A Robust Economic Load Dispatch in Community Microgrid Considering Incentive-based Demand Response

Abstract

Effective uncertainties management is required to realize stable operation for community microgrids consisting of electric loads, variable renewable energies (VREs), electric vehicles (EVs), etc. The authors propose a robust energy management (REM) controller for optimizing system operation against uncertainties. Practical solutions are provided to the microgrid system operator when power imbalances arise from unpredictable events. The functions of the proposed REM controller consist of (1) loads/VREs forecasting algorithm using artificial intelligence techniques, (2) day-ahead 24-hour unit commitment based on the prediction error, and (3) intra-day 1-hour economic load dispatch (ELD) algorithm that secures the feasible operation regions with controllable resources. This paper proposes a robust ELD method against the uncertainties which cause supply and demand mismatch. During unpredictable events, the mismatch is effectively treated and resolved using incentive-based demand response (IDR). The scheme of the IDR program based on genetic algorithm (GA) is offered by the system operator to the consumers in the community microgrid. The feasible solutions are provided to the consumers as an incentive to prevent the power imbalance problem.