A bilevel approach to reduce peak load of community microgrid with distributed generators

Decentralized energy systems can be an alternative to stabilizing the power system in a rapidly changing power market environment. In this regard, it is very important to level the significant gap between electricity loads and power generation, which is caused by expanding renewable energy resources. This study investigates an electricity control strategy to encourage forming a microgrid and to level the load profile that the microgrid optimizes based on its individual objective. To address the problems encountered by two players at different decision levels, this study introduces a bilevel optimization model that considers two players' objectives. In the proposed model, the first player is called the grid system operator, and the decisions of the player are subsidy rates for distributed generators and an energy storage system. The second player is called the community microgrid, and the major decisions of the player are the configuration and operation of the microgrid. To solve the problem, an efficient algorithm is developed based on Karush-Kuhn-Tucker (KKT) conditions and a decomposition approach. Numerical experiments show that the peak load can be reduced by setting an adequate subsidy rate.