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Effect of Saharan dust episodes on the accuracy of photovoltaic energy production forecast in Hungary (Central Europe)

Author

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  • Varga, György
  • Gresina, Fruzsina
  • Szeberényi, József
  • Gelencsér, András
  • Rostási, Ágnes

Abstract

In order to meet global sustainability goals, in particular, the rapid decarbonisation of the energy sector in combination with geopolitical energy security issues, as well as further improvement in regional air quality-the so-called renewable energy sources are becoming increasingly critical and important. Photovoltaic power (PV) generation is clearly the most widely deployed (non-hydro) renewable energy source globally, which still has a significant growth potential in many countries, including Hungary.

Suggested Citation

  • Varga, György & Gresina, Fruzsina & Szeberényi, József & Gelencsér, András & Rostási, Ágnes, 2024. "Effect of Saharan dust episodes on the accuracy of photovoltaic energy production forecast in Hungary (Central Europe)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 193(C).
  • Handle: RePEc:eee:rensus:v:193:y:2024:i:c:s1364032124000121
    DOI: 10.1016/j.rser.2024.114289
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    1. ., 2023. "European trends in referendum authorization," Chapters, in: Referendum Authorization Procedures in Europe, chapter 2, pages 26-53, Edward Elgar Publishing.
    2. Maëva Labouyrie & Cristiano Ballabio & Ferran Romero & Panos Panagos & Arwyn Jones & Marc W. Schmid & Vladimir Mikryukov & Olesya Dulya & Leho Tedersoo & Mohammad Bahram & Emanuele Lugato & Marcel G. , 2023. "Patterns in soil microbial diversity across Europe," Nature Communications, Nature, vol. 14(1), pages 1-21, December.
    3. Ahmed, R. & Sreeram, V. & Mishra, Y. & Arif, M.D., 2020. "A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    4. ., 2023. "Copy Europe or Go it Alone?," Chapters, in: The Footballization of China, chapter 4, pages 85-109, Edward Elgar Publishing.
    5. Behnam Zakeri & Katsia Paulavets & Leonardo Barreto-Gomez & Luis Gomez Echeverri & Shonali Pachauri & Benigna Boza-Kiss & Caroline Zimm & Joeri Rogelj & Felix Creutzig & Diana Ürge-Vorsatz & David G. , 2022. "Pandemic, War, and Global Energy Transitions," Energies, MDPI, vol. 15(17), pages 1-23, August.
    6. James D. Atkinson & Benjamin J. Murray & Matthew T. Woodhouse & Thomas F. Whale & Kelly J. Baustian & Kenneth S. Carslaw & Steven Dobbie & Daniel O’Sullivan & Tamsin L. Malkin, 2013. "The importance of feldspar for ice nucleation by mineral dust in mixed-phase clouds," Nature, Nature, vol. 498(7454), pages 355-358, June.
    7. Gandoman, Foad H. & Abdel Aleem, Shady H.E. & Omar, Noshin & Ahmadi, Abdollah & Alenezi, Faisal Q., 2018. "Short-term solar power forecasting considering cloud coverage and ambient temperature variation effects," Renewable Energy, Elsevier, vol. 123(C), pages 793-805.
    8. Shivashankar, S. & Mekhilef, Saad & Mokhlis, Hazlie & Karimi, M., 2016. "Mitigating methods of power fluctuation of photovoltaic (PV) sources – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1170-1184.
    9. Notton, Gilles & Nivet, Marie-Laure & Voyant, Cyril & Paoli, Christophe & Darras, Christophe & Motte, Fabrice & Fouilloy, Alexis, 2018. "Intermittent and stochastic character of renewable energy sources: Consequences, cost of intermittence and benefit of forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 87(C), pages 96-105.
    10. Barbieri, Florian & Rajakaruna, Sumedha & Ghosh, Arindam, 2017. "Very short-term photovoltaic power forecasting with cloud modeling: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 242-263.
    11. Campos, José & Csontos, Csaba & Munkácsy, Béla, 2023. "Electricity scenarios for Hungary: Possible role of wind and solar resources in the energy transition," Energy, Elsevier, vol. 278(PB).
    12. James D. Atkinson & Benjamin J. Murray & Matthew T. Woodhouse & Thomas F. Whale & Kelly J. Baustian & Kenneth S. Carslaw & Steven Dobbie & Daniel O’Sullivan & Tamsin L. Malkin, 2013. "Erratum: The importance of feldspar for ice nucleation by mineral dust in mixed-phase clouds," Nature, Nature, vol. 500(7463), pages 490-490, August.
    13. Maghami, Mohammad Reza & Hizam, Hashim & Gomes, Chandima & Radzi, Mohd Amran & Rezadad, Mohammad Ismael & Hajighorbani, Shahrooz, 2016. "Power loss due to soiling on solar panel: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1307-1316.
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