Optimal Control of Distributed Energy Resources using Model Predictive Control

In an isolated power system (rural microgrid), distributed energy resources (DERs), such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement fossil fueled generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The problem is formulated as a multi-objective optimization problem with the goals of minimizing fuel costs and changes in power output of diesel generators, minimizing costs associated with low battery life of energy storage, and maximizing the ability to maintain real-time power balance during operations. Two control modes are considered for controlling the energy storage to compensate either net load variability or wind variability. Model predictive control (MPC) is used to solve the aforementioned problem and the performance is compared to an open-loop look-ahead dispatch problem under high penetration of wind. Simulation studies using different prediction horizons further demonstrate the efficacy of the closed-loop MPC in compensating for uncertainties in the system caused by wind and demand.