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PV Maximum Power-Point Tracking by Using Artificial Neural Network

Author

Listed:
  • Farzad Sedaghati
  • Ali Nahavandi
  • Mohammad Ali Badamchizadeh
  • Sehraneh Ghaemi
  • Mehdi Abedinpour Fallah

Abstract

In this paper, using artificial neural network (ANN) for tracking of maximum power point is discussed. Error back propagation method is used in order to train neural network. Neural network has advantages of fast and precisely tracking of maximum power point. In this method neural network is used to specify the reference voltage of maximum power point under different atmospheric conditions. By properly controling of dc-dc boost converter, tracking of maximum power point is feasible. To verify theory analysis, simulation result is obtained by using MATLAB/SIMULINK.

Suggested Citation

  • Farzad Sedaghati & Ali Nahavandi & Mohammad Ali Badamchizadeh & Sehraneh Ghaemi & Mehdi Abedinpour Fallah, 2012. "PV Maximum Power-Point Tracking by Using Artificial Neural Network," Mathematical Problems in Engineering, Hindawi, vol. 2012, pages 1-10, March.
    • Handle: RePEc:hin:jnlmpe:506709
    DOI: 10.1155/2012/506709
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    Cited by:

    1. Kuei-Hsiang Chao & Muhammad Nursyam Rizal, 2021. "A Hybrid MPPT Controller Based on the Genetic Algorithm and Ant Colony Optimization for Photovoltaic Systems under Partially Shaded Conditions," Energies, MDPI, vol. 14(10), pages 1-17, May.

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