Stochastic Optimization Scheme to Schedule Energy Supply and Demands in an Islanded Microgrid

Abstract

With the increasing awareness of climate change and the declining prices of renewable energy sources (RESs), societies are transforming themselves to access cheap and clean energy. Solar and Wind are the two most abundantly available energy resources that can be accessed in remote areas where it is infeasible for a national grid to supply electricity. However, the RESs are intermittent in nature show high variability in output power, and become more volatile without the integration of the national grid. In this paper, we address such a problem of RESs uncertainty in an islanded microgrid, incorporating both supply-side and demand-side energy management techniques. We propose a model predictive time-ahead rolling horizon based optimization approach, that generates cost-optimal scheduling signals for various energy supply entities and flexible load demands. The objective of this work is to; 1) minimize the operating cost of the power generators, 2) minimize electricity cost for the energy consumers, and 3) maximize the consumers’ satisfaction level. The numerical results show that our optimization strategy ensures the supply and demand balance applying cost-efficient decisions under any uncertain circumstances using error-correcting rolling time horizon based strategy.