Real-time scheduling of community microgrid

Abstract

The community microgrid (CMG), powered by local energy resources and energy storage devices, is one of the most promising intelligent entities for the future smart grid. However, the scheduling of CMG energy resources for real-time energy management is a challenging optimization problem due to the variability of renewable generation and complex system constraints. In this work, a new three-layer real-time scheduling framework is proposed. The novelty of the proposed approach stems from the feedback mechanism introduced between the scheduling layers which enables the generation of cost-effective schedules. The proposed approach has better ability to handle the impacts of variations in renewable generations/demand within the CMG. To solve the real-time scheduling problem of CMG, a heuristic-based differential evolution (DE) algorithm is introduced. The significance of the developed heuristic is that it can generate feasible solutions with lower computational effort. The performance of the proposed algorithm is validated by solving benchmark problems and comparing the results with state-of-the-art algorithms. Finally, the developed scheduling framework is employed for real-time energy management of CMG. The experimental results confirm the efficacy of the proposed scheduling approach over the existing ones.