해양환경안전학회지 (Journal of the Korean Society of Marine Environment & Safety)

  • 제25권6호
  • /
  • Pages.658-665
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  • 2019
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  • 1229-3431(pISSN)
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  • 2287-3341(eISSN)
해양환경안전학회 (The Korean Society of Marine Environment and safety)
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유전 알고리즘을 활용한 부유식 해상풍력단지 최적위치 선정

Optimal Site Selection of Floating Offshore Wind Farm using Genetic Algorithm

  • 이정석 (한국해양대학교 대학원) ;
  • 손우주 (한국해양대학교 대학원) ;
  • 이보경 (한국해양대학교 선박운항과) ;
  • 조익순 (한국해양대학교 해사글로벌학부)
  • 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)
  • 투고 : 2019.10.07
  • 심사 : 2019.10.28
  • 발행 : 2019.10.31
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초록

신재생 에너지 자원중 풍력발전은 비약적인 기술 발전과 시장 규모가 급속하게 성장하고 있다. 최근 육상풍력발전단지의 공간적 한계, 환경 문제 등으로 인하여 설치 공간이 해상으로 이동되었고, 더욱 풍부한 풍황 조건을 가진 깊은 수심에 설치되는 부유식 해상풍력단지의 개발이 활발하게 진행되고 있다. 해상교통관점에서 해상풍력단지의 최적위치 선정은 선박과 풍력기들의 간섭을 최소화 하고 사고 확률이 적은 곳이며, 선박 밀집도가 낮은 해역이 최적위치로 선정된다. 본 연구에서는 유전 알고리즘 기반의 계절별 1주일 기간 선박자동식별장치 데이터를 유전자 및 염색체로 구성하였다. 80개의 유전자로 구성하고 유전 알고리즘의 적합도 평가를 거쳐 부유식 해상풍력단지의 계절별 최적위치를 선정하였다. 더 나아가 계절별 최적위치 점수를 합산하여 최종 최적위치를 선정하였다. 분석 해역에서 최적위치는 11개로 나타났으며, 해상교통관점에서 유전 알고리즘을 통한 최적위치 선정이 적용 가능함을 확인하였다.

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.

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참고문헌

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피인용 문헌

  1. AIS 기반 해양시설물과 선박간 권고 안전이격거리 선정에 관한 연구 vol.43, pp.6, 2019, https://doi.org/10.5394/kinpr.2019.43.6.420
  2. An Investigation of the Ship Safety Distance for Bridges across Waterways Based on Traffic Distribution vol.8, pp.5, 2019, https://doi.org/10.3390/jmse8050331
  3. Verification of Novel Maritime Route Extraction Using Kernel Density Estimation Analysis with Automatic Identification System Data vol.8, pp.5, 2019, https://doi.org/10.3390/jmse8050375
  4. Optimization of wind power plant sizing and placement by the application of multi-objective genetic algorithm (GA) in Madhya Pradesh, India vol.32, 2019, https://doi.org/10.1016/j.suscom.2021.100606
  5. Extracting the Maritime Traffic Route in Korea Based on Probabilistic Approach Using Automatic Identification System Big Data vol.12, pp.2, 2019, https://doi.org/10.3390/app12020635