CN-122022222-A - Virtual power plant leading building group operation management method based on Stackelberg game

CN122022222ACN 122022222 ACN122022222 ACN 122022222ACN-122022222-A

Abstract

The invention discloses a virtual power plant leading building group operation management method based on a Stackelberg game, and relates to the technical field of power dispatching optimization. The method solves the decisions of each main body by using the improved multi-objective genetic algorithm of the nested linear programming, so that the economic benefits of the virtual power plant and the building groups are ensured, and meanwhile, the virtual power plant can consider the energy supply economy and simultaneously take the multiple objectives of reliability and high efficiency into consideration. Finally, in order to cope with the difference of energy utilization habit and energy utilization characteristics of the building group comprehensive energy systems in different regions, the method introduces a pareto optimal solution set weighting coefficient solver, and improves universality of the method for management of the actual decentralized building group comprehensive energy systems.

Inventors

WANG HAIYAN
LI WEI
LI DONG
ZHANG QI
FAN XIANSHEN
ZHOU XIANGYU
LI JUAN
QIN ZHENYI
ZHANG JINGRU
LIU TIANYU
XUAN SHIPENG

Assignees

国网山东省电力公司济宁供电公司

Dates

Publication Date: 20260512
Application Date: 20251120

Claims (10)

1. The utility model provides a virtual power plant dominant building group operation management method based on a Stackelberg game, which is characterized by comprising the following steps: s1, building a virtual power plant game framework through a Stackelberg game according to a virtual power plant and building group comprehensive energy system; S2, establishing a multi-objective operation optimization model through the virtual power plant game framework according to an operation optimization objective, wherein the operation optimization objective comprises active power loss factors accumulated in branch transmission, average voltage drop factors of all nodes and interaction cost factors of the virtual power plant game framework and all building group comprehensive energy systems; s3, according to real-time electricity price decisions of the virtual power plant, the virtual power plant feels through self supply-demand, and an operation optimization model of the building group comprehensive energy system is built; S4, carrying out coefficient coupling processing through a pareto optimal solution set weighting coefficient solver according to the operation optimization target; S5, establishing a Stackelberg game model through participants, game strategies and utility functions according to the virtual power plant game framework; And S6, solving the optimal decision of each main body through a multi-objective genetic algorithm of a nested linear programming solver according to the Stackelberg game model.
2. The method according to claim 1, wherein S4 comprises: s41, according to the operation optimization target, performing min-max standardization processing and performing linear mapping on minimum-maximum data within a range of 0-1 to realize standardization processing; s42, according to the standardized operation optimization target, the electric energy interaction direction of the virtual power plant is simulated by multiplying the electric energy interaction direction by the pareto optimal solution set weighting coefficient.
3. The method of claim 1, wherein in S6, according to the tuckelberg game model, the upper virtual power plant is solved and the pareto optimal solution set weighting coefficients are nested through a multi-objective genetic algorithm, and the pareto solution set is subjected to optimal population selection.
4. The method according to claim 1, wherein in S6, linear programming management is performed on the lower building group through a multi-objective genetic algorithm according to the tuckelberg game model, and the optimal decision result of each main body is used as an optimization constraint condition of other main bodies to perform a mutual game.
5. A virtual power plant-dominated architecture group operation management device based on a jackbelg game, the device comprising: the framework building module is used for building a virtual power plant game framework through a Stackelberg game according to the virtual power plant and the building group comprehensive energy system; the target model module is used for establishing multiple targets through the virtual power plant game framework according to an operation optimization target, wherein the operation optimization target comprises active power loss factors accumulated in branch transmission, average voltage drop factors of all nodes and interaction cost factors of the virtual power plant game framework and the building group comprehensive energy system; The system model module is used for making feel through self supply-demand according to real-time electricity price decisions of the virtual power plant and establishing a building group comprehensive energy system operation optimization model; The algorithm introducing module is used for carrying out coefficient coupling processing through a pareto optimal solution set weighting coefficient solver according to the operation optimization target; The strategy building module is used for building a Stackelberg game model through a participant, a game strategy and a utility function according to the virtual power plant game framework; and the strategy analysis module is used for solving the optimal decision of each main body through a multi-objective genetic algorithm of a nested linear programming solver according to the Stackelberg game model.
6. The device according to claim 5, wherein the algorithm introduction module specifically comprises: The first optimizing unit is used for carrying out the min-max standardization processing according to the operation optimizing target and carrying out the linear mapping on the minimum-maximum data within the range of 0-1 so as to realize the standardization processing; And the second optimizing unit is used for simulating the electric energy interaction direction of the virtual power plant by multiplying the pareto optimal solution set weighting coefficient according to the standardized operation optimizing target.
7. The apparatus of claim 5, wherein the policy analysis module is configured to solve an upper layer virtual power plant by a multi-objective genetic algorithm and nest pareto optimal solution set weighting coefficients to perform optimal population selection on the pareto solution set.
8. The apparatus of claim 5, wherein the policy analysis module performs linear programming management on the lower building group through a multi-objective genetic algorithm, and performs a reciprocal game by using an optimal decision result of each principal as an optimization constraint condition of other principals.
9. An electronic device comprising a memory and a processor, the memory configured to store one or more computer instructions, wherein the one or more computer instructions when executed by the processor implement the method of any of claims 1-4.
10. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program which, when executed by a processor, is adapted to carry out the method according to any of the preceding claims 1-4.

Description

Virtual power plant leading building group operation management method based on Stackelberg game Technical Field The invention discloses a virtual power plant leading building group operation management method based on a Stackelberg game, and relates to the technical field of power dispatching optimization. Background To achieve the carbon neutralization commitment in the middle of the 21 st century, the permeability of renewable energy sources in electrical power systems is expected to continue to increase. As an excellent carrier of distributed renewable energy sources, the number of micro-grids and integrated energy system building groups is continuously increasing. The large-scale operation scheduling and management of the large-scale operation scheduling and management is a hot problem due to the large number, small volume, scattered layout and large distance. The building group is taken as one of the most concentrated scenes of the electric load in China, and the building group of the integrated energy system based on the coupled distributed renewable energy formed by the building group is difficult to integrate, unify, manage and schedule directly through the power grid due to special electric energy interaction habit and electric energy interaction characteristics caused by the mixed coexistence of various buildings. The virtual power plant technology can be developed rapidly by means of the dynamic optimization of energy production and consumption and the balance of a power grid, so that the integration, supply and management of the power demand of the building group comprehensive energy system are possible. However, the conventional operation optimization method for the distributed energy system is difficult to ensure and balance benefits of all parties, difficult to ensure transaction fairness and difficult to solve sharp benefit conflicts. Under the background, the power grid is required to integrate, supply and manage the power requirements of the building group comprehensive energy system through a distributed operation optimization method, so that the safe operation of the power system and the reliable energy utilization of the building group are ensured. How to guarantee the interests of all parties and realize the operation scheduling and management of a plurality of building groups in a long-distance and large-range, and the challenges of long-distance energy supply reliability and high efficiency are met, so that the method is very important for unified management scheduling of an integrated and dispersed building group comprehensive energy system and adapting to the situation of a distributed energy system. Disclosure of Invention Aiming at the problems of the prior art, the invention provides a virtual power plant leading building group operation management method and device based on a Stackelberg game, which adopts the following technical scheme: In a first aspect, a virtual power plant-dominated architecture group operation management method based on a Stackelberg game, the method comprising: s1, building a virtual power plant game framework through a Stackelberg game according to a virtual power plant and building group comprehensive energy system; S2, establishing a multi-objective operation optimization model through the virtual power plant game framework according to an operation optimization objective, wherein the operation optimization objective comprises active power loss factors accumulated in branch transmission, average voltage drop factors of all nodes and interaction cost factors of the virtual power plant game framework and all building group comprehensive energy systems; s3, according to real-time electricity price decisions of the virtual power plant, the virtual power plant feels through self supply-demand, and an operation optimization model of the building group comprehensive energy system is built; S4, carrying out coefficient coupling processing through a pareto optimal solution set weighting coefficient solver according to the operation optimization target; S5, establishing a Stackelberg game model through participants, game strategies and utility functions according to the virtual power plant game framework; And S6, solving the optimal decision of each main body through a multi-objective genetic algorithm of a nested linear programming solver according to the Stackelberg game model. In some implementations, S4 specifically includes: s41, according to the operation optimization target, performing min-max standardization processing and performing linear mapping on minimum-maximum data within a range of 0-1 to realize standardization processing; s42, according to the standardized operation optimization target, the electric energy interaction direction of the virtual power plant is simulated by multiplying the electric energy interaction direction by the pareto optimal solution set weighting coefficient. In some implementations, in S6, according to the stacking game