A Survey on Multi-Objective Optimization in Microgrid Systems

Renewable energy resources (RES) are closely linked to grid stability problems. The main challenge of RES is the uncertainty caused by parameters such as irradiation, wind velocity, or temperature. In this connection, Multi-Objective Optimization (MOO) Algorithms can be used as an intelligent control system for a microgrid by ensuring continuity of power supply in case of grid failures. Based on grid reliability and local demand, MOO can make real-time decisions about disconnecting from the primary grid (islanding) and when to reconnect. It can help in MG control systems by optimizing energy storage systems (ESS) operation by determining when to charge and discharge them based on electricity prices, grid demand, and renewable energy availability. This survey discusses an MG and its different challenges with RES with Photovoltaic (PV) as a primary component and prominent energy sources such as a utility grid, Diesel Genset (DG), Wind Turbine (WT) and ESS. In this research, a unique classification approach of different problems in Microgrid (MG) is identified and discussed. This paper focuses on the MOO algorithms used in MG for their energy management systems (EMS) and technical and economic problems and investigates how MOO can play a significant role in solving such problems.