G.N. Sideratos∗ and N.D. Hatziargyriou∗


  1. [1] IEA Wind Energy Annual Report 2003.
  2. [2] N. Hatziargyriou & A. Zervos, Wind power development inEurope, Proceedings of the IEEE, 89 (12), 2001, 1765–1782.
  3. [3] Wind Energy: The Facts, An Analysis of Wind Energy in theEU-25, EWEA, 2004.
  4. [4] Wind Power Outlook 2004,
  5. [5] J. Stefanakis, CRETE: An ideal case study for increased windpower penetration in medium sized autonomous power systems,IEEE Winter Meeting, 1999.
  6. [6] N. Hatziargyriou, A. Tsikalakis, A. Dimeas, D. Georgiadis, A.Gigantidou, J. Stefanakis, & E. Thalassinakis, Security andeconomic impacts of high wind power penetration in islandsystems, 2004 Cigre Session, Paris, August 2004.
  7. [7] L.H. Nielsen, P.E. Morthorst, K. Skytte, P.H. Jensen, P.B.Eriksen, A.G. Sorensen, F. Nissen, B. Godske, H. Ravn, K.Staerkind, & J. Havsager, Wind power and a liberalised NorthEuropean electricity exchange, Proc. EWEC’99, Nice, France,1–5 March 1999.
  8. [8] B. Sorensen & P. Meibom, Can wind power be sold in aderegulated electricity market? Proc. EWEC’99, Nice, France,1–5 March 1999.
  9. [9] G. Bathurst & G. Strbac, The value of intermittent renewablesources in the first week of NETA, Tyndall Briefing, Note No.2, 3 April 2001.
  10. [10] P. Pinson, T. Rancin, & G. Karniotakis, Short-term windpower prediction for offshore wind farms – Evaluation on fuzzy-neural network based model, Proc. 2004 Global Wind PowerConference, Chicago, 28–31 March 2004.
  11. [11] P. Pinson & G. Karniotakis, On-line assessment of predictionrisk for wind power production forecasts, Proc. EWEC’03,Madrid, Spain, 16–19 July 2003.
  12. [12] T.S. Nielsen & H. Madsen, Statistical methods for predictingwind power, Proc. EWEC’97, Dublin, Ireland, October 1997.
  13. [13] T.S. Nielsen, H. Madsen, & J. Tofting, Experiences withstatistical methods for wind power prediction, Proc. GlobalWindpower Conference and Exhibition, Paris, France, 2–5April 2002.
  14. [14] G. Giebel, L. Landberg, T.S. Nielsen, & H. Madsen, TheZephyr Project – the next generation prediction system, Proc.Global Windpower Conference and Exhibition, Paris, France,2–5 April 2002.
  15. [15] G. Karniotakis, G.S. Stavrakakis, & E.F. Nogaret, Windpower forecasting using advanced neural network models, IEEETransactions on Energy Conversion, 11 (4), 1996, 762–767.
  16. [16] B. Ernst, K. Rohrig, H. Regber, & P. Schorn, Managing 3000MW wind power in a transmission system operation center,Proc. EWEC01, Copenhagen, Denmark, 2–6 June 2001.
  17. [17] B. Bailey, M.C. Brower, & J. Zack, Short-term wind forecasting,Proc. EWEC’99, Nice, France, 1–5 March 1999.
  18. [18] I. Sanchez, J. Usaola, O. Ravelo, C. Velasco, J. Dominguez,M.G. Lobo, G. Gonzalez, & F. Soto, SIPREOLICO – Awind power prediction system based on flexible combinationof dynamic models. Application to the Spanish power system,World Wind Energy Conference, Berlin, Germany, June 2002.
  19. [19] G. Giebel, R. Brownsword, & G. Kariniotakis, The stateof the art in short-term prediction of wind power: A lit-erature overview, Deliverable D1.1 of ANEMOS project,
  20. [20] G. Giebel, L. Landberg, G. Kariniotakis, & R. Brownsword,State-of-the-art on methods and software tools for short-termprediction of wind energy production, Proc. EWEC, 2003,Madrid, Spain.
  21. [21] G. Kariniotakis & Anemos partners, What performance canbe expected by short-term wind power prediction modelsdepending on site characteristics, Proc. EWEC04, London,UK, 22–25 November 2004.287

Important Links:

Go Back