IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v151y2015icp320-334.html
   My bibliography  Save this item

Layout optimization for maximizing wind farm power production using sequential convex programming

Citations

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


Cited by:

  1. Veisi, Amin Allah & Shafiei Mayam, Mohammad Hossein, 2017. "Effects of blade rotation direction in the wake region of two in-line turbines using Large Eddy Simulation," Applied Energy, Elsevier, vol. 197(C), pages 375-392.
  2. Cao, Lichao & Ge, Mingwei & Gao, Xiaoxia & Du, Bowen & Li, Baoliang & Huang, Zhi & Liu, Yongqian, 2022. "Wind farm layout optimization to minimize the wake induced turbulence effect on wind turbines," Applied Energy, Elsevier, vol. 323(C).
  3. Hou, Peng & Hu, Weihao & Chen, Cong & Soltani, Mohsen & Chen, Zhe, 2016. "Optimization of offshore wind farm layout in restricted zones," Energy, Elsevier, vol. 113(C), pages 487-496.
  4. Petković, Dalibor & Shamshirband, Shahaboddin & Kamsin, Amirrudin & Lee, Malrey & Anicic, Obrad & Nikolić, Vlastimir, 2016. "Survey of the most influential parameters on the wind farm net present value (NPV) by adaptive neuro-fuzzy approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1270-1278.
  5. 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.
  6. 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.
  7. Moreno, Sinvaldo Rodrigues & Pierezan, Juliano & Coelho, Leandro dos Santos & Mariani, Viviana Cocco, 2021. "Multi-objective lightning search algorithm applied to wind farm layout optimization," Energy, Elsevier, vol. 216(C).
  8. Guirguis, David & Romero, David A. & Amon, Cristina H., 2016. "Toward efficient optimization of wind farm layouts: Utilizing exact gradient information," Applied Energy, Elsevier, vol. 179(C), pages 110-123.
  9. Li, Qing'an & Cai, Chang & Kamada, Yasunari & Maeda, Takao & Hiromori, Yuto & Zhou, Shuni & Xu, Jianzhong, 2021. "Prediction of power generation of two 30 kW Horizontal Axis Wind Turbines with Gaussian model," Energy, Elsevier, vol. 231(C).
  10. Chen, Kaixuan & Lin, Jin & Qiu, Yiwei & Liu, Feng & Song, Yonghua, 2022. "Joint optimization of wind farm layout considering optimal control," Renewable Energy, Elsevier, vol. 182(C), pages 787-796.
  11. Amin Allah, Veisi & Shafiei Mayam, Mohammad Hossein, 2017. "Large Eddy Simulation of flow around a single and two in-line horizontal-axis wind turbines," Energy, Elsevier, vol. 121(C), pages 533-544.
  12. Chen, K. & Song, M.X. & Zhang, X. & Wang, S.F., 2016. "Wind turbine layout optimization with multiple hub height wind turbines using greedy algorithm," Renewable Energy, Elsevier, vol. 96(PA), pages 676-686.
  13. Lo Brutto, Ottavio A. & Thiébot, Jérôme & Guillou, Sylvain S. & Gualous, Hamid, 2016. "A semi-analytic method to optimize tidal farm layouts – Application to the Alderney Race (Raz Blanchard), France," Applied Energy, Elsevier, vol. 183(C), pages 1168-1180.
  14. Vasel-Be-Hagh, Ahmadreza & Archer, Cristina L., 2017. "Wind farm hub height optimization," Applied Energy, Elsevier, vol. 195(C), pages 905-921.
  15. Serrano González, Javier & Burgos Payán, Manuel & Riquelme Santos, Jesús Manuel, 2018. "Optimal design of neighbouring offshore wind farms: A co-evolutionary approach," Applied Energy, Elsevier, vol. 209(C), pages 140-152.
  16. Yang, Xiaolei & Pakula, Maggie & Sotiropoulos, Fotis, 2018. "Large-eddy simulation of a utility-scale wind farm in complex terrain," Applied Energy, Elsevier, vol. 229(C), pages 767-777.
  17. Yang, An-Shik & Su, Ying-Ming & Wen, Chih-Yung & Juan, Yu-Hsuan & Wang, Wei-Siang & Cheng, Chiang-Ho, 2016. "Estimation of wind power generation in dense urban area," Applied Energy, Elsevier, vol. 171(C), pages 213-230.
  18. 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.
  19. Li, Qing'an & Wang, Ye & Kamada, Yasunari & Maeda, Takao & Xu, Jianzhong & Zhou, Shuni & Zhang, Fanghong & Cai, Chang, 2022. "Diagonal inflow effect on the wake characteristics of a horizontal axis wind turbine with Gaussian model and field measurements," Energy, Elsevier, vol. 238(PB).
  20. Rafael V. Rodrigues & Corinne Lengsfeld, 2019. "Development of a Computational System to Improve Wind Farm Layout, Part I: Model Validation and Near Wake Analysis," Energies, MDPI, vol. 12(5), pages 1-24, March.
  21. Parada, Leandro & Herrera, Carlos & Flores, Paulo & Parada, Victor, 2018. "Assessing the energy benefit of using a wind turbine micro-siting model," Renewable Energy, Elsevier, vol. 118(C), pages 591-601.
  22. Schönleber, Kevin & Collados, Carlos & Pinto, Rodrigo Teixeira & Ratés-Palau, Sergi & Gomis-Bellmunt, Oriol, 2017. "Optimization-based reactive power control in HVDC-connected wind power plants," Renewable Energy, Elsevier, vol. 109(C), pages 500-509.
  23. 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.
  24. Feng, Ju & Shen, Wen Zhong, 2017. "Design optimization of offshore wind farms with multiple types of wind turbines," Applied Energy, Elsevier, vol. 205(C), pages 1283-1297.
  25. Liu, Weiqi & Shi, Jian & Chen, Hailong & Liu, Hengxu & Lin, Zi & Wang, Lingling, 2021. "Lagrangian actuator model for wind turbine wake aerodynamics," Energy, Elsevier, vol. 232(C).
  26. Dhiman, Harsh S. & Deb, Dipankar & Foley, Aoife M., 2020. "Lidar assisted wake redirection in wind farms: A data driven approach," Renewable Energy, Elsevier, vol. 152(C), pages 484-493.
  27. Cao, Yankai & Zavala, Victor M. & D’Amato, Fernando, 2018. "Using stochastic programming and statistical extrapolation to mitigate long-term extreme loads in wind turbines," Applied Energy, Elsevier, vol. 230(C), pages 1230-1241.
  28. Wędzik, Andrzej & Siewierski, Tomasz & Szypowski, Michał, 2016. "A new method for simultaneous optimizing of wind farm’s network layout and cable cross-sections by MILP optimization," Applied Energy, Elsevier, vol. 182(C), pages 525-538.
  29. Kyoungboo Yang, 2020. "Determining an Appropriate Parameter of Analytical Wake Models for Energy Capture and Layout Optimization on Wind Farms," Energies, MDPI, vol. 13(3), pages 1-17, February.
  30. Gionfra, Nicolò & Sandou, Guillaume & Siguerdidjane, Houria & Faille, Damien & Loevenbruck, Philippe, 2019. "Wind farm distributed PSO-based control for constrained power generation maximization," Renewable Energy, Elsevier, vol. 133(C), pages 103-117.
  31. Zhang, Baoshou & Song, Baowei & Mao, Zhaoyong & Tian, Wenlong, 2017. "A novel wake energy reuse method to optimize the layout for Savonius-type vertical axis wind turbines," Energy, Elsevier, vol. 121(C), pages 341-355.
  32. 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).
  33. 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.
  34. Dhoot, Aditya & Antonini, Enrico G.A. & Romero, David A. & Amon, Cristina H., 2021. "Optimizing wind farms layouts for maximum energy production using probabilistic inference: Benchmarking reveals superior computational efficiency and scalability," Energy, Elsevier, vol. 223(C).
  35. Kaldellis, John K. & Triantafyllou, Panagiotis & Stinis, Panagiotis, 2021. "Critical evaluation of Wind Turbines’ analytical wake models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
  36. Dhunny, A.Z. & Lollchund, M.R. & Rughooputh, S.D.D.V., 2017. "Wind energy evaluation for a highly complex terrain using Computational Fluid Dynamics (CFD)," Renewable Energy, Elsevier, vol. 101(C), pages 1-9.
  37. Liu, Weiqi & Liu, Weixing & Zhang, Liang & Sheng, Qihu & Zhou, Binzhen, 2018. "A numerical model for wind turbine wakes based on the vortex filament method," Energy, Elsevier, vol. 157(C), pages 561-570.
  38. Liu, Heng-xu & Tian, Yi-nong & Liu, Wei-qi & Jin, Ye-qing & Kong, Fan-kai & Chen, Hai-long & Zhong, Yu-guang, 2023. "Aerodynamic interference characteristics of multiple unit wind turbine based on vortex filament wake model," Energy, Elsevier, vol. 268(C).
  39. Garcia Marrero, Luis Enrique & Arzola Ruíz, José, 2021. "Web-based tool for the decision making in photovoltaic/wind farms planning with multiple objectives," Renewable Energy, Elsevier, vol. 179(C), pages 2224-2234.
  40. Kuo, Jim Y.J. & Romero, David A. & Beck, J. Christopher & Amon, Cristina H., 2016. "Wind farm layout optimization on complex terrains – Integrating a CFD wake model with mixed-integer programming," Applied Energy, Elsevier, vol. 178(C), pages 404-414.
  41. Annas Fauzy & Cheng-Dar Yue & Chien-Cheng Tu & Ta-Hui Lin, 2021. "Understanding the Potential of Wind Farm Exploitation in Tropical Island Countries: A Case for Indonesia," Energies, MDPI, vol. 14(9), pages 1-26, May.
  42. Siniscalchi-Minna, Sara & Bianchi, Fernando D. & De-Prada-Gil, Mikel & Ocampo-Martinez, Carlos, 2019. "A wind farm control strategy for power reserve maximization," Renewable Energy, Elsevier, vol. 131(C), pages 37-44.
  43. 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).
  44. Hou, Peng & Hu, Weihao & Soltani, Mohsen & Chen, Cong & Chen, Zhe, 2017. "Combined optimization for offshore wind turbine micro siting," Applied Energy, Elsevier, vol. 189(C), pages 271-282.
  45. Cheng-Dar Yue & Yi-Shegn Chiu & Chien-Cheng Tu & Ta-Hui Lin, 2020. "Evaluation of an Offshore Wind Farm by Using Data from the Weather Station, Floating LiDAR, Mast, and MERRA," Energies, MDPI, vol. 13(1), pages 1-20, January.
  46. Parada, Leandro & Herrera, Carlos & Flores, Paulo & Parada, Victor, 2017. "Wind farm layout optimization using a Gaussian-based wake model," Renewable Energy, Elsevier, vol. 107(C), pages 531-541.
  47. Park, Junyoung & Park, Jinkyoo, 2019. "Physics-induced graph neural network: An application to wind-farm power estimation," Energy, Elsevier, vol. 187(C).
  48. 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).
  49. Guirguis, David & Romero, David A. & Amon, Cristina H., 2017. "Gradient-based multidisciplinary design of wind farms with continuous-variable formulations," Applied Energy, Elsevier, vol. 197(C), pages 279-291.
  50. Nagpal, Shriya V. & Liu, M. Vivienne & Anderson, C. Lindsay, 2021. "A comparison of deterministic refinement techniques for wind farm layout optimization," Renewable Energy, Elsevier, vol. 168(C), pages 581-592.
  51. Gao, Xiaoxia & Yang, Hongxing & Lu, Lin, 2016. "Optimization of wind turbine layout position in a wind farm using a newly-developed two-dimensional wake model," Applied Energy, Elsevier, vol. 174(C), pages 192-200.
  52. Mamdouh Abdulrahman & David Wood, 2019. "Wind Farm Layout Upgrade Optimization," Energies, MDPI, vol. 12(13), pages 1-25, June.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.