Frequency Control in a Microgrid Using Decentralized Brain Emotional Learning Based Intelligent Controllers

Frequency control is very important in microgrids. It plays a vital role in the stability as well as the power quality of the microgrid. The Load Frequency Control (LFC) must posses disturbance rejection capabilities as well as robustness against parameter uncertainty. In this paper decentralized Brain Emotional Learning Based Intelligent Controllers (BELBIC) is proposed for the frequency control of a microgrid. BELBIC controllers have a good disturbance rejection and robustness to plant parameters' variation, these make it an ideal controller for the frequency control of the microgrid. Decentralized BELBIC controllers are designed simultaneously for each of the Distributed Generation (DG) unit and the controllers' parameters are obtained using Particle Swarm Optimization (PSO) based on the Integral Time Square Error (ITSE) criterion. The simulation results are compared to decentralized PID controllers as well as Fractional Order PID (FOPID) controllers which were designed using the same procedures, the results are reported and shows the superiority of using BELBIC controllers for this application.