Abstract
With the increasing presence of intermittent Renewable Energy Sources (RESs), energy scheduling over loads and Battery Energy Storage System (BESS) in the MicroGrid (MG) become even more important. Especially in autonomous mode, MG will face the difficulties while local RESs production cannot satisfy critical loads’ requests. In this paper, a two-stage control scheme based on Model Predictive Control (MPC) is proposed for coordinating energy scheduling and optimizing Demand Response (DR) of Autonomous MicroGrids (AMGs) when there is an imbalance between the RES supply and demand. Firstly, Distributed Network Operator (DNO) will make an optimal decision based on the information received, which include trading with the other MGs, using the energy from BESS, or adjusting the controllable loads. Secondly, the optimized operational options will be tracked by each MG over a long time horizon, typically one day. With the proposed scheme, not only we maintain a supply-demand balance with load cutting or shifting, but also minimize the discomfort of active users. Detailed algorithm and simulations of the overall system are presented.
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