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Artificial Intelligence for Photovoltaic Systems

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Solar Photovoltaic Power Plants

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

Abstract

Photovoltaic systems have gained an extraordinary popularity in the energy generation industry. Despite the benefits, photovoltaic systems still suffer from four main drawbacks, which include low conversion efficiency, intermittent power supply, high fabrication costs and the nonlinearity of the PV system output power. To overcome these issues, various optimization and control techniques have been proposed. However, many authors relied on classical techniques, which were based on intuitive, numerical or analytical methods. More efficient optimization strategies would enhance the performance of the PV systems and decrease the cost of the energy generated. In this chapter, we provide an overview of how Artificial Intelligence (AI) techniques can provide value to photovoltaic systems. Particular attention is devoted to three main areas: (1) Forecasting and modelling of meteorological data, (2) Basic modelling of solar cells and (3) Sizing of photovoltaic systems. This chapter will aim to provide a comparison between conventional techniques and the added benefits of using machine learning methods.

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Author information

Authors and Affiliations

  1. School of Engineering, University of Glasgow, University Avenue, Glasgow, UK

    Rami Ghannam, Paulo Valente Klaine & Muhammad Imran

Authors
  1. Rami Ghannam
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  2. Paulo Valente Klaine
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  3. Muhammad Imran
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Corresponding author

Correspondence to Rami Ghannam .

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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Ghannam, R., Klaine, P.V., Imran, M. (2019). Artificial Intelligence for 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_6

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  • DOI: https://doi.org/10.1007/978-981-13-6151-7_6

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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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