Comparison of ANN and ANFIS based MPPT controller for grid connected PV Systems

被引:0
|
作者
Arora, Ankita [1 ]
Gaur, Prerna [1 ]
机构
[1] Univ Delhi, NSIT, Dept Instrumentat & Control Engn, Delhi 110007, India
关键词
Maximum power point tracking; Artificial Neural Network; Adaptive Neuro Fuzzy Inference System; Photovoltaic;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper presents comparison analysis of artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS) artificial intelligence (AI) based maximum power point tracking (MPPT) techniques for tracking maximum power from the Photovoltaic (PV) array. These algorithms are essential since PV arrays have non-linear characteristics with its firm dependence on changing solar irradiation and temperature. To increase the power extracted from solar panel, PV array must operate at a maximum power point (MPP) under given load conditions. Conventional algorithms such as Perturb and Observe (P&O) and Incremental-Conductance (Inc-Cond) suffers, with high oscillations during changing solar irradiation leading to low efficiency, therefore AI based techniques are designed and presented in this paper. ANFIS is more efficient in tracking MPP with less settling time, less overshoot, less oscillations and less time taken to track MPP than ANN based Controller.
引用
收藏
页数:6
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