Classification and comparison of maximum power point tracking techniques for photovoltaic system: A review

被引:446
作者
Reisi, Ali Reza [1 ]
Moradi, Mohammad Hassan [2 ]
Jamasb, Shahriar [2 ]
机构
[1] Islamic Azad Univ, Dept Elect Engn, Shahrekord Branch, Shahrekord, Iran
[2] Bu Ali Sina Univ, Dept Elect Engn, Fac Engn, Hamadan, Iran
关键词
MPPT; PV system; Offline; Online; Hybrid methods; EXTREMUM-SEEKING; BATTERY STORAGE; NEURAL-NETWORK; MPPT CONTROL; DC MOTOR; ALGORITHM; PERFORMANCE; CONTROLLER; GENERATION; CONVERTER;
D O I
10.1016/j.rser.2012.11.052
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In recent years there has been a growing attention towards use of solar energy. The main advantages of photovoltaic (PV) systems employed for harnessing solar energy are lack of greenhouse gas emission, low maintenance costs, fewer limitations with regard to site of installation and absence of mechanical noise arising from moving parts. However, PV systems suffer from relatively low conversion efficiency. Therefore, maximum power point tracking (MPPT) for the solar array is essential in a PV system. The nonlinear behavior of PV systems as well as variations of the maximum power point-with solar irradiance level and temperature complicates the tracking of the maximum power point. A variety of MPPT methods have been proposed and implemented. This review paper introduces a classification scheme for MPPT methods based on three categories: offline, online and hybrid methods. This classification, which can provide a convenient reference for future work in PV power generation, is based on the manner in which the control signal is generated and the PV power system behavior as it approaches steady state conditions. Some of the methods from each class are simulated in Matlab/Simulink environment in order to compare their performance. Furthermore, different MPPT methods are discussed in terms of the dynamic response of the PV system to variations in temperature and irradiance, attainable efficiency, and implementation considerations. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:433 / 443
页数:11
相关论文
共 77 条
[1]  
Abdelsalam AK, 2011, IEEE T POWER ELECTR, V4, P26
[2]  
Al-Amoudi A, 1998, IEE CONF PUBL, P80, DOI 10.1049/cp:19980504
[3]  
Al-Amoundi A, 2000, IEE P-GENER TRANSM D, V147, P310, DOI DOI 10.1049/IP-GTD:20000605
[4]   Maximum power point tracking using fuzzy logic control [J].
Algazar, Mohamed M. ;
AL-monier, Hamdy ;
Abd EL-Halim, Hamdy ;
Salem, Mohamed Ezzat El Kotb .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2012, 39 (01) :21-28
[5]   MATCHING OF A DC MOTOR TO A PHOTOVOLTAIC GENERATOR USING A STEP-UP CONVERTER WITH A CURRENT-LOCKED LOOP [J].
ALGHUWAINEM, SM .
IEEE TRANSACTIONS ON ENERGY CONVERSION, 1994, 9 (01) :192-198
[6]  
Andersen MSM, 1995, IEEE IND ELEC, P572, DOI 10.1109/IECON.1995.483472
[7]   Maximum power point traking controller for PV systems using neural networks [J].
Bahgat, ABG ;
Helwa, NH ;
Ahmad, GE ;
El Shenawy, ET .
RENEWABLE ENERGY, 2005, 30 (08) :1257-1268
[8]   Concerning "Maximum Power Point Tracking for Photovoltaic Optimization Using Ripple-Based Extremum Seeking Control" [J].
Bazzi, Ali M. ;
Krein, Philip T. .
IEEE TRANSACTIONS ON POWER ELECTRONICS, 2011, 26 (06) :1611-1612
[9]   Comparison of fuzzy logic and neural network in maximum power point tracker for PV systems [J].
Ben Salah, Chokri ;
Ouali, Mohamed .
ELECTRIC POWER SYSTEMS RESEARCH, 2011, 81 (01) :43-50
[10]  
Bianconi E, INT J ELECT POWER EN, V44