EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 336 (2022) E3S Web Conf., 336 (2022) 00013 References
Open Access
Issue
E3S Web Conf.
Volume 336, 2022
The International Conference on Energy and Green Computing (ICEGC’2021)
Article Number 00013
Number of page(s) 7
DOI https://doi.org/10.1051/e3sconf/202233600013
Published online 17 January 2022
  1. Global Wind Report. [Online]. Available: http://www.gwec.net/. [Google Scholar]
  2. Veeramachaneni, Markus Wagner, Una-May O’Reilly, Frank Neumann, “Optimizing Energy Output and Layout Costs for Large Wind Farms using Particle Swarm Optimization,” Evolutionary Computation (CEC), 2012 IEEE Congress, pp. 1-7, Jun. (2012). [Google Scholar]
  3. Zhao, M., Chen, Z., Blaabjerg, F.,”Optimization of electrical system for offshore wind farm via genetic algorithm,” Renewable Power Generation, IET, vol. 3, pp. 205-216. [Google Scholar]
  4. Bahirat Nandigam, M. Dhali S.K., “Optimal design of an offshore wind farm layout,” Power Electronics, Electrical Drives, Automation and Motion, 2008, SPEEDAM 2008 International Symposium, pp. 1470-1474, Jun. (2008). [Google Scholar]
  5. Youjie Ma, Haishan Yang, Xuesong Zhou and Li Ji, “The dynamic modeling of wind farms considering wake effects and its optimal distribution,” World Non-Grid-Connected Wind Power and Energy Conference, 2009. WNWEC 2009, pp. 1-4, Nanjing, Sep. (2009). [Google Scholar]
  6. Tahavorgar, A., Quaicoe, J.E., “Estimation of wake effect in wind farms using design of experiment methodology,” Energy Conversion Congress and Exposition (ECCE), 2013 IEEE, pp. 3317-3324, Sep. (2013). [Google Scholar]
  7. Hou, P., Zhu, J., Ma, K., Yang, G., Hu, W., & Chen, Z. A review of offshore wind farm layout optimization and electrical system design methods. In Journal of Modern Power Systems and Clean Energy (Vol. 7, Issue 5, pp. 975–986). Springer Heidelberg. (2019). [CrossRef] [Google Scholar]
  8. G.C. Larsen, J. Højstrup and H.A. Madsen, “Wind Fields in Wakes,” EUWEC ‘96, Gothenburg, (1996). [Google Scholar]
  9. Sten Frandsen, Rebecca Barthelmie, Sara Pryor, Ole Rathmann, Søren Larsen, Jørgen Højstrup and Morten Thøgersen, “Analytical Modelling of Wind Speed Deficit in Large Offshore Wind Farms,” Wind Energ. 2006, pp. 39-53, Jan. (2006). [CrossRef] [Google Scholar]
  10. Frandsen, S., Barthelmie, R.J., Pryor, S.C., Rathmann, O., Larsen, S.E., Højstrup, J., Nielsen, P. and Thøgersen, M.L., “The necessary distance between large wind farms offshore – study,” Risø-R-1518(EN) (2005). [Google Scholar]
  11. Wu Yuan-Kang, Lee Ching-Yin, Chen Chao-Rong, Hsu Kun-Wei, Tseng Huang-Tien, “Optimization of the wind turbine layout and transmission system planning for a large-scale offshore wind farm by AI technology,” Industry Applications Society Annual Meeting (IAS), 2012 IEEE, pp. 1-9, 7-11 Oct. (2012). [Google Scholar]
  12. A. Kusiak, H. Zheng, “Optimization of wind turbine energy and power factor with an evolutionary computation algorithm,” Renewable Energy, Vol. 35, pp. 685–694, Mar. (2010). [CrossRef] [Google Scholar]
  13. Yunus Eroğlu, Serap Ulusam Seçkiner, “Design of wind farm layout using ant colony algorithm,” Renewable Energy, Vol. 44, pp. 53-62, Aug. (2012). [CrossRef] [Google Scholar]
  14. Beatriz Pérez, Roberto Mínguez, Raúl Guanche, “Offshore wind farm layout optimization using mathematical programming techniques,” Renewable Energy, Vol. 53, pp. 389-399, May (2013). [CrossRef] [Google Scholar]
  15. Sittichoke Pookpunt, Weerakorn Ongsakul, “Optimal placement of wind turbines within wind farm using binary particle swarm optimization with time-varying acceleration coefficients,” Renewable Energy, Vol. 55, pp. 266-276, Jul. (2013). [CrossRef] [Google Scholar]
  16. Gao, X.; Yang, H.; Lu, L.; Koo, P. Wind turbine layout optimization using multi-population genetic algorithm and a case study in Hong Kong offshore. J. Wind Eng. Ind. Aerodyn. (2015). [Google Scholar]
  17. Wu, X.; Hu, W.; Huang, Q.; Chen, C.; Chen, Z.; Blaabjerg, F. optimized placement of onshoreWind Farms Considering Topography. Energies (2019). [Google Scholar]
  18. N.A. Andersen, S.J. Sørensen, J.N. Shen, Analysis of turbulent wake behind a wind turbine, Lyngby, 2013. [Google Scholar]
  19. R. Shakoor, M.Y. Hassan, A. Raheem, Y.K. Wu, Wake effect modeling: A review of wind farm layout optimization using Jensen’s model, Renewable and Sustainable Energy Reviews, 58, 1048–1059, (2016). [CrossRef] [Google Scholar]
  20. L. Wang, A.C.C. Tan, M. Cholette, Y. Gu, “Comparison of the effectiveness of analytical wake models for wind farm with constant and variable hub heights,” Energy Conversion and Management, 124, 189–202, (2016). [CrossRef] [Google Scholar]
  21. H. Sun, X. Gao, H. Yang, A review of full-scale wind-field measurements of the wind-turbine wake effect and a measurement of the wake-interaction effect, Renewable and Sustainable Energy Reviews, 132, 110042, (2020). [CrossRef] [Google Scholar]
  22. P. S. Valverde, A. J. N. A. Sarmento, and M. Alves, “Offshore wind farm layout optimization -State of the art,” Proc. Int. Offshore Polar Eng. Conf., vol. 1, no. 1, pp. 157–163, (2013). [Google Scholar]
  23. C. Carrillo, A.F. Obando Montaño, J. Cidrás, E. Díaz-Dorado, Review of power curve modelling for wind turbines, Renewable and Sustainable Energy Reviews, 21, 572–581, (2013). [Google Scholar]
  24. J. Feng, W.Z. Shen, “Wind farm layout optimization in complex terrain: A preliminary study on a Gaussian hill,” in Journal of Physics: Conference Series, Institute of Physics Publishing, (2014). [Google Scholar]
  25. T. Göçmen, P. Van Der Laan, P.E. Réthoré, A.P. Diaz, G.C. Larsen, S. Ott, Wind turbine wake models developed at the technical university of Denmark: A review, Renewable and Sustainable Energy Reviews, 60, 752–769, (2016). [Google Scholar]
  26. Hou P, Hu W, Chen Z. Optimisation for offshore wind farm cable connection layout using adaptive particle swarm optimisation minimum spanning tree method. IET Renew Power Gener (2016). [Google Scholar]
  27. Li DD, He C, Fu Y. Optimization of internal electric connection system of large offshore wind farm with hybrid genetic and immune algorithm. In: 2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies; (2008). [Google Scholar]
  28. El Mokhi, C.; Addaim, A. Optimal Substation Location of a Wind Farm Using Different Metaheuristic Algorithms. In Proceedings of the 6th IEEE International Conference on Optimization and Applications (ICOA2020), Beni Mellal, Morocco, 20–21 April (2020). [Google Scholar]
  29. Lerch, M., De-Prada-Gil, M., & Molins, C. A metaheuristic optimization model for the inter-array layout planning of floating offshore wind farms. International Journal of Electrical Power and Energy Systems, 131. (2021). [Google Scholar]
  30. Banzo, M., & Ramos, A. Stochastic optimization model for electric power system planning of offshore wind farms. IEEE Transactions on Power Systems, 26(3), 1338–1348. (2011). [CrossRef] [Google Scholar]
  31. Mokhi, C. el, & Addaim, A. Optimization of wind turbine interconnections in an offshore wind farm using metaheuristic algorithms. Sustainability (Switzerland), 12(14), 1–24. (2020). [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.