Microgrid generation expansion planning using agent-based simulation

This paper explores new application of agent-based simulation in the novel framework of exploitation of renewable resources in microgrids. A bi-layer (operational layer and investment layer) multi-agent model is proposed for microgrid operators (MGOs) to maximize their long-term planning profits in an energy market, which is built and regulated by the utility company (UC) in order to alleviate UC's environmental obligations. UC tries to maximize its revenue and minimize payment to satisfy demand for renewable generation. The results of investment plans with peaked choice probabilities in the investment layers are treated as the best decisions of MGOs' expansion planning in the evolutionary game. An example with twenty years planning horizon is given to illustrate the proposed model and market mechanism.