Scenario-Based Approach for Efficient Energy Management in Microgrids Considering Parameters Uncertainty

At present, one of the essential steps in microgrids (MG) optimization models is to consider the uncertainty of variables such as the intermittency of renewable energy sources (RES), electrical demand alteration, and market price volatility. More recently, MGs have received increasing attention, which needs to manage the uncertainty associated with future changes and variations of network parameters. This paper presents an optimal stochastic model for scheduling grid-connected MG energy comprises dispatchable resources such as micro-turbine and fuel cell units, non-dispatchable resources such as photovoltaic and wind turbine systems and a battery storage system. The optimal daily energy scheduling is required to obtain the MG's minimum operation cost over a 24-h horizon. The general algebraic modeling system (GAMS) is used to solve the optimization problem formulated in this work. Uncertainty of RESs, electrical demand, and market price are taken into account in the optimization model. The results obtained validate the effectiveness of the solution.