Renew. Energy Environ. Sustain.
Volume 6, 2021
Achieving Zero Carbon Emission by 2030
Article Number 40
Number of page(s) 11
Published online 29 October 2021
  1. A.S. Darwish, R. Al-Dabbagh, Wind energy state of the art: present and future technology advancements, Renew. Energy Environ. Sustain. 5, 7 (2020) [Google Scholar]
  2. J.Y. Jin, R. Ghani, M.S. Virk, Wind turbine wake effects on wind resource assessments − a case study, E3S Web Conf. 186, 03003 (2020) [CrossRef] [EDP Sciences] [Google Scholar]
  3. Y. Wang, Q. Hu, L. Li, A.M. Foley, D. Srinivasan, Approaches to wind power curve modeling: a review and discussion, Renew. Sustain. Energy Rev. 116 (2019) [Google Scholar]
  4. M.J. Churchfield, A review of wind turbine wake models and future directions, in Proceedings of 2013 North American Wind Energy Academy (NAWEA) Symposium (2013) p. 1–20 [Google Scholar]
  5. N.P. Dufresne, M. Wosnik, Velocity deficit and swirl in the turbulent wake of a wind turbine, Mar. Technol. Soc. J. 47, 4 (2013) [Google Scholar]
  6. A. Rasheed, K. Sørli, R. Holdahl, T. Kvamsdal, A multiscale approach to micrositing of wind turbines, Energy Proc. 14 (2012) [Google Scholar]
  7. J.K. Kaldellis, M. Kapsali, E. Kaldelli, E. Katsanou, Comparing recent views of public attitude on wind energy, photovoltaic and small hydro applications, Renew. Energy 52 (2013) [Google Scholar]
  8. L. Tian, W. Zhu, W. Shen, Y. Song, N. Zhao, Prediction of multi-wake problems using an improved Jensen wake model, Renew. Energy 102B (2017) [Google Scholar]
  9. G.C. Larsen, H.A. Madsen, F. Bingöl, J. Mann, S. Ott, J.N. Sørensen, V. Okulov, N. Troldborg, M. Nielsen, K. Thomsen, T.J. Larsen, R. Mikkelsen, Dynamic wake meandering modeling, Risø National Laboratory, Denmark 1607 (2007) [Google Scholar]
  10. A.A. Veisi, M.H.S. Mayam, Large Eddy Simulation of flow around a single and two in-line horizontal-axis wind turbines, Energy 121 (2017) [Google Scholar]
  11. H. Hu, Z. Yang, P. Sarkar, Dynamic wind loads and wake characteristics of a wind turbine model in an atmospheric boundary layer wind, Exp. Fluids 52, 5 (2012) [Google Scholar]
  12. J.K. Kaldellis, D. Zafirakis, The influence of technical availability on the energy performance of wind farms: overview of critical factors and development of a proxy prediction model, J. Wind Eng. Ind. Aerodyn. 115 (2013) [Google Scholar]
  13. X. Gao, H. Yang, L. Lin, Optimization of wind turbine layout position in a wind farm using a newly-developed two-dimensional wake model, Appl. Energy 174 (2016) [Google Scholar]
  14. E. Barlas, W.J. Zhu, W.Z. Shen, M. Kelly, S. Andersen, Effects of wind turbine wake on atmospheric sound propagation, Appl. Acoust. 122 (2017) [Google Scholar]
  15. A. Laratro, M. Arjomandi, R. Kelso, B. Cazzolato, A discussion of wind turbine interaction and stall contributions to wind farm noise, J. Wind Eng. Ind. Aerodyn. 127 (2014) [Google Scholar]
  16. D. Heimann, Y. Käsler, G. Gross, The wake of a wind turbine and its influence on sound propagation, Meteorolog. Zeitsch. 20 (2011) [Google Scholar]
  17. I.F.S.A. Kabir, E.Y.K. Ng, Effect of different atmospheric boundary layers on the wake characteristics of NREL phase VI wind turbine, Renew. Energy 130 (2019) [Google Scholar]
  18. S. Rockel, J. Peinke, M. Hölling, R.B. Cal, Dynamic wake development of a floating wind turbine in free pitch motion subjected to turbulent inflow generated with an active grid, Renew. Energy 112, 2 (2017) [CrossRef] [Google Scholar]
  19. D.A. Katsaprakakis, D.G. Christakis, Wind parks design, including representative case studies, in Comprehensive Renewable Energy, edited by A. Sayigh, J.K. Kaldellis (Oxford, Elsevier, 2012) [Google Scholar]
  20. M. Kapsali, J.K. Kaldellis, Offshore wind power basics, in Comprehensive Renewable Energy, edited by A. Sayigh, J.K. Kaldellis (Oxford, Elsevier, 2012) [Google Scholar]
  21. F. Porté-Agel, M. Bastankhah, S. Shamsoddin, Wind-turbine and wind-farm flows: a review, Boundary-Layer Meteorol. 174 (2019) [Google Scholar]
  22. B. Sanderse, Aerodynamics of wind turbine wakes − Literature review (Energy Research Centre of the Netherlands, 2009) [Google Scholar]
  23. F. Zahle, N.N. Sørensen, On the influence of far-wake resolution on wind turbine flow simulations, J. Phys.: Conf. Ser. 75, 1 (2007) [Google Scholar]
  24. J.K. Kaldellis, P. Triantafyllou, P. Stinis, Critical evaluation of Wind Turbines' analytical wake models, Renew. Sustain. Energy Rev. 144C, 110991 (2021) [CrossRef] [Google Scholar]
  25. L. Tian, W. Zhu, W. Shen, N. Zhao, Z. Shen, Development and validation of a new two-dimensional wake model for wind turbine wakes, J. Wind Eng. Ind. Aerodyn. 137 (2015) [Google Scholar]
  26. M. Talavera, F. Shu, Experimental study of turbulence intensity influence on wind turbine performance and wake recovery in a low-speed wind tunnel, Renew. Energy 107 (2017) [Google Scholar]
  27. M.S. Adaramola, P.Å. Krogstad, Experimental investigation of wake effects on wind turbine performance, Renew. Energy 36, 8 (2011) [Google Scholar]
  28. R.J. Barthelmie, S.C. Pryor, S.T. Frandsen, K.S. Hansen, J.G. Schepers, K. Rados, W. Schlez, A. Neubert, L.E. Jensen, S. Neckelmann, Quantifying the impact of wind turbine wakes on power output at offshore wind farms, J. Atmos. Ocean. Technol. 27, 8 (2010) [Google Scholar]
  29. J.F. Ainslie, Calculating the flowfield in the wake of wind turbines, J. Wind Eng. Ind. Aerodyn. 27, 1–3 (1988) [Google Scholar]
  30. D. Gallacher, G. More, Lidar measurements and visualisation of turbulence and wake decay length, in Proceedings of Europe's Premier Wind Energy Event (EWEA), 10-13 March 2014, p. 1–10 [Google Scholar]
  31. T. Ishihara, G.W. Qian, A new Gaussian-based analytical wake model for wind turbines considering ambient turbulence intensities and thrust coefficient effects, J. Wind Eng. Ind. Aerodyn. 177 (2018) [Google Scholar]
  32. H.S. Dhiman, D. Deb, A.M. Foley, Bilateral Gaussian wake model formulation for wind farms: a forecasting based approach, Renew. Sustain. Energy Rev. 127 (2020) [Google Scholar]
  33. H. Sun, H. Yang, Numerical investigation of the average wind speed of a single wind turbine and development of a novel three-dimensional multiple wind turbine wake model, Renew. Energy 147, 1 (2020) [CrossRef] [Google Scholar]
  34. L. Parada, C. Herrera, P. Flores, V. Parada, Wind farm layout optimization using a Gaussian-based wake model, Renew. Energy 107 (2017) [Google Scholar]
  35. R. Shakoor, M.Y. Hassa, A. Raheem, Y.K. Wu, Wake effect modeling: a review of wind farm layout optimization using Jensen's model, Renew. Sustain. Energy Rev. 58 (2016) [Google Scholar]
  36. 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, Renew. Sustain. Energy Rev. 132, 110042 (2020) [CrossRef] [Google Scholar]
  37. E. Machefaux, G.C. Larsen, J.P. Murcia Leon, Engineering models for merging wakes in wind farm optimization applications, J. Phys: Conf. Ser. 625 (2015) [Google Scholar]
  38. M. Gaumond, P.E. Réthoré, A. Bechmann, S. Ott, G.C. Larsen, A. Peňa, K.S. Hansen, Benchmarking of Wind Turbine Wake Models in Large Offshore Wind Farms (DTU Wind Energy, 2012) [Google Scholar]
  39. S. Jeon, B. Kim, J. Huh, Comparison and verification of wake models in an onshore wind farm considering single wake condition of the 2 MW wind turbine, Energy 93, 2 (2015) [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.