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The impact of tropical cyclones on potential offshore wind farms

Mattu, K. L., Bloomfield, H. C. ORCID:, Thomas, S., Martinez-Alvarado, O. ORCID: and Rodriguez-Hernandez, O. (2022) The impact of tropical cyclones on potential offshore wind farms. Energy for Sustainable Development, 68. pp. 29-39. ISSN 0973-0826

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To link to this item DOI: 10.1016/j.esd.2022.02.005


The climate crisis has led to an increased interest in renewable energy, and in wind energy in particular. Wind farms with the largest generating potential are generally located offshore. In this study we consider the case of Mexico, a sub-tropical country in North-America. Due to Mexico’s location, offshore wind farms (OWF) would be at risk of damage from strong winds associated with tropical cyclones (TCs) in both the Pacific and the Gulf of Mexico basins. Thus, here we ask whether there are any regions in Mexico combining a high generating potential and a low risk from tropical cyclones. To answer this question, the ERA5 reanalysis has been used to identify two sites on the Pacific coast and two sites in the Gulf of Mexico with high wind power potential. Then, using the ERA5 reanalysis and TC best-track observational data, the potential effects of four major hurricanes and the climatological hazard posed by TC-related damaging winds on OWFs at those sites have been investigated. The return period for TCs with near-surface winds exceeding $50\ \mathrm{m~s^{-1}}$, a threshold associated with increased structural damage likelihood, has been estimated at as low as 8 years for the Gulf of Mexico and above 64 years for Pacific coast. Therefore, in terms of the magnitude of the TC-related hazard, the Pacific coast sites are found to be preferred as locations for the development of OWFs. These results are relevant for any planning of offshore wind energy in Mexico, and the methodology applicable to any other sub-tropical region in which the risk of tropical cyclones is present.

Item Type:Article
Divisions:Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:104064


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