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A probabilistic risk assessment framework for the impact assessment of extreme events on renewable power plant components

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  • Sánchez-Pozo, Nadia N.
  • Vanem, Erik
  • Bloomfield, Hannah
  • Aizpurua, Jose I.

Abstract

Climate change is expected to worsen the frequency, intensity, and impacts of extreme weather events. Renewable energy sources (RESs) play a key role in the decarbonization process to decelerate climate change effects. However, extreme events pose a significant threat to renewable energy infrastructure. Accordingly, understanding the impacts of extremes on RESs becomes crucial to ensure the reliability of power grids. In this context, this research presents a novel probabilistic risk assessment framework to evaluate the degradation of wind turbine transformers (WTTs) and photovoltaic (PV) panels in the face of extreme weather conditions. The framework uses a Gaussian copula to model the joint probability of extreme events, effectively incorporating multivariate phenomena. Case studies involving WTTs and PV panels operated in different wind and solar power plants, illustrate the effectiveness of the proposed methodology, demonstrating its ability to capture the combined influence of different meteorological variables on degradation rates. These results underscore the potential of this framework to assess weather-related risks in renewable energy systems, thereby enhancing their resilience and reliability.

Suggested Citation

  • Sánchez-Pozo, Nadia N. & Vanem, Erik & Bloomfield, Hannah & Aizpurua, Jose I., 2025. "A probabilistic risk assessment framework for the impact assessment of extreme events on renewable power plant components," Renewable Energy, Elsevier, vol. 240(C).
    • Handle: RePEc:eee:renene:v:240:y:2025:i:c:s0960148124022365
    DOI: 10.1016/j.renene.2024.122168
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    1. Samantha M. Treacy & Alexandra B. Moura, 2025. "The effects and financial impacts of wildfire smoke on solar photovoltaic power production in Alberta, Canada," Working Papers REM 2025/0373, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.

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