Greedy robust wind farm layout optimization with feasibility guarantee

Ning Quan, Harrison M. Kim

Research output: Contribution to journalArticlepeer-review


This article proposes a method with light data requirements for generating robust wind farm layouts. Robustness in this work is quantified as the lowest energy conversion efficiency of the wind farm across all wind directions. A quadratic integer programming formulation for generating robustness-maximizing layouts is presented. Small instances of the proposed formulation can be solved to optimality using branch and bound. A modified greedy algorithm that guarantees solution feasibility with regards to inter-turbine safety distance is proposed to find solutions to larger problem instances. A series of experiments were conducted using real world wind data collected at two sites to demonstrate the trade-offs in power generation between robust layouts and power output maximizing layouts. The results show a loss of around 1.1% in hourly power generation in return for an increase in minimum power output of 1% to 45% across all directions for robust layouts generated in the experiments. The increase in robustness largely depends on the shape and orientation of the wind farm relative to the dominant wind direction, as well as the difference between the average wind speed at the site of the wind farm and rated wind speed of the turbines.

Original languageEnglish (US)
Pages (from-to)1152-1167
Number of pages16
JournalEngineering Optimization
Issue number7
StatePublished - Jul 3 2019


  • Wind farm
  • greedy algorithm
  • layout optimization
  • robust

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Optimization
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Applied Mathematics


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