Proposing an Artificial Neural Network Based Controller for a Stand-Alone MicroGrid

DOI: 10.5176/2251-2179_ATAI17

Authors: Ali Asghar Ghadimi and Farzad Razavi

Abstract:

This paper is concerned with the generation control in small stand-alone MicroGrids consisting of inverter interfaced Distributed Generation (DG) units. An intelligent and on-line Microgrid Management System (MGMS) using Artificial Neural Network (ANN) controller is proposed in this study for MicroGrid control. It determines the amount of power produced from generation units in a stand-alone MicroGrid. The ANN trained with a data generated from a Genetic Algorithm (GA) solved optimal power flow problem, which defines generation unit’s power in order to have a minimum power loss in the system, considering normal buses voltage and rating of generation units.

Keywords: MicroGrid, State Estimation, Genetic Algorithm, Artificial Neural Network, Load Sharing, Distributed Generation