Optimal Micro-siting of Wind Turbines in an Offshore Wind Farm Using Frandsen-Gaussian Wake Model

Siyu Tao, Stefanie Kuenzel, Qingshan Xu, Zhe Chen

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This paper proposes a method to obtain the optimal placement of wind turbines (WTs) in an offshore wind farm (WF). The optimization objective is to minimize the levelized average cost per net electric power generated by a WF with a fixed number of WTs while the distance between WTs is not less than the allowed minimal distance in the far wake region. The WT wake losses have been taken into account, with the Frandsen-Gaussian (F-G) wake model and the optimization problem is subsequently solved by the Hybrid Grey Wolf Optimization (HGWO) algorithm. Synthesis methods which contain a special WT ranking strategy for multiple WTs are described in detail. Both the F-G model and Jensen’s model are applied in the offshore WF optimization simulation platform for comparison. Simulation results demonstrate that the F-G model is more consistent with real wakes and thus the optimization result is more accurate than the commonly used Jensen’s model.
Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalIEEE Transactions on Power Systems
Early online date14 May 2019
Publication statusE-pub ahead of print - 14 May 2019


  • Frandsen-Gaussian wake model, Hybrid Grey Wolf Optimization algorithm, micro-siting, offshore wind farm planning, optimization, wake effect

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