Study on offshore wind farm layout optimization based on decommissioning strategy

Haiying Sun, Hongxing Yang, Xiaoxia Gao

Research output: Journal article publicationConference articleAcademic researchpeer-review

8 Citations (Scopus)

Abstract

Published by Elsevier Ltd. In recent years, along with the first generation of wind power reaching retirement age, the high decommissioning cost arises with more and more attention all around the word. To reduce this huge cost, an innovative offshore wind farm layout optimization method based on decommissioning strategy is presented in this paper. In the optimization method, the decommissioning strategy means that the foundations can be reused after the retirement of the first generation of wind turbines, and then smaller second-generation wind turbines will be installed on the original foundations. The optimization process is based on the Multi-Population Genetic Algorithm (MPGA). A conceptual two-dimensional (2D) wake model is adopted to calculate wind losses caused by wake effect. The Cost of Energy (COE) is regarded as the criteria to judge the effectiveness of this new method. The way to estimate costs will also be introduced in this study. Finally, a case study in Waglan sea area in Hong Kong is analyzed and discussed. From the case results, Hong Kong is an ideal region to develop the offshore wind industry, and the proposed optimization method can reduce the COE down to 1.02 HK$/kWh.
Original languageEnglish
Pages (from-to)566-571
Number of pages6
JournalEnergy Procedia
Volume143
DOIs
Publication statusPublished - 1 Jan 2017
Event1st Joint Conference on World Engineers Summit - Applied Energy Symposium and Forum: Low Carbon Cities and Urban Energy, WES-CUE 2017 - Singapore, Singapore
Duration: 19 Jul 201721 Jul 2017

Keywords

  • Cost of energy
  • Decommissioning strategy
  • Multi-population genetic algorithm
  • Offshore wind farm layout optimization

ASJC Scopus subject areas

  • Energy(all)

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