Akademik Veri Yönetim Sistemi
JOURNAL OF ELECTRICAL SYSTEMS, cilt.14, sa.4, ss.134-146, 2018 (ESCI)
This paper presents a battery charge control scheme for grid-connected microgrids, which are composed of renewable energy sources and battery banks. The proposed charge control strategy primarily aims to support utility grid in peak demand times and safe charge management of battery groups. In addition, battery charge control is related to economic benefits by providing stored renewable energy during inefficient hours of renewable energy generation. We proposed an adaptive neural fuzzy inference system to manage battery charging process. This system charges batteries from renewable energy sources in peak off times of energy demand and discharges the stored energy to support utility grid in peak times. Two renewable energy generation scenarios are simulated in Matlab/Simulink simulation environment to demonstrate effectiveness of the proposed method. In these scenarios, the cases of 1 kW solar panel system and 1 kW wind turbine integrated a domestic microgrid are tested. The simulation results show that the controller can achieve to support utility grid in peak demand times with energy cost benefits and keep battery charge state in healthy working conditions.