Abstract
This paper proposes and evaluates an adaptive neuro-fuzzy inference system (ANFIS) based battery energy management system (BEMS). The proposed configuration consists of photovoltaic (PV) and wind energy conversion system (WECS) based hybrid renewable energy system as the primary source and battery system as the energy storage device. The all the primary sources is connected to the DC bus by a DC/DC converter whereas, Battery storage system is connected using Bi-Directional system for charging and discharging purpose. An ANFIS based supervisory control system is proposed in this paper which determines effective battery management system by analyzing the power demand by the load and the state of charge (SOC) of the battery furthermore, an fuzzy logic controller (FLC) based maximum power point tracking (MPPT) is used in the PV and wind energy conversion system (WECS) to track the maximum available power for the different irradiance and wind velocity respectively. The obtained results are compared with the fuzzy logic-based energy management system to test the effectiveness of the system. A 500 W PV system and a 500 W Permanent magnet synchronous generator (PMSG) based WECS is implemented for its simplicity and high efficiency. The proposed control topology is designed and tested using MATLAB/Simulink.
Cite
CITATION STYLE
Nagaiah*, M., & Sekhar, Dr. K. C. (2019). An Effective Battery Energy Management System in Hybrid Solar/Wind System using ANFIS Controlled Bi-Directional DC-DC Converter. International Journal of Recent Technology and Engineering (IJRTE), 8(4), 4150–4158. https://doi.org/10.35940/ijrte.d6876.118419
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