Agent based Control for Microgrids

This paper presents a general framework for the control of distributed energy resources organized in microgrids. The proposed architecture is based on the agent technology and aims to integrate several functionalities, as well to be adaptable to the complexity and the size of the microgrid. To achieve this, the idea of layered learning is used, where the various controls and actions of the agents are grouped depending on their effect on the environment. A novel approach called multiagent reinforcement learning is introduced in order to increase the intelligence and the efficiency of the microgrid.