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An Improved Maximum Power Point Tracking Controller for PV Systems Using Artificial Neural Network

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Warianty tytułu
PL
Ulepszona metoda śledzenia maksymalnej mocy systemu fotowoltaicznego z wykorzystaniem sieci neuronowej
Języki publikacji
EN
Abstrakty
EN
This paper presents an improved maximum power point tracking (MPPT) controller for PV systems. An Artificial Neural Network and the classical P&O algorithm were employed to achieve this objective. MATLAB models for a neural network, PV module, and the classical P&O algorithm are developed. However, the developed MPPT uses the ANN to predict the optimum voltage of the PV system in order to extract the maximum power point (MPP). The developed ANN has a feedback propagation configuration and it has four inputs which are solar radiation, ambient temperature, and the temperature coefficients of Isc and Voc of the modeled PV module. Meanwhile, the optimum voltage of the PV system is the output of the developed ANN. Based on the results; the response of the proposed MPPT controller is faster than the classical P&O algorithm. Moreover, the average tracking efficiency of the developed algorithm was 95.51% as compared to 85.99% of the classical P&O algorithm. Such developed controller increases the conversion efficiency of a PV system.
PL
W artykule zaprezentowano ulepszony układ śledzenia maksymalnej mocy w systemie fotowoltaicznym. Zastosowano sieć neuronową i klasyczny algorytm P&O. Sieć neuronowa w sprzężeniu zwrotnym ma cztery wejścia: promieniowanie słoneczne, temperatura otoczenia i współczynniki temperaturowe Isc i Voc. Wyjściem jest optymalne napięcie systemu.
Słowa kluczowe
Rocznik
Strony
116--121
Opis fizyczny
Bibliogr. 12 poz., schem., wykr.
Twórcy
autor
autor
autor
  • Department of Electrical Power Engineering, Universiti Tenaga Nasional (UNITEN), 43000 Kajang, Malaysia, amahmoud@uniten.edu.my
Bibliografia
  • [1] Joe-Air Jiang, Tsong-Liang Huang, Ying-Tung Hsiao, Chia-Hong Chen, Maximum Power Tracking for Photovoltaic Power Systems, Tamkang Journal of Science and Engineering, 2005, Vol. 8, No. 2, pp. 147-153.
  • [2] Mohamed Azab, A New Maximum Power Point Tracking for Photovoltaic Systems, Proceedings of World Academy of Science Engineering and Technology, October 2008 ,Vol. 34, pp. 571-574.
  • [3] R.Ramaprabha, and B.L. Mathur, Intelligent Controller based Maximum Power Point Tracking for Solar PV System, International Journal of Computer Applications (0975 – 8887), January 2011, Vol. 12, No.10, pp. 37- 41.
  • [4] N. Femia, G. Petrone, G. Spagnolo and M. Vitelli, Optimization of Perturb and Observe Maximum Power Point Tracking Method, IEEE Transactions on Power Electronics, July 2005, Vol. 20, No. 4, pp. 963 – 973.
  • [5] J. Youngseok, S. Junghun, Y. Gwonjong and C. Jaeho, Improved Perturbation and Observation Method (IP&O) of MPPT Control for Photovoltaic Power Systems, The 31st Photovoltaic Specialists Conference, Lake Buena Vista, Florida, 3-7 January 2005, pp. 1788 – 1791.
  • [6] B. Amrouche, M. Belhamel, A.Guessoum, Artificial intelligence based P&O MPPT method for photovoltaic systems, Revue des Energies Renouvelables (ICRESD-07), Tlemcen (2007), pp.11–16.
  • [7] K. H. Hussein, I. Muta, T. Hoshino, M. Osakada, Maximum photovoltaic power tracking: an algorithm for rapidly changing atmospheric conditions, in IEE Proc. Generation, Transmission and Distribution, 1995, vol. 142, pp. 59-64.
  • [8] T.Tafticht, K. Agbossou , M. L.Doumbia, A.Che’riti, An Improved Maximum Power Point Tracking Method for Photovoltaic Systems, Renewable Energy, 2008, Vol. 33, pp. 1508–1516.
  • [9] Tamer T. N. Khatib, Azah Mohamed, Marwan Mahmoud, Nawshad Amin, An Efficient Maximum Power Point Tracking Controller for a Standalone Photovoltaic System, International Review on Modeling and Simulation (I.R.E.MO.S.), April 2010, Vol. 3, No. 2, pp. 129-139.
  • [10]V. Salas, E. O., A.Barrado, A. lazaro, Review of the maximum power point tracking algorithms for standalone photovoltaic systems, Solar Energy Materials & Solar Cells, 2006, Vol. 90, pp.1555–1578.
  • [11]Dezso Sera, Remus Teodorescu, Jochen Hantschel, Michael Knoll, Optimized Maximum Power Point Tracker for Fast-Changing Environmental Conditions, Industrial Electronics, IEEE Transactions on, July 2008, Vol. 55, No. 7, pp. 2629 –2637.
  • [12]Tamer T. N. Khatib, A. Mohamed, N. Amin, K. Sopian, An Efficient Maximum Power Point Tracking Controller for Photovoltaic Systems Using New Boost Converter Design and Improved Control Algorithm, WSEAS Transactions on power systems, April 2010, Issue 2, Vol. 5, pp. 53-63.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPOH-0063-0004
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