Collector system layout optimization framework for large-scale offshore wind farms

Yingying Chen, Zhao Yang Dong, Ke Meng, Feng Ji Luo, Zhao Xu, Kit Po Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

38 Citations (Scopus)


A new collector system layout optimization (CSLO) framework for large-scale offshore wind farms (OWFs) is proposed in this paper. First, a self-adaptive allocation method is proposed to determine the location of substations and to allocate each turbine to its geographically closest substation. And then, in order to minimize the annualized investment cost, maintenance cost, and levelized cable losses cost, while satisfying a group of operational constraints, the proposed CSLO model is formulated as a mixed-integer nonlinear programming problem, which is solved by the Benders decomposition algorithm. Multiple substations and cable types are also considered in the model. The validity and effectiveness of the proposed methods are demonstrated in two OWF cases consisting of 30 and 100 units.
Original languageEnglish
Article number7454777
Pages (from-to)1398-1407
Number of pages10
JournalIEEE Transactions on Sustainable Energy
Issue number4
Publication statusPublished - 1 Oct 2016


  • Benders decomposition
  • collector system layout
  • fuzzy C-means clustering
  • offshore wind farm planning

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment

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