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An Online Self Recurrent Direct Adaptive Neuro-Fuzzy Wavelet Based Control of Photovoltaic Systems

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Solar Photovoltaic Power Plants

Part of the book series: Power Systems ((POWSYS))

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Abstract

Solar through photovoltaic is an inexhaustible energy source which contributes to enhance the sustainability of the society. Though, photovoltaic systems experience some fundamental problems such as low conversion efficiency particularly during high weather variations and the high nonlinearity between the photovoltaic output power and current. These problems involve in photovoltaic systems need the use of advanced intelligent control methods. This book chapter develops a new direct adaptive maximum power point tracking control for photovoltaic systems. The new proposed technique integrates a Chebyshev wavelet in the consequent part of existing neuro-fuzzy structure. The parameters of the proposed controller are tuned adaptively online using backpropagation algorithm. The performance of the proposed method is tested under high uncertainties appearing from solar irradiance, temperature and fluctuations in load. Finally, simulation results are provided to show that the proposed control method is better than other existing methods in terms of efficiency, load tracking and output power.

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Author information

Authors and Affiliations

  1. School of Electrical Engineering, Chongqing University, Chongqing, China

    Syed Zulqadar Hassan

  2. Faculty of Engineering, Department of Electrical and Electronics Engineering, Sakarya University, Sakarya, Turkey

    Tariq Kamal

  3. Research Group in Electrical Technologies for Sustainable and Renewable Energy (PAIDI-TEP023), Department of Electrical Engineering, Higher Polytechnic School of Algeciras, University of Cadiz, Algeciras, Spain

    Tariq Kamal

  4. Department of Electrical Engineering, COMSATS University, Abbottabad Campus, Islamabad, Pakistan

    Sidra Mumtaz & Laiq Khan

Authors
  1. Syed Zulqadar Hassan
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  2. Tariq Kamal
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  3. Sidra Mumtaz
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  4. Laiq Khan
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Corresponding author

Correspondence to Syed Zulqadar Hassan .

Editor information

Editors and Affiliations

  1. Faculty of Automation and Computers, Politehnica University of Timișoara, Timișoara, Romania

    Radu-Emil Precup

  2. Department of Electrical and Electronics Engineering, Sakarya University, Serdivan/Sakarya, Turkey

    Tariq Kamal

  3. School of Electrical Engineering, Chongqing University, Chongqing, China

    Syed Zulqadar Hassan

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Hassan, S.Z., Kamal, T., Mumtaz, S., Khan, L. (2019). An Online Self Recurrent Direct Adaptive Neuro-Fuzzy Wavelet Based Control of Photovoltaic Systems. In: Precup, RE., Kamal, T., Zulqadar Hassan, S. (eds) Solar Photovoltaic Power Plants. Power Systems. Springer, Singapore. https://doi.org/10.1007/978-981-13-6151-7_11

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  • DOI: https://doi.org/10.1007/978-981-13-6151-7_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6150-0

  • Online ISBN: 978-981-13-6151-7

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