Game theoretical analysis on capacity configuration for microgrid based on multi-agent system. (February 2021)

• Record Type: Journal Article
• Authors: Jin, Shunping; Wang, Shoupeng; Fang, Fang
• Is Part Of: International journal of electrical power & energy systems. Volume 125(2021)
• Publication Date: 2021-02
• Subjects: Microgrid -- Capacity configuration -- Game theory -- Multi-agent system -- Uncertainty; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2020.106485
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: Structured a wind/photovoltaic/gas microgrid with multi-agent form. Propose a game model for capacity configuration of microgrids. Uncertainty of wind power and solar power are taken into account. The Nash Equilibrium is iterated out, and an optimal scheme is summarized. Non-cooperation and cooperation game results are analyzed and compared. Abstract: With the rapid growth of centralized utilization of large-scale renewable energy, to improve the stability of power grid and reduce operating costs, microgrid and renewable distributed generation (DG) has become the key direction of China. For a microgrid integrated with wind turbines, photovoltaic (PV) and micro-gas-turbine, the installed capacities need to be configured rationally to achieve economical and reliable power supply. In this paper, a structure of a microgrid based on multi-agent system (MAS) is established, and a game-theory-based optimization model is presented for the capacity configuration of these agents. The economic interests between the agents and their actions are analyzed by the game model. Besides, the interactions between microgrid and power grid, and the uncertainty of wind power and solar power are taken into account. The Nash Equilibrium of the game is worked out by particle swarm optimization, as the reference for the configuration of the agents. In the end, a wind/solar/gas microgrid model is used for the numerical tests to analyze and compare the effectiveness of the game optimization. The results show that under cooperative game, the investors' profits of wind turbines, PV and micro-gas-turbine increase by 6%, 19%, 88% compared with the non-cooperative game, while the total configured capacities decrease by 10%.