Artificial Intelligence for Photovoltaic Systems

  • Rami GhannamEmail author
  • Paulo Valente Klaine
  • Muhammad Imran
Part of the Power Systems book series (POWSYS)


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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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Rami Ghannam
    • 1
    Email author
  • Paulo Valente Klaine
    • 1
  • Muhammad Imran
    • 1
  1. 1.School of EngineeringUniversity of GlasgowGlasgowUK

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