Optimization of Energy Management in Microgrid Integrated with EV, BESS & Renewable Sources

This paper proposes an innovative energy management strategy for a microgrid (MG) integrated with electric vehicles (EVs), battery energy storage systems (BESS), and renewable energy sources. The aim is to optimize the MG operation by incorporating price-based demand response (PBDR) and incentive-based demand response (IBDR). The proposed demand response mechanism benefits MG operators and end users. The objective of the MG operator is to reduce the power purchase cost from the grid, minimize the fuel cost of conventional distributed generators, and maximize revenue generated by consumers participating in DR. The proposed objective encourages energy consumers to participate in the DR program by minimizing their electricity bills and offering incentives. The fuzzy max-min method is approached to obtain optimal solutions as both objectives are conflicting. This work addresses the uncertainties in renewable energy sources, load demand, and electricity prices using Hong’s (2m + 1) point estimation method. The proposed method leads to a 13.86% energy cost saving for MG operators.