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Modelling of a Large Solar PV Facility: England’s Mallard Solar Farm Case Study

Author

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  • Tariq Muneer

    (School of Computing, Engineering and the Built Environment, Edinburgh Napier University, Edinburgh EH10 5DT, UK)

  • Mehreen Saleem Gul

    (School of Energy, Geoscience, Infrastructure and Society, Heriot Watt University, Edinburgh EH14 4AS, UK)

  • Marzia Alam

    (School of Energy, Geoscience, Infrastructure and Society, Heriot Watt University, Edinburgh EH14 4AS, UK)

Abstract

With reference to energy generation, the global society has to urgently address three factors that are now critical: sustainability in terms of climate change, security in terms of the war that is currently raging in Europe with consequences that are being felt around the globe and the steep incline of fossil-fuel based energy costs. Around the world, large-scale solar farms are being constructed with tracking systems to improve the efficiency of photovoltaic (PV) modules. This article presents a comparison of energy generation of fixed-slope versus tracking PV modules. The analysis was based on a twenty-year dataset for two locations, namely, Lincoln (England) and Bhavnagar (India), which differ in terms of latitude, sky clarity and ambient temperature. It was demonstrated that a fixed-slope system facing the equator provides a healthy energy receipt that is a high fraction of the energy receipt of a tracking system. Furthermore, analysis was also carried out for a PV facility that will host the largest solar farm in England to conclude that regardless of the solar farm installation location, the use of bifacial PV is beneficial.

Suggested Citation

  • Tariq Muneer & Mehreen Saleem Gul & Marzia Alam, 2022. "Modelling of a Large Solar PV Facility: England’s Mallard Solar Farm Case Study," Energies, MDPI, vol. 15(22), pages 1-17, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:22:p:8609-:d:975247
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    References listed on IDEAS

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    1. Dimitra G. Vagiona, 2021. "Comparative Multicriteria Analysis Methods for Ranking Sites for Solar Farm Deployment: A Case Study in Greece," Energies, MDPI, vol. 14(24), pages 1-23, December.
    2. Ram Machlev & Zohar Batushansky & Sachin Soni & Vladimir Chadliev & Juri Belikov & Yoash Levron, 2020. "Verification of Utility-Scale Solar Photovoltaic Plant Models for Dynamic Studies of Transmission Networks," Energies, MDPI, vol. 13(12), pages 1-21, June.
    3. Mehreen Gul & Yash Kotak & Tariq Muneer & Stoyanka Ivanova, 2018. "Enhancement of Albedo for Solar Energy Gain with Particular Emphasis on Overcast Skies," Energies, MDPI, vol. 11(11), pages 1-17, October.
    4. Maria Krechowicz & Adam Krechowicz & Lech Lichołai & Artur Pawelec & Jerzy Zbigniew Piotrowski & Anna Stępień, 2022. "Reduction of the Risk of Inaccurate Prediction of Electricity Generation from PV Farms Using Machine Learning," Energies, MDPI, vol. 15(11), pages 1-21, May.
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    Cited by:

    1. Savas Alkan & Yavuz Ates, 2023. "Pilot Scheme Conceptual Analysis of Rooftop East–West-Oriented Solar Energy System with Optimizer," Energies, MDPI, vol. 16(5), pages 1-25, March.

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