Multi-objective economic/emission optimal energy management system for scheduling micro-grid integrated virtual power plant

Abstract

Due to rapid socioeconomic growth and current environmental concerns, reducing global greenhouse gas emissions is a key step toward sustainable development. In recent years, some researchers have begun to adopt new grid management technologies such as virtual power plants (VPP) that allow them to improve energy management and cost and reduce gas emissions. The integration of distributed energy resources (DER), such as solar photovoltaic and wind power, combined with micro-turbines and energy storage systems and with the support of VPP intelligence, will contribute immensely to improving micro-grids (MGs) energy performance and reducing gas emissions. In this paper, an expert multi-objective feasibility enhanced particle swarm optimization algorithm is adopted for the optimal scheduling of energy management system to reduce the total operating cost and net emission simultaneously. The proposed algorithm is tested on an Algerian reel building-MG integrated VPP with DERs and combined cooling, heat, and power generation. Finally, different cases are simulated for a 24-h time and discussed to demonstrate the validity of the proposed VPP energy system and the effectiveness of the adopted algorithm to reduce gas emissions and the total operating cost.