Decentralized Energy Management System in Microgrid Considering Uncertainty and Demand Response

Smart energy management and control systems can improve the efficient use of electricity maintain balance between supply demand. This paper proposes modeling a decentralized system (EMS) to reduce operation costs under renewable generation load uncertainties. There are three stages proposed strategy. First, this applies an autoregressive moving average (ARMA) model for forecasting PV wind generations as well power Second, optimal scheduling process is designed minimize operating costs. The well-known algorithm particle swarm optimization (PSO) applied provide among WT systems, fuel-based units, required from main grid. Third, demand response (DR) program introduced shift flexible in microgrid achieve active system. Simulation results demonstrate performance method using forecast data hourly profile. simulation show that cost worst-case uncertainty. load-shifting reduced peak by 4.3% filled valley 5% provides minimum total with framework.