Multi-objective multi-agent distributed game optimization method for distributed energy

Abstract

The invention discloses a multi-target multi-main-body distributed game optimization method for distributed energy sources, and belongs to the technical field of power system automation. Aiming at the multi-target, multi-constraint, nonlinear and multi-main-body game characteristics of a plurality of types of distributed energy sources, the invention provides the multi-target multi-main-body distributed game optimization method. According to the economical, environment-friendly and high-efficiency target demands of the joint optimization of the plurality of types of distributed energy sources, the method builds a multi-energy-system multi-target joint optimization model through combining the output and climbing rate constraints of the plurality of types of distributed energy sources. Based on the distributed coordination optimization theory, the method enables the whole model to be divided into a plurality of subsystem multi-target joint optimization models, employs an improved multi-target optimization algorithm for solving, and obtains a Pareto solution set of each subsystem, thereby finally forming an optimal Pareto solution set for the whole system and providing a reliable decision support for a decision maker.

Description

technical field [0001] The invention discloses a distributed energy-oriented multi-objective multi-agent distributed game optimization method, belonging to the technical field of power system automation. Background technique [0002] As more and more distributed energy sources such as wind power and photovoltaics are connected to the grid system, the joint optimization problem of multi-energy systems presents complex characteristics such as multi-objective and multi-constraint. Mutual game characteristics, traditional distributed optimization methods generally only consider its multi-objective characteristics or multi-agent game characteristics, ignoring the multi-objective and multi-agent coordination problems in distributed energy optimization. Since various energy sources have their own different independent characteristics and various distributed energy sources generally belong to different stakeholders, the optimization scheme that only considers the multi-objective cha...

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Problems solved by technology

[0002] As more and more distributed energy sources such as wind power and photovoltaics are connected to the grid system, the joint optimization problem of multi-energy systems presents complex characteristics such as multi-objective and multi-constraint. Mutual game characteristics, traditional distributed optimization methods generally only consider its multi-objective characteristics or multi-agent game characteristics, ignoring the multi-objective and multi-agent coordination problems in distributed energy optimization

Since a variety of energy sources have their own different independent characteristics and various distributed energy sources generally belong to different stakeholders, the optimization scheme that only considers the multi-objective characteristics of the optimization problem ignores the overall consideration of individual characteristics

In addition, because the optimal configuration of distributed energy resources has a variety of target requirements, only considering the single target requirements of its multi-agent characteristics cannot meet its actual engineering needs

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