A comparison study of power performance and extreme load effects of large 10‐MW offshore wind turbines

Author:

Wang Shuaishuai1,Xing Yihan2ORCID,Karuvathil Anuraj2,Gaidai Oleg3

Affiliation:

1. Norwegian University of Science and Technology Trondheim Norway

2. Department of Mechanical and Structural Engineering and Materials Science University of Stavanger Stavanger Norway

3. Shanghai Engineering Research Centre of Marine Renewable Energy College of Engineering Science and Technology Shanghai Ocean University Shanghai China

Abstract

AbstractThe utilisation of offshore wind turbines has rapidly increased in the last decade, which has resulted in a steady increase in wind turbine sizes. The global average offshore wind turbine size has increased from 1.5 MW to 6 MW in the last two decades. The research community has started to investigate huge 10 to 15 MW offshore wind turbines in recent years, resulting in the study of very innovative floating wind turbines using various substructure technologies. With this backdrop, this paper will investigate and thoroughly compare the power performance of extreme load effects of a large offshore 10 MW turbine installed on the monopile, spar, and semisubmersible substructures. This is performed by using the average conditional exceedance rate (ACER) and Gumbel methods to predict the extreme responses under the operating conditions of 8, 12, and 16 m/s mean wind speed, representing the below‐rated, rated, and above‐rated regions, respectively. The results show that the power performance and extreme loads experienced depends significantly on the operating regions. The mean power generation between the three different types of offshore wind turbines (OWTs) are closely in the whole operating range, which standard deviations differ significantly. Large standard deviations of power generation appear in the spar turbine under the below‐rated condition. Further, it was observed that the spar wind turbine generally experiences larger extreme loads due to larger platform pitch motion. In addition, the ACER method shows a better prediction for the 1, 2 and 5‐year extreme responses than the Gumbel method, which is due to the relatively poor data fitting of the Gumbel method at the upper tail. The study is believed to consolidate and close the knowledge gap in understanding wind turbine responses across the most common offshore substructure technologies and provide a basis for design and deployment of OWTs.

Publisher

Institution of Engineering and Technology (IET)

Subject

Renewable Energy, Sustainability and the Environment

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