• N. TKOUTI Electrical engineering department University of Biskra, Algeria
  • A. MOUSSI Electrical engineering department University of Biskra, Algeria


paper presents a fuzzy logic controller (FLC) used as a maximum power point tracker(MPPT) of a line commutated inverter in
a photovoltaic (PV) grid connected system, under variable irradiance conditions. The purpose is to find the relationship
between the maximum power point (MPP) and weather parameters and track the MPP and transferring the maximum power to
utility grid. The design of control rules were found by genetic algorithms (GAs) to modulate the firing angle of the inverter for
tracking the MPP. Simulation results prove the superior tracking efficiency of the fuzzy controller optimized under variable
KEYWORDS: Fuzzy Controller, Genetic Algorithm, Grid Connection, Maximum Power Point Tracking, Photovoltaic
Energy. Weather conditions.


[1] M.Fadaee*, M.A.M. Radzi Multi-objective
optimization of stand-alone hybrid renewable energy
system by using evolutionary algorithms: A review
Renewable and sustainable Energy Reviews 16(2012),
pp: 3364-3369.
[2] A. Bouilotaa , A.Millita, b, *, S. A. Kalogirouc New
MPPT method for stand alone photovoltaic systems
operating under partially shaded conditions. Energy 55
(2013): 1172-1185.
[3] Ganesh Kumar Venayagamoorthy*, Richard L. Welch
Energy dispatch controllers for a photovoltaic system.
Engineering Applications of Artificial Intelligence
23(2010): 249-261.
[4] A. Messaia, A.Mellitb,*,1, A.GuessoumC, S.A.
Kalogiroud Maximum power point tracking using a
GA optimized fuzzy logic controller and its FPGA
implementation. Solar Energy 85(2011): 265-277.
[5] W. Swiegers and J. Enslin An Integrated Maximum
Power Point Tracker for Photovoltaic Panels.
Proceedings of IEEE International Symposium on
Industrial Electronic1998, Vol. 1, 1998: 40-44.
[6] Trishan Esram, and Patrick L. Chapman Comparison
of Photovoltaic Array Maximum Power Point
Tracking Techniques. IEEE Transactions on Energy
Conversion, vol. 22, No. 2: 439-449, June 2007.
[7] A. Brambilla New Approach to Photovoltaic Arrays
reference power
output power Maximum Power Point Tracking. Proceeding of 30th
IEEE Power Electronics Specialists Conference, Vol.
2, 1998: 632-637.
[8] C.Larbes, S.M.Ait Cheikh, T.Obeidi, A.Zerguerras
Genetic Algorithms Optimized Fuzzy Logic Control
for the Maximum Power Point Tracking in
Photovoltaic System. Renewable Energy 34 (2009)
[9] Anastasios I. Dounis*, Panagiotis Kofinas,
Constantine Alafodimos, Dimitrios Tseles Adaptive
fuzzy gain scheduling PID controller for maximum
power point tracking of photovoltaic system.
Renewable energy 60(2013): 202-214
[10] Shawu Lia,b, Xianwen Gaoa,*, Lina Wanga, Sanjun
Liub A novel maximum power point tracking control
method with variable weather parameters for
photovoltaic systems. Solar energy 97(2013) : 529-
[11] M.U. Siddiquia,*, M. Abidob Parameter estimation for
five-and seven-parameter photovoltaic electrical
models using evolutionary algorithms. Applied soft
computing 13(2013): 4608-4621.
[12] A.Terki*, A.Moussi, A.Betka, N.Terki An improved
efficiency of fuzzy logic control of PMBLDC for PV
pumping system Applied mathematical modeling
36(2012) 934-944.
[13] A. Betka*, A. Attali, Optimization of a photovoltaic
pumping system based on the optimal control theory,
Sol. Energ. 84 (2010) 1273–1283
Comment citer
TKOUTI, N.; MOUSSI, A.. MAXIMUM POWER POINT TRACKER USING GENETIC FUZZY CONTROLLER FOR PHOTOVOLTAIC GRID CONNECTED ARRAY. Courrier du Savoir, [S.l.], v. 19, mars 2015. ISSN 1112-3338. Disponible à l'adresse : >>. Date de consultation : 18 sep. 2020