Multi-Criteria Optimization of Wind Turbines in an Offshore Wind Farm with Monopile Foundation Considering Structural Integrity and Energy Generation

被引：0
作者：
Ali, Sajid [1 ]
Park, Hongbae [2 ]
Lee, Daeyong [2 ]
机构：
[1] Kunsan Natl Univ, Energy Innovat Res Ctr Wind Turbine Support Struct, 558 Daehak Ro, Gunsan 54150, Jeonrabug Do, South Korea
[2] Kunsan Natl Univ, Grad Sch, Dept Wind Energy, 558 Daehak Ro, Gunsan Si 54150, Jeollabuk Do, South Korea
来源：
JOURNAL OF MARINE SCIENCE AND ENGINEERING | 2024年 / 12卷 / 12期
基金：
新加坡国家研究基金会;
关键词：
extreme analysis; wind; hydro; optimization; offshore design; applied load; GENETIC ALGORITHM; LAYOUT; PLACEMENT; MODELS; WAKE;
D O I：
10.3390/jmse12122313
中图分类号：
U6 [水路运输]; P75 [海洋工程];
学科分类号：
0814 ; 081505 ; 0824 ; 082401 ;
摘要：
Offshore wind energy plays a crucial role in achieving renewable energy targets, with OWFs facing unique environmental challenges that impact turbine performance and structural demands. This study develops an advanced optimization methodology to identify the most effective layout configurations for offshore wind farms (OWFs) with monopile foundations, focusing on enhancing structural integrity and energy generation efficiency. Using a multi-criteria optimization approach, the effects of wind turbine spacing, angular orientation, and height on energy yield and monopile loading were evaluated. Based on a seven-year dataset from the Ouido site in South Korea, where the mean wind speed is 6.95 m/s at a 150 m hub height, optimized configurations were determined. For average wind conditions, a turbine spacing of 250 m, a hub height of 148 m, and an orientation angle of 36.87 degrees minimized wake losses and distributed structural loads effectively. Under rated wind speeds of 10.59 m/s, a spacing of 282 m, a hub height of 155 m, and an orientation angle of 45 degrees further enhanced performance. These designs reduced wake interference by 25%, decreased monopile fatigue loads by 18%, and lowered the levelized cost of electricity (LCOE) by up to 15%. This study's findings provide a robust framework for optimizing OWFs to increase energy yield, improve operational efficiency, and ensure economic viability.
引用
收藏
页数：25
相关论文
共 68 条
  • [21] Hardy S., Ergun H., Van Hertem D., A greedy algorithm for optimizing offshore wind transmission topologies, IEEE Trans. Power Syst, 37, pp. 2113-2121, (2022)
  • [22] Eroglu Y., Seckiner S.U., Design of wind farm layout using ant colony algorithm, Renew. Energy, 44, pp. 53-62, (2012)
  • [23] Kunakote T., Sabangban N., Kumar S., Tejani G.G., Panagant N., Pholdee N., Comparative performance of twelve metaheuristics for wind farm layout optimisation, Arch. Comput. Methods Eng, 29, pp. 717-730, (2022)
  • [24] Celik I., Yildiz C., Sekkeli M., Implementation of realistic wind farm layout optimization using artificial bee colony algorithm, Energy Sources Part A Recovery Util. Environ. Eff, 44, pp. 7253-7268, (2022)
  • [25] Herbert-Acero J.-F., Franco-Acevedo J.-R., Valenzuela-Rendon M., Probst-Oleszewski O., Linear wind farm layout optimization through computational intelligence, MICAI 2009: Advances in Artificial Intelligence, pp. 692-703, (2009)
  • [26] Bilbao M., Alba E., Simulated annealing for optimization of wind farm annual profit, Proceedings of the 2009 2nd International Symposium on Logistics and Industrial Informatics, pp. 1-5
  • [27] Mosetti G., Poloni C., Diviacco B., Optimization of wind turbine positioning in large wind farms by means of a genetic algorithm, J. Wind Eng. Ind. Aerodyn, 51, pp. 105-116, (1994)
  • [28] Huang H.S., Distributed genetic algorithm for optimization of wind farm annual profits, Proceedings of the 2007 International Conference on Intelligent Systems Applications to Power Systems
  • [29] Mohandes M., Khan S.A., Rehman S., Al-Shaikhi A., Liu B., Iqbal K., GARM: A Stochastic Evolution based Genetic Algorithm with Rewarding Mechanism for Wind Farm Layout Optimization, FME Trans, 51, pp. 575-584, (2023)
  • [30] Gao X., Yang H., Lin L., Koo P., Wind turbine layout optimization using multipopulation genetic algorithm and a case study in Hong Kong offshore, J. Wind Eng. Ind. Aerodyn, 139, pp. 89-99, (2015)
1234567