Robust design optimization of supporting structure of offshore wind turbine

Yang, H. and Zhu, Y. (2015) Robust design optimization of supporting structure of offshore wind turbine. Journal of Marine Science and Technology, 20(4), pp. 689-702. (doi:10.1007/s00773-015-0323-4)

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In this paper, we present a robust design optimization (RDO) framework for the supporting structures of offshore wind turbines that takes uncertainties into consideration. Given the large sizes of turbines and the high complexity of ocean engineering systems, optimizing the supporting structures of offshore wind turbines can significantly save costs while enabling the structures to survive the severe ocean environment. The type of RDO used in our study focuses on reducing the structural weight of a turbine and lowering its variation to achieve stable (or robust) operation and minimal cost. To save computational costs, the design of experiment process was introduced for sensitivity analysis of the design variables and the arrangement of sampling points. The metamodel technology including the Kriging model was used in this study to replace the time-consuming finite element model for dynamic response analysis. A simple test case using a cantilever was introduced first for briefly illustrating the validity of the RDO framework method. Deterministic optimization (DO), which does not consider uncertainties, was conducted simultaneously for comparison. Subsequently, the numerical case of a tripod-type supporting structure of a 5 MW offshore wind turbine was built for formal optimization. The comparison revealed that the reliability of constraints in RDO was much higher than that in DO, whereas the standard deviation in RDO was lower, implying that robust and reliable design results were obtained even under the influence of uncertainties. The results also demonstrated the feasibility of application of the proposed RDO framework method to other offshore supporting structures.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Yang, Dr Hezhen
Authors: Yang, H., and Zhu, Y.
College/School:College of Science and Engineering > School of Engineering > Infrastructure and Environment
Journal Name:Journal of Marine Science and Technology
ISSN (Online):1437-8213
Published Online:22 May 2015

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