ANN-Based Self-Tuning Frequency Control Design for an Isolated Microgrid

Abstract

The increasing need for electrical energy, limited fossil fuel reserves, and the increasing concerns with environmental issues call for fast development in the area of distributed generations (DGs) and renewable energy sources (RESs). A Microgrid (MG) as one of the newest concepts in the power systems consists of several DGs and RESs that provides electrical and heat power for local loads. Increasing in number of MGs and nonlinearity/complexity due to entry of MGs to the power systems, classical and nonflexible control structures may not represent desirable performance over a wide range of operating conditions. Therefore, more flexible and intelligent optimal approaches are needed. Following the advent of optimization/intelligent methods, such as artificial neural networks (ANNs), some new potentials and powerful solutions for MG control problems such as frequency control synthesis have arisen. The present chapter addresses an ANN-based optimal approach scheduling of the droop coefficients for the purpose of frequency regulation in the MGs.