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Bibliometric Analysis of Extreme Weather Research: Patterns and Partnerships in Power Grid Resilience Studies

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  • Mohammad Ali Tofigh

    (Higher Institution Center of Excellence (HICoE), UM Power Energy Dedicated Center (UMPEDAC), Level 4, Wisma R&D, Universiti Malaya, Jalan Pantai Baharu, Kuala Lumpur 59990, Malaysia
    Faculty of Information Sciences and Engineering, Management and Science University, Shah Alam 40150, Malaysia)

  • Jeyraj Selvaraj

    (Higher Institution Center of Excellence (HICoE), UM Power Energy Dedicated Center (UMPEDAC), Level 4, Wisma R&D, Universiti Malaya, Jalan Pantai Baharu, Kuala Lumpur 59990, Malaysia
    Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Padang, Padang 25131, Indonesia
    Department of Mathematical Sciences, Saveetha School of Engineering, SIMATS, Chennai 602105, Tamil Nadu, India)

  • Nasrudin Abd Rahim

    (Higher Institution Center of Excellence (HICoE), UM Power Energy Dedicated Center (UMPEDAC), Level 4, Wisma R&D, Universiti Malaya, Jalan Pantai Baharu, Kuala Lumpur 59990, Malaysia)

Abstract

The reliability and robustness of global electrical networks are being impacted by the reciprocal effects of climate change and severe weather events. This article assesses research and collaborative trends to further these concerns. This study attempts to identify trends, principal contributors, and emerging fields of research by a comprehensive bibliometric analysis of articles relevant to power system resilience during extreme weather events. A comprehensive search was conducted in the Web of Science and Scopus databases to acquire appropriate papers from 2014 to 2025. The implementation criteria for eligibility requirements comprised peer-reviewed publications, including reviews and conference papers. The Bibliometrix and Biblioshiny tools were used to conduct data analysis, evaluating keyword co-occurrences, citation networks, and cooperation networks. The study selection process and reporting adhered to the PRISMA 2020 framework. A dataset of 1178 documents from 535 sources indicated an annual growth rate of 13.06%. China was the most producing country, while the USA, China, UK, and Iran became the most cited countries. Keyword analysis identified common topics including resilience, power outages, and extreme weather, alongside an increasing focus on AI-driven modeling, distributed energy resources, and optimization algorithms. This systematic review emphasizes the growing research field addressing power system resilience, focusing on improvements in modeling strategies, optimization approaches, and risk management applications. Future research must concentrate on the integration of AI, evaluations of regional vulnerabilities, and the development of predictive frameworks to tackle rising climate concerns.

Suggested Citation

  • Mohammad Ali Tofigh & Jeyraj Selvaraj & Nasrudin Abd Rahim, 2025. "Bibliometric Analysis of Extreme Weather Research: Patterns and Partnerships in Power Grid Resilience Studies," Sustainability, MDPI, vol. 17(12), pages 1-20, June.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:12:p:5658-:d:1682993
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    References listed on IDEAS

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    1. Banghua Xie & Changfan Li & Zili Wu & Weiming Chen, 2021. "Topological Modeling Research on the Functional Vulnerability of Power Grid under Extreme Weather," Energies, MDPI, vol. 14(16), pages 1-27, August.
    2. Habibollah Raoufi & Vahid Vahidinasab & Kamyar Mehran, 2020. "Power Systems Resilience Metrics: A Comprehensive Review of Challenges and Outlook," Sustainability, MDPI, vol. 12(22), pages 1-24, November.
    3. Tommaso Bragatto & Massimo Cresta & Fabrizio Cortesi & Fabio Massimo Gatta & Alberto Geri & Marco Maccioni & Marco Paulucci, 2019. "Assessment and Possible Solution to Increase Resilience: Flooding Threats in Terni Distribution Grid," Energies, MDPI, vol. 12(4), pages 1-13, February.
    4. Adeniyi Kehinde Onaolapo & Rudiren Pillay Carpanen & David George Dorrell & Evans Eshiemogie Ojo, 2022. "A Comparative Assessment of Conventional and Artificial Neural Networks Methods for Electricity Outage Forecasting," Energies, MDPI, vol. 15(2), pages 1-21, January.
    5. Fang Yao & Jiawei Wang & Fushuan Wen & Chung-Li Tseng & Xingyong Zhao & Qiang Wang, 2019. "An Integrated Planning Strategy for a Power Network and the Charging Infrastructure of Electric Vehicles for Power System Resilience Enhancement," Energies, MDPI, vol. 12(20), pages 1-20, October.
    6. Neal R. Haddaway & Matthew J. Page & Chris C. Pritchard & Luke A. McGuinness, 2022. "PRISMA2020: An R package and Shiny app for producing PRISMA 2020‐compliant flow diagrams, with interactivity for optimised digital transparency and Open Synthesis," Campbell Systematic Reviews, John Wiley & Sons, vol. 18(2), June.
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    8. Zhai, Xiangyu & Li, Zening & Li, Zhengmao & Xue, Yixun & Chang, Xinyue & Su, Jia & Jin, Xiaolong & Wang, Peng & Sun, Hongbin, 2025. "Risk-averse energy management for integrated electricity and heat systems considering building heating vertical imbalance: An asynchronous decentralized approach," Applied Energy, Elsevier, vol. 383(C).
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    10. Muthusamy Thirumalai & Raju Hariharan & Thangaraj Yuvaraj & Natarajan Prabaharan, 2024. "Optimizing Distribution System Resilience in Extreme Weather Using Prosumer-Centric Microgrids with Integrated Distributed Energy Resources and Battery Electric Vehicles," Sustainability, MDPI, vol. 16(6), pages 1-41, March.
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