Frequency Control in Microgrid Communities Using Neural Networks

Abstract

This paper proposes a controller design for battery energy storage systems (BESS) and plug-in hybrid electric vehicles (PHEV) integration for frequency control in microgrid communities (MG) with solar photovoltaics (PV s) and wind turbines as distributed generators (DG). These DG s are intermittent power sources and are the causes of possible severe frequency fluctuations in MG s. The proposed control is a PID controller, while the design is based on neural networks. To obtain the appropriate input parameters of the proposed PID controller, a multilayer feedforward neural network is configured and implemented using MATLAB s Deep Learning Toolbox with random values as input. Results demonstrate the effectiveness of the proposed design method. A comparison of the results from the proposed approach with those from particle swarm optimization method proves proposed method is better and more effective.