Energy Management through Multi-objective Optimization of Cost and Pollution

Abstract

Energy management and optimization have become an emerging necessity in microgrids, considering that in recent times, the integration of renewable energy resources has gained quite a lot of importance in reducing dependency on non-renewable resources. This paper focuses on optimizing the cost and level of pollution in the microgrid, which are two mostly contradictory elements, through an effective allocation of energy demands among DERs and the main grid. In this work, the Multi-objective Particle Swarm Optimization technique is employed to handle the financial implications and environmental impacts involved in microgrid operations. Indeed, it is expected that this work will provide ample information on how economic and ecological considerations can be traded off during energy management.