Smart Energy Management System for Distributed Generations in AC Microgrid

This paper proposes a novel smart energy management system (EMS) for distributed generations (DGs) in AC microgrid. The considered microgrid consists of two DGs, energy storage system, and loads. The solar PV system and the wind energy conversion system (WECS) are selected as an input power source of DGs. Model predictive control technique is used to regulate each DG's output current whereas adaptive neuro-fuzzy inference system (ANFIS) based EMS is developed to manage the available energy in AC microgrid. The proposed method is validated analytically and through Hardware-in-the-Loop (HIL) experiments. The carried out HIL experiments prove the merit of the proposed method.