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Lui, Y.H., Lui, C.L., Huang, J.W. and Chen, J.H. (2013) Neural-Network-Based Maximum Power Point Tracking Methods for Photovoltaic Systems Operating under Fast Changing Environments. Solar Energy, 89, 42-53.
http://www.sciencedirect.com/science/journal/0038092X/89/supp/C

has been cited by the following article:

• TITLE: Maximum Power Point Tracking Using Fuzzy Logic Controller under Partial Conditions

  AUTHORS: Areen Abdallah Allataifeh, Khaled Bataineh, Mohammad Al-Khedher

  KEYWORDS: Fuzzy Logic Controller, Maximum Power Point, Photovoltaic System, Partial Shading

  JOURNAL NAME: Smart Grid and Renewable Energy, Vol.6 No.1, January 15, 2015

  ABSTRACT: This study proposes a fuzzy system for tracking the maximum power point of a PV system for solar panel. The solar panel and maximum power point tracker have been modeled using MATLAB/Simulink. A simulation model consists of PV panel, boost converter, and maximum power point tack MPPT algorithm is developed. Three different conditions are simulated: 1) Uniform irradiation; 2) Sudden changing; 3) Partial shading. Results showed that fuzzy controller successfully find MPP for all different weather conditions studied. FLC has excellent ability to track MPP in less than 0.01 second when PV is subjected to sudden changes and partial shading in irradiation.