Distributed Multi-Agent System-Based Load Frequency Control for Multi-Area Power System in Smart Grid

This paper presents an intelligent controller for "load frequency control (LFC)" application in "smart grid (SG)" environment having changes in communication topology (CT) via amulti-agent system (MAS) technology. In this study, network-induced effects, time delay, and change in CT have been addressed to examine the system performance in a closed loop. An event-triggered control method is used to reduce the communication burden in a network. An intelligent controller based on reinforcement learning consists of two levels, estimator agent and controller agent, in each multi-area system. Particle swarm optimization is used to tune the controller parameters. Furthermore, the proposed control strategy and system architecture as MAS for LFC in SG are analyzed in detail, verified for various load conditions and different network configurations. In addition, mean-square error of the power system states with CT is also analyzed. The results of this study validate the feasibility of the proposed control, as well as the capability of the MAS for the operation of LFC in SG with changes in CT.