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The Pursuit of the Maximum Power Point of a Photovoltaic System Using Artificial Neural Network

Part of the Lecture Notes in Networks and Systems book series (LNNS,volume 102)


The use of maximum power point tracking techniques in photovoltaic systems attracts particular attention to research and ensures that the photovoltaic energy system delivers as much as possible of the output power available to the load, regardless of the climatic conditions (variation in temperature and solar radiation), the choice and development are made to implement a more appropriate and effective maximum power point tracking controller using neural networks.

In order to obtain maximum power point tracking, the importance has also been given in this paper to the photovoltaic panel, these inputs (temperature and solar radiation) and also to the control of the power converter.

The results obtained using the Matlab/Simulink environment; confirm the effectiveness of the proposed method in terms of efficiency, fast calculation time of its robustness and the precision of its outputs which allow giving decisions correct, reliable and immediate.


  • Maximum power point tracking (MPPT)
  • Photovoltaic (PV) system
  • Artificial neural network (ANN)
  • Boost converter
  • Perturbation and observation (P & O)

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  • DOI: 10.1007/978-3-030-37207-1_11
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Correspondence to F. Saadaoui .

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Saadaoui, F., Mammar, K., Hazzab, A. (2020). The Pursuit of the Maximum Power Point of a Photovoltaic System Using Artificial Neural Network. In: Hatti, M. (eds) Smart Energy Empowerment in Smart and Resilient Cities. ICAIRES 2019. Lecture Notes in Networks and Systems, vol 102. Springer, Cham.

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