Ukrainian Antarctic Journal

Vol 23 No 2(31) (2025): Ukrainian Antarctic Journal
Articles

Renewable energy-based power generation in Antarctica: Roadmap for optimal sizing, placement and uncertainties prediction using AI-guided technological advances

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  • Muhammad Fahad Shinwari,
  • Muhamad Zahim Sujod,
  • Norhafidzah Mohd Saad,
  • Nor Azwan Mohamed Kamari,
  • Muhamad Zalani Daud,
  • Erhan Arslan
Muhammad Fahad Shinwari
Faculty of Electrical & Electronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, Pekan, 26600, Malaysia
Muhamad Zahim Sujod
Faculty of Electrical & Electronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, Pekan, 26600, Malaysia
Norhafidzah Mohd Saad
Faculty of Electrical & Electronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, Pekan, 26600, Malaysia
Nor Azwan Mohamed Kamari
Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi, 43600, Malaysia
Muhamad Zalani Daud
Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu, Kuala Terengganu, 21300, Malaysia
Erhan Arslan
TÜBİTAK Marmara Research Center, Polar Research Institute, Gebze/Kocaeli, 41470, Türkiye
DOI: https://doi.org/10.33275/1727-7485.2.2025.754
Published December 30, 2025
Keywords
  • Antarctica renewable energy,
  • energy efficiency,
  • Grey Wolf Optimisation,
  • Random Forest Regression,
  • solar photovoltaic and wind power,
  • technological innovations
    • ...More
    Less
How to Cite
Fahad Shinwari, M., Zahim Sujod, M., Mohd Saad, N., Mohamed Kamari, N. A., Zalani Daud, M., & Arslan, E. (2025). Renewable energy-based power generation in Antarctica: Roadmap for optimal sizing, placement and uncertainties prediction using AI-guided technological advances. Ukrainian Antarctic Journal, 23(2(31), 97-114. https://doi.org/10.33275/1727-7485.2.2025.754

Copyright (c) 2025 Ukrainian Antarctic Journal

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Abstract

Antarctica, the most remote and environmentally extreme region on Earth, presents unique challenges for energy generation due to its harsh climate, isolation, and logistical constraints. The continent’s research stations, vital for advancing global understanding of climate change, glaciology, ecosystem, and environmental studies, have historically relied on fossil fuels for power, which poses significant logistical and environmental risks, high operational costs, and ethical concerns related to fossil fuel usage in such a pristine environment. This paper provides a comprehensive review of the current landscape of renewable energy adoption in Antarctica, focusing on key research stations such as Princess Elisabeth Station, McMurdo Station, and others that have adopted solar, wind, and hybrid power systems. The paper also discusses the major challenges to widespread renewable energy adoption, including extreme weather conditions, temperature fluctuations, equipment reliability issues, seasonal energy variability, and technological limitations in energy capture and storage systems capabilities. In response to these challenges, the paper explores the potential of advanced computational and artificial intelligence methods to enhance renewable energy system planning in Antarctica. Furthermore, it highlights emerging opportunities for improving renewable energy efficiency and reliability by integrating advanced technologies such as Grey Wolf Optimisation for optimal energy source placement, Random Forest Regression for weather prediction, and innovations in hybrid solar and wind power. The findings underscore the critical need for technological advancements and international collaboration with the Polar Research Institute, Türkiye, to improve energy sustainability, specifically in Horseshoe Island, as well as across the broader Antarctic region. The research concludes by offering recommendations for future research directions, including the implementation of robust data-driven forecasting models and high-performance energy storage technologies. These strategies aim to support the full transition of Antarctica’s energy infrastructure to renewable sources, in alignment with urgent global goals to reduce carbon emissions and the imperative to protect one of the Earth’s most fragile ecosystems.

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