Optimal Time-of-use Pricing for Renewable Energy-powered Microgrids: A Multi-agent Evolutionary Game Theory-based Approach

While price schedules can help improve the economic efficiency of renewable energy-powered microgrids, time-of-use (TOU) pricing has been identified as an effective way for microgrid development, which is presently limited by its high costs. In this study, we propose an evolutionary game theoretic model to explore optimal TOU pricing for development of renewable energy-powered microgrids by applying a multi-agent system, that comprises a government agent, local utility company agent, and different types of consumer agents. In the proposed model, we design objective functions for the company and the consumers and obtain a Nash equilibrium using backward induction. Two pricing strategies, namely, the TOU seasonal pricing and TOU monthly pricing, are evaluated and compared with traditional fixed pricing. The numerical results demonstrate that TOU schedules have significant potential for development of renewable energy-powered microgrids and are recommended for an electric company to replace traditional fixed pricing. Additionally, TOU monthly pricing is more suitable than TOU seasonal pricing for microgrid development.