Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81229
Title: Investigation into offshore wind farm repowering optimization in Hong Kong
Authors: Sun H 
Gao X
Yang H 
Keywords: Levelised cost of energy
Multi-population genetic algorithm
Offshore wind farm layout optimization
Repowering strategy
Wake effect
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
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Sun_nvestigation_offshore_wind.pdf1.59 MBAdobe PDFView/Open
Access
View full-text via PolyU eLinks SFX Query
Show full item record
PIRA download icon_1.1View/Download Contents

Page view(s)

10
Citations as of Oct 22, 2019

Download(s)

4
Citations as of Oct 22, 2019

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.