IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v205y2017icp1283-1297.html
   My bibliography  Save this item

Design optimization of offshore wind farms with multiple types of wind turbines

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Mahdi Abkar, 2018. "Theoretical Modeling of Vertical-Axis Wind Turbine Wakes," Energies, MDPI, vol. 12(1), pages 1-10, December.
  2. Hayat, Imran & Chatterjee, Tanmoy & Liu, Huiwen & Peet, Yulia T. & Chamorro, Leonardo P., 2019. "Exploring wind farms with alternating two- and three-bladed wind turbines," Renewable Energy, Elsevier, vol. 138(C), pages 764-774.
  3. Win Naung, Shine & Nakhchi, Mahdi Erfanian & Rahmati, Mohammad, 2021. "High-fidelity CFD simulations of two wind turbines in arrays using nonlinear frequency domain solution method," Renewable Energy, Elsevier, vol. 174(C), pages 984-1005.
  4. Wang, Xuefei & Zeng, Xiangwu & Yang, Xu & Li, Jiale, 2019. "Seismic response of offshore wind turbine with hybrid monopile foundation based on centrifuge modelling," Applied Energy, Elsevier, vol. 235(C), pages 1335-1350.
  5. Taufal Hidayat & Makbul A. M. Ramli & Mohammed M. Alqahtani, 2024. "Optimization of Non-Uniform Onshore Wind Farm Layout Using Modified Electric Charged Particles Optimization Algorithm Considering Different Terrain Characteristics," Sustainability, MDPI, vol. 16(7), pages 1-28, March.
  6. Li, Jiale & Wang, Xuefei & Yu, Xiong (Bill), 2018. "Use of spatio-temporal calibrated wind shear model to improve accuracy of wind resource assessment," Applied Energy, Elsevier, vol. 213(C), pages 469-485.
  7. Song, Mengxuan & Chen, Kai & Wang, Jun, 2020. "A two-level approach for three-dimensional micro-siting optimization of large-scale wind farms," Energy, Elsevier, vol. 190(C).
  8. Sun, Haiying & Yang, Hongxing, 2018. "Study on an innovative three-dimensional wind turbine wake model," Applied Energy, Elsevier, vol. 226(C), pages 483-493.
  9. Sun, Jian & Liu, Gang & Sun, Boyang & Xiao, Gang, 2021. "Light-stacking strengthened fusion based building energy consumption prediction framework via variable weight feature selection," Applied Energy, Elsevier, vol. 303(C).
  10. Sun, Haiying & Yang, Hongxing & Gao, Xiaoxia, 2019. "Investigation into spacing restriction and layout optimization of wind farm with multiple types of wind turbines," Energy, Elsevier, vol. 168(C), pages 637-650.
  11. Krzysztof Wrobel & Krzysztof Tomczewski & Artur Sliwinski & Andrzej Tomczewski, 2021. "Optimization of a Small Wind Power Plant for Annual Wind Speed Distribution," Energies, MDPI, vol. 14(6), pages 1-18, March.
  12. Yang, Kyoungboo & Kwak, Gyeongil & Cho, Kyungho & Huh, Jongchul, 2019. "Wind farm layout optimization for wake effect uniformity," Energy, Elsevier, vol. 183(C), pages 983-995.
  13. Ju, Xinglong & Liu, Feng, 2019. "Wind farm layout optimization using self-informed genetic algorithm with information guided exploitation," Applied Energy, Elsevier, vol. 248(C), pages 429-445.
  14. Artigao, Estefania & Martín-Martínez, Sergio & Honrubia-Escribano, Andrés & Gómez-Lázaro, Emilio, 2018. "Wind turbine reliability: A comprehensive review towards effective condition monitoring development," Applied Energy, Elsevier, vol. 228(C), pages 1569-1583.
  15. Martinez, A. & Iglesias, G., 2022. "Mapping of the levelised cost of energy for floating offshore wind in the European Atlantic," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
  16. Pollini, Nicolò, 2022. "Topology optimization of wind farm layouts," Renewable Energy, Elsevier, vol. 195(C), pages 1015-1027.
  17. Yi Zhang & Dapeng Zhang & Haoyu Jiang, 2023. "A Review of Offshore Wind and Wave Installations in Some Areas with an Eye towards Generating Economic Benefits and Offering Commercial Inspiration," Sustainability, MDPI, vol. 15(10), pages 1-32, May.
  18. Guo, Zijian & Liu, Tanghong & Xu, Kai & Wang, Junyan & Li, Wenhui & Chen, Zhengwei, 2020. "Parametric analysis and optimization of a simple wind turbine in high speed railway tunnels," Renewable Energy, Elsevier, vol. 161(C), pages 825-835.
  19. Díaz, Guzmán & Coto, José & Gómez-Aleixandre, Javier, 2019. "Levelized income loss as a metric of the adaptation of wind and energy storage to variable prices," Applied Energy, Elsevier, vol. 238(C), pages 1179-1191.
  20. Kirchner-Bossi, Nicolas & Porté-Agel, Fernando, 2024. "Wind farm power density optimization according to the area size using a novel self-adaptive genetic algorithm," Renewable Energy, Elsevier, vol. 220(C).
  21. Lin, Zi & Cevasco, Debora & Collu, Maurizio, 2020. "A methodology to develop reduced-order models to support the operation and maintenance of offshore wind turbines," Applied Energy, Elsevier, vol. 259(C).
  22. Valsaraj, P. & Thumba, Drisya Alex & Asokan, K. & Kumar, K. Satheesh, 2020. "Symbolic regression-based improved method for wind speed extrapolation from lower to higher altitudes for wind energy applications," Applied Energy, Elsevier, vol. 260(C).
  23. Barbarelli, S. & Florio, G. & Amelio, M. & Scornaienchi, N.M., 2018. "Preliminary performance assessment of a novel on-shore system recovering energy from tidal currents," Applied Energy, Elsevier, vol. 224(C), pages 717-730.
  24. Ge, Mingwei & Wu, Ying & Liu, Yongqian & Li, Qi, 2019. "A two-dimensional model based on the expansion of physical wake boundary for wind-turbine wakes," Applied Energy, Elsevier, vol. 233, pages 975-984.
  25. Chen, Jincheng & Wang, Feng & Stelson, Kim A., 2018. "A mathematical approach to minimizing the cost of energy for large utility wind turbines," Applied Energy, Elsevier, vol. 228(C), pages 1413-1422.
  26. Brogna, Roberto & Feng, Ju & Sørensen, Jens Nørkær & Shen, Wen Zhong & Porté-Agel, Fernando, 2020. "A new wake model and comparison of eight algorithms for layout optimization of wind farms in complex terrain," Applied Energy, Elsevier, vol. 259(C).
  27. Ling, Ziyan & Zhao, Zhenzhou & Liu, Yige & Liu, Huiwen & Ali, Kashif & Liu, Yan & Wen, Yifan & Wang, Dingding & Li, Shijun & Su, Chunhao, 2024. "Multi-objective layout optimization for wind farms based on non-uniformly distributed turbulence and a new three-dimensional multiple wake model," Renewable Energy, Elsevier, vol. 227(C).
  28. Zhang, Ziyu & Huang, Peng, 2023. "Prediction of multiple-wake velocity and wind power using a cosine-shaped wake model," Renewable Energy, Elsevier, vol. 219(P1).
  29. Yuanhang Qi & Peng Hou & Guisong Liu & Rongsen Jin & Zhile Yang & Guangya Yang & Zhaoyang Dong, 2021. "Cable Connection Optimization for Heterogeneous Offshore Wind Farms via a Voronoi Diagram Based Adaptive Particle Swarm Optimization with Local Search," Energies, MDPI, vol. 14(3), pages 1-21, January.
  30. Mas-Soler, Jordi & Uzunoglu, Emre & Bulian, Gabriele & Guedes Soares, C. & Souto-Iglesias, Antonio, 2021. "An experimental study on transporting a free-float capable tension leg platform for a 10 MW wind turbine in waves," Renewable Energy, Elsevier, vol. 179(C), pages 2158-2173.
  31. Azlan, F. & Kurnia, J.C. & Tan, B.T. & Ismadi, M.-Z., 2021. "Review on optimisation methods of wind farm array under three classical wind condition problems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
  32. Shen, Wen Zhong & Lin, Jian Wei & Jiang, Yu Hang & Feng, Ju & Cheng, Li & Zhu, Wei Jun, 2023. "A novel yaw wake model for wind farm control applications," Renewable Energy, Elsevier, vol. 218(C).
  33. Cheng, Yu & Zhang, Mingming & Zhang, Ziliang & Xu, Jianzhong, 2019. "A new analytical model for wind turbine wakes based on Monin-Obukhov similarity theory," Applied Energy, Elsevier, vol. 239(C), pages 96-106.
  34. Siyu Tao & Andrés Feijóo & Jiemin Zhou & Gang Zheng, 2020. "Topology Design of an Offshore Wind Farm with Multiple Types of Wind Turbines in a Circular Layout," Energies, MDPI, vol. 13(3), pages 1-16, January.
  35. Sergen Tumse & Mehmet Bilgili & Alper Yildirim & Besir Sahin, 2024. "Comparative Analysis of Global Onshore and Offshore Wind Energy Characteristics and Potentials," Sustainability, MDPI, vol. 16(15), pages 1-28, August.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.