Multi-Objective Based Optimal Scheduling of Microgrid Considering Uncertainties

Abstract

This paper proposes a multi-objective based optimal scheduling methodology for a Microgrid (MG) including diesel generators, solar PV, wind generators, demand response (DR), battery energy storage systems (BESSs) and electric vehicles (EVs), Different uncertainties exist in the microgrids, and they are mainly caused by intermittent output power of non-dispatchable renewable power generation such as solar PV and wind power outputs. Power outputs from solar PV, wind, BESSs and EVs are modeled, and their uncertainties are handled by considering the probability analysis. Here, the operating cost of MG and amount of emission released are considered as two objectives to be optimized for the optimal scheduling of MG considering uncertainties. The operating cost minimization objective is formulated by incorporating the cost due to power to/from main grid and MG, diesel generators, solar PV, wind units, EVs, BESSs, and DR. First, these two objectives are optimized independently by using enhanced genetic algorithm (EGA), and then they are optimized simultaneously by using nondominated sorting genetic algorithm-II. Simulations are carried out on a test Microgrid system by including all the MG components, single and multiple objectives.