Title :
Adaptive neuro-fuzzy inference system based maximum power point tracking of a solar PV module
Author :
Iqbal, A. ; Abu-Rub, H. ; Ahmed, Sk M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas A&M Univ. at Qatar, Doha, Qatar
Abstract :
This paper presents and analyses the operation of an Adaptive Neuro-Fuzzy Inference System (ANFIS) based maximum power point tracker (MPPT) for solar photovoltaic (SPV) energy generation system. The MPPT works on the principle of adjusting the voltage of the solar PV modules by changing the duty ratio of the boost converter. The duty ratio of boost converter is calculated for given solar irradiance and temperature condition by a closed-loop control scheme. The ANFIS is trained to generate the maximum power corresponding to the given solar irradiance level and temperature. The response of ANFIS based control system is highly precise and offers very fast response. Simulation results are provided to validate the concept.
Keywords :
adaptive control; closed loop systems; fuzzy control; fuzzy neural nets; fuzzy reasoning; maximum power point trackers; neurocontrollers; photovoltaic power systems; power convertors; power generation control; solar power stations; ANFIS based control system; MPPT; adaptive neuro-fuzzy inference system; closed-loop control scheme; maximum power point tracking; solar PV module; solar photovoltaic energy generation system; Algorithm design and analysis; Artificial intelligence; Mathematical model; Power generation; Renewable energy resources; Short circuit currents; Temperature control; Adaptive Neuro-Fuzzy Inference System (ANFIS); Maximum Power Point tracker; Solar PV; boost converter;
Conference_Titel :
Energy Conference and Exhibition (EnergyCon), 2010 IEEE International
Conference_Location :
Manama
Print_ISBN :
978-1-4244-9378-4
DOI :
10.1109/ENERGYCON.2010.5771737
