ASCC & international research aims to calculate risk conditions for floating offshore wind

An article by Advanced Structures & Composites Center (ASCC) researchers Saravanan Bhaskaran, Amrit Shankar Verma, and Andrew J. Goupee, along with University of Surrey researcher, Subhamoy Bhattacharya, Norwegian University of Science and Technology researcher, Amir R. Nejad, and Dalian University of Technology Deepwater Engineering Research Center researcher, Wei Shi was published in Energies Journal. The publication titled, “Comparison of Extreme Wind and Waves Using Different Statistical Methods in 40 Offshore Wind Energy Lease Areas Worldwide”, aims to approximately calculate extreme wind and wave conditions spanning multiple newly designated offshore wind lease sites on six continents. 

These calculations are critical for risk assessment and the development of offshore wind turbines. This study unearthed valuable information for the development of offshore wind farms, which hold the potential to power not just the state of Maine, but the United States.

“Within 50 miles of the U.S. coasts, there is enough offshore wind capacity, theoretically, to power the country four times over.” – Dr. Habib Dagher, ASCC Executive Director

Comparison of Extreme Wind and Waves Using Different Statistical Methods in 40 Offshore Wind Energy Lease Areas Worldwide

Saravanan Bhaskaran, Amrit Shankar Verma, Andrew J. Goupee, Subhamoy Bhattacharya, Amir R. Nejad and Wei Shi

Energies Journal (2023)

https://www.mdpi.com/1996-1073/16/19/6935

Abstract

With the ongoing global drive towards renewable energy, several potential offshore wind energy lease areas worldwide have come into focus. This study aims to estimate the extreme wind and wave conditions across several newly designated offshore wind lease sites spanning six continents that are crucial for risk assessment and the design of offshore wind turbines. Firstly, the raw data of wind speeds and wave heights prevailing in these different lease areas were obtained. Following this, an in-depth extreme value analysis was performed over different return periods. Two principal methodologies were applied for this comparative study: the block-maxima and the peaks-over-threshold (POT) approaches. Various statistical techniques, including the Gumbel method of moments, Gumbel maximum likelihood, Gumbel least-squares, and the three-parameter GEV, were employed under the block-maxima approach to obtain the distribution parameters. The threshold for the POT approach was defined using the mean residual life method, and the distribution parameters were obtained using the maximum likelihood method. The Gumbel least-squares method emerged as the most conservative estimator of extreme values in the majority of cases, while the POT approach generally yielded lower extreme values compared to the block-maxima approach. However, the results from the POT approach showed large variations based on the selected threshold. This comprehensive study’s findings will provide valuable input for the efficient planning, design, and construction of future offshore wind farms.

Keywords: offshore wind turbines; extreme value analysis; block maxima; peaks-over-threshold

Contact: Amy Blanchard amy.i.blanchard@maine.edu