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|Title:||Investigation into offshore wind farm repowering optimization in Hong Kong||Authors:||Sun H
|Keywords:||Levelised cost of energy
Multi-population genetic algorithm
Offshore wind farm layout optimization
|Issue Date:||2019||Publisher:||Manchester University Press||Source:||International journal of low-carbon technologies, 2019, v. 14, no. 2, p. 302-311 How to cite?||Journal:||International journal of low-carbon technologies||Abstract:||With the growing prosperity of the offshore wind energy market and the approaching end of the lifetime of the first-generation offshore wind farms, the high decommissioning cost has attracted increasing attention all over the world. To decrease this cost, the spotential repowering strategies are applied into the wind farm optimization and investigated in this study. In the repowering optimization strategy, the wind turbine foundations are not dismantled immediately after their service lifetime, and the lifecycle of them is extended to two generations' service time. The costs of removing the first foundations and installing the second foundations are saved. With the layout optimization method, the wind loss caused by wake effect can be decreased, which improve the energy output of the wind farm in the whole lifetime. Levelised cost of energy (LCoE) is set as the criterion to evaluate the wind farm layout. Both aligned and optimized layouts are analyzed in this study. A case study in Sha Chau Island seawater area in Hong Kong is then discussed. The results reveal that Hong Kong has many advantages to exploit offshore wind power and the repowering optimization layout is practical for cost-saving. According to this study, the LCoE of an offshore wind power farm in Sha Chau Island seawater area could be decreased to 0.9130 HK$/kWh.||URI:||http://hdl.handle.net/10397/81229||ISSN:||1748-1317||EISSN:||1748-1325||DOI:||10.1093/ijlct/ctz016||Rights:||© The Author(s) 2019. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
The following publication Haiying Sun, Xiaoxia Gao, Hongxing Yang, Investigation into offshore wind farm repowering optimization in Hong Kong, International Journal of Low-Carbon Technologies, Volume 14, Issue 2, June 2019, Pages 302–311, is available at https://doi.org/10.1093/ijlct/ctz016
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