilization, most of the existing technologies are limited to the mutual conversion between electric - heat and electric - hydrogen, and fail to achieve efficient conversion between hydrogen and heat. This limitation restricts the multi - energy complementarity of the integrated energy system, resulting in the system being unable to fully utilize renewable energy, thereby reducing energy utilization efficiency.

[0005] In addition, with the large - scale access of renewable energies such as wind energy and solar energy, their volatility and intermittency characteristics pose great challenges to the safe and stable operation of the power grid and the supply - demand balance of the integrated energy system. The existing integrated energy systems are still insufficient in dealing with the access of a high proportion of renewable energies, and it is difficult to ensure the stability and economy of the system.

[0006] Chinese Patent with publication number CN115347596A discloses an optimization method for a multi - energy complementary system based on electric - thermal - hydrogen hybrid energy storage. Although this method considers the mutual conversion between electrical energy storage, thermal energy storage, and hydrogen energy storage, there are still the following problems in practical applications:

[0007] 1. Unreasonable capacity configuration of the energy storage system: When configuring the capacity of the energy storage system, this method fails to fully consider the annual operation cost of the system, including investment cost, operation and maintenance cost, and energy cost, etc., resulting in the configured energy storage capacity not being optimal in terms of economy. This limitation may prevent the system from achieving the best economic benefits in actual operation.

[0008] 2. Incomplete energy conversion pathways: This method mainly focuses on the mutual conversion between electrothermal and electrohydrogen, while neglecting the efficient conversion between hydrogen and heat. This incompleteness of the energy conversion pathway limits the multi-energy complementarity of the system, making it difficult for the system to fully utilize renewable energy, thereby reducing the overall energy utilization efficiency.

[0009] 3. Limitations of the optimization method: In the optimization process, this method may adopt relatively simple optimization algorithms such as linear programming and genetic algorithms. These algorithms may have problems such as slow convergence speed and being easily trapped in local optimal solutions when solving complex system optimization problems, resulting in unsatisfactory optimization results and being unable to effectively meet the actual application requirements.

[0010] 4. Lack of flexibility: This method may lack flexibility in the scheduling strategy and cannot be adjusted in real time according to meteorological conditions such as annual light intensity and wind speed, as well as changes in load demand. This inflexible scheduling strategy directly affects the overall operation efficiency of the system and the consumption level of new energy.

[0011] In summary, there are many deficiencies in the existing technology in the optimization configuration of energy storage technology, energy conversion and utilization in integrated energy systems, and there is an urgent need for improvement and innovation to achieve a more efficient and flexible energy management solution. Summary of the Invention

[0012] In view of this, the present invention proposes a multi-component hybrid energy storage system combined with hydrogen-doped combustion and its capacity configuration optimization method, aiming to solve the deficiencies of traditional energy systems in multi-energy complementarity and flexibility, especially the challenges faced when dealing with the volatility of renewable energy and changes in user loads. Existing energy systems often have difficulty effectively integrating various energy forms such as electricity, heat, cold, and hydrogen, resulting in low resource utilization efficiency and causing greater impact on the environment. The present invention proposes a multi-component hybrid energy storage system combined with hydrogen-doped combustion and its capacity configuration optimization method, adjusts the hydrogen-doping ratio of the gas turbine, constructs a multi-energy complementary integrated energy system model, and takes economic cost and environmental cost as indicators to reasonably configure the energy supply of each device in the system and the capacity of each energy storage link, so as to reduce costs and make reasonable configurations.

[0013] To achieve the above object, the technical solution of the present invention is realized as follows:

[0014] A multi-component hybrid energy storage system combined with hydrogen-doped combustion includes an electric power system, a thermal power system, and a cold air system. The electric power system includes a wind power generation unit, a photovoltaic unit, a gas turbine, an external power grid, and an electrolyzer. The electrolyzer is used to provide hydrogen for the gas turbine, and hydrogen and natural gas are burned simultaneously in the gas turbine according to a preset ratio; the thermal power system includes a ground source heat pump and a heat recovery device; the cold air system includes an absorption refrigeration unit;

[0015] The heat recovery device is coupled with the gas turbine, and the heat energy generated during the hydrogen-doped combustion process of the gas turbine is stored in the heat recovery device; the electric energy generated by the gas turbine is output to the external power grid and the ground source heat pump; the ground source heat pump is used to provide heating and cooling loads;

[0016] The heat source output end of the heat recovery device is connected to the heat supply end and the heat source input end of the absorption refrigeration unit;

[0017] It also includes an intelligent control system, which is used to regulate the operation of the power system, thermal system and cooling system according to the heating and cooling load requirements and power generation conditions, so as to realize the conversion and output of four energy forms: hydrogen-electricity-heat-cooling.

[0018] Furthermore, it also includes a storage system. The storage system includes a storage battery and a heat storage device. The storage battery is connected to the wind power generation unit. The heat source input end of the heat storage device is connected to the ground source heat pump and the heat recovery device. The output end of the heat storage device is connected to the heat supply end;

[0019] The intelligent control system also comprehensively regulates the operation of the power system, thermal system and cooling system according to the storage capacity of the storage system.

[0020] Furthermore, the intelligent control system includes an equipment model, a mathematical model for capacity configuration optimization, an objective function model, and a constraint condition model. Among them, the objective function model contains an objective function of economic cost and environmental cost parameters. The constraint condition model includes constraint conditions such as equipment capacity limitation and / or energy conversion efficiency limitation and / or energy balance constraint and / or charge and discharge limitation of energy storage equipment. The intelligent control system outputs capacity configuration results and optimization target results according to the objective function and the constraint condition model, and conducts mutual conversion between three different energy forms: electricity, heat or cooling, and hydrogen.

[0021] Furthermore, based on the equipment model, the mathematical model for capacity configuration optimization, the constraint conditions, the initial data, and the equipment energy supply strategy, the intelligent control system sets the capacity configuration optimization problem as a mixed integer linear programming problem, and uses an intelligent algorithm to solve the mathematical model for capacity configuration optimization, and outputs capacity configuration results and optimization target results.

[0022] Furthermore, the equipment model includes a wind power generation model, a photovoltaic power generation model, a CCHP model, and a storage system model, where:

[0023] The wind power generation model is:

[0024]

[0025] Among them, v t is the instantaneous wind speed, v in , v r and v outThey are the cut-in wind speed, rated wind speed and cut-out wind speed respectively, and P r is the rated power of the wind turbine;

[0026] The photovoltaic power generation model is:

[0027]

[0028] Among them, P PV is the output power of the photovoltaic panel, G t is the solar irradiance, G STC is the irradiance under standard test conditions, λ is the temperature coefficient, and T STC is the surface temperature of the photovoltaic panel under standard test conditions, and P STC is the output power of the photovoltaic panel under standard measurement;

[0029] The CCHP system includes a hydrogen-doped gas turbine, a ground-source heat pump, a heat recovery device and an absorption chiller. The CCHP model is:

[0030]

[0031] Among them, V NG is the instantaneous consumption volume of natural gas, η GT is the output efficiency of the gas turbine, K NG is the power generation per cubic meter of natural gas, 9.7 kWh / m 3 , V H2 is the instantaneous consumption volume of hydrogen, K H2 is the power generation per cubic meter of hydrogen, 1.79 kWh / m 3 , V H2 : V NG ≤30%;

[0032] Q hp = E hp COP hp ;

[0033] Among them, E hp is the input electric power of the ground-source heat pump, Q hp is the output heat (cold) power of the ground-source heat pump, and COP hp is the conversion coefficient of the ground-source heat pump;

[0034] Q rec = 0.85Q GT ;

[0035] Among them, Q rec is the output heat power of the heat recovery device, and Q GT is the output heat power of the gas turbine;

[0036] Q a = Q rec COPa ;

[0037] Among them, Q a is the cooling power output by the absorption chiller, and COP a is the refrigeration efficiency;

[0038] The storage system includes a battery, a heat storage device, and a hydrogen storage device. The storage system model is:

[0039]

[0040] Among them, SOC(t + 1) and SOC(t) are the state of charge of the battery at times t + 1 and t, and are the charge and discharge powers of the battery, respectively, and are the charge and discharge efficiencies of the battery, respectively;

[0041]

[0042] Among them, S HS (t + 1) and S HS (t) are the capacities of the heat storage device at times t + 1 and t, and are the heat charging and discharging powers of the heat storage device, respectively, and are the heat charging and discharging efficiencies of the heat storage device, respectively;

[0043] V H (t + 1) = V H (t) + V in (t) - V out (t);

[0044] Among them, V H (t + 1) and V H (t) are the hydrogen capacities of the hydrogen storage device at times t + 1 and t, V in (t) and V out (t) are the volume of hydrogen input and the volume of hydrogen output by the hydrogen storage device, respectively.

[0045] Furthermore, the objective function model is:

[0046] F = min(C cap + C o&m + C en + C grid + C CE );

[0047] In the formula, C cap is the investment cost, C o&m is the operation and maintenance cost, C enis the energy cost, C grid is the grid interaction cost, and C CE is the carbon emission cost;

[0048] Among them, the investment cost model of the energy storage system is:

[0049]

[0050] Among them, K1 and K2 are the total amounts of equipment optimized according to the number and capacity of equipment; C k is the investment cost per unit equipment or unit power; r is the actual rate of return, m is the expected service life of equipment k, and cap k is the capacity of equipment k;

[0051] The operation and maintenance cost model of the energy storage system is:

[0052]

[0053] Among them, Γ d is the total number of days of designed operation; k is the total number of equipment; ξ k is the maintenance cost per kWh of equipment k, is the output power of equipment k;

[0054] The energy cost model of the energy storage system is:

[0055]

[0056] Among them, λ ng is the unit price of natural gas;

[0057] The grid interaction cost model of the energy storage system is:

[0058]

[0059] Among them, λ grid is the unit power purchase price;

[0060] The carbon emission cost model of the energy storage system is:

[0061] C CE = κG ACE ;

[0062] Among them, κ is the treatment price per kg of carbon dioxide;

[0063]

[0064] Among them, ε ng and ε ng are the carbon emission coefficients of natural gas and power purchase.

[0065] Further, the constraint condition model includes at least one of the following constraint conditions:

[0066] (1) Overall electrical balance, thermal balance, and cold balance constraints of devices in the intelligent regulation system:

[0067]

[0068] (2) Upper and lower limit constraints of devices in the intelligent regulation system:

[0069] E K,min ≤E K ≤E K,max ;

[0070] (3) Operation constraints of devices in the intelligent regulation system:

[0071]

[0072] where SOC is the state of charge or remaining capacity of the energy storage device, and are the charging / discharging (thermal) powers of the energy storage device respectively;

[0073] (4) Ramp constraints of devices in the intelligent regulation system:

[0074]

[0075] where and are the upper and lower limits of the ramp of a certain device respectively.

[0076] Further, the device energy supply strategy includes:

[0077] Step A: Prioritize the use of photovoltaic units and wind turbine generators to maximize the proportion of renewable energy in the system energy supply;

[0078] Step B: Use the hydrogen - blended gas turbine to dynamically allocate the energy supply capacity according to the system's cooling and heating load demands to ensure the stable operation of the system;

[0079] Step C: When the renewable energy supply is insufficient, select the battery to discharge and supplement the energy supply according to the remaining capacity of the battery; when the renewable energy supply is excessive, store the excess electricity in the battery for subsequent use;

[0080] Step D: If the system still cannot meet the load demand after the above steps, connect to the external large - scale power grid to purchase electricity to meet the remaining load demand and ensure continuous and stable power supply of the system.

[0081] The mathematical model for capacity configuration optimization includes:

[0082] A data input module for receiving electricity price and gas price information, actual user demand data, real-time weather conditions, economic parameter settings, and equipment efficiency data;

[0083] An optimization processing module, including an initialization step, which includes setting an objective function, designing constraint conditions, and setting operating variables, and setting a mixed-integer linear programming problem during the optimization process, and solving it through a solver to obtain the optimal capacity configuration of the energy supply of each device;

[0084] A result output module for outputting the capacity configuration result and the optimal solution of the objective function;

[0085] A data processing module for calculating and outputting the economic cost and environmental cost of the output capacity configuration plan. Another object of the present invention is to propose a capacity configuration optimization method for an electric-thermal-cooling-hydrogen multi-component hybrid energy storage system combined with hydrogen-doped combustion, which is applied to the multi-component hybrid energy storage system combined with hydrogen-doped combustion as described above, including:

[0086] S1: Establish equipment models for energy conversion and storage in each link of electricity, heat, cooling, and hydrogen in the intelligent control system;

[0087] S2: Set an objective function including economic cost and environmental cost parameters, and construct a comprehensive total cost model;

[0088] S3: Set constraint conditions according to the actual operating conditions of the intelligent control system;

[0089] S4: Based on the equipment models, objective functions, and constraint conditions established in steps S1 to S3, construct a mathematical model for capacity configuration optimization;

[0090] S5: Adjust the energy supply strategy of the equipment in the intelligent control system;

[0091] S6: The optimization processing module of the mathematical model for capacity configuration optimization transforms the capacity configuration optimization problem into a mixed-integer linear programming problem, and uses a solver to solve it to obtain the optimal capacity configuration of each equipment link;

[0092] S7: The mathematical model for capacity configuration optimization outputs the capacity configuration result and the optimal solution of the objective function, and outputs the economic cost and environmental cost of the system.

[0093] The present invention provides a multi - energy hybrid energy storage system combined with hydrogen - doped combustion and an optimization method for its capacity configuration. By adjusting the proportion of hydrogen - doped combustion, the generated hydrogen enters the gas turbine for combustion, replacing part of the natural gas consumption. A ground - source heat pump device is added to increase and improve the conversion links among electricity, heat, and hydrogen. Meanwhile, considering economic and environmental objectives, according to the operation of the proposed integrated energy system and the energy supply strategies of each part, an optimization method for the capacity configuration of the electricity - heat - cold - hydrogen multi - energy hybrid energy storage system combined with hydrogen - doped combustion is established, enhancing the economy and environmental performance of the system and improving the multi - energy complementarity and conversion ability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0094] The attached drawings that form a part of the present invention are used to provide a further understanding of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0095] Figure 1 is the structural block diagram of the multi - energy hybrid energy storage system combined with hydrogen - doped combustion of the present invention;

[0096] Figure 2 is the electricity - heat - hydrogen energy flow conversion diagram of the multi - energy hybrid energy storage system combined with hydrogen - doped combustion of the present invention;

[0097] Figure 3 is the flow chart of the optimization method for the capacity configuration of the multi - energy hybrid energy storage system combined with hydrogen - doped combustion of the present invention;

[0098] Figure 4 is the annual meteorological change trend chart disclosed by the present invention;

[0099] Figure 5 is the annual energy supply time sequence chart of each device disclosed by the present invention;

[0100] Figure 6 is the logic block diagram of the optimization method for the capacity configuration of the multi - energy hybrid energy storage system combined with hydrogen - doped combustion described in the embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0101] In order to make the technical means, objectives, and effects of the present invention easy to understand, the embodiments of the present invention will be described in detail below with reference to specific drawings.

[0102] It should be noted that all the terms indicating direction and position in the present invention, such as "upper", "lower", "left", "right", "front", "rear", "vertical", "horizontal", "inner", "outer", "top", "bottom", "lateral", "longitudinal", "center", etc., are only used to explain the relative positional relationship and connection situation between components in a certain specific state (as shown in the drawings), and are only for the convenience of describing the present invention, rather than requiring the present invention to be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the present invention. In addition, the descriptions involving "first", "second", etc. in the present invention are only for descriptive purposes, and should not be construed as indicating or implying their relative importance or implicitly specifying the quantity of the indicated technical features.

[0103] In the description of the present invention, unless otherwise clearly specified and defined, the terms "mounted", "connected", and "coupled" shall be construed in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection; it may be directly connected, or indirectly connected through an intermediate medium, and it may be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0104] In the description of this specification, the descriptions with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic descriptions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0105] Such as Figures 1 to 6As shown in the figure, the present application discloses a multi - hybrid energy storage system combined with hydrogen - doped combustion, which includes a power system for providing electricity, a thermal system and a cold - air system for distributing heating and cooling loads. The power system includes a wind turbine generator for converting wind energy into electricity, a photovoltaic unit for converting light energy into electricity, and an external power grid. It also includes a gas turbine, an external power grid, a ground - source heat pump, an electrolyzer and a storage battery. The thermal system includes a gas turbine, a ground - source heat pump, a heat recovery device and a heat storage device. The cold - air system includes an absorption refrigeration unit. The ground - source heat pump can switch between heating / cooling modes according to different heating and cooling load demands. The hydrogen - doped gas turbine can burn hydrogen and natural gas simultaneously according to a preset ratio, and output electric energy and heat energy. The multi - hybrid energy system adopts the combination of hydrogen - doped combustion and ground - source heat pump to flexibly convert three different energy forms: hydrogen - electricity, hydrogen - heat, and electricity - heat. Through the storage system (storage battery, hydrogen storage and heat storage devices) and the actual power generation of renewable energy, when wind power and photovoltaic power are sufficient to meet the user load demand, the energy is stored, and when it is difficult to meet the user demand, it is released to quantitatively regulate the input and output energy.

[0106] The multi - hybrid energy storage system combined with hydrogen - doped combustion disclosed in the present application is specifically an electricity - heat - cold - hydrogen multi - hybrid energy storage system combined with hydrogen - doped combustion. This system integrates a power system, a thermal system, a cold - air system and an energy storage system. The power system includes two renewable energy sources, photovoltaic and wind power, a gas turbine, an external power grid, and an electrolyzer. The electrolyzer is used to provide hydrogen for the gas turbine, and hydrogen and natural gas in the gas turbine burn simultaneously according to a preset ratio. The thermal system includes a ground - source heat pump and a heat recovery device, which are responsible for distributing heating and cooling loads. The absorption refrigeration unit is for the cold - air system to provide cold air. The heat recovery device is coupled with the gas turbine, and the heat energy generated during the hydrogen - doped combustion process of the gas turbine is stored in the heat recovery device. The electric energy generated by the gas turbine is output to the external power grid and the ground - source heat pump. The ground - source heat pump is used to provide heating and cooling loads.

[0107] The heat source output end of the heat recovery device is connected to the heat supply end and the heat source input end of the absorption refrigeration unit.

[0108] It also includes an intelligent control system, which is used to regulate the operation of the power system, the thermal system and the cold - air system according to the heating and cooling load demands and the power generation situation, so as to realize the conversion and output of four energy forms: hydrogen - electricity - heat - cold.

[0109] The multi - hybrid energy storage system combined with hydrogen - doped combustion described in this application. When the power generation from renewable energy sources (such as wind energy and solar energy) is sufficient, the intelligent control system will preferentially utilize these clean energies to meet the electricity demand of users. The remaining electric energy is then converted into hydrogen through an electrolyzer for storage. At the same time, a ground - source heat pump is used for the conversion of thermal energy and cold energy to ensure that the energy demand under different seasons and load conditions is met. When the user load demand increases or the supply of renewable energy is insufficient, the hydrogen - doped gas turbine will start and burn hydrogen and natural gas simultaneously according to a set ratio to provide electric energy and thermal energy. The ground - source heat pump can switch between heating / cooling modes according to different hot and cold load demands, effectively regulating the hot and cold loads of the multi - hybrid energy storage system. Through the flexible allocation of the storage system, the storage system stores energy when the renewable energy generation is sufficient and releases it during peak demand periods, achieving the efficient inter - conversion and dynamic balance of electricity, hydrogen, and heat, ensuring the stable operation of the multi - hybrid energy storage system under different loads and meteorological conditions, thereby realizing the flexible conversion and balance of the three energy forms of electricity, hydrogen, and heat. Preferably, the storage system includes a storage battery and a heat storage device. The storage battery is connected to the wind turbine generator set. The heat source input end of the heat storage device is connected to the ground - source heat pump and the heat recovery device, and the output end of the heat storage device is connected to the heating terminal. The intelligent control system also comprehensively regulates the operation of the power system, the thermal system, and the air - conditioning system according to the storage capacity of the storage system.

[0110] The multi - energy hybrid energy storage system combined with hydrogen - enriched combustion significantly improves the energy utilization efficiency and flexibility of the multi - energy hybrid energy storage system on the basis of the original electricity - heat and electricity - hydrogen conversion by introducing a hydrogen - enriched gas turbine and a ground - source heat pump. The hydrogen - enriched gas turbine can burn hydrogen and natural gas simultaneously and directly output electric energy and heat energy, avoiding energy losses in the traditional energy conversion process and improving the overall energy utilization efficiency. The ground - source heat pump uses electric energy to achieve the conversion of heat energy and cold energy, replacing the traditional boiler, further enhancing the environmental protection and energy efficiency of the multi - energy hybrid energy storage system. The introduction of the storage system enables the multi - energy hybrid energy storage system to flexibly store and release energy according to the actual power generation of renewable energy, effectively balancing the load of the multi - energy hybrid energy storage system and increasing the consumption rate and utilization rate of renewable energy. The multi - energy hybrid energy storage system combined with hydrogen - enriched combustion described in this application constructs a more perfect and efficient electricity - hydrogen - heat conversion path through the combination of hydrogen - enriched combustion and the ground - source heat pump, realizing the flexible conversion and inter - conversion of three different energy forms of electricity, hydrogen, and heat, enhancing the stability and response speed of the multi - energy hybrid energy storage system. This multi - energy hybrid energy storage system not only improves the energy utilization efficiency but also enhances the flexibility and stability of the multi - energy hybrid energy storage system, contributing to reducing the dependence on traditional fossil fuels, reducing carbon emissions, and achieving environmental protection and sustainable development. At the same time, through the synergistic effect of the storage system and the energy conversion device, the intelligent control system can accurately and efficiently respond to user load demands, shaving peaks and filling valleys, further improving the overall performance and operation efficiency of the multi - energy hybrid energy storage system.

[0111] As a preferred example of the present application, for the multi - hybrid energy storage system combined with hydrogen - enriched combustion, its intelligent control system includes equipment models such as a power system (wind turbine generator sets, photovoltaic generator sets, external power grid, gas turbine, electrolyzer), a thermal system (ground - source heat pump, heat recovery device), and a cold - air system (absorption refrigeration unit), and also includes a mathematical model for capacity configuration optimization, an objective function model, and a constraint condition model. Among them, the objective function model establishes an objective function by including parameters of economic cost and environmental cost. For example, taking the sum of the economic cost and environmental cost of the intelligent control system as the lowest as the objective function, the economic cost includes equipment investment cost, operation and maintenance cost, and energy purchase cost, etc. The environmental cost considers the carbon emissions and other environmental pollutant emissions in the energy conversion process. The intelligent control system combines the actual operating conditions and sets a constraint condition model including constraint conditions such as equipment capacity limits and / or energy conversion efficiency limits and / or energy balance constraints and / or charge - discharge limits of energy storage devices. Especially for the operation of the hydrogen - enriched gas turbine, it sets the mixing ratio limit of hydrogen and natural gas and the combustion efficiency constraint. Based on the above - mentioned equipment model, objective function, and constraint conditions, a mathematical model for capacity configuration optimization is established. The intelligent control system outputs the capacity configuration result and the optimization objective result according to the objective function and the constraint condition model, and can realize the flexible conversion between three different energy forms of electricity, heat (cold), and hydrogen. Preferably, the intelligent control system proposes a mixed - integer linear programming problem based on the equipment model, the mathematical model for capacity configuration optimization, constraint conditions, initial data, operation strategies, and the energy supply strategies of each part of the equipment, and solves the mathematical model through an intelligent algorithm to output the capacity configuration result and the optimization objective result of the intelligent control system. Among them, the operation strategies and the energy supply strategies of each part of the equipment include equipment scheduling plans, energy conversion paths, and charge - discharge plans of energy storage devices under different load demands and different renewable energy power generation situations. Based on the energy balance relationship, the conversion between four different energy forms of electricity, heat, cold, and hydrogen is realized, and the capacity configuration result and the optimization objective result of the intelligent control system are output by solving the mathematical model through an intelligent algorithm.

[0112] The working principle of the multi - energy hybrid energy storage system combined with hydrogen - enriched combustion is to build an intelligent control system, including equipment models such as renewable energy sources, hydrogen - enriched gas turbines, ground - source heat pumps, and storage systems, to achieve flexible conversion between three different energy forms: electricity, heat (cooling), and hydrogen. First, based on the characteristics and operating parameters of various equipment, the intelligent control system establishes a detailed system framework, and comprehensively considers economic costs and environmental costs to set an optimized objective function aiming to minimize costs and maximize environmental benefits. On this basis, by analyzing various constraints during the operation of the intelligent control system, such as equipment capacity limitations and energy conversion efficiencies, a mathematical model for optimizing capacity configuration is established. Subsequently, using this model, the intelligent control system can accurately calculate the optimal configuration plan for each device and formulate corresponding operation strategies and energy supply plans for each part. Throughout the process, the intelligent control system follows the principle of energy balance to ensure flexible conversion and complementarity between the three energy forms of electricity, heat (cooling), and hydrogen to meet the diverse needs of users at different times. This mechanism effectively enhances the overall stability and response ability of the multi - energy hybrid energy storage system.

[0113] Through the application of hydrogen - enriched combustion technology and refined capacity configuration optimization, the intelligent control system can achieve efficient utilization of equipment, reduce operating costs, and thus improve the overall economic efficiency. Considering the environmental costs in the objective function, the intelligent control system pays more attention to environmental protection during operation, helps reduce carbon emissions, and promotes green development. It can adjust the energy supply and energy storage strategies of each device in real - time according to user needs and the actual power generation of renewable energy sources to ensure stable supply and efficient conversion of the three energy forms of electricity, heat (cooling), and hydrogen.

[0114] As a preferred example of this application, the equipment model includes a wind power generation model, a photovoltaic power generation model, a CCHP model, and a storage system model, where:

[0115] Wind power generation model:

[0116]

[0117] Among them, v t is the instantaneous wind speed, v in , v r and v out are the cut - in wind speed, rated wind speed, and cut - out wind speed respectively, and P r is the rated power of the fan;

[0118] Photovoltaic power generation model:

[0119]

[0120] Among them, P PVis the output power of the photovoltaic panel, G t is the solar irradiance, G STC is the irradiance under standard test conditions, λ is the temperature coefficient, T STC is the surface temperature of the photovoltaic panel under standard test conditions, P STC is the output power of the photovoltaic panel under standard measurement;

[0121] The CCHP system model composed of a hydrogen - doped gas turbine, a ground - source heat pump, a heat recovery device, and an absorption chiller is:

[0122]

[0123] where, V NG is the instantaneous consumption volume of natural gas, η GT is the output efficiency of the gas turbine, K NG is the power generation per cubic meter of natural gas, 9.7 kWh / m 3 , V H2 is the instantaneous consumption volume of hydrogen, K H2 is the power generation per cubic meter of hydrogen, 1.79 kWh / m 3 ;

[0124] Q hp = E hp COP hp ;

[0125] where, E hp is the input electric power of the ground - source heat pump, Q hp is the output heat (cold) power of the ground - source heat pump, COP hp is the conversion coefficient of the ground - source heat pump;

[0126] Q rec = 0.85Q GT ;

[0127] where, Q rec is the output heat power of the heat recovery device, Q GT is the output heat power of the gas turbine;

[0128] Q a = Q rec COP a ;

[0129] where, Q a is the output cold power of the absorption chiller, COP a is the refrigeration efficiency;

[0130] The storage system includes a battery, a heat storage device, and a hydrogen storage device, and its model is:

[0131]

[0132] Among them, SOC(t + 1) and SOC(t) are the state of charge of the battery at times t + 1 and t, and are the charging and discharging powers of the battery respectively, and are the charging and discharging efficiencies of the battery respectively;

[0133]

[0134] Among them, S HS (t + 1) and S HS (t) are the capacities of the heat storage device at times t + 1 and t, and are the heat charging and discharging powers of the heat storage device respectively, and are the heat charging and discharging efficiencies of the heat storage device respectively;

[0135] V H (t + 1) = V H (t) + V in (t) - V out (t);

[0136] Among them, V H (t + 1) and V H (t) are the hydrogen capacities of the hydrogen storage device at times t + 1 and t, V in (t) and V out (t) are the volume of hydrogen input to and the volume of hydrogen output from the hydrogen storage device respectively.

[0137] In this application, by constructing an equipment model including a wind power generation module, a photovoltaic power generation module, CCHP (Combined Cooling, Heating and Power), and a storage system, the wind power generation module, the photovoltaic power generation module, the CCHP system, and the energy storage module are skillfully integrated. By introducing the wind power generation and photovoltaic power generation modules, the system significantly reduces the dependence on traditional fossil fuels, effectively reduces greenhouse gas emissions and environmental pollution, and enhances the green sustainability of the energy system. Combining the hydrogen - doped gas turbine, the ground - source heat pump, the heat recovery device, and the absorption chiller integrated with the CCHP system and the storage system, through precisely regulating the consumption ratio of natural gas and hydrogen, the input electric power of the ground - source heat pump, and the heat recovery and refrigeration efficiency, the multi - level utilization and efficient conversion of energy are realized. By optimizing the parameter settings and cooperative working modes of each module, the overall energy utilization efficiency of the multi - element hybrid energy storage system is significantly improved, not only reducing the operating cost, but also enhancing the stability and reliability of the energy supply. In addition, this solution can also flexibly adjust the energy input ratio and output mode according to the energy resource conditions and demand changes in different regions, ensuring the personalization and intelligentization of the energy supply.

[0138] As a preferred example of this application, the objective function is:

[0139] F = min(C cap + C o&m + C en + C grid + C CE );

[0140] In the formula, C cap is the investment cost, C o&m is the operation and maintenance cost, C en is the energy cost, C grid is the grid interaction cost, and C CE is the carbon emission cost;

[0141] Among them, the investment cost model of the energy storage system is:

[0142]

[0143] Among them, K1 and K2 are the total equipment amounts optimized according to the equipment quantity and capacity; C k is the investment cost per unit equipment or unit power; r is the actual rate of return, m is the expected service life of equipment k, and cap k is the capacity of equipment k;

[0144] The operation and maintenance cost model of the energy storage system is:

[0145]

[0146] Among them, Γ d is the total number of days of designed operation; k is the total number of equipment; ξ k is the maintenance cost per kWh of equipment k, is the output power of equipment k;

[0147] The energy cost model of the energy storage system is:

[0148]

[0149] Among them, λ ng is the unit price of natural gas;

[0150] The grid interaction cost model of the energy storage system is:

[0151]

[0152] Among them, λ grid is the unit power purchase price;

[0153] The carbon emission cost model of the energy storage system is:

[0154] CCE = κG ACE ;

[0155] where κ is the treatment price per kg of carbon dioxide;

[0156]

[0157] where ε ng and ε ng are the carbon emission coefficients of natural gas and purchased electricity.

[0158] Based on the innovative combination of an electro-thermal-cooling-hydrogen multi-energy hybrid energy storage system with hydrogen-doped combustion, this application also constructs a comprehensive total cost model. This model comprehensively covers multiple dimensions such as investment costs, operation and maintenance costs, energy costs, grid interaction costs, and carbon emission costs. It comprehensively considers the economic and environmental costs of the multi-energy hybrid energy storage system. Through an optimization algorithm, it reasonably allocates the energy supply strategies of each device in the multi-energy hybrid energy storage system and the capacity configuration of each energy storage link, and reasonably configures the capacity of each energy storage link to ensure that the entire multi-energy hybrid energy storage system meets the energy demand while achieving the goals of the lowest total cost and the least carbon emissions, ensuring that the multi-energy hybrid energy storage system reaches the optimal state in terms of economy and environmental protection. That is, through the introduction of hydrogen-doped combustion technology, the integration of ground-source heat pumps, and the establishment of a comprehensive cost model, the present invention realizes the perfect combination of multi-energy complementarity, efficient conversion, and cost optimization. Through the establishment of the comprehensive cost model, while the multi-energy hybrid energy storage system pursues economic benefits, it can also fully consider the requirements of environmental protection, achieving a win-win situation of economic and environmental benefits.

[0159] As a preferred example of this application, the multi-energy hybrid energy storage system combined with hydrogen-doped combustion has constraint conditions including at least one of the following:

[0160] (1) The operation of the multi-energy hybrid energy storage system needs to satisfy the overall electrical balance, thermal balance, and cooling balance constraints:

[0161]

[0162] where K e , K h , and K c are the equipment numbers of the power generation, heat supply, and refrigeration capacities in the system respectively, are the electrical, heat supply, and refrigeration loads respectively;

[0163] (2) The operation of the multi-energy hybrid energy storage system needs to satisfy the upper and lower limit constraints of each device:

[0164] E K,min ≤ E K ≤ E K,max ;

[0165] E K refers to the energy state or energy storage level of a certain device in the multi - component hybrid energy storage system;

[0166] (3) The operation of the multi - component hybrid energy storage system needs to satisfy the operation constraints of each device in the storage system:

[0167]

[0168] where SOC is the state of charge or remaining capacity of the energy storage device, and are the charge - discharge (thermal) powers of the energy storage device respectively;

[0169] (4) The operation of the multi - component hybrid energy storage system needs to satisfy other constraints such as the ramp - rate constraints of each device:

[0170]

[0171] where and are the upper and lower limits of the ramp - up of a certain device respectively.

[0172] The multi - component hybrid energy storage system disclosed in this application, through a series of constraint conditions, ensures the efficient, stable and reliable operation of the intelligent control system, and realizes the fine control of each device. It first ensures that the entire multi - component hybrid energy storage system satisfies the basic constraints of overall electrical balance, thermal balance and cold balance, which is the basis for the stable operation of the multi - component hybrid energy storage system; on this basis, the intelligent control system further considers the upper and lower limit constraints of each device, that is, the output power of the device needs to be within the specified range to avoid overload or under - load; at the same time, the intelligent control system also strictly manages the operation of the energy storage device to ensure that the power of the energy storage device fluctuates between the preset minimum and maximum values, and the initial and final powers are consistent to maintain the continuous and stable operation of the multi - component hybrid energy storage system; in addition, the intelligent control system also introduces ramp - rate constraints and penalty constraints to cope with the rapid change of the charge - discharge rate of the energy storage device, so that it can adapt to the rapid change of the load without causing violent fluctuations in the multi - component hybrid energy storage system, and ensure the response speed and stability of the multi - component hybrid energy storage system. Through these comprehensive constraint conditions, the intelligent control system can dynamically adjust the output power of each device, meet the overall load demand, and realize the efficient utilization of energy. This multi - component hybrid energy storage system provides a new solution for the field of integrated energy management through intelligent management and control, as well as the innovative application of hydrogen - doped combustion technology, demonstrating its significant technical advantages and broad application prospects.

[0173] As a preferred example of this application, the device energy supply strategy includes:

[0174] Step A: Prioritize the use of photovoltaic units and wind turbine generators to maximize the proportion of renewable energy in the energy supply of the multi - energy hybrid energy storage system;

[0175] Step B: Utilize a hydrogen - blended gas turbine to dynamically allocate energy supply capacity according to the cooling and heating load requirements of the multi - energy hybrid energy storage system to ensure the stable operation of the multi - energy hybrid energy storage system;

[0176] Step C: When the renewable energy supply is insufficient, select the battery discharge to supplement the energy supply according to the remaining capacity of the battery; when the renewable energy supply is excessive, store the excess electricity in the battery for subsequent use;

[0177] Step D: If the multi - energy hybrid energy storage system still cannot meet the load demand after the above steps, connect to the external large - scale power grid to purchase electricity from the external large - scale power grid to meet the remaining load demand and ensure continuous and stable power supply of the multi - energy hybrid energy storage system.

[0178] The multi - energy hybrid energy storage system combined with hydrogen - blended combustion described in this application realizes the maximum utilization of renewable energy and the effective management of the load of the multi - energy hybrid energy storage system through a series of priority settings and dynamic adjustment strategies. First, the multi - energy hybrid energy storage system preferentially uses the renewable energy generated by photovoltaic units and wind turbine generators, aiming to increase the proportion of these clean energies in the overall energy supply, thereby enhancing the consumption capacity of renewable energy; when the total energy supply from photovoltaic and wind power is insufficient to meet the cooling and heating load requirements of the multi - energy hybrid energy storage system, the hydrogen - blended gas turbine will adjust according to the real - time load changes to ensure timely meeting of the energy supply demand; if the total energy supply from renewable energy and the hydrogen - blended gas turbine within the multi - energy hybrid energy storage system is still lower than the load demand, the multi - energy hybrid energy storage system will automatically evaluate the remaining capacity of the battery and selectively release the energy stored in the battery to make up for the shortage, while when the energy supply exceeds the load demand, the excess electricity will be stored in the battery for subsequent use; finally, if the multi - energy hybrid energy storage system still cannot meet the load demand after all the above adjustments, it will connect to the external large - scale power grid and purchase electricity from the large - scale power grid in a timely manner to ensure continuous and stable power supply of the multi - energy hybrid energy storage system under any circumstances. This solution not only improves the comprehensive efficiency of the energy system through intelligent adjustment and multi - energy complementarity, but also provides strong support for realizing a green, low - carbon, safe and efficient energy supply system, promoting the wide application of renewable energy and future sustainable development.

[0179] As a preferred example of this application, the mathematical model for optimizing capacity configuration can perform data input, optimization, output, and data processing. The input data includes electricity price and gas price, user demand and weather conditions, economic parameters, and equipment efficiency. The optimization process includes initialization, and the initialization process includes setting the objective function, designing constraints, and setting operating variables. And during the optimization process, a MILP problem is proposed and solved by a solver (Gurobi commercial solver) to obtain the optimal configuration of each equipment link. The output data includes the capacity configuration result and the optimal result of the objective function. The model is solved to obtain the optimized capacity configuration result, and the economic cost and environmental cost of the multi - energy hybrid energy storage system are output. Among them, the mathematical model for optimizing capacity configuration can:

[0180] Obtain the initial electricity, heat, and cooling load data of the park;

[0181] Obtain the annual meteorological historical data, time - of - use electricity price, and gas price data;

[0182] Obtain basic parameters such as equipment operation efficiency, rated power, start - stop time, etc.

[0183] In the example of this application, the solver is the Gurobi commercial solver used in Matlab.

[0184] The multi - energy hybrid energy storage system with hydrogen - blended combustion disclosed in this application, based on the equipment model, objective function, and constraint conditions, establishes a mathematical model for optimizing capacity configuration. It not only integrates the initial electricity, heat, and cooling load data of the park, but also incorporates the annual meteorological historical data, time - of - use electricity price and gas price information. Based on the existing annual light intensity and wind speed data, it clusters into typical days through the K - means algorithm, as well as key parameters such as equipment operation efficiency, rated power, start - stop time, etc. In the optimization process, the model first clarifies the optimization objective through the initialization step, that is, to minimize the economic cost and environmental cost of the system, and accordingly designs a series of constraints to ensure the stability and reliability of the operation of the multi - energy hybrid energy storage system. Subsequently, the intelligent control system transforms the complex optimization problem in the mathematical model of capacity configuration optimization into a mixed - integer linear programming (MILP) problem and uses the Gurobi commercial solver in the Matlab environment for efficient solution. Gurobi is known for its powerful computing power and efficient algorithm, and can quickly find the optimal configuration scheme for each equipment link, thereby outputting detailed data including the capacity configuration result and the optimal value of the objective function, providing strong support for the economic and environmental friendliness of the multi - energy hybrid energy storage system.

[0185] Through this process, the intelligent control system can output detailed data including the capacity configuration result and the optimal value of the objective function, ensuring the flexible conversion and efficient utilization of electricity, heat, cooling, and hydrogen, so as to meet the energy needs of the park.

[0186] As a preferred example of the present application, when the hydrogen-doped gas turbine burns hydrogen and natural gas simultaneously to output electric energy and heat energy, the hydrogen doping ratio is not more than 30%. That is, in the CCHP system model, V H2 :V NG ≤ 30%. By setting the limit that the mixing ratio of hydrogen and natural gas in the hydrogen-doped gas turbine is not more than 30%, the optimal combustion efficiency and energy conversion rate can be achieved. This not only takes into account the high calorific value and clean combustion characteristics of hydrogen, but also takes into account the wide availability and cost-effectiveness of natural gas, thus maximizing the energy utilization efficiency and the flexibility of system output while ensuring the stable operation of the multi-source hybrid energy storage system.

[0187] The present application also discloses a method for optimizing the capacity configuration of a multi-source hybrid energy storage system combined with hydrogen-doped combustion, which is used for the multi-source hybrid energy storage system combined with hydrogen-doped combustion described in the above embodiments, and includes:

[0188] S1: Establish equipment models for energy conversion and storage in each link of electricity, heat, cold, and hydrogen in the intelligent control system;

[0189] S2: Set an objective function including economic cost and environmental cost parameters, and construct a comprehensive total cost model;

[0190] S3: Set constraint conditions according to the actual operating conditions of the intelligent control system;

[0191] S4: Based on the equipment models, objective function, and constraint conditions established in steps S1 to S3, construct a mathematical model for optimizing capacity configuration;

[0192] S5: Adjust the equipment energy supply strategy of the intelligent control system;

[0193] S6: The optimization processing module of the mathematical model for optimizing capacity configuration converts the capacity configuration optimization problem into a mixed-integer linear programming problem, and uses a solver to solve it to obtain the optimal capacity configuration of each equipment link;

[0194] S7: The mathematical model for optimizing capacity configuration outputs the capacity configuration result and the optimal solution of the objective function, and outputs the economic cost and environmental cost of the multi-source hybrid energy storage system.

[0195] The capacity configuration optimization method of the multi - energy hybrid energy storage system combined with hydrogen - enriched combustion disclosed in the present invention includes: clustering into typical days through the K - means algorithm based on the existing annual light intensity and wind speed data; building a distributed energy system with a ground - source heat pump and hydrogen - enriched combustion to provide power, heating, and cooling loads for users; selecting two objectives of economy and carbon emissions, configuring comprehensive constraint conditions, converting carbon emissions into a part of the economic objective function, and configuring the capacities of each link to achieve the optimal economy; using the integer linear programming method to determine the global optimal configuration plan according to the optimized configuration plan. The present invention can solve the problem that the existing technology lacks a reasonable energy storage system optimization configuration plan, which is not conducive to the economy and environmental protection of the multi - energy hybrid energy storage system, saves fuel, makes full use of renewable energy, and realizes the flexible conversion and stable output between electricity - heat or cold - hydrogen.

[0196] The capacity configuration optimization method of the multi - energy hybrid energy storage system combined with hydrogen - enriched combustion described in this application, through the collaborative utilization of different energy forms, first, the intelligent control system establishes equipment models for energy conversion and storage in each link of electricity, heat, cold, and hydrogen, which can comprehensively reflect the characteristics of various energy sources and the relationships between them; then, considering economic and environmental costs, the intelligent control system formulates a comprehensive total cost model to balance economic benefits and environmental impacts during the optimization process; by setting a series of constraint conditions, it ensures that the multi - energy hybrid energy storage system meets the requirements of safety and stability during operation; subsequently, using the initial load data, historical meteorological data, time - of - use electricity price, and equipment operation parameters of the park, a mathematical model is established to optimize the capacity configuration; this mathematical model can reasonably allocate the energy supply capabilities of various equipment, especially during the hydrogen - enriched combustion process, by adjusting the hydrogen incorporation ratio, reducing natural gas consumption, and at the same time combining ground - source heat pump technology to improve the energy conversion efficiency between electricity, heat, and hydrogen; finally, through the calculation of the solver, the intelligent control system can output the optimal configuration plan for each equipment, providing a scientific basis for achieving efficient, economic, and environmental energy utilization.

[0197] Through the above optimization method, the intelligent control system can flexibly adjust the hydrogen blending ratio, effectively reduce the consumption of traditional natural gas, reduce carbon emissions, meet the goals of sustainable development, improve the environmental friendliness of the multi - energy hybrid energy storage system, and make the conversion between electricity, heat, and hydrogen more efficient with the addition of a ground - source heat pump, enhancing the multi - energy complementarity ability of the multi - energy hybrid energy storage system, enabling flexible adjustment under different load demands to ensure efficient energy utilization. In addition, the capacity configuration optimization scheme of the multi - energy hybrid energy storage system makes the operation of each device more coordinated, improves the overall economy, and reduces the operating cost. The research results show that the multi - energy hybrid energy storage system has great potential in improving the efficiency and stability of the new power system, can meet the needs of future energy structure transformation, provides strong support for realizing low - carbon and intelligent energy management, and further promotes the application and development of clean energy.

[0198] Compared with the prior art, the present invention proposes a multi - energy hybrid energy storage system combined with hydrogen - blended combustion and its capacity configuration optimization method, which has the following beneficial effects:

[0199] 1. The present invention provides a multi - energy hybrid energy storage system combined with hydrogen - blended combustion. By adjusting the hydrogen - blending combustion ratio, the generated hydrogen enters the gas turbine for combustion, replacing part of the natural gas consumption; adding a ground - source heat pump device increases and improves the conversion link between electricity, heat, and hydrogen. Considering economic and environmental goals, according to the operation of the proposed intelligent control system and the energy supply strategies of each part, a capacity configuration optimization method for an electricity - heat - cold - hydrogen multi - energy hybrid energy storage system combined with hydrogen - blended combustion is established, enhancing the economy and environmental friendliness of the multi - energy hybrid energy storage system and improving the multi - energy complementarity and conversion ability of the multi - energy hybrid energy storage system.

[0200] 2. The present invention proposes a flexible capacity configuration scheme that combines hydrogen - blended combustion with a ground - source heat pump. In this way, compared with traditional distributed systems for electricity - heat and electricity - hydrogen conversion, a more flexible and efficient hydrogen - electricity - heat conversion path is constructed. The research results show that the electricity - heat - hydrogen coupling system of multi - hybrid energy storage has flexibility and stability and has great potential in improving the efficiency and stability of the new power system.

[0201] As a specific example of this application, in the photovoltaic power generation model, λ is the temperature coefficient - 0.0047, and T STC is the surface temperature of the photovoltaic panel under standard test conditions, which is 25 °C; in the CCHP system model, COP hp is the conversion coefficient of the ground - source heat pump, and its value is 4.

[0202] Example 1:

[0203] As Figure 1As shown in the figure, the multi - energy hybrid energy storage system combined with hydrogen - enriched combustion includes a power system for providing electricity. The power system consists of two renewable energy sources, namely photovoltaic and wind power, a gas turbine, an external power grid, a ground - source heat pump, an electrolyzer, and a battery; the thermal system consists of a gas turbine, a ground - source heat pump, a heat recovery device, and a heat storage device. An absorption chiller is used for the cold - air system to provide cold air. In addition, the ground - source heat pump can switch between heating / cooling modes according to different requirements of heating and cooling loads. The hydrogen - enriched gas turbine can burn hydrogen and natural gas simultaneously at a certain ratio, outputting electric energy and thermal energy, and the maximum hydrogen - enrichment ratio is 30%.

[0204] The power system includes a wind turbine generator for converting wind energy into electrical energy; a photovoltaic unit for converting light energy into electrical energy, and an external power grid;

[0205] The storage system includes a battery, a heat storage device, and a hydrogen storage device.

[0206] On the basis of the original electricity - heat and electricity - hydrogen conversions, this system adds a hydrogen - enriched gas turbine. This energy - conversion device can burn hydrogen and natural gas simultaneously and directly output electric power and thermal power, realizing the direct conversion of hydrogen to electricity and hydrogen to heat; adding a ground - source heat pump can replace the traditional boiler to achieve the conversion of electricity to heat. The mathematical model of the hydrogen - enriched gas turbine is as follows:

[0207]

[0208] Where, P GT is the output electric power of the gas turbine, V NG is the instantaneous consumption volume of natural gas, η GT is the output efficiency of the gas turbine, K NG is the electricity generation per cubic meter of natural gas, 9.7 kWh / m 3 . V H2 is the instantaneous consumption volume of hydrogen, K H2 is the electricity generation per cubic meter of hydrogen, 1.79 kWh / m 3 . Particularly, V H2 : V NG , that is, the maximum hydrogen - enrichment ratio of the gas turbine is 30%. The output thermal power of the gas turbine is as follows:

[0209]

[0210] Where, Q GT is the output thermal power of the gas turbine.

[0211] Inputting electrical energy to the ground - source heat pump, it can convert the input electrical energy into thermal energy or cold energy for output. The specific model is as follows:

[0212] Q hp = Ehp COP hp

[0213] Among them, E hp is the input electric power of the ground source heat pump, and Q hp is the output heat (cold) power of the ground source heat pump, and COP hp is the conversion coefficient of the ground source heat pump, with a value of 4.

[0214] As Figure 2 shown, the system combines hydrogen-enriched combustion (hydrogen-electricity, hydrogen-heat) with a ground source heat pump (electricity-heat). In this way, on the basis of traditional electricity-heat (boiler) and electricity-hydrogen (electrolyzer), a more perfect and efficient electricity-hydrogen-heat conversion path is constructed. It can effectively achieve flexible conversion among three different energy forms: electricity, hydrogen, and heat. And through the introduction of a storage system (battery, hydrogen storage, and heat storage devices), it is possible to store energy when the wind power and photovoltaic power are sufficient to meet the user load demand according to the actual power generation of renewable energy, and release it when it is difficult to meet the user demand, flexibly and quantitatively regulate the input and output energy, smooth out peaks and fill in valleys, further improve the consumption rate and utilization rate of renewable energy, and accurately and efficiently respond to user load demands. The combination of the storage system with energy conversion devices such as hydrogen-enriched gas turbines and ground source heat pumps makes the electricity-hydrogen-heat conversion path of this system more flexible and efficient. The power system, the thermal system, and the storage system are connected through various energy conversion devices and interact and constrain each other with a certain energy balance relationship to respond to the variable demands of users, enabling flexible interconversion among three different energy forms: electricity, heat (cold), and hydrogen, which is more conducive to the stable operation of the system.

[0215] For example, the operation of the integrated energy system needs to meet the overall electricity balance, heat balance, and cold balance constraints:

[0216]

[0217] Example 2:

[0218] As Figure 3 shown, the capacity configuration optimization method of the multi-energy hybrid energy storage system combined with hydrogen-enriched combustion Figure 3 shows the flow chart of the system configuration and operation strategy. It includes data input, optimization, output, and data processing. The input data includes electricity price and gas price, user demand and weather conditions, economic parameters, and equipment efficiency. The optimization process includes initialization. The initialization process has setting the objective function, design constraints, and setting operation variables, and in the optimization process, a MILP problem needs to be proposed. This study uses the Gurobi commercial solver, which depends on its fast calculation ability. The output data includes the capacity configuration result and the optimal result of the objective function.

[0219] The objective function considering both the economic cost and environmental cost of the integrated energy system is established as follows:

[0220] F = min(C cap + C o&m + C en + C grid + C CE )

[0221] In the formula, C cap is the initial investment cost, C o&m is the operation and maintenance cost, C en is the energy cost, C grid is the grid interaction cost, and C CE is the carbon emission cost.

[0222] Among them, the investment cost model of the energy storage system is:

[0223]

[0224] Among them, K1 and K2 are the total equipment amounts optimized according to the number and capacity of the equipment respectively; C k is the investment cost per unit equipment or unit power; r is the actual rate of return, m is the expected service life of equipment k, and cap k is the capacity of equipment k.

[0225] The operation and maintenance cost model of the energy storage system is:

[0226]

[0227] Among them, Γ d is the total number of days of designed operation; k is the total number of equipment; ξ k is the maintenance cost per kWh of equipment k, is the output power of equipment k.

[0228] The energy cost model of the energy storage system is:

[0229]

[0230] Among them, λ ng is the unit price of natural gas.

[0231] The grid interaction cost model of the energy storage system is:

[0232]

[0233] Among them, λ grid is the unit power purchase price.

[0234] The carbon emission cost model of the energy storage system is:

[0235] C CE = κG ACE

[0236] where κ is the treatment price per kg of carbon dioxide.

[0237]

[0238] where ε ng and ε ng are the carbon emission coefficients of natural gas and purchased electricity.

[0239] The operation of the integrated energy system and the output (energy supply) strategies of each part are proposed as follows:

[0240] 1) First, the output of photovoltaic and wind power is used for energy supply to consume renewable energy as much as possible and increase the proportion of renewable energy output for energy supply;

[0241] 2) Secondly, a hydrogen-blended gas turbine is used to mainly meet the cooling and heating loads to distribute the output for energy supply in each link;

[0242] 3) If the output of the power system is still less than the load demand, the output of the battery is selected according to the battery capacity at this time to meet the demand; if it is greater than the load demand, the surplus power is stored in the battery;

[0243] 4) If the demand still cannot be met, electricity needs to be purchased from the external large power grid.

[0244] Example 3:

[0245] The system is located in the northern part of Zhangjiakou, China. The local hourly wind speed, global irradiance, and ambient temperature are as Figure 4 shown. The date of the meteorological data starts from January 1st of a certain year and lasts for a whole year. According to the annual meteorological data and the models of wind turbines and photovoltaics, the annual output of wind power and photovoltaics can be calculated, that is, by clustering the existing annual light intensity and wind speed data into typical days using the K-means algorithm, a distributed energy system with a ground-source heat pump and hydrogen combustion is built to provide power, heating, and cooling loads for users. The area adopts a peak-valley electricity price model, and its time-of-use electricity price is shown in Table 1. The peak-hour electricity price for the system to purchase electricity from the external power grid is set at 1.1662 yuan / kWh, the normal-hour electricity price is 0.8724 yuan / kWh, and the valley-hour electricity price is 0.6072 yuan / kWh. The economic and technical parameters of the equipment are necessary data in the system optimization process. Table 2 lists the economic parameters of each subsystem, and Table 3 lists the parameters of the energy storage equipment.

[0246] Table 1 Local time-of-use electricity price

[0247] Time period Time (h) Electricity price (yuan / kWh) Peak period 10:00-13:00,17:00-22:00 1.1662 Flat period 7:00-10:00,13:00-17:00,22:00-23:00 0.8724 Valley period 0:00-7:00,23:00-24:00 0.6072

[0248] Table 2 Economic parameters of each equipment

[0249]

[0250]

[0251] Example 4:

[0252] According to the described objective function, constraint conditions, and output strategy, a mixed-integer linear programming problem and a capacity configuration optimization mathematical model for an electric-thermal-cooling-hydrogen multi-energy hybrid energy storage system combined with hydrogen-doped combustion are established, and solved using the Gurobi commercial solver in Matlab to obtain the optimal configuration and scheduling plan for each equipment link. The optimal configuration of each equipment link is shown in Table 3. The scheduling plan for a typical day is as Figure 5 shown.

[0253] Table 3 Optimal capacity configuration of each equipment link

[0254]

[0255] Table 4 Results of the system's final optimized cost indicators

[0256]

[0257] The present invention provides an electric-thermal-cooling-hydrogen multi-energy hybrid energy storage system combined with hydrogen-doped combustion and its capacity configuration optimization method. By adjusting the proportion of hydrogen-doped combustion, the generated hydrogen enters the gas turbine for combustion, replacing part of the natural gas consumption; adding a ground-source heat pump device, increasing and improving the conversion link between electricity, heat, and hydrogen. At the same time, considering economic and environmental objectives, according to the operation of the proposed integrated energy system and the output strategies of each part, a capacity configuration optimization method for the electric-thermal-cooling-hydrogen multi-energy hybrid energy storage system combined with hydrogen-doped combustion is established, enhancing the economy and environmental performance of the system and improving the multi-energy complementarity and conversion ability of the system. This application realizes a flexible capacity configuration plan, combining hydrogen-doped combustion with a ground-source heat pump. In this way, compared with traditional distributed systems for electric-thermal and electro-hydrogen conversion, a more flexible and efficient hydrogen-electricity-heat conversion path is constructed.

[0258] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A multi-component hybrid energy storage system combined with hydrogen-blended combustion, characterized in that: It includes an electric system, a thermal system, and a cooling system. The electric system includes a wind turbine, a photovoltaic unit, a gas turbine, an external power grid, and an electrolyzer. The electrolyzer is used to provide hydrogen for the gas turbine. The hydrogen and natural gas in the gas turbine are burned simultaneously according to a preset ratio. The thermal system includes a ground source heat pump and a heat recovery device. The cooling system includes an absorption refrigeration unit. The heat recovery device is coupled to the gas turbine, and the heat energy generated by the gas turbine during the hydrogen-blended combustion process is stored in the heat recovery device; the electric energy generated by the gas turbine is output to the external power grid and the ground source heat pump; the ground source heat pump is used to provide cooling and heating loads; The heat source output end of the heat recovery device is connected to the heat supply terminal and the heat source input end of the absorption refrigeration unit; It also includes an intelligent control system, which is used to control the operation of the power system, thermal system and cooling system according to the cooling and heating load demand and power generation conditions, and realize the conversion and output of the four energy forms of hydrogen-electricity-heat-cold.

2. The multi-component hybrid energy storage system combined with hydrogen-blended combustion according to claim 1, characterized in that: It also includes a storage system, which includes a battery and a heat storage device, the battery is connected to the wind turbine generator set, the heat source input end of the heat storage device is connected to the ground source heat pump and the heat recovery device, and the output end of the heat storage device is connected to the heating terminal; The intelligent control system also comprehensively controls the operation of the power system, the thermal system and the cooling system according to the storage capacity of the storage system.

3. The multi-component hybrid energy storage system combined with hydrogen-blended combustion according to claim 2 is characterized in that: The intelligent control system includes an equipment model, a mathematical model for capacity configuration optimization, an objective function model, and a constraint model, wherein the objective function model includes objective functions of economic cost and environmental cost parameters, and the constraint model includes constraints including equipment capacity limitation and / or energy conversion efficiency limitation and / or energy balance constraint and / or energy storage equipment charging and discharging limitation. The intelligent control system outputs capacity configuration results and optimization target results according to the objective function and constraint model, and converts between three different energy forms: electricity, heat or cold, and hydrogen.

4. The multi-component hybrid energy storage system combined with hydrogen-blended combustion according to claim 3 is characterized in that: The intelligent control system sets the capacity configuration optimization problem as a mixed integer linear programming problem based on the equipment model, the mathematical model of capacity configuration optimization, constraints, initial data and equipment energy supply strategy, and uses an intelligent algorithm to solve the mathematical model of capacity configuration optimization, and outputs the capacity configuration result and the optimization target result.

5. The multi-component hybrid energy storage system combined with hydrogen-blended combustion according to claim 3 or 4, characterized in that: The equipment model includes a wind power generation model, a photovoltaic power generation model, a CCHP model and a storage system model, wherein: The wind power generation model is: Among them, v t is the instantaneous wind speed, v in , v r and v out are cut-in wind speed, rated wind speed and cut-out wind speed respectively, P r is the rated power of the fan; The photovoltaic power generation model is: Among them, P PV is the output power of the photovoltaic panel, G t is the solar irradiance, G STC is the irradiance under standard test conditions, λ is the temperature coefficient, T STC is the surface temperature of the photovoltaic panel under standard test conditions, P STC The output power of photovoltaic panels measured by standard; The CCHP system includes a gas turbine, a ground source heat pump, a heat recovery device and an absorption chiller. The CCHP model is: P GT =V NG or GT K NG +V H2 or GT K H2 ; Among them, V NG is the instantaneous consumption volume of natural gas, η GT is the gas turbine output efficiency, K NG The power generation capacity of natural gas is 9.7kWh / m 3 , V H2 is the instantaneous consumption volume of hydrogen, K H2 The power generation capacity of each cubic meter of hydrogen is 1.79kWh / m 3 , V H2 :V NG ≤30%; Q hp =E hp COP hp ; Among them, E hp is the input power of the ground source heat pump, Q hp is the output heat (cooling) power of the ground source heat pump, COP hp is the conversion coefficient of the ground source heat pump; Q rec =0.85Q GT ; Among them, Q rec The heat recovery device outputs thermal power, Q GT Output thermal power to the gas turbine; Q a =Q rec COP a ; Among them, Q a The cooling power output of the absorption chiller, COP a is the refrigeration efficiency; The storage system includes batteries, heat storage devices and hydrogen storage devices. The storage system model is: Among them, SOC(t+1) and SOC(t) are the state of charge of the battery at time t+1 and t. and are the charging and discharging power of the battery, and are the charge and discharge efficiency of the battery respectively; Among them, S HS (t+1) and S HS (t) is the capacity of the heat storage device at time t+1 and t, and are the charging and discharging power of the heat storage device, and are the charging and discharging efficiencies of the heat storage device, respectively; V H (t+1)=V H (t)+V in (t)-V out (t); Among them, V H (t+1) and V H (t) is the hydrogen capacity of the hydrogen storage device at time t+1 and t, V in (t) and V out (t) are the volume of hydrogen input and output of the hydrogen storage device respectively.

6. The multi-component hybrid energy storage system combined with hydrogen-blended combustion according to claim 3 or 4, characterized in that: The objective function model is: F=min(C cap +C o&m +C en +C grid +C CE ); In the formula, C cap is the investment cost, C o&m is the operation and maintenance cost, C en is the energy cost, C grid is the grid interaction cost and C CE for the cost of carbon emissions; Among them, the investment cost model of the energy storage system is: Among them, K1 and K2 are the total number of equipment after optimization according to the number and capacity of equipment; C k is the investment cost per unit of equipment or per unit of power; r is the actual rate of return, m is the expected service life of equipment k, cap k is the capacity of device k; The operation and maintenance cost model of the energy storage system is: Among them, Γ d is the total number of days of design operation; k is the total number of equipment; ξ k is the maintenance cost per kWh of equipment k, is the output power of device k; The energy cost model of the energy storage system is: Among them, λ ng is the unit price of natural gas; The grid interaction cost model of the energy storage system is: Among them, λ grid The unit electricity purchase price; The carbon emission cost model of the energy storage system is: C CE =κG ACE ; Among them, κ is the treatment price per kg of carbon dioxide; Among them, ε ng and ε ng is the carbon emission coefficient of natural gas and purchased electricity.

7. The multi-component hybrid energy storage system combined with hydrogen-blended combustion according to claim 3 or 4, characterized in that: The constraint model includes at least one of the following constraints: (1) Overall electrical balance, thermal balance, and cold balance constraints of equipment in the intelligent control system: (2) Upper and lower limit constraints of equipment in the intelligent control system: AND K,min ≤E K ≤E K,max ; (3) Operation constraints of equipment in the intelligent control system: Where SOC is the state of charge or remaining capacity of the energy storage device. and are the charging and discharging (thermal) power of the energy storage device respectively; (4) Climbing constraints of equipment in intelligent control system: in and They are the upper and lower climbing limits of a certain equipment respectively.

8. The multi-component hybrid energy storage system combined with hydrogen-blended combustion according to claim 4, characterized in that: The device energy supply strategy includes: Step A: Give priority to the use of photovoltaic units and wind turbines to maximize the proportion of renewable energy in the system's energy supply; Step B: Use hydrogen-blended gas turbines to dynamically allocate energy supply capacity according to the system's cooling and heating load requirements to ensure stable system operation; Step C: When the renewable energy supply is insufficient, the battery is discharged to supplement the energy supply according to the remaining capacity of the battery; when the renewable energy supply is excessive, the excess power is stored in the battery for subsequent use; Step D: If the system still cannot meet the load demand after the above steps, it will purchase electricity from the external large power grid to meet the remaining load demand through connection with the external large power grid to ensure continuous and stable power supply of the system.

9. The multi-component hybrid energy storage system combined with hydrogen-blended combustion according to claim 4, characterized in that: The mathematical model for capacity configuration optimization includes: Data input module, used to receive electricity and gas price information, actual user demand data, real-time weather conditions, economic parameter settings, and equipment efficiency data; The optimization processing module includes an initialization step, wherein the initialization step includes setting an objective function, designing constraints, and setting operating variables, and setting a mixed integer linear programming problem during the optimization process, and solving it through a solver to obtain the optimal capacity configuration of the energy supply of each device; Result output module, used to output capacity configuration results and the optimal solution of the objective function; The data processing module is used to calculate and output the economic cost and environmental cost of the output capacity configuration plan.

10. A capacity configuration optimization method for a multi-component hybrid energy storage system combined with hydrogen-blended combustion, characterized in that: The multi-component hybrid energy storage system combined with hydrogen-blended combustion as claimed in any one of claims 1 to 9 comprises: S1: Establish equipment models for energy conversion and storage in the intelligent control system, including electricity, heat, cold and hydrogen; S2: Set the objective function including economic cost and environmental cost parameters and build a comprehensive total cost model; S3: Set constraints according to the actual operating conditions of the intelligent control system; S4: constructing a mathematical model for capacity configuration optimization based on the equipment model, objective function and constraint conditions established in steps S1 to S3; S5: Adjust the equipment energy supply strategy of the intelligent control system; S6: The optimization processing module of the mathematical model of capacity configuration optimization transforms the capacity configuration optimization problem into a mixed integer linear programming problem, and solves it using a solver to obtain the optimal capacity configuration of each equipment link; S7: The mathematical model of capacity configuration optimization outputs the capacity configuration results and the optimal solution of the objective function, and outputs the system economic cost and environmental cost.

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