A stochastic model for microgrids planning considering smart prosumers, electric vehicles and energy storages

Abstract

This paper introduces a three-stage stochastic optimization (TSSO) structure for energy management of a distribution system consisting of four microgrids, where distribution system planning is performed considering the requested schedule of microgrids and SHs. SHs do their planning with the goal of cost minimization at the first stage. Then, microgrid planning is performed taking into account the SH requested program at the second stage. Ultimately, main grid planning is performed taking into account the requested program of microgrids at stage 3. In order to deal with uncertainties caused by renewable power generations (RPGs), load demand and electric vehicle (EV) users' behavior, a scenario-based (SB) stochastic technique is used and the problem is modeled in the linear programming (LP) format. The model is solved through the GUROBI solver in the GAMS environment and the results reveal that energy storage (ES) devices, demand response program (DRP) and vehicle-to-grid (V2G) services lead to the improvement of the voltage profile, the relief of the congestion in the vital lines and a 20.37 % reduction of operating cost. In addition, the outcomes showed that the main grid operator can adopt a more optimal schedule for microgrids through distribution feeder reconfiguration (DFR) and thereby reduce their operating cost.