Genetic algorithms optimized fuzzy logic control for the maximum power point tracking in photovoltaic system

被引：206
|
作者：
Larbes, C. [1 ]
Cheikh, S. M. Ait [1 ]
Obeidi, T. [1 ]
Zerguerras, A. [1 ]
机构：
[1] Ecole Natl Polytech, Lab Dispositifs Commun & Convers Photovolta, Dept Elect, El Harrach 16200, Alger, Algeria
来源：
RENEWABLE ENERGY | 2009年 / 34卷 / 10期
关键词：
Photovoltaic system; MPPT; Fuzzy logic; Genetic algorithm; DC-DC converter; DESIGN;
D O I：
10.1016/j.renene.2009.01.006
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 an intelligent control method for the maximum power point tracking (MPPT) of a photovoltaic system under variable temperature and irradiance conditions. First, for the purpose of comparison and because of its proven and good performances, the perturbation and observation (P&O) technique is briefly introduced. A fuzzy logic controller based MPPT (FLC) is then proposed which has shown better performances compared to the P&O MPPT based approach. The proposed FLC has been also improved using genetic algorithms (GA) for optimisation. Different development stages are presented and the optimized fuzzy logic MPPT controller (OFLC) is then simulated and evaluated, which has shown better performances. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码：2093 / 2100
页数：8
相关论文
共 50 条
  • [1] Maximum power point tracking using fuzzy logic control for photovoltaic system
    Soufi, Youcef
    Bechouat, Mohcene
    Kahla, Sami
    Bouallegue, Kais
    2014 INTERNATIONAL CONFERENCE ON RENEWABLE ENERGY RESEARCH AND APPLICATION (ICRERA), 2014, : 902 - 906
  • [2] A Fuzzy Control Maximum Power Point Tracking Photovoltaic System
    Purnama, Irwan
    Lo, Yu-Kang
    Chiu, Huang-Jen
    IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ 2011), 2011, : 2432 - 2439
  • [3] Hopfield Neural Network Optimized Fuzzy Logic Controller for Maximum Power Point Tracking in a Photovoltaic System
    Subiyanto, Azah Mohamed
    Shareef, Hussain
    INTERNATIONAL JOURNAL OF PHOTOENERGY, 2012, 2012
  • [4] A Research on the Fuzzy Control with Genetic Algorithm for Maximum Power Point Tracking of Photovoltaic Power System
    Dai Yi-zong
    Miao De-jun
    SENSORS, MEASUREMENT AND INTELLIGENT MATERIALS, PTS 1-4, 2013, 303-306 : 1153 - 1157
  • [5] Evaluation of Fuzzy Logic based Maximum Power Point Tracking for Photovoltaic Power System
    Yetayew, T. T.
    Jyothsna, T. R.
    2015 IEEE POWER, COMMUNICATION AND INFORMATION TECHNOLOGY CONFERENCE (PCITC-2015), 2015, : 217 - 222
  • [6] Fuzzy control for maximum power-point tracking of a photovoltaic system
    Ben Safia, Z.
    Allouch, M.
    Harrabi, N.
    Bahloul, M.
    Chaabane, M.
    Aitouche, A.
    2018 7TH INTERNATIONAL CONFERENCE ON SYSTEMS AND CONTROL (ICSC), 2018, : 263 - 269
  • [7] The Maximum Power Point Tracking Algorithm for Photovoltaic Power System Based on Fuzzy Logic Double Loop Control
    Wu, Chengming
    Jiang, Feng
    Wang, Qin
    Hu, Hanwen
    2011 INTERNATIONAL CONFERENCE ON ELECTRONICS, COMMUNICATIONS AND CONTROL (ICECC), 2011, : 1130 - 1133
  • [8] The maximum power point tracking algorithm for photovoltaic power system based on fuzzy logic double loop control
    Su, Hai-Bin
    Wang, Guang-Zheng
    Wang, Ji-Dong
    Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control, 2010, 38 (21): : 215 - 218
  • [9] Fuzzy Logic Control for the tracking of maximum power point of a PV system
    Bouchafaa, F.
    Hamzaoui, I.
    Hadjammar, A.
    IMPACT OF INTEGRATED CLEAN ENERGY ON THE FUTURE OF THE MEDITERRANEAN ENVIRONMENT, 2011, 6 : 633 - 642
  • [10] Maximum Power Point Tracking of Photovoltaic System Using Taguchi-based Fuzzy Logic Control
    Hong, Ying-Yi
    Buay, Peter Mark P.
    Beltran, Angelo A., Jr.
    2019 IEEE MILAN POWERTECH, 2019,
12345