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Lookup NU author(s): Dr Hannah BloomfieldORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
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.
Author(s): Sanchez-Pozo N, Vanem E, Bloomfield HC, Aizpurua JI
Publication type: Article
Publication status: Published
Journal: Renewable Energy
Year: 2025
Volume: 240
Print publication date: 15/02/2025
Online publication date: 19/12/2024
Acceptance date: 12/12/2024
Date deposited: 24/01/2025
ISSN (print): 0960-1481
ISSN (electronic): 1879-0682
Publisher: Elsevier Ltd
URL: https://doi.org/10.1016/j.renene.2024.122168
DOI: 10.1016/j.renene.2024.122168
ePrints DOI: 10.57711/54cv-5215
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