Extreme Weather Impacts on Microgrid Components: A Critical Review Establishing Data-Driven Methods as the Definitive Path Forward

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Abstract

To address climate change, there is an acceleration of the integration of renewable energy (RE) technologies into power systems (including microgrids(MGs)) worldwide, with forecasts indicating that RE sources (RES) will be responsible for meeting approximately 50% of global energy consumption by 2025. While this transition supports meeting national and global targets and sustainability goals, it introduces significant operational challenges to electricity networks due to the weatherdependent nature of RE generation whilst there is growing electricity demand for heat, transport and other sectors. MGs have emerged as a popular option for meeting the growing demands from electric vehicle (EV) fleets and other emerging loads while enhancing the reliability and resilience of distribution networks (DNs). However, the renewable resources and components within the MGs also remain vulnerable to extreme weather conditions. This paper presents a comprehensive review of extreme weather impacts on key renewable-based MG components and hence the MG’s overall operations. Specifically, we discuss how extreme meteorological conditions can affect performance parameters, reliability metrics, and control requirements of key components like photovoltaic (PV) systems, EVs, and battery energy storage systems (BESS) within an MG. We conclude that robust weather aware data-driven frameworks and tools utilizing advanced forecasting algorithms are necessary to improve MG stability, efficiency, and operational security.
Original languageEnglish
Title of host publicationInternational Conference on Smart Grid (icSmartGrid)
Pages1-6
Number of pages6
Publication statusPublished - 29 May 2025

Keywords

  • Microgrids
  • Extreme Weather Events
  • Photovoltaic Systems
  • Battery Energy Storage Systems
  • Electric Vehicles
  • Data-Driven Approaches
  • Machine Learning
  • Energy Management Systems

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