Optimal Management of Microgrids With External Agents Including Battery/Fuel Cell Electric Vehicles

This paper studies the economic dispatch problem for a microgrid that interacts with external agents. First, the microgrid acts in the day-ahead market to find the optimal schedule for its internal resources, considering the consumption and generation forecast and the energy price prediction. Once the day-ahead market has closed, external agents such as other microgrids in the same network, aggregators or electric vehicles can interact with the microgrid through a local energy market. If an external agent requests a specific energy profile that offers an economic benefit, the microgrid controller will propose supplying the closest profile to that requested, depending on the benefit offered. The proposed solution allows the microgrid to respond to external requests, thus optimizing its economic benefit. The problem is solved using model predictive control (MPC), and the operation and degradation costs are included in the objective function. In order to capture both continuous/discrete dynamics and switching between different operating conditions, the plant is modeled using the mixed logic dynamic framework. The MPC problem is solved by means of mixed-integer quadratic programming.