Multi-objective energy management and environmental index optimization of a microgrid using swarm intelligence algorithm

Abstract

Due to the need for better reliability, high energy quality, lower losses and cost, and clean environment, the application of renewable energy sources such as wind energy and solar energy in recent years has become more widespread mainly. In this work, one of the most general of all swarm intelligence algorithms, called particle swarm optimization (PSO) is applied to solve the optimal energy management (OEM) and environmental index optimization (EIO) problems of micro-grid (MG) operating by renewable and sustainable generation systems (RSGS). The PSO approach was examined and tested on standard MG composed of different types of RSGS, such as wind turbines (WT), photovoltaic systems (PV), fuel cells (FC), micro turbine (MT), and diesel electric generator (DEG) with energy storage systems (ESS). The results are promising and show the effectiveness and robustness of proposed approach to solve the OEM and the EIO. The results obtained were compared with some well-known references. The results show that the optimization process reduced the energy generation costs from 257283 ($/h), 263929 ($/h), and 263526 ($/h), respectively. While the environmental index further improved to 0.1548 (ton/h).