An Intelligent Multi Agent based Approach for Autonomous Energy Management in a Microgrid

Abstract

The integration of highly intermittent and unpredictable distributed energy resources increases the complexities in the energy management system (EMS). Therefore, the conventional control used in microgrid EMS is no more effective and requires alternative control strategies that can cope up with the new dynamics in the system. Adopted from computer science, a distributed artificial intelligence technique called multi agent system (MAS) can serve this purpose well due to its inherent autonomous nature, scalability, flexibility, and adaptability. Consequently, in this paper, a new multi agent based architecture for microgrid energy management system has been proposed. The proposed model considers different forecasting agents and a real time correction agent for microgrid energy management. The performance of proposed MAS based microgrid EMS modeled in a new platform called Stateflow has been evaluated by developing different scenarios considering resource fluctuations and load variations. The simulation results demonstrate the effectiveness of the proposed architecture in outperforming the conventional microgrid energy management system and the effective usage of each component of the microgrid.