A method for operation optimization and benefit coordination planning of an integrated energy complementary coupling system

Abstract

This invention relates to the field of integrated energy system technology, specifically to a method for optimizing the operation and coordinating the benefits of a complementary and coupled integrated energy system. The method includes: constructing a three-layer architecture of electricity, hydrogen, and synthetic methane / methanol, sequentially coupled; then using trapezoidal function fuzzy parameters to describe the uncertainty of wind and solar power output, and performing fuzzy equivalent transformation based on confidence levels to obtain quantified wind and solar power forecast data; next, using economic efficiency, stability, and environmental performance as three optimization dimensions, and based on the deviation satisfaction function method, transforming the multi-objective optimization into a single-objective comprehensive satisfaction maximization problem to obtain the optimal system scheduling scheme; finally, constructing a two-layer benefit coordination planning model based on the improved Shapley value method, first performing a primary allocation among the three modules, and then a secondary allocation within each module. This improves system economics while effectively reducing wind and solar power curtailment and user energy consumption plan adjustments, achieving a fair distribution of benefits among multiple stakeholders.

Description

Technical Field

[0001] This invention relates to the field of integrated energy system technology, and in particular to a method for optimizing the operation and coordinating the benefits of integrated energy complementary coupling systems. Background Technology

[0002] Integrated energy systems, by integrating multiple energy conversion and storage technologies, can effectively mitigate the volatility of renewable energy and improve energy utilization efficiency. In recent years, the integrated energy complementary coupling system of electricity, hydrogen, methane, and methanol, as an emerging energy system architecture, has shown significant application prospects in improving the absorption of new energy sources and reducing dependence on traditional fossil fuels. Currently, preliminary research has been conducted on the operation optimization and benefit distribution of such systems, such as using scenario analysis or stochastic programming to handle the uncertainty of wind and solar power output, and establishing a multi-stakeholder benefit distribution mechanism based on cooperative game theory.

[0003] However, existing technologies still have the following shortcomings: On the one hand, some studies have not fully considered the uncertainty of wind and solar power output in the operation optimization of integrated energy complementary coupling systems, resulting in insufficient comprehensiveness and robustness of the optimization scheduling results; on the other hand, when the system involves multiple stakeholders (such as power generation units, energy storage units, load units, and chemical synthesis units), traditional benefit allocation methods, if directly calculated based on the number of stakeholders, are prone to falling into the curse of dimensionality. Moreover, existing allocation methods are often based only on economic benefit contributions, failing to take into account the actual impact of each stakeholder on the system's operational stability and environmental benefits, thus limiting the fairness and incentive effect of the allocation results. Summary of the Invention

[0004] The purpose of this invention is to provide a method for optimizing the operation and coordinating the benefits of a comprehensive energy complementary coupling system. It aims to construct an optimization method for the operation of a comprehensive energy complementary coupling system that takes into account the uncertainty of wind and solar power output, while taking into full account the economic, stability and environmental goals.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: The present invention provides a method for optimizing the operation and coordinating the benefits of a comprehensive energy complementary coupling system, comprising: S1: constructing an operation model for an electric power module, an operation model for a hydrogen energy module, and an operation model for a methane-methanol synthesis module, forming a three-layer coupling architecture of electric-hydrogen-methane-methanol consisting of an electric power module, a hydrogen energy module, and a methane-methanol synthesis module coupled sequentially. The electric power module supplies electricity to the hydrogen energy module through an electrolyzer. The hydrogen energy module produces hydrogen through an electrolyzer and then transports the surplus hydrogen to the methane-methanol synthesis module. The methane-methanol synthesis module reacts a portion of the hydrogen produced in the electrolyzer with carbon dioxide captured by a carbon capture device to produce methane and methanol. S2: using trapezoidal function fuzzy parameters to describe the uncertainty of wind power output and photovoltaic output, and performing fuzzy equivalent transformation on the predicted wind power output and predicted photovoltaic output according to a preset confidence level. S2: Obtain quantified wind and solar power output forecast data; S3: Using economic, stability, and environmental objectives as three optimization dimensions, based on the quantified wind and solar power output forecast data from step S2, solve the operation optimization model of the three-layer coupled architecture constructed in step S1 to obtain the optimal scheduling scheme of the integrated energy complementary coupled system. The economic objective is to maximize the difference between energy sales revenue and operating costs, the stability objective is to minimize the adjustment of user energy consumption plans, and the environmental objective is to minimize wind and solar curtailment; S4: Based on the optimal scheduling scheme obtained in step S3, construct a two-layer benefit coordination planning model based on the improved Shapley value method. In the first layer allocation, the total system revenue is allocated once among the power module, hydrogen module, and synthetic methane-methanol module. Then, in the second layer allocation, a secondary allocation is performed within each module to obtain the final benefit allocation result for each participating entity.

[0006] In step S2, the fuzzy parameters of the trapezoidal function are represented in quadruplet form: ;in, and Indicates the upper and lower limits of the parameter. and This represents the most likely value of the parameter; the numerical equivalent transformation of the fuzzy parameters of the trapezoidal function follows the formula: ;in, This represents the preset confidence level, with a value range of [0.5, 1].

[0007] In step S3, the multi-objective optimization is transformed into a single-objective comprehensive satisfaction maximization problem by using the deviation satisfaction function method. The single-objective comprehensive satisfaction is the weighted aggregate value of the three sub-objective satisfaction functions. Each sub-objective satisfaction function is calculated based on the optimal and worst values ​​of the sub-objective functions.

[0008] In step S4, the two-level benefit coordination planning model based on the improved Shapley value method introduces three dimensions: economic benefit contribution, stability benefit contribution, and environmental benefit contribution. The comprehensive allocation factor for each participating entity is calculated using the following formula: ;in, The comprehensive allocation factor for subject i, The contribution of entity i to economic benefits The contribution of the stability benefits to subject i. The contribution of environmental benefits to subject i. , These are the dimensional weight coefficients for the contribution to economic benefits, the contribution to stability benefits, and the contribution to environmental benefits, respectively.

[0009] In step S1, the power module operation model includes a coal-fired power unit operation mathematical model, a photovoltaic power unit operation mathematical model, a wind power unit operation mathematical model, a load reduction operation mathematical model, and a load transfer operation mathematical model. The power module supplies power to both the hydrogen energy module and the methane-methanol synthesis module while meeting the needs of the load users.

[0010] In step S1, the hydrogen energy module operation model includes the electrolyzer operation mathematical model, the hydrogen storage tank operation mathematical model, and the transferable hydrogen load operation mathematical model. The hydrogen energy module delivers surplus hydrogen to the methane-methanol synthesis module while meeting the needs of hydrogen load users.

[0011] The operating model of the methane-methanol synthesis module in step S1 includes the mathematical model of the carbon capture equipment, the mathematical model of the methane synthesis equipment, and the mathematical model of the methanol synthesis equipment. The carbon dioxide captured by the methane-methanol synthesis module comes from the atmosphere and carbon emissions from coal-fired power units.

[0012] In the numerical equivalent transformation step of the fuzzy parameters of the trapezoidal function, the input fuzzy equivalent data are used as the input data for step S3 to construct the output constraint and power balance constraint in the running optimization model.

[0013] The deviation satisfaction function method constructs a single-objective comprehensive satisfaction function according to the following formula: ;in, For multi-objective optimization, the aggregated total satisfaction is... , These are the weighting coefficients; The optimal value of the sub-objective function is... This represents the worst value of the sub-objective function.

[0014] In step S4, the first-level allocation is to distribute the total system revenue among the power module, hydrogen module, and methane-methanol synthesis module according to the comprehensive allocation factor. The second-level allocation is to distribute the module revenue among the participating entities within each module according to the comprehensive allocation factor. The participating entities include thermal power units, wind power units, photovoltaic units, electrolyzers, hydrogen storage tanks, users with transferable electricity load, users with reducible electricity load, users with transferable hydrogen load, carbon capture equipment, methanation reactors, and methanol synthesis equipment.

[0015] Compared with the prior art, this application has the following advantages: 1. This invention constructs a three-dimensional multi-objective operation optimization model with the core objectives of economic efficiency (maximizing the difference between energy sales revenue and operating costs), stability (minimizing adjustments to user energy consumption plans), and environmental efficiency (minimizing wind and solar curtailment). It transforms the multi-objective problem into a single-objective comprehensive satisfaction maximization problem using the deviation satisfaction function method. Compared to existing methods that only consider economic efficiency or employ single-objective optimization, this invention effectively reduces the adjustment range of user energy consumption plans and decreases wind and solar curtailment while pursuing economic benefits. It achieves synergistic optimization of the system's economic efficiency, stability, and environmental impact, thereby improving the overall operational quality of the integrated energy complementary coupling system.

[0016] 2. This invention employs trapezoidal function fuzzy parameters to model the uncertainties in wind and solar power output. Through a four-tuple representation and numerical equivalence transformation formula, it quantifies the predicted wind and solar power output based on different confidence levels. Compared to commonly used scenario analysis or stochastic programming methods in existing technologies, the trapezoidal fuzzy parameter method of this invention can more flexibly characterize the fluctuation range of wind and solar power output with less prior data. Furthermore, it directly embeds the quantified uncertain data into the output constraints and power balance constraints of the optimization model, significantly improving the adaptability and robustness of the optimized scheduling scheme to wind and solar uncertainties.

[0017] 3. This invention constructs a two-layer, multi-dimensional benefit coordination planning model based on an improved Shapley value method: the first layer allocates the total system benefits among the power module, hydrogen module, and methane-methanol synthesis module; the second layer performs secondary allocation within each module for each participating entity. This two-layer structure reduces the combined computational scale of the Shapley value method from a one-time allocation of all entities (complexity O(N!)) to the sum of the complexity of allocation within the three modules (O(N1!) + O(N2!) + O(N3!)), effectively solving the problem of dimensionality curse that easily occurs when there are too many participating entities. Simultaneously, this invention introduces three dimensions—economic benefit contribution, stability benefit contribution, and environmental benefit contribution—to calculate a comprehensive allocation factor. This ensures that benefit allocation is not only based on economic contribution but also reflects the actual contribution of each entity to the stable operation of the system and environmental improvement. Compared with existing allocation methods that rely solely on economic contribution or single-dimensional correction factors, the allocation results are fairer and more reasonable, promoting long-term stable cooperation among multiple entities.

[0018] 4. This invention integrates multiple stages, including renewable energy power generation, water electrolysis for hydrogen production, hydrogen storage, carbon capture, methane synthesis, and methanol synthesis, into a complete energy conversion and value-added chain by constructing a three-layer architecture that sequentially couples an electrical energy module, a hydrogen energy module, and a methane-methanol synthesis module. After meeting the hydrogen load demand, the hydrogen energy module transports surplus hydrogen to the downstream methane-methanol synthesis module, where it reacts with captured carbon dioxide to produce high-value-added methane and methanol. Compared with existing systems that only couple two stages, electricity-hydrogen or electricity-gas, this invention achieves three-stage energy value-added from electrical energy to hydrogen energy and then to chemical products, significantly improving the conversion efficiency of clean energy and the overall economic efficiency of the system. Attached Figure Description

[0019] Figure 1 This is a flowchart of a method for optimizing the operation and coordinating the benefits of a comprehensive energy complementary coupling system, provided in an embodiment of this application. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0021] In the description of the invention, it should be understood that the terms "upper," "lower," "left," "right," "front," "rear," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or relative positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Unless otherwise specified, the above-mentioned orientational descriptions can be flexibly set in practical applications, provided that the relative positional relationships shown in the accompanying drawings are satisfied.

[0022] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0023] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "communication" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection. They can refer to a direct connection or an indirect connection through an intermediate medium, or a communication between the internal components of two elements. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0024] In embodiments of the invention, the terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, article, or apparatus that includes that element.

[0025] In embodiments of the present invention, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" or "for example" in embodiments of the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Rather, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0026] Reference Figure 1 This application provides a method for optimizing the operation and coordinating the benefits of a comprehensive energy complementary coupling system, including: S1: Construct an operating model for the power module, a hydrogen module, and a methane-methanol synthesis module, forming a three-layer coupling architecture of electricity-hydrogen-methane-methanol, in which the power module, hydrogen module, and methane-methanol synthesis module are coupled sequentially. The power module supplies electricity to the hydrogen module through an electrolyzer. The hydrogen module produces hydrogen through an electrolyzer and then transports the excess hydrogen to the methane-methanol synthesis module. The methane-methanol synthesis module reacts a portion of the hydrogen produced in the electrolyzer with carbon dioxide captured by a carbon capture device to produce methane and methanol.

[0027] As one possible implementation, the power module operation model in step S1 includes a coal-fired power unit operation mathematical model, a photovoltaic power unit operation mathematical model, a wind power unit operation mathematical model, a load reduction operation mathematical model, and a load transfer operation mathematical model. The power module supplies power to both the hydrogen energy module and the methane-methanol synthesis module while meeting the needs of the load users.

[0028] For example, the power generation of a coal-fired power unit varies depending on the fuel input. The fuel consumption and power generation of a coal-fired power unit have a quadratic function relationship, as shown in the following formula:

[0029] in, for Output of coal-fired power units during specific periods The following figures represent coal consumption, where a, b, and c are the coal consumption coefficients of the coal-fired power unit. The output of the coal-fired power unit... Down Carbon dioxide emissions during the period for:

[0030] in, The carbon emission coefficient for standard coal is 0.67 tons of carbon per ton of standard coal, based on the values ​​released by the National Bureau of Statistics. The coefficient for carbon dioxide emissions per unit of carbon combustion is set at 3.67 tons of carbon dioxide per ton of carbon.

[0031] For example, the operating constraints of coal-fired power units include output constraints, ramp-up constraints, minimum continuous start-stop time constraints, and maximum number of start-stop cycles constraints. Specifically: Coal-fired power units during the period Output constraints:

[0032] Coal-fired power units during the period Climbing constraints:

[0033]

[0034] Coal-fired power units during the period Continuous start-stop time constraints:

[0035]

[0036]

[0037]

[0038] In the formula: , These are the maximum and minimum outputs of the coal-fired power unit, respectively. The unit during the period The running state is an integer variable between 0 and 1. =1 indicates that the coal-fired power unit is in Operating during specific time periods Indicates that coal-fired power units are in Service interruption during certain periods; , These represent the maximum upward and downward climbing rates of the coal-fired power unit, respectively. For coal-fired power units Time-limited power-on action, =1 indicates a switch from shutdown to startup; For the unit in Time-limited shutdown operation, This indicates a switch from power-on to power-off. , These are the minimum continuous start-up and minimum continuous shutdown times for thermal power units, respectively.

[0039] For example, the actual amount of photovoltaic power absorbed is usually less than the power generated, resulting in curtailment of solar power, as detailed below:

[0040]

[0041] in, This refers to the photovoltaic power generation capacity and actual consumption. This refers to the amount of light discarded. The solar radiation efficiency during time period t; The solar radiation area during time period t; Let be the solar radiation intensity at time t, which can be described by a Beta distribution; The actual light intensity during time period t; This represents the maximum solar irradiance for photovoltaic systems. It is the Gamma function; , The shape parameter of the Beta distribution; These represent the mean and standard deviation of the light intensity, respectively.

[0042] The actual amount of wind power absorbed is usually less than the generating capacity, resulting in wind curtailment, as detailed below:

[0043]

[0044] in, , The wind turbine's power generation and actual power consumption at time t; For the amount of wind curtailed; when or In the case of ;when In the case of ;when In this case, ; These refer to wind power cut-in, cut-out, and rated wind speed, respectively. This refers to the rated power of the wind power.

[0045] As one possible implementation, the hydrogen energy module operation model in step S1 includes an electrolyzer operation mathematical model, a hydrogen storage tank operation mathematical model, and a transferable hydrogen load operation mathematical model. The hydrogen energy module delivers surplus hydrogen to the methane-methanol synthesis module while meeting the needs of hydrogen load users.

[0046] For example, transferable electrical loads must meet upper and lower limits for reduction, cumulative reduction limits, and minimum continuous reduction time constraints, as detailed below:

[0047] in, To reduce the amount of electrical load; This represents the maximum amount of electrical load that can be reduced. The state of the reduced electrical load is a 0-1 variable; This is the minimum continuous operating time to reduce electrical load.

[0048] Transferable electrical loads must meet constraints on upper and lower limits of transfer power, transfer power balance, mutual exclusion of transfer states, and minimum continuous operating time, as detailed below:

[0049] in, , This refers to the amount of transferable electrical load entering and leaving the system. This represents the maximum amount of transferable electrical load that can be transferred in and out. These are the state variables for the transfer of electrical loads into and out of the system. This is the minimum continuous operating time for transferable electrical loads.

[0050] Electrolyzers enable the rapid conversion of electrical energy into hydrogen energy, as detailed below:

[0051] in, The figures represent the hydrogen production volume, hydrogen production efficiency, and input power of the electrolyzer during time period t. These are the maximum input power and ramp limit of the electrolytic cell, respectively. These are the coefficients of the quadratic, linear, and constant terms of the rated power and conversion efficiency of the electrolytic cell, respectively.

[0052] For example, the operation of a hydrogen storage tank must meet constraints on power, hydrogen storage capacity, and operating status, as detailed below:

[0053] in, Hydrogen charging / discharging power and hydrogen storage capacity of the hydrogen storage tank; Hydrogen storage tank filling and discharging efficiency; The maximum hydrogen charging / discharging power of the hydrogen storage tank; These represent the maximum and minimum hydrogen storage capacity of the hydrogen storage tank. The hydrogen storage tank is a 0-1 variable representing the hydrogen charging and discharging state.

[0054] The transferable hydrogen load must meet the following constraints: upper and lower limits of transfer power, transfer power balance, mutual exclusion of transfer states, and transfer time period.

[0055] in, , This refers to the amount of transferable hydrogen load transferred in and out; This represents the maximum amount of hydrogen load that can be transferred in and out. , The 0-1 variables represent the transferable hydrogen load input and output states; The start and end times for the permissible transfer of transferable hydrogen load; The start and end times for the transferable hydrogen load to be transferred out.

[0056] As one possible implementation, the operating model of the methane-methanol synthesis module in step S1 includes a mathematical model of the carbon capture equipment, a mathematical model of the methane synthesis equipment, and a mathematical model of the methanol synthesis equipment. The carbon dioxide captured by the methane-methanol synthesis module comes from the atmosphere and carbon emissions from coal-fired power units.

[0057] The carbon captured by the methane-methanol synthesis module system originates from atmospheric and thermal power unit carbon emissions. After synthesizing methane and methanol, these can be sold through pipelines for profit. For example, the energy consumption for carbon capture operation includes both stationary energy consumption and carbon capture energy consumption. Its operation must meet energy consumption and ramp-up constraints, as detailed below:

[0058] in, , , Energy consumption for carbon capture operation, carbon capture capacity, and stationary energy consumption; The energy consumption required to capture a unit volume of carbon dioxide using carbon capture and sequestration. The carbon capture start / stop state is represented by a 0-1 variable; This represents the maximum energy consumption and ramp-up limit for carbon capture operations.

[0059] The methanation reactor chemically reacts a portion of the hydrogen generated in the electrolyzer with CO2 captured by the carbon capture device to produce methane. Its operation must meet energy consumption and ramp-up constraints, as detailed below:

[0060] in, The input electrical power and consumption of the methanation reactor during time period t are respectively... Volume, volume of hydrogen consumed, and volume of methane produced; The operating efficiency of the methanation reactor; This is the lower heating value of methane; These are the maximum input power, ramp-up limit, and consumption of the methanation reactor, respectively. The maximum value of the volume.

[0061] The operation of methanol synthesis equipment must meet energy consumption and ramp-up constraints, as detailed below:

[0062] in, These are the operating energy consumption, synthesized alcohol quantity, and hydrogen consumption of the alcohol synthesis equipment, respectively. This refers to the energy consumption for synthesizing a unit volume of methanol in a synthetic alcohol equipment. This represents the maximum energy consumption and ramp-up limit for the alcohol synthesis equipment.

[0063] S2: The uncertainty of wind power output and photovoltaic output is described by trapezoidal function fuzzy parameters. Based on the preset confidence level, the predicted wind power output and photovoltaic output are subjected to fuzzy equivalent transformation to obtain quantified wind and solar power output prediction data.

[0064] To address the prediction errors in wind and solar power output and ensure the safe and stable operation of the system, a trapezoidal function fuzzy parameter is used to describe the uncertainties in wind and solar power output within the system.

[0065] in, Membership function; The membership parameter determines the shape of the membership function. The membership parameter can be determined based on historical statistical values. and Indicates the upper and lower limits of the parameter. and This indicates the most likely value for the parameter.

[0066] For example, the fuzzy parameters of the trapezoidal function in step S2 are represented in the form of a quadruple: The numerical equivalent transformation of the fuzzy parameters of the trapezoidal function is performed according to the formula: ;in, This represents the preset confidence level, with a value range of [0.5, 1].

[0067] Therefore, the predicted output of photovoltaic power can be expressed as follows (the same applies to wind power):

[0068]

[0069] in, ; This is the proportionality coefficient. .

[0070] In the numerical equivalent transformation step of the fuzzy parameters of the trapezoidal function, the input fuzzy equivalent data are used as the input data for step S3 to construct the output constraint and power balance constraint in the running optimization model.

[0071] S3: Using economic, stability, and environmental objectives as the three optimization dimensions, based on the wind and solar power output prediction data quantified in step S2, solve the operation optimization model of the three-layer coupled architecture constructed in step S1 to obtain the optimal scheduling scheme of the integrated energy complementary coupled system. The economic objective is to maximize the difference between energy sales revenue and operating costs, the stability objective is to minimize the adjustment of user energy consumption plans, and the environmental objective is to minimize the amount of wind and solar curtailment.

[0072] For example, the economic advantages of a comprehensive energy complementary coupling system are reflected in the maximum difference between energy sales revenue and operating costs; its stability is reflected in the minimum adjustment required for users' energy consumption plans; and its environmental benefits are reflected in the minimum amount of wind and solar curtailment, as detailed below:

[0073]

[0074]

[0075]

[0076]

[0077] in, The operating costs and energy sales revenue of the integrated energy complementary coupling system; This refers to the fuel price coefficient for thermal power units. This refers to the operating cost coefficient for wind power and photovoltaic units. It serves as a compensation coefficient for the adjustment of transferable electricity, electricity reduction, and hydrogen load; This is the operating cost coefficient for the electrolytic cell; Cost coefficient for filling and discharging hydrogen into hydrogen storage tanks; , Operating cost coefficients for carbon capture, methane synthesis, and methanol synthesis equipment; The clearing price for the electricity and hydrogen energy markets; Electricity purchase and sale for a comprehensive energy complementary coupling system; The amount of hydrogen purchased and sold for the integrated energy complementary coupling system; For the price of selling methane, The price of methanol for sale.

[0078] The following constraints must be met: 1. Power balance constraint: The operation of the integrated energy complementary coupling system must meet the power balance constraints of electricity and hydrogen, as follows:

[0079]

[0080]

[0081] in, The actual electricity and hydrogen consumption of electricity and hydrogen load users; Plan electricity and hydrogen consumption for electricity and hydrogen load users before demand response.

[0082] Energy trading constraints: Integrated energy complementary coupling systems participating in electricity and hydrogen energy market transactions must meet trading volume and trading status constraints, as follows:

[0083]

[0084] in, The maximum traded electricity and hydrogen volume for the integrated energy complementary coupling system; For the state variables of electricity purchase and sale; This refers to the state variables for purchasing and selling hydrogen.

[0085] As one possible implementation, in step S3, the multi-objective optimization is transformed into a single-objective comprehensive satisfaction maximization problem by using the deviation satisfaction function method. The single-objective comprehensive satisfaction is the weighted aggregate value of the three sub-objective satisfaction functions, and each sub-objective satisfaction function is calculated based on the optimal and worst values ​​of the sub-objective functions.

[0086] The deviation satisfaction function method is a mathematical approach for multi-objective optimization and decision-making. Its core idea is to define a satisfaction function corresponding to the deviation of each objective from its ideal value, and then aggregate multiple satisfaction levels into a total satisfaction level through weighted or combined methods. This transforms the multi-objective problem into a single-objective problem. This method is flexible and intuitive in handling conflicts between objectives and inconsistencies in measurement, as detailed below:

[0087] in, represents the aggregated total satisfaction of the multi-objective optimization model; 𝜔 represents the weighting coefficients; The optimal value of the sub-objective function is... This represents the worst value of the sub-objective function.

[0088] S4: Based on the optimal scheduling scheme obtained in step S3, a two-level benefit coordination planning model based on the improved Shapley value method is constructed. In the first-level allocation, the total system benefit is allocated among the power module, hydrogen module, and methane-methanol synthesis module. Then, in the second-level allocation, a secondary allocation is carried out within each module to obtain the final benefit allocation result of each participating entity.

[0089] As one possible implementation, in step S4, the two-level benefit coordination planning model based on the improved Shapley value method introduces three dimensions: economic benefit contribution, stability benefit contribution, and environmental benefit contribution. The comprehensive allocation factor for each participating entity is calculated using the following formula: ;in, The comprehensive allocation factor for subject i, The contribution of entity i to economic benefits The contribution of the stability benefits to subject i. The contribution of environmental benefits to subject i. , These are the dimensional weight coefficients for the contribution to economic benefits, the contribution to stability benefits, and the contribution to environmental benefits, respectively.

[0090] For example, the economic dimension:

[0091] in, as the main body The economic benefit contribution of S; S represents the current alliance; The total number of alliance members; This represents the number of entities in the current alliance. as the main body Net cost after joining Alliance S; For the alliance Remove the main body Net cost after; For economic factors.

[0092] The analysis of the distribution of benefits between the stability dimension and the environmental dimension is similar to the above.

[0093] Stability dimension:

[0094] in, as the main body The amount of stable benefit contribution; as the main body Adjustments to user energy consumption plans after joining Alliance S; For the alliance Remove the main body Adjustments to user energy consumption plans following this; It is a stabilizing factor.

[0095] Environmental dimension:

[0096] in, as the main body The environmental benefits contributed by; as the main body The amount of wind and solar power curtailed after joining Alliance S; For the alliance Remove the main body The amount of wind and solar power curtailed afterward; Environmental factors.

[0097] As one possible implementation, in step S4, the first-level allocation is to distribute the total system revenue among the power module, hydrogen module, and methane-methanol synthesis module according to a comprehensive allocation factor. The second-level allocation is to distribute the module revenue among the participating entities within each module according to a comprehensive allocation factor. The participating entities include thermal power units, wind power units, photovoltaic units, electrolyzers, hydrogen storage tanks, users with transferable electricity load, users with reducible electricity load, users with transferable hydrogen load, carbon capture equipment, methanation reactors, and methanol synthesis equipment.

[0098] It should be understood that before implementing the method provided in the embodiments of this application, it is necessary to input various basic parameters of the integrated energy complementary coupling system, including but not limited to: power generation equipment parameters (coal consumption coefficient, output upper and lower limits, ramp rate, carbon emission coefficient of thermal power units; rated power, operating cost coefficient, cut-in / cut-out / rated wind speed, irradiance Beta distribution parameters, etc. of wind turbines and photovoltaic units), energy storage equipment parameters (rated power, efficiency curve, ramp rate upper limit of electrolyzers; capacity upper and lower limits, hydrogen charging and discharging efficiency, hydrogen charging and discharging power upper and lower limits of hydrogen storage tanks), and load-side parameters (adjustment compensation coefficients of transferable and reducible electrical loads, transfer...). / Reduction limits, minimum continuous operating time; similar parameters for transferable hydrogen load), downstream synthesis module parameters (fixed energy consumption and unit carbon capture energy consumption of carbon capture equipment; operating efficiency and energy consumption coefficient of methane and methanol synthesis equipment), grid parameters (clearing prices of electricity and hydrogen energy markets; selling prices of methane and methanol), forecast data (wind power output forecast curves, photovoltaic power output forecast curves, electricity load forecast curves, and hydrogen load forecast curves for typical days), trapezoidal fuzzy parameters (quaternion parameters and confidence levels of wind power and photovoltaic power output), optimization parameters (weighting coefficients of multi-objective satisfaction functions and dimensional weighting coefficients of benefit allocation models). By executing steps S1 to S4, the optimal scheduling scheme is output (including the output of thermal power units, actual wind and solar power consumption, electrolyzer input power, hydrogen storage tank charging and discharging power, carbon capture, methane and methanol production, electricity / hydrogen purchase and sale, and load adjustment amount that can be transferred / reduced, etc.), the benefit allocation results of each entity (the final revenue value of each participating entity after the two-level allocation), and the comprehensive performance indicators of the system (including total energy sales revenue, total operating cost, total wind and solar curtailment, total adjustment amount of user energy consumption plan, and aggregated overall satisfaction value).

[0099] In the description of this specification, specific features, structures, materials, or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0100] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for operation optimization and benefit coordination planning of an integrated energy complementary coupling system, characterized in that, include: S1: Construct operation models for the power module, hydrogen module, and methane-methanol synthesis module, forming a three-layer coupled architecture of electricity-hydrogen-methane-methanol, where the power module supplies electricity to the hydrogen module via an electrolyzer. The hydrogen module produces hydrogen through the electrolyzer and then supplies excess hydrogen to the methane-methanol synthesis module. The methane-methanol synthesis module reacts a portion of the hydrogen produced by the electrolyzer with carbon dioxide captured by a carbon capture device to produce methane and methanol. S2: Use trapezoidal function fuzzy parameters to describe wind power output and solar power output. To address the uncertainty in power output, a fuzzy equivalent transformation is performed on the predicted wind and solar power outputs based on a preset confidence level to obtain quantified wind and solar power output prediction data. S3: Using economic, stability, and environmental objectives as three optimization dimensions, and based on the quantified wind and solar power output prediction data from step S2, the operation optimization model of the three-layer coupled architecture constructed in step S1 is solved to obtain the optimal scheduling scheme for the integrated energy complementary coupled system. The economic objective is to maximize the difference between energy sales revenue and operating costs; the stability objective is to minimize the adjustment amount to user energy consumption plans; and the environmental objective is to minimize wind and solar power curtailment. S4: Based on the optimal scheduling scheme obtained in step S3, a two-level benefit coordination planning model based on the improved Shapley value method is constructed. In the first-level allocation, the total system benefit is allocated among the power module, the hydrogen module, and the synthetic methane-methanol module. Then, in the second-level allocation, a secondary allocation is performed within each module to obtain the final benefit allocation result for each participating entity.

2. The method for operation optimization and benefit coordination planning of a comprehensive energy complementary coupling system according to claim 1, characterized in that, In step S2, the fuzzy parameters of the trapezoidal function are represented in quadruplet form: ;in, and Indicates the upper and lower limits of the parameter. and This represents the most likely value of the parameter; the numerical equivalent transformation of the fuzzy parameters of the trapezoidal function is according to the formula: ;in, This represents the preset confidence level, with a value range of [0.5, 1].

3. The method for operation optimization and benefit coordination planning of a comprehensive energy complementary coupling system according to claim 1, characterized in that, In step S3, the multi-objective optimization is transformed into a single-objective comprehensive satisfaction maximization problem by using the deviation satisfaction function method. The single-objective comprehensive satisfaction is the weighted aggregate value of the three sub-objective satisfaction functions, and each sub-objective satisfaction function is calculated based on the optimal and worst values ​​of the sub-objective functions.

4. The method for operation optimization and benefit coordination planning of a comprehensive energy complementary coupling system according to claim 1, characterized in that, In step S4, the two-level benefit coordination planning model based on the improved Shapley value method introduces three dimensions: economic benefit contribution, stability benefit contribution, and environmental benefit contribution, to calculate the comprehensive allocation factor for each participating entity. The comprehensive allocation factor is calculated according to the following formula: ;in, The comprehensive allocation factor for subject i, The contribution of entity i to economic benefits The contribution of the stability benefits to subject i. The contribution of environmental benefits to subject i. , These are the dimensional weighting coefficients for the contribution of economic benefits, the contribution of stability benefits, and the contribution of environmental benefits, respectively.

5. The method for operation optimization and benefit coordination planning of a comprehensive energy complementary coupling system according to claim 1, characterized in that, The power module operation model in step S1 includes a coal-fired power unit operation mathematical model, a photovoltaic power unit operation mathematical model, a wind power unit operation mathematical model, a load reduction operation mathematical model, and a load transfer operation mathematical model. The power module supplies power to both the hydrogen energy module and the synthetic methane-methanol module while meeting the needs of the load users.

6. The method for operation optimization and benefit coordination planning of a comprehensive energy complementary coupling system according to claim 1, characterized in that, The hydrogen energy module operation model in step S1 includes an electrolyzer operation mathematical model, a hydrogen storage tank operation mathematical model, and a transferable hydrogen load operation mathematical model. The hydrogen energy module delivers surplus hydrogen to the methane-methanol synthesis module while meeting the needs of hydrogen load users.

7. The method for operation optimization and benefit coordination planning of a comprehensive energy complementary coupling system according to claim 1, characterized in that, The operating model of the methane-methanol synthesis module in step S1 includes a mathematical model for the operation of the carbon capture equipment, a mathematical model for the operation of the methane synthesis equipment, and a mathematical model for the operation of the methanol synthesis equipment. The carbon dioxide captured by the methane-methanol synthesis module comes from the atmosphere and carbon emissions from the coal-fired power unit.

8. The method for operation optimization and benefit coordination planning of a comprehensive energy complementary coupling system according to claim 2, characterized in that, In the numerical equivalent transformation step of the fuzzy parameters of the trapezoidal function, the input fuzzy equivalent data are used as the input data for step S3 to construct the output constraint and power balance constraint in the running optimization model.

9. The method for operation optimization and benefit coordination planning of a comprehensive energy complementary coupling system according to claim 3, characterized in that, The deviation satisfaction function method constructs a single-objective comprehensive satisfaction function according to the following formula: ;in, For multi-objective optimization of aggregated total satisfaction, , These are the weighting coefficients; The optimal value of the sub-objective function is... This represents the worst value of the sub-objective function.

10. The method for operation optimization and benefit coordination planning of a comprehensive energy complementary coupling system according to claim 1, characterized in that, In step S4, the first-level allocation is to distribute the total system revenue among the power module, the hydrogen module, and the methane-methanol synthesis module according to the comprehensive allocation factor. The second-level allocation is to distribute the module revenue among the participating entities within each module according to the comprehensive allocation factor. The participating entities include thermal power units, wind power units, photovoltaic units, electrolyzers, hydrogen storage tanks, users with transferable electricity load, users with reducible electricity load, users with transferable hydrogen load, carbon capture equipment, methanation reactors, and methanol synthesis equipment.

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