An Optimal Maximum Power Point Tracking Algorithm for PV Systems With Climatic Parameters Estimation

被引：58

作者：

Chikh, Ali ^{[1
]}

Chandra, Ambrish ^{[1
]}

机构：

[1] Ecole Technol Super, Dept Elect Engn, Montreal, PQ H3C 1K3, Canada

来源：

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY | 2015年 / 6卷 / 02期

关键词：

Adaptive neuro-fuzzy (ANFIS) solar cell model; instantaneous conductance; junction conductance; junction current; maximum power point tracking (MPPT); photovoltaic (PV) system; PERTURB; OPTIMIZATION;

D O I：

10.1109/TSTE.2015.2403845

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

This paper presents a maximum power point tracking (MPPT) method for photovoltaic (PV) systems with reduced hardware setup. It is realized by calculating the instantaneous conductance and the junction conductance of the array. The first one is done using the array voltage and current, whereas the second one, which is a function of the array junction current, is estimated using an adaptive neuro-fuzzy (ANFIS) solar cell model. Knowing the difficulties of measuring solar radiation and cell temperature, since those require two extra sensors that will increase the hardware circuitry and measurement noise, an analytical model is proposed to estimate them with a denoising-based wavelet algorithm. The proposed MPPT technique helps to reduce the hardware setup using only one voltage sensor, while increases the array power efficiency and MPPT response time. The simulation and experimental results are provided to validate the MPPT algorithm operation as well as the climatic parameters estimation capabilities.

引用

页码：644 / 652

页数：9

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