A computationally-efficient layout optimization method for real wind farms considering altitude variations
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DOI: 10.1016/j.energy.2017.05.076
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Cited by:
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- Wang, Longyan & Cholette, Michael E. & Zhou, Yunkai & Yuan, Jianping & Tan, Andy C.C. & Gu, Yuantong, 2018. "Effectiveness of optimized control strategy and different hub height turbines on a real wind farm optimization," Renewable Energy, Elsevier, vol. 126(C), pages 819-829.
- 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.
- Navarro Diaz, Gonzalo P. & Saulo, A. Celeste & Otero, Alejandro D., 2021. "Full wind rose wind farm simulation including wake and terrain effects for energy yield assessment," Energy, Elsevier, vol. 237(C).
- Kyoungboo Yang & Kyungho Cho, 2019. "Simulated Annealing Algorithm for Wind Farm Layout Optimization: A Benchmark Study," Energies, MDPI, vol. 12(23), pages 1-15, November.
- 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).
- Froese, Gabrielle & Ku, Shan Yu & Kheirabadi, Ali C. & Nagamune, Ryozo, 2022. "Optimal layout design of floating offshore wind farms," Renewable Energy, Elsevier, vol. 190(C), pages 94-102.
- Masoudi, Seiied Mohsen & Baneshi, Mehdi, 2022. "Layout optimization of a wind farm considering grids of various resolutions, wake effect, and realistic wind speed and wind direction data: A techno-economic assessment," Energy, Elsevier, vol. 244(PB).
- Rae-Jin Park & Jeong-Hwan Kim & Byungchan Yoo & Minhan Yoon & Seungmin Jung, 2022. "Verification of Prediction Method Based on Machine Learning under Wake Effect Using Real-Time Digital Simulator," Energies, MDPI, vol. 15(24), pages 1-15, December.
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Keywords
Wind farm; Layout optimization; Irregular boundary shape; Non-flat terrain;All these keywords.
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