Wind-solar-hydrogen integrated energy optimization method and system considering methanation and carbon capture

Abstract

The present application provides a wind-solar-hydrogen comprehensive energy optimization method considering methanation and carbon capture, and belongs to the field of energy optimization. The method comprises the following steps: establishing a wind-solar-hydrogen comprehensive energy architecture considering carbon capture and methanation; based on the wind-solar-hydrogen comprehensive energy architecture considering carbon capture and methanation, establishing mathematical models of each energy flow conversion and storage device; based on the mathematical models of each energy flow conversion and storage device, establishing a scheduling model objective function and a capacity configuration objective function, and establishing constraint conditions of the scheduling model objective function and the capacity configuration objective function, wherein the scheduling model objective function is the minimum value of the sum of the energy purchase cost, the amount of abandoned wind and abandoned light, and the operation and maintenance cost, and the capacity configuration objective function is the minimum value of the sum of the construction cost, the operation and maintenance cost, and the carbon emission cost; and the optimal scheduling scheme and the optimal capacity configuration scheme are obtained by using a CPLEX solver. The present application provides a scheduling and capacity planning model considering system flexibility, which is innovative in model establishment and has universality.

Description

Technical Field

[0001] This invention belongs to the field of integrated energy optimization operation technology, and particularly relates to a wind, solar and hydrogen integrated energy optimization method and system that takes into account methanation and carbon capture. Background Technology

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

[0003] With the rapid expansion of wind power installed capacity, many integrated wind and solar energy systems based on wind and solar power farms have been established. However, these traditional integrated wind and solar energy systems have many problems. As can be seen from the annual output curves of wind and solar power, their output is greatly affected by weather, time, and environmental factors, exhibiting randomness and intermittency, with significant fluctuations. Wind and solar output is concentrated between 6:00 AM and 6:00 PM daily, but peak load times often do not match this period. This leads to situations where high wind and solar output results in low load demand and wind / solar curtailment, while low wind and solar output results in high load demand and energy demand gaps. Furthermore, the energy storage methods used in traditional integrated wind and solar energy systems are generally conventional electrochemical or physical energy storage, which are relatively inefficient. These shortcomings make the output of traditional integrated wind and solar energy systems extremely unstable, resulting in poor power quality. Simultaneously, the lack of energy storage and energy conversion equipment leads to poor system flexibility, wind and solar power absorption capacity, and peak shaving and valley filling capabilities. The systems suffer from significant wind and solar curtailment, and their economic and environmental performance is also poor, failing to meet the current national integrated energy development strategy requirements.

[0004] The existing technical problems of wind and solar integrated energy systems mainly consist of two parts: (1) The existing systems lack energy conversion and storage equipment, resulting in serious wind and solar curtailment problems, failing to meet stable and sufficient power output, lacking sufficient peak shaving and valley filling capabilities, and having poor overall economic efficiency, environmental friendliness, and wind and solar absorption capacity; (2) The current scheduling and capacity configuration methods for wind and solar integrated energy systems mainly include: a) establishing and solving scheduling and capacity configuration models based on objective functions (minimum operating cost, maximum energy utilization rate, etc.) and constraints; b) establishing and solving scheduling and capacity planning models that consider the differences in energy flow such as electricity, heat, and gas; c) establishing and solving scheduling and capacity planning models that consider the uncertainty of source load. Currently, the scheduling and capacity planning methods for integrated energy systems are mainly based on the algorithm innovation of the above three models. For the establishment and solution of scheduling and capacity configuration models for new wind and solar integrated energy systems with more flexible equipment, the existing methods are not universal. Summary of the Invention

[0005] To overcome the shortcomings of the existing technologies, this invention provides a wind-solar-hydrogen integrated energy optimization method and system that takes into account methanation and carbon capture. It designs a wind-solar-hydrogen integrated energy system that takes into account carbon capture, methanation, and hydrogen storage, and provides its day-ahead economic dispatch and capacity configuration method. For integrated energy systems with added flexible equipment such as methanation reactors and carbon capture, a new dispatch and capacity planning model that considers system flexibility is proposed. The model establishment and solution methods are innovative and have universality.

[0006] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions: The first aspect of this invention provides a method for optimizing integrated wind, solar, and hydrogen energy by taking into account methanation and carbon capture.

[0007] A wind-solar-hydrogen integrated energy optimization method considering methanation and carbon capture includes the following steps: Establish a comprehensive energy architecture that integrates wind, solar and hydrogen energy, taking into account carbon capture and methanation; Based on the integrated wind, solar and hydrogen energy architecture that takes into account carbon capture and methanation, mathematical models of various energy flow conversion and storage devices are established. Based on the mathematical models of various energy flow conversion and storage devices, a scheduling model objective function and a capacity configuration objective function are established, along with constraints on these functions. The scheduling model objective function is the minimum sum of energy purchase cost, wind and solar curtailment, and operation and maintenance cost, while the capacity configuration objective function is the minimum sum of construction, operation and maintenance cost, and carbon emission cost. The CPLEX solver in MATLAB is used to solve the objective functions of the scheduling model and the capacity configuration to obtain the optimal scheduling scheme and the optimal capacity configuration scheme.

[0008] The second aspect of the present invention provides a wind-solar-hydrogen integrated energy optimization system that takes into account methanation and carbon capture.

[0009] A wind-solar-hydrogen integrated energy optimization system that takes into account methanation and carbon capture includes: The energy architecture building module is configured to: establish a wind, solar, and hydrogen integrated energy architecture that takes into account carbon capture and methanation; The equipment model building module is configured to: establish mathematical models of various energy flow conversion and storage devices based on the integrated wind, solar and hydrogen energy architecture that takes into account carbon capture and methanation; The objective function establishment module is configured to: establish the scheduling model objective function and the capacity configuration objective function based on the mathematical models of each energy flow conversion and storage device, and establish the constraints of the scheduling model objective function and the capacity configuration objective function. The scheduling model objective function is the minimum value of the sum of energy purchase cost, wind and solar curtailment amount and operation and maintenance cost, and the capacity configuration objective function is the minimum value of the sum of construction, operation and maintenance cost and carbon emission cost. The solver module is configured to use MATLAB's CPLEX solver to solve the objective function of the scheduling model and the objective function of capacity configuration, and obtain the optimal scheduling scheme and the optimal capacity configuration scheme.

[0010] A third aspect of the present invention provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps of the wind-solar-hydrogen integrated energy optimization method taking into account methanation and carbon capture as described in the first aspect of the present invention.

[0011] The fourth aspect of the present invention provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the wind-solar-hydrogen integrated energy optimization method taking into account methanation and carbon capture as described in the first aspect of the present invention.

[0012] The above one or more technical solutions have the following beneficial effects: 1. The integrated wind, solar, and hydrogen energy architecture established in this invention, which incorporates carbon capture and methanation, couples three energy sources: electricity, heat, and gas. The hydrogen energy storage system, including an electrolyzer, hydrogen storage tank, and fuel cell, can convert electrical energy into hydrogen energy, enabling wind and solar energy consumption and peak shaving, without time constraints. The addition of a methanation reactor further converts hydrogen into natural gas (P2G), enriching the system's energy sources and freeing wind and solar energy consumption capacity from the limitations of hydrogen storage capacity. The carbon capture device can collect emissions from equipment using natural gas as fuel. This achieves the goals of environmental protection and green hydrogen. By converting excess electricity into hydrogen and natural gas (P2G), the system's energy sources are diversified, mitigating the problem of insufficient wind and solar energy absorption capacity due to hydrogen storage limitations. Through the addition of these flexible devices, this wind-solar-hydrogen integrated energy system, which incorporates carbon capture and methanation, effectively addresses the issues of poor flexibility, wind and solar energy absorption capacity, and peak shaving capabilities, while also exhibiting good environmental performance indicators.

[0013] 2. This invention establishes models for each device, using the input power of each device as the decision variable (the quantity to be determined), and establishes a model of their energy flow conversion relationship based on their energy conversion efficiency. The objective function is to minimize total energy cost, wind and solar curtailment, and operating cost, with the safe and economical operating range of each device as the constraint. Calculations were performed using MATLAB's CPLEX solver, ultimately determining the output of each device over 24 hours, as well as the total energy cost, wind and solar curtailment, and total operating cost. The results show that compared to traditional regional integrated energy systems, the wind-solar-hydrogen integrated energy system designed in this invention reduces wind and solar curtailment by 86.7% and total cost by 57.5%, while also reducing costs by 3412.97. of emission.

[0014] 3. This invention establishes a mathematical model based on the energy flow efficiency relationship of each device, takes the configuration capacity of each device as the decision variable (to be determined), takes the minimum construction and operation and maintenance cost and the minimum carbon emission as the objective function, takes the configuration capacity of each device as the constraint condition, and uses MATLAB's CPLEX solver to calculate the optimal capacity configuration scheme. Finally, the optimal capacity configuration scheme of this design is found to reduce the total cost by 6.43%, electricity purchase by 17%, and gas purchase by 32.01% compared with the optimal configuration scheme of the traditional wind and solar integrated energy system.

[0015] 4. The wind-solar-hydrogen integrated energy optimization method and system proposed in this invention, which takes into account methanation and carbon capture, has excellent wind and solar energy absorption, peak shaving and valley filling capabilities, and good economic efficiency. Because the energy purchase is reduced, the carbon emissions of the system are greatly reduced, achieving the goal of environmental protection and green hydrogen. At the same time, it also verifies the universality and practicality of the day-ahead economic dispatch and capacity configuration modeling and calculation proposed in this design.

[0016] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0017] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0018] Figure 1 This is a flowchart of the method in the first embodiment; Figure 2 This is a diagram of the integrated wind, solar, and hydrogen energy architecture that takes carbon capture and methanation into account in Example 1; Figure 3 A schematic diagram showing the predicted values ​​of wind and solar power output and load. Figure 4(a) is a schematic diagram of wind and solar power output and load power on a typical day in spring; Figure 4(b) is a schematic diagram of wind and solar power output and load power on a typical summer day; Figure 4(c) is a schematic diagram of wind and solar power output and load power on a typical autumn day; Figure 4(d) is a schematic diagram of wind and solar power output and load power on a typical winter day; Figure 5 A schematic diagram of the day-ahead dispatch results for traditional wind and solar integrated energy; Figure 6 A schematic diagram of the scheduling results of the wind-solar-hydrogen integrated energy system of this invention; Figure 7 This diagram illustrates the cost comparison between the optimal capacity configuration scheme of this design and a traditional integrated energy system. Figure 8 This diagram illustrates a comparison between the optimal capacity configuration scheme of this design and the energy purchase scheme of a traditional integrated energy system. Figure 9 This is a system structure diagram of the second embodiment. Detailed Implementation

[0019] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0020] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations of the present invention.

[0021] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0022] Example 1 This embodiment discloses a wind-solar-hydrogen integrated energy optimization method that takes into account methanation and carbon capture.

[0023] like Figure 1 As shown, the integrated wind-solar-hydrogen energy optimization method considering methanation and carbon capture includes the following steps: Establish a comprehensive energy architecture that integrates wind, solar and hydrogen energy, taking into account carbon capture and methanation; Based on the integrated wind, solar and hydrogen energy architecture that takes into account carbon capture and methanation, mathematical models of various energy flow conversion and storage devices are established. Based on the mathematical models of various energy flow conversion and storage devices, a scheduling model objective function and a capacity configuration objective function are established, along with constraints on these functions. The scheduling model objective function is the minimum sum of energy purchase cost, wind and solar curtailment, and operation and maintenance cost, while the capacity configuration objective function is the minimum sum of construction, operation and maintenance cost, and carbon emission cost. The CPLEX solver in MATLAB is used to solve the objective functions of the scheduling model and the capacity configuration to obtain the optimal scheduling scheme and the optimal capacity configuration scheme.

[0024] Furthermore, a comprehensive energy architecture integrating wind, solar, and hydrogen, taking into account carbon capture and methanation, will be established, specifically as follows: The integrated wind, solar, and hydrogen energy architecture, which considers carbon capture and methanation, involves the coupling of three energy sources: electricity, heat, and gas. The electricity load is powered by the grid, batteries, wind turbines, photovoltaic units, fuel cells, and gas turbines. The wind turbines and photovoltaic units are connected to an electrolyzer, which is connected to a hydrogen storage tank. The hydrogen storage tank is connected to a methanation reactor, which is connected to a gas turbine and a gas boiler. The gas turbine is connected to a carbon capture device, which is connected to the methanation reactor. The gas load is powered by natural gas from the natural gas pipeline network and the methanation reactor. The heat load is powered by the electrolyzer, fuel cells, gas turbine, gas boiler, and methanation reactor.

[0025] Furthermore, when wind and solar power output is high and load demand is low, resulting in wind and solar curtailment, the electrolyzer operates, converting electrical energy into hydrogen energy and storing it in a hydrogen storage tank. When wind and solar power output is low but load demand is high, the fuel cell operates, converting the hydrogen energy stored in the hydrogen storage tank into electrical energy. Part of the hydrogen energy in the storage tank is supplied to the fuel cell, and the other part is supplied to the methanation reactor. When the hydrogen storage tank has no remaining storage but wind and solar curtailment still occurs, the hydrogen in the storage tank is fed into the methanation reactor, where it reacts with carbon capture devices collected from the gas turbine exhaust. The reaction produces .

[0026] Furthermore, mathematical models for each energy flow conversion and storage device are established, specifically as follows: Establish models for hydrogen production using electrolyzers, including hydrogen production power, heat production power, hydrogen storage capacity over time period t, hydrogen output power from hydrogen storage tanks over time period t, output electrical and thermal power models for fuel cells, battery electrical storage capacity over time period t, output electrical and thermal power models for gas turbines over time period t, output thermal power models for gas-fired boilers over time period t, and carbon capture devices over time period t. Energy model, natural gas power model of methane reactor output during time period t, and thermal power model of methane reactor output during time period t.

[0027] Specifically, Figure 2This diagram illustrates a wind-solar-hydrogen integrated energy architecture that incorporates carbon capture and methanation. This architecture couples three energy sources: electricity, heat, and gas. Electricity primarily comes from wind power, solar power, grid power, fuel cells, batteries, and gas turbines. When wind and solar output is high but load demand is low, curtailment occurs. In this case, an electrolyzer operates, converting electricity into hydrogen energy, which is stored in a hydrogen storage tank. Conversely, when wind and solar output is low but load demand is high, the fuel cell operates, converting the hydrogen stored in the storage tank into electricity. A portion of the hydrogen stored in the storage tank is supplied to the fuel cell, and the remainder to the methanation reactor. When the storage tank is empty but curtailment continues, the hydrogen from the storage tank is fed into the methanation reactor, where it is combined with gas turbine exhaust gas captured by the carbon capture unit. The reaction produces As one of the sources of natural gas for the system, it meets the gas load while reducing the cost of purchasing natural gas.

[0028] Excess electricity is converted into hydrogen and natural gas (P2G), enriching the system's energy sources and mitigating the problem of insufficient wind and solar energy absorption capacity caused by hydrogen storage limitations. Simultaneously, the electrolyzer, fuel cell, methanation reactor, gas turbine, and gas boiler in the system generate significant heat during operation, which is collected on a heat pipe network to supply the system's heat load. By incorporating these flexible devices, the wind-solar-hydrogen integrated energy system designed in this invention, which incorporates carbon capture and methanation, effectively addresses the issues of poor flexibility, wind and solar energy absorption capacity, and peak shaving capabilities, while also exhibiting good environmental performance.

[0029] The optimal scheduling scheme is then solved using the day-ahead economic scheduling method: First, models of each device are established, with the input power of each device as the decision variable (to be determined). Based on their energy conversion efficiency, models of their energy flow conversion relationships are established. The objective function is to minimize total energy cost, wind and solar curtailment, and operating cost. The safe and economical operating range of each device is used as a constraint. One scheduling cycle is 24 hours, and the unit scheduling time is 1 hour. Data from a wind and solar power station is used, and the wind and solar forecast values ​​and load forecast values ​​are known. Two scenarios are set up for comparison: a traditional wind-solar integrated energy system and the novel wind-solar-hydrogen integrated energy system proposed in this design. Calculations are performed using MATLAB's CPLEX solver. Finally, the output of each device, total energy cost, wind and solar curtailment, and total operating cost are calculated for 24 time periods. The results show that compared to the traditional regional integrated energy system, the wind and solar curtailment of the proposed wind-solar-hydrogen integrated energy system is reduced by 86.7%; the total cost is reduced by 57.5%, and the cost is reduced by 3412.97. of emission.

[0030] A. The mathematical models for each energy conversion and storage device are as follows: (1) Establish hydrogen production power model and heat production power model of electrolyzer for hydrogen production:

[0031]

[0032] In the formula The hydrogen production power of the electrolyzer during time period t; The input electrical power of the electrolytic cell during time period t; The heat generation power of the electrolytic cell during time period t; and These are the hydrogen production efficiency and heat generation efficiency of the electrolyzer, respectively.

[0033] (2) Hydrogen storage capacity model for time period t and hydrogen power output model of hydrogen storage tank for time period t:

[0034]

[0035] In the formula The amount of hydrogen stored during time period t; and These are the hydrogen storage efficiency and hydrogen release efficiency, respectively. The hydrogen output power of the hydrogen storage tank during time period t. and These represent the hydrogen power supplied from the hydrogen storage tank to the methane generator and fuel cell, respectively. μ is the self-charge / discharge rate, which is a fixed value.

[0036] (3) Output electrical power model and thermal power model of fuel cell:

[0037]

[0038] In the formula and These are the output electrical power and thermal power of the fuel cell, respectively. Let t be the hydrogen power delivered to the fuel cell during time period t. and These represent the hydrogen-to-electricity and hydrogen-to-heat efficiencies of the fuel cell, respectively.

[0039] (4) Battery storage capacity model for time period t:

[0040] In the formula The amount of battery charge stored during time period t; and These are the charge and discharge efficiencies, respectively. This refers to the charging power. α represents the discharge power. α represents the self-discharge rate, which is a fixed value.

[0041] (5) Output electrical power model and output thermal power model of the gas turbine during time period t:

[0042]

[0043]

[0044] In the formula , and The output electrical power, input natural gas power, and output thermal power of the gas turbine during time period t; and These refer to the gas-to-electricity and gas-to-heat conversion efficiencies of the gas turbine, respectively. The input electrical power of the carbon capture device during time period t; The electrical power supplied to the gas turbine for the load during time period t.

[0045] (6) Output thermal power model of gas boiler during time period t:

[0046] In the formula , These represent the output thermal power and input natural gas power of the gas-fired boiler during time period t; This refers to the gas-to-heat conversion efficiency of a gas-fired boiler.

[0047] (7) Carbon capture device during time period t Energy model:

[0048] In the formula For the efficiency of carbon capture devices; The input electrical power of the carbon capture device during time period t; where To capture 1 mol The required electrical energy; Captured for time period t Amount (mol); For time period t energy.

[0049] (8) Model of natural gas power output from methane reactor during time period t, and model of thermal power output from methane reactor during time period t:

[0050]

[0051] in The amount of methane output from the methane reactor during time period t; The volume of methane output from the methane reactor during time period t; The heat energy generated per mol of reaction; The output power of the methane reactor during time period t is the natural gas output. Let t be the thermal power output of the methane reactor during time period t. LHV is the lower calorific value of natural gas, which is a constant. The input-output power balance of the methanation reactor is shown in the following equation:

[0052] B. The objective function of the scheduling model is:

[0053]

[0054]

[0055]

[0056] , and These are functions representing energy purchase cost, wind and solar curtailment volume, and operation and maintenance cost, respectively. , These are the costs of purchasing electricity and gas, respectively. Let t be the electrical power during time period t. Purchase natural gas power for time period t. and These are the wind power forecast and the solar power forecast, respectively. and These are the planned values ​​for wind power and solar power, respectively. For wind and solar power curtailment penalties; The sum of the operation and maintenance costs of all equipment can be obtained by multiplying the unit operation and maintenance cost of each equipment by its power consumption.

[0057] in: These are the unit operation and maintenance costs for wind turbines, photovoltaic units, electrolyzers, hydrogen storage tanks, batteries, fuel cells, methane reactors, gas turbines, gas boilers, and carbon capture devices, respectively.

[0058] C. The constraints are:

[0059]

[0060]

[0061]

[0062] in For purchasing power, and These are the battery charging and discharging power, For electrical load power, This represents the power load of natural gas.

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[0080]

[0081] The optimal capacity configuration scheme is solved below. The capacity configuration method is as follows: First, a mathematical model was established based on the energy flow efficiency relationship of each device. The configured capacity of each device was used as the decision variable (to be determined), with minimum construction and operation costs and minimum carbon emissions as the objective functions. The configured capacity of each device was used as the constraint condition. The wind and solar power output and load values ​​were known. To demonstrate the model's applicability throughout the year, calculations were performed on typical days in spring, summer, autumn, and winter. The cost and power output of the proposed wind-solar-hydrogen integrated energy system were compared with those of a traditional wind-solar integrated energy system under different conditions. The optimal capacity configuration scheme was calculated using MATLAB's CPLEX solver. The final results showed that, compared to the optimal configuration scheme of a traditional wind-solar integrated energy system, the optimal capacity configuration scheme of this design reduced the total cost by 6.43%, electricity purchase by 17%, and gas purchase by 32.01%.

[0082] The above calculations verify that the proposed integrated wind-solar-hydrogen energy system with carbon capture has excellent wind and solar energy absorption, peak shaving and valley filling capabilities, and good economic efficiency.

[0083] A. The mathematical models for each energy flow conversion and storage device in the capacity configuration are consistent with the aforementioned scheduling model, and are omitted here.

[0084] B. The objective function for capacity allocation is shown below:

[0085] (1) Economic indicators:

[0086]

[0087]

[0088]

[0089] in The initial construction investment cost for each piece of equipment; For the operation and maintenance costs of each piece of equipment; The depreciation cost of each piece of equipment; , , , The unit annual construction investment costs are respectively for electrolyzers, fuel cells, hydrogen storage tanks, and batteries; , , and These are the unit operation and maintenance costs for electrolyzers, fuel cells, hydrogen storage tanks, and batteries, respectively. , , , These are the unit depreciation costs for the electrolyzer, fuel cell, hydrogen storage tank, and battery, respectively. For electricity purchase costs; For gas purchase costs; r is the capital recovery factor; m is the interest rate; and m is the useful life. , , and These are the configuration capacities of the electrolyzer, fuel cell, hydrogen storage tank, and battery, respectively.

[0090] (2) Carbon emission costs (environmental indicators)

[0091] in The carbon emission cost per unit of electricity ; The carbon emission cost per unit volume of natural gas, ; For the power purchased; For gas purchase power.

[0092] C. The constraints are: (1) Power balance:

[0093] , These represent the wind power and solar power output during time period t, respectively. The electrical load power during time period t (2) Thermal power balance:

[0094] , , , and These represent the power of the electrolyzer, hydrogen fuel cell, gas turbine, gas boiler, and electrical load during time period t.

[0095]

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[0100]

[0101]

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[0109] Table 1. Cost Comparison of Traditional Integrated Energy Systems and This Design under Day-ahead Economic Dispatch

[0110] Figure 3 — Figure 8 Both Table 1 and Table 2 contain data calculated using the scheduling and capacity configuration method proposed in this invention. Figure 3 — Figure 5 As shown in Table 1, the wind-solar-hydrogen integrated energy system of this invention reduces wind and solar curtailment by 86.7% compared to traditional regional integrated energy systems; the total cost is reduced by 57.5%, and the cost is reduced by 3412.97. Carbon emissions. Figure 6 — Figure 8 It can be seen that the optimal configuration scheme of the wind-solar-hydrogen integrated energy system proposed in this design reduces the total cost by 6.43%, electricity purchase by 17%, and gas purchase by 32.01% compared with the traditional integrated energy system.

[0111] The above description verifies that the proposed integrated wind-solar-hydrogen energy system, which incorporates carbon capture, possesses excellent wind and solar energy utilization, peak shaving and valley filling capabilities, and good economic efficiency. Because it reduces energy purchases, the system's carbon emissions are significantly reduced, achieving the goals of environmental protection and green hydrogen. It also verifies the universality and practicality of the day-ahead economic dispatch and capacity configuration modeling and calculation proposed in this design.

[0112] Example 2 This embodiment discloses a wind-solar-hydrogen integrated energy optimization system that takes into account methanation and carbon capture.

[0113] like Figure 9 As shown, the integrated wind-solar-hydrogen energy optimization system, which takes into account methanation and carbon capture, includes: The energy architecture building module is configured to: establish a wind, solar, and hydrogen integrated energy architecture that takes into account carbon capture and methanation; The equipment model building module is configured to: establish mathematical models of various energy flow conversion and storage devices based on the integrated wind, solar and hydrogen energy architecture that takes into account carbon capture and methanation; The objective function establishment module is configured to: establish the scheduling model objective function and the capacity configuration objective function based on the mathematical models of each energy flow conversion and storage device, and establish the constraints of the scheduling model objective function and the capacity configuration objective function. The scheduling model objective function is the minimum value of the sum of energy purchase cost, wind and solar curtailment amount and operation and maintenance cost, and the capacity configuration objective function is the minimum value of the sum of construction, operation and maintenance cost and carbon emission cost. The solver module is configured to use MATLAB's CPLEX solver to solve the objective function of the scheduling model and the objective function of capacity configuration, and obtain the optimal scheduling scheme and the optimal capacity configuration scheme.

[0114] Example 3 The purpose of this embodiment is to provide a computer-readable storage medium.

[0115] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the wind-solar-hydrogen integrated energy optimization method taking into account methanation and carbon capture as described in Embodiment 1 of this disclosure.

[0116] Example 4 The purpose of this embodiment is to provide an electronic device.

[0117] An electronic device includes a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the wind-solar-hydrogen integrated energy optimization method taking into account methanation and carbon capture as described in Embodiment 1 of this disclosure.

[0118] The steps and methods involved in the apparatuses of Embodiments 2, 3, and 4 above correspond to those in Embodiment 1. For specific implementation details, please refer to the relevant description section of Embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.

[0119] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0120] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for integrated wind-solar-hydrogen energy optimization considering methanation and carbon capture, characterized in that, Includes the following steps: Establish a comprehensive wind, solar, and hydrogen energy architecture that incorporates carbon capture and methanation, specifically as follows: The integrated wind, solar, and hydrogen energy architecture, which considers carbon capture and methanation, involves the coupling of three energy sources: electricity, heat, and gas. The electrical load's power sources include grid power, batteries, wind turbines, photovoltaic units, fuel cells, and gas turbines. Wind turbines and photovoltaic units are connected to electrolyzers, which are connected to hydrogen storage tanks. The hydrogen storage tanks are connected to methanation reactors, which are connected to gas turbines and gas boilers. The gas turbines are connected to carbon capture devices, which are connected to the methanation reactors. The gas load's natural gas sources are natural gas pipelines and the methanation reactors. The heat load's heat sources are electrolyzers, fuel cells, gas turbines, gas boilers, and the methanation reactors. When wind and solar power output is high and load demand is low, resulting in wind and solar curtailment, the electrolyzer operates, converting electrical energy into hydrogen energy and storing it in a hydrogen storage tank. When wind and solar power output is low but load demand is high, the fuel cell operates, converting the hydrogen energy stored in the hydrogen storage tank into electrical energy. Part of the hydrogen energy in the storage tank is supplied to the fuel cell, and the other part is supplied to the methanation reactor. When the hydrogen storage tank has no remaining capacity but wind and solar curtailment still occurs, the hydrogen in the storage tank is fed into the methanation reactor, where it reacts with carbon capture devices collecting emissions from the gas turbines. The reaction produces ; Based on a wind-solar-hydrogen integrated energy architecture that considers carbon capture and methanation, mathematical models are established for each energy flow conversion and storage device, specifically: Establish models for hydrogen production using electrolyzers, including hydrogen production power, heat production power, hydrogen storage capacity over time period t, hydrogen output power from hydrogen storage tanks over time period t, output electrical and thermal power models for fuel cells, battery electrical storage capacity over time period t, output electrical and thermal power models for gas turbines over time period t, output thermal power models for gas-fired boilers over time period t, and carbon capture devices over time period t. Energy model, natural gas power model of methane reactor output at time t, and thermal power model of methane reactor output at time t; Based on the mathematical models of various energy flow conversion and storage devices, a scheduling model objective function and a capacity configuration objective function are established, along with constraints on these functions. The scheduling model objective function is the minimum sum of energy purchase cost, wind and solar curtailment, and operation and maintenance cost, while the capacity configuration objective function is the minimum sum of construction, operation and maintenance cost, and carbon emission cost. The CPLEX solver in MATLAB is used to solve the objective functions of the scheduling model and the capacity configuration to obtain the optimal scheduling scheme and the optimal capacity configuration scheme.

2. The integrated wind-solar-hydrogen energy optimization method considering methanation and carbon capture as described in claim 1, characterized in that, The objective function of the scheduling model is: in, , and These are functions representing energy purchase cost, wind and solar curtailment volume, and operation and maintenance cost, respectively. , These are the costs of purchasing electricity and gas, respectively. Let t be the electrical power during time period t. Purchase natural gas power for time period t. and These are the wind power forecast and the solar power forecast, respectively. and These are the planned values ​​for wind power and solar power, respectively. For wind and solar power curtailment penalties; This is the sum of the operation and maintenance costs of each piece of equipment.

3. The integrated wind-solar-hydrogen energy optimization method considering methanation and carbon capture as described in claim 1, characterized in that, The capacity allocation objective function is: in, The initial construction investment cost for each piece of equipment, For the operation and maintenance costs of each piece of equipment, The depreciation cost of each piece of equipment, For electricity purchase costs, For gas purchase costs, Here, r is the capital recovery coefficient, and r is the interest rate. The carbon emission cost per unit of electricity The carbon emission cost per unit volume of natural gas, For the power purchase capacity, For gas purchase power.

4. The integrated wind-solar-hydrogen energy optimization method considering methanation and carbon capture as described in claim 1, characterized in that, The objective function of the scheduling model is constrained by the safe and economical operating range of each device, while the objective function of capacity allocation is constrained by the allocated capacity of each device.

5. A wind-solar-hydrogen integrated energy optimization system that takes into account methanation and carbon capture, characterized in that: include: The energy architecture building module is configured to: establish a comprehensive wind, solar, and hydrogen energy architecture that takes into account carbon capture and methanation, specifically: The integrated wind, solar, and hydrogen energy architecture, which considers carbon capture and methanation, involves the coupling of three energy sources: electricity, heat, and gas. The electrical load's power sources include grid power, batteries, wind turbines, photovoltaic units, fuel cells, and gas turbines. Wind turbines and photovoltaic units are connected to electrolyzers, which are connected to hydrogen storage tanks. The hydrogen storage tanks are connected to methanation reactors, which are connected to gas turbines and gas boilers. The gas turbines are connected to carbon capture devices, which are connected to the methanation reactors. The gas load's natural gas sources are natural gas pipelines and the methanation reactors. The heat load's heat sources are electrolyzers, fuel cells, gas turbines, gas boilers, and the methanation reactors. When wind and solar power output is high and load demand is low, resulting in wind and solar curtailment, the electrolyzer operates, converting electrical energy into hydrogen energy and storing it in a hydrogen storage tank. When wind and solar power output is low but load demand is high, the fuel cell operates, converting the hydrogen energy stored in the hydrogen storage tank into electrical energy. Part of the hydrogen energy in the storage tank is supplied to the fuel cell, and the other part is supplied to the methanation reactor. When the hydrogen storage tank has no remaining capacity but wind and solar curtailment still occurs, the hydrogen in the storage tank is fed into the methanation reactor, where it reacts with carbon capture devices collecting emissions from the gas turbines. The reaction produces ; The equipment model building module is configured to: establish mathematical models for each energy flow conversion and storage device based on a wind-solar-hydrogen integrated energy architecture that takes into account carbon capture and methanation, specifically: Establish models for hydrogen production using electrolyzers, including hydrogen production power, heat production power, hydrogen storage capacity over time period t, hydrogen output power from hydrogen storage tanks over time period t, output electrical and thermal power models for fuel cells, battery electrical storage capacity over time period t, output electrical and thermal power models for gas turbines over time period t, output thermal power models for gas-fired boilers over time period t, and carbon capture devices over time period t. Energy model, natural gas power model of methane reactor output at time t, and thermal power model of methane reactor output at time t; The objective function establishment module is configured to: establish the scheduling model objective function and the capacity configuration objective function based on the mathematical models of each energy flow conversion and storage device, and establish the constraints of the scheduling model objective function and the capacity configuration objective function. The scheduling model objective function is the minimum value of the sum of energy purchase cost, wind and solar curtailment amount and operation and maintenance cost, and the capacity configuration objective function is the minimum value of the sum of construction, operation and maintenance cost and carbon emission cost. The solver module is configured to use MATLAB's CPLEX solver to solve the objective function of the scheduling model and the objective function of capacity configuration, and obtain the optimal scheduling scheme and the optimal capacity configuration scheme.

6. A computer-readable storage medium having a program stored thereon, characterized in that, When executed by the processor, the program implements the steps in the wind-solar-hydrogen integrated energy optimization method that takes into account methanation and carbon capture as described in any one of claims 1-4.

7. An electronic device, comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the wind-solar-hydrogen integrated energy optimization method that takes into account methanation and carbon capture as described in any one of claims 1-4.

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