Day-Ahead Scheduling of Multi-Energy Microgrids Based on a Stochastic Multi-Objective Optimization Model

Dealing with multi-objective problems has several interesting benefits, one of which is that it supplies the decision-maker complete information regarding Pareto front, as well a clear overview various trade-offs are involved in problem. The selection such representative set is, and itself, problem must take into consideration number choices to show uniformity representation and/or coverage order ensure quality solution. In this study, day-ahead scheduling been transformed optimization due inclusion objectives, operating cost multi-energy multi-microgrids (MMGs) profit Distribution Company (DISCO). purpose proposed system determine best operation combined heat power (CHP) unit, gas boiler, energy storage, demand response program, transaction electricity natural (NG). Electricity traded by MGs DISCO at prices dynamic fixed, respectively. Through scenario generation probability density functions, uncertainties wind speed, solar irradiation, electrical, demands have considered. By using mixed-integer linear programming (MILP) for reduction, high generated scenarios significantly reduced. ɛ-constraint approach was used solved nonlinear (MINLP) obtain solution meets needs both these objective functions.