해상풍력발전단지 최적배치를 위한 In-house 코드 개발
Development of an In-house Code for Layout Optimization of Offshore Wind Farms
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
In this study, an in-house code to optimize an offshore wind farm layout based on economic analysis was constructed using Matlab. The code uses a wind resource file obtained from a commercial wind resource analysis program and a power curve provided as user input to calculate the power generation from wind turbines. For optimization, the model uses the golden section search and the parabolic interpolation method that are available as an internal function in Matlab. The verification of the in-house code was made in two steps. In the first step, a region on the east coast of Korea was selected and the code was applied to find the optimal layout within that region with a specified minimum wind turbine spacing by considering wind farm power production only. The results were then compared with the results from a commercial wind farm layout optimization program. In the second step, the in-house code was applied to find the optimal layout within the same region by considering economics. In the comparison, the in-house code showed similar optimization results to WindPRO for power production, and it clearly showed that the layout optimized for economics is much different from that for power production.
Abstract
In this study, an in-house code to optimize an offshore wind farm layout based on economic analysis was constructed using Matlab. The code uses a wind resource file obtained from a commercial wind resource analysis program and a power curve provided as user input to calculate the power generation from wind turbines. For optimization, the model uses the golden section search and the parabolic interpolation method that are available as an internal function in Matlab. The verification of the in-house code was made in two steps. In the first step, a region on the east coast of Korea was selected and the code was applied to find the optimal layout within that region with a specified minimum wind turbine spacing by considering wind farm power production only. The results were then compared with the results from a commercial wind farm layout optimization program. In the second step, the in-house code was applied to find the optimal layout within the same region by considering economics. In the comparison, the in-house code showed similar optimization results to WindPRO for power production, and it clearly showed that the layout optimized for economics is much different from that for power production.
참고문헌 (27)
- "Renewable Energy 3020 Implentation Plan"[URL]
- 2019 Annual Report on Wind Energy Industry in Korea, "Korea Wind Energy Industry Association", ~ (2020)
- "Global Offshore Renewable map are available online"[URL]
- 우재균, "AWS 풍황데이터를 이용한 강원풍력발전단지 연간에너지발전량 예측", 한국태양에너지학회 논문집, 31(2), pp.72~81 (2011), 한국태양에너지학회
- 송원, "국가바람지도와 상용 단지설계 프로그램을 활용한 국내해상풍력단지 공급가능 잠재량 산정", 한국태양에너지학회 논문집, 36(4), pp.21~29 (2016), 한국태양에너지학회
- 박웅식, "다중 배제분석을 이용한 강원도 내 풍력발전단지 유망후보지 선정", 한국태양에너지학회 논문집, 35(2), pp.1~10 (2015), 한국태양에너지학회
- 송원, "Investigation on Promising Offshore Wind Farm Sites and their Wind Farm Capacity Factors considering Wake Losses in Korea", 풍력에너지저널, 9(1), pp.27~36 (2018), 한국풍력에너지학회[DOI]
- A note on wind generator interaction, "Jensen N.O.", RISØ National Laboratory, ~, pp.DK-4000 (1983)
- Zhenzhou, S., "Multiple Wind Turbine Wakes Modeling Considering the Faster Wake Recovery in Overlapped Wakes", Energies, 12(4), pp.680~ (2019)
- 권일한, "와이블 형상계수에 따른 이용률 변화", 한국태양에너지학회 논문집, 33(1), pp.32~39 (2013), 한국태양에너지학회
- 김민지, "유동해석 결과를 이용한 풍력발전단지 연간 발전량 예측 및 경제성 분석 코드 개발", 풍력에너지저널, 11(3), pp.23~30 (2020), 한국풍력에너지학회[DOI]
- Investigation on potential sites for additional domestic offshore wind farms, Project Final Report, "Kangwon National University", Korea Institute of Energy Technology Evaluation and Planning, ~ (2013)
- Preliminary Validity Study Report of Public Institution Project, "Korea Development Institution", ~ (2018)
- Kim, C. J., "A Study on Application of Wind Power System on Islands for Micro Grid Construction in Korea", Master, pp.2017
- Standard market unit price of electric construction, "Ministry of Trade Industry and Energy", ~ (2020)
- Wind Directions, "Supply Chain : The Race to Meet Demand" (2007)
- Renewable Power Generation Costs in 2019, "International Renewable Energy Agency(IRENA)", ~ (2020)
- Kim, H. G., "Development and Validation of The Wind Farm Simulation Tool including Wind Farm Control Algorithm", Doctor, pp.2019
- 김진한, "MERRA 재해석 자료를 이용한 복잡지형 내 풍력발전단지연간에너지발전량 예측", 한국태양에너지학회 논문집, 34(2), pp.82~90 (2014), 한국태양에너지학회
- 송원, "해상풍력발전단지 연간발전량 예측을 위한 MERRA 재해석 데이터 적용 타당성 연구", 한국태양에너지학회 논문집, 35(2), pp.33~42 (2015), 한국태양에너지학회
- 고월, "MERRA 재해석 데이터를 이용한 중국 동하이대교 풍력단지 에너지발전량 예측", 한국태양에너지학회 논문집, 35(3), pp.1~8 (2015), 한국태양에너지학회
- Kim, H. G., "Wind Resource Assessment on the Western Offshore of Korea Using MERRA Reanalysis Data", Journal of Wind Energy, 4(1), pp.39~45 (2013)
- 김현구, "재해석자료를 이용한 전지구 풍력자원의 장기간 통계분석", 풍력에너지저널, 9(3), pp.19~24 (2018), 한국풍력에너지학회[DOI]
- 권일한, "MERRA 재해석자료를 이용한 국내 해상풍력단지 유망 후보지 선정에 관한 연구", 석사, 융합시스템공학과, pp.2014
- "Digital Map" (2018)[URL]
- "Land Cover Map" (2007)[URL]
- A Feasibility Study for Mid-sized Offshore Wind Power Plant in Korea, Project Final Report, "Korea Electric Power Research Institute", ~ (2011)