Title :
Artificial Neural Network based maximum power point tracker for photovoltaic system
Author :
Anitha, S.D. ; Prabha, S.B.J.
Abstract :
Most of the existing MPPT algorithms suffer from the drawback of being slow or wrong tracking. Due to this the utilization efficiency is reduced. MPPT is used to maximize the output from the PVarray by tracking continuously the maximum power point. Among all MPPT methods, Perturb and Observe (P&O) method is used for its simplicity. In this paper Perturb and Observe method is used. But it moves the operating point far from the maximum point due to rapidly changing condition. In order to bring the operating point to the maximum, Artificial Neural Network (ANN) is used to improve the efficiency by detecting the atmospheric condition.
Keywords :
maximum power point trackers; neural nets; photovoltaic power systems; power engineering computing; ANN; MPPT algorithms; PV array; artificial neural network; atmospheric condition; maximum power point tracker; photovoltaic system; Artificial Neural Network; Photovoltaic; maximum power point;
Conference_Titel :
Sustainable Energy and Intelligent Systems (SEISCON 2011), International Conference on
Conference_Location :
Chennai
DOI :
10.1049/cp.2011.0348
