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http://dx.doi.org/10.7837/kosomes.2019.25.6.658

Optimal Site Selection of Floating Offshore Wind Farm using Genetic Algorithm  

Lee, Jeong-Seok (Graduate School of Korea Maritime and Ocean University)
Son, Woo-Ju (Graduate School of Korea Maritime and Ocean University)
Lee, Bo-Kyeong (Department of Ship Operation, Korea Maritime and Ocean University)
Cho, Ik-Soon (Division of Global Maritime Studies, Korea Maritime and Ocean University)
Publication Information
Journal of the Korean Society of Marine Environment & Safety / v.25, no.6, 2019 , pp. 658-665 More about this Journal
Abstract
Among the renewable energy resources, wind power is growing rapidly in terms of technological development and market share. Recently, onshore wind farm have been affected by limitations of terrestrial space and environmental problems. Consequently, installation sites have been moved to the sea, and the development of floating offshore wind farms that are installed at deep waters with more abundant wind conditions is actively underway. In the context of maritime traffic, the optimal site of offshore wind farms is required to minimize the interference between ships and wind turbines and to reduce the probability of accidents. In this study, genetic algorithm based AIS(Automatic Indentification System) data composed of genes and chromosomes has been used. The optimal site of floating offshore wind farm was selected by using 80 genes and by evaluating the fitness of genetic algorithm. Further, the final site was selected by aggregating the seasonal optimal site. During analysis, 11 optimal site were found, and it was verified that the final site selected usng the genetic algorithm was viable from the perspective of maritime traffic.
Keywords
Floating Offshore Wind Farm; Optimal Site; Genetic Algorithm; Ship Density; AIS Data;
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Times Cited By KSCI : 3  (Citation Analysis)
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