Integrated optimization of offshore wind farm layout design and turbine opportunistic condition-based maintenance

Sanling Song, Qing Li, Frank A. Felder, Honggang Wang, David W. Coit

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)


A two-stage optimization model has been developed for an offshore wind farm that integrates layout design and turbine maintenance policy-making. In Stage 1, first, the optimal development of the offshore wind resource aims to maximize the wind energy production by seeking the optimal turbine layout under uncertainty of wind conditions, in which the optimal number of turbines N and their productive placement are determined. Then, the locations of N turbines are further optimized for maximal energy production. Due to the unique maintenance challenges for offshore wind farm, in Stage 2, we develop computational tools for a novel opportunistic condition-based maintenance policy, in which the periodic inspection intervals are chosen to ensure the reliable energy production with limited maintenance costs. In this study, probabilistic models are built for stochastic wind speeds and directions. We apply Monte Carlo simulation for sampling wind data from the wind probabilistic models considering multiple seasonal scenarios. The algorithm efficiency of the two-stage optimization framework is demonstrated based on the results of a case of wind farm development along the New Jersey coast.

Original languageEnglish
Pages (from-to)288-297
Number of pages10
JournalComputers and Industrial Engineering
Publication statusPublished - Jun 2018


  • Condition-based maintenance
  • Offshore wind farm
  • Opportunistic maintenance

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

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