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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 used in this study and 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. Simulation results in a typical distribution system consisting two DG units show that the proposed method can meet the requirements of the system and DG units rating in stand-alone operations. In this way the system is managed in an on-line, optimal, and reliable situation that guarantee the continuity of power to loads in stand-alone mode of a MicroGrid.

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

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