CN-121981422-A - Wind power hydrogen production and methanation system scheduling method, system, equipment and medium considering uncertainty and carbon constraint

CN121981422ACN 121981422 ACN121981422 ACN 121981422ACN-121981422-A

Abstract

The invention relates to the technical field of renewable energy and power system scheduling, and discloses a wind power hydrogen production and methanation system scheduling method, system, equipment and medium considering uncertainty and carbon constraint. The method comprises the steps of constructing a multi-energy coupling system model comprising wind power, an electrolytic tank, a methanation device, a thermal power generating unit and carbon capture equipment, adopting fuzzy opportunity constraint planning to process uncertainty of wind power and load, converting fuzzy constraint into a clear equivalent form through confidence level, introducing a reward and punishment ladder type carbon transaction mechanism on the basis, dynamically adjusting carbon price according to the difference between actual carbon emission and quota, and finally integrating investment, operation and maintenance, resource transaction and carbon transaction cost with the minimum total cost of the whole life cycle of the system as a target, and establishing an optimization model and solving to obtain the optimal scheduling instruction of each equipment. The invention improves the economical efficiency, reliability and low-carbon synergy of the system under uncertain environment and carbon constraint.

Inventors

HAN ZIJIAO
GAO JIAWEN
HU JINGWEI
WANG YANG
LI YONGRUI
Lu Sichen
ZHANG YANNI
BAI JIANSHI
LIU RENHAN
HU JINJING

Assignees

国网辽宁省电力有限公司

Dates

Publication Date: 20260505
Application Date: 20251205

Claims (10)

1. A wind power hydrogen production and methanation system scheduling method taking uncertainty and carbon constraint into consideration is characterized by comprising the following steps of, Constructing a wind power hydrogen production and methanation system, determining initial parameters of each device of the system, and constructing a mathematical model; based on initial parameters and a mathematical model, adopting a fuzzy opportunity constraint planning method to obtain an uncertainty analysis result of wind power output and electric load; An uncertainty model is built according to an uncertainty analysis result of wind power output and electric load; based on the uncertainty model, setting a confidence level, and converting the uncertainty constraint into a clear equivalence class; Dividing intervals according to the difference between the actual carbon emission and the initial quota and setting a reward and punishment coefficient to adjust the carbon transaction price according to constraint conversion; And establishing an objective function with the minimum total cost of the whole life cycle of the system as a target through carbon transaction price, and optimizing and solving to obtain an optimal scheduling instruction of each device in the system.
2. The wind power hydrogen production and methanation system scheduling method considering uncertainty and carbon constraint as claimed in claim 1, wherein the steps of constructing the wind power hydrogen production and methanation system, determining initial parameters of each device of the system, and establishing a mathematical model comprise, The electric power output of the wind turbine generator is connected to an electrolytic tank device for hydrogen production, and the produced hydrogen and carbon dioxide captured by a carbon capture device from a thermal power generating unit are jointly conveyed to a methanation device for reaction to obtain methane; initial parameters of all equipment of the system are determined, and a mathematical model of wind power hydrogen production and methanation is established.
3. The wind power hydrogen production and methanation system scheduling method considering uncertainty and carbon constraint as claimed in claim 2, wherein the method for scheduling wind power hydrogen production and methanation system is characterized in that the method for scheduling wind power output and electric load uncertainty is obtained by adopting a fuzzy opportunity constraint programming method based on initial parameters and mathematical models, and comprises the following steps of, And analyzing uncertainty of wind power output and electric load by adopting a fuzzy opportunity constraint method, and converting the uncertainty problem into a deterministic problem by adopting a possibility measure.
4. A wind power hydrogen production and methanation system scheduling method considering uncertainty and carbon constraint as claimed in claim 3, wherein the uncertainty model is constructed by the uncertainty analysis result of wind power output and electric load, and comprises, And calculating four key parameter values of the trapezoidal membership function by using the proportionality coefficient obtained by statistics of historical data with the predicted value of wind power output and electric load as a reference, and constructing an uncertainty model.
5. The wind power hydrogen production and methanation system scheduling method considering uncertainty and carbon constraints as claimed in claim 4, wherein the step of setting a confidence level based on an uncertainty model to convert the uncertainty constraints into clear equivalence classes comprises, Under the set confidence level, the relation between the fuzzy variable and the constraint boundary is defined by defining an auxiliary function, so that the original opportunity constraint condition is equivalently converted into a group of linear inequality constraint on the decision variable; The power balancing opportunity constraint expression is: Wherein, the Indicating the degree of confidence of the event, As a fuzzy parameter of the load, The complementary output of the thermal power generating unit when the wind power is insufficient, Is the first Fuzzy parameters of the output of each wind turbine generator, Is a confidence level; because the uncertainty processing capability is embedded in the fuzzy parameters, rotation standby constraint is not required to be set independently, and the constraint expression is as follows: The accurate power constraint of the system operation comprises an equality constraint and an inequality constraint, describes the actual power flow relation, and has the expression: Wherein, the Is a system A reference predicted value of the electrical load at the moment, And Respectively systems Prediction errors of the electric load and the wind power output at the moment, Is a system The air quantity is discarded at the moment, Is that Reference predicted value of wind power output at moment, Is that The carbon capture and the sealing device can collect and store the power consumption at any time, Is that The power consumption of the methanation device at the moment, Is that The power consumption of the alkaline electrolyzer is always equal to that of the prior art.
6. The wind power hydrogen production and methanation system scheduling method considering uncertainty and carbon constraint as claimed in claim 5, wherein the dividing the interval according to the constraint conversion and the difference between the actual carbon emission and the initial quota, setting a reward and punishment coefficient to adjust the carbon trade price comprises, And introducing a reward and punishment stepped carbon transaction mechanism, dividing the difference between the actual carbon emission of the system and the initial free quota, and setting a differentiated carbon transaction price calculation rule.
7. The method for scheduling the wind power hydrogen production and methanation system taking uncertainty and carbon constraint into consideration as claimed in claim 6, wherein the method for scheduling the wind power hydrogen production and methanation system by carbon transaction price establishes an objective function with the minimum total cost of the whole life cycle of the system as a target, and optimally solves to obtain an optimal scheduling instruction of each device in the system, and comprises the following steps of, The mathematical expression with minimized total cost of the whole life cycle is formed by integrating the annual value of the initial investment cost of the equipment, the operation maintenance cost, the resource transaction cost formed by the coal purchase cost and the electricity and gas selling income and the carbon transaction cost; and taking the lowest cost of the full life cycle as an objective function, incorporating various constraint conditions, and adopting a solver to carry out iterative optimization to obtain an optimal scheduling instruction of each device in the system.
8. A wind power hydrogen production and methanation system scheduling system taking uncertainty and carbon constraint into consideration, a method for scheduling a wind power hydrogen production and methanation system taking uncertainty and carbon constraint into consideration as claimed in any one of claims 1-7, comprising: the system modeling module is used for constructing a physical structure of the wind power hydrogen production and methanation system, determining initial parameters of all equipment and establishing a mathematical model of the system; The uncertainty modeling module is used for analyzing the uncertainty of the wind power output and the electric load by adopting a fuzzy opportunity constraint planning method and constructing an uncertainty model; The constraint conversion module converts uncertainty constraint into a clear equivalent mathematical expression under a set confidence level; The carbon transaction pricing module is used for dividing intervals and setting reward and punishment coefficients according to the difference value between the actual carbon emission and the initial free quota, and dynamically adjusting the carbon transaction price; The optimization solving module is used for establishing an objective function with the minimum total cost of the whole life cycle of the system as a target, integrating investment cost, running cost, carbon transaction cost and the like, adopting an optimization algorithm to solve, and outputting an optimal scheduling instruction of each device The scheduling instruction execution module converts the scheduling instruction output by the optimization solving module into an actual control signal, and transmits the actual control signal to each execution device, and the system performs real-time scheduling and operation control.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of a wind power hydrogen production and methanation system scheduling method taking into account uncertainty and carbon constraints as defined in any one of claims 1 to 7.
10. A computer readable storage medium having stored thereon a computer program, characterized in that the computer program when executed by a processor implements the steps of a wind power hydrogen production and methanation system scheduling method taking into account uncertainty and carbon constraints according to any one of claims 1 to 7.

Description

Wind power hydrogen production and methanation system scheduling method, system, equipment and medium considering uncertainty and carbon constraint Technical Field The invention relates to the technical field of renewable energy comprehensive utilization and power system scheduling, in particular to a wind power hydrogen production and methanation system scheduling method, system, equipment and medium considering uncertainty and carbon constraint. Background With the continuous acceleration of global energy transformation and industrial decarburization processes, the renewable energy source with fluctuation represented by wind power is connected into a power grid in a large scale, and meanwhile, green energy carriers such as hydrogen energy, methane and the like are used as important energy storage and chemical raw materials, so that the co-production and high-efficiency utilization of the renewable energy source become a key path for constructing a clean low-carbon, safe and high-efficiency energy system. Under the background, the wind power hydrogen production and methanation system is used as a typical 'electricity-hydrogen-carbon-gas' multi-energy flow coupling system, and the optimal scheduling of the system faces multiple challenges such as strong uncertainty of wind and light output, imperfect carbon constraint mechanism, difficult coordination of economy and low carbon property and the like. The existing scheduling method for the wind power hydrogen production and methanation system mainly has the following problems that firstly, the prior art is limited in treatment of wind power and load uncertainty, most of the prior art relies on prediction precision to be improved, or a too conservative robust optimization method is adopted, the former is difficult to ensure reliability in actual operation, the latter sacrifices system economy, effective balance of operation safety and economy in uncertain environments cannot be achieved, secondly, in terms of a carbon constraint mechanism, a traditional carbon punishment model is a single fixed price mode, the cost cannot be dynamically adjusted according to actual emission level, the guiding effect on low-carbonization operation of the system is limited, the system cannot adapt to the refined scheduling requirement in a marketized carbon transaction environment, finally, the prior scheduling strategy often separates uncertainty treatment, carbon cost calculation and operation optimization, and lacks an integrated modeling and solving framework, so that scheduling response of the system is not consistent when coping with source load fluctuation and carbon constraint, and integral optimization of full life cycle cost and carbon emission is difficult to achieve. Therefore, when the existing method is used for coping with double challenges of high-volatility renewable energy sources and strict carbon constraints, the cooperative optimization of economic dispatch and low-carbon operation is difficult to realize while the operation reliability of the system is ensured, and an integrated dispatch strategy which can integrate uncertainty analysis and a stepped carbon transaction mechanism and has stronger adaptability and economy is needed. Disclosure of Invention In view of the existing problems, the invention provides a scheduling method, a scheduling system, a scheduling equipment and a scheduling medium for a wind power hydrogen production and methanation system, which take uncertainty and carbon constraint into consideration. Therefore, the invention solves the technical problem of how to realize multi-objective collaborative optimization of system economy, low carbon and operation reliability by constructing an integrated optimization scheduling model of an electric-hydrogen-carbon-methane multi-energy flow coupling system fused with a stepped carbon transaction mechanism and integrating an uncertainty processing method combining robustness and adaptability under the multiple challenges of strong uncertainty of wind and light output, load fluctuation and dynamic change of a carbon transaction market. In order to solve the technical problems, the invention provides the following technical scheme that the scheduling method of the wind power hydrogen production and methanation system taking uncertainty and carbon constraint into consideration comprises the following steps of, Constructing a wind power hydrogen production and methanation system, determining initial parameters of each device of the system, and constructing a mathematical model; based on initial parameters and a mathematical model, adopting a fuzzy opportunity constraint planning method to obtain an uncertainty analysis result of wind power output and electric load; An uncertainty model is built according to an uncertainty analysis result of wind power output and electric load; based on the uncertainty model, setting a confidence level, and converting uncertainty constraint into clear equivalence cla