메뉴 건너뛰기




Volumn 45, Issue , 2014, Pages 188-197

Wind energy forecast in complex sites with a hybrid neural network and CFD based method

Author keywords

Neural networks; Power forecast; SCADA; Wind energy

Indexed keywords


EID: 84893663314     PISSN: 18766102     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1016/j.egypro.2014.01.021     Document Type: Conference Paper
Times cited : (35)

References (24)
  • 2
    • 79961126223 scopus 로고    scopus 로고
    • Current methods and advances in forecasting of wind power generation
    • Aoife MF, Paul GL, Antonino M, Eamon J. Current methods and advances in forecasting of wind power generation. Renewable Energy Volume 37, Issue 1, 2012; p. 1-8
    • (2012) Renewable Energy , vol.37 , Issue.1 , pp. 1-8
    • Aoife, M.F.1    Paul, G.L.2    Antonino, M.3    Eamon, J.4
  • 7
    • 34648852323 scopus 로고    scopus 로고
    • Locally recurrent neural networks for wind speed prediction using spatial correlation
    • Barbounis TG, Theocharis JB Locally recurrent neural networks for wind speed prediction using spatial correlation. Information Sciences 2007; 177(24):5775-97.
    • (2007) Information Sciences , vol.177 , Issue.24 , pp. 5775-5797
    • Barbounis, T.G.1    Theocharis, J.B.2
  • 11
    • 84869380569 scopus 로고    scopus 로고
    • Wind turbine condition monitoring based on SCADA data using normal behavior models. Part 1: System description
    • January DOI: 10.1016/j.asoc.2012.08.033
    • Schlechtingen M, Ferreira Santos I, Achiche S. Wind turbine condition monitoring based on SCADA data using normal behavior models. Part 1: System description; Applied Soft Computing, January 2013, Volume 13, Issue 1, pp. 259-270, DOI: 10.1016/j.asoc.2012.08.033
    • (2013) Applied Soft Computing , vol.13 , Issue.1 , pp. 259-270
    • Schlechtingen, M.1    Ferreira Santos, I.2    Achiche, S.3
  • 12
    • 79751491467 scopus 로고    scopus 로고
    • The prediction and diagnosis of wind turbine faults
    • DOI: 10.1016/j.renene.2010.05.014
    • Kusiak A, Li W. The prediction and diagnosis of wind turbine faults; Renewable Energy, 2011, 36, pp. 16-23, DOI: 10.1016/j.renene.2010.05.014,
    • (2011) Renewable Energy , Issue.36 , pp. 16-23
    • Kusiak, A.1    Li, W.2
  • 13
    • 84871851194 scopus 로고    scopus 로고
    • Monitoring wind farms with performance curves
    • January DOI: 10.1109/TSTE.2012.2212470
    • Kusiak A, Verna A. Monitoring wind farms with performance curves; IEEE Transactions On Sustainable Energy, January 2012, Volume 4, Issue 1, pp. 192-199, DOI: 10.1109/TSTE.2012.2212470
    • (2012) IEEE Transactions on Sustainable Energy , vol.4 , Issue.1 , pp. 192-199
    • Kusiak, A.1    Verna, A.2
  • 14
    • 84872032989 scopus 로고    scopus 로고
    • Wind turbine condition monitoring by the approach of SCADA data analysis
    • May DOI:10.1016/j.renene.2012.11.030
    • Yang W, Court R, Jiang J. Wind turbine condition monitoring by the approach of SCADA data analysis; Renewable Energy, May 2013, Volume 53, pp. 365-376, DOI:10.1016/j.renene.2012.11.030
    • (2013) Renewable Energy , vol.53 , pp. 365-376
    • Yang, W.1    Court, R.2    Jiang, J.3
  • 16
    • 84877918603 scopus 로고    scopus 로고
    • Developing a model for hardness prediction in water-quenched and tempered AISI 1045 steel through an artificial neural network
    • Taghizadeh S, et al, Developing a model for hardness prediction in water-quenched and tempered AISI 1045 steel through an artificial neural network. Materials & Design, 2013. 51(0): p. 530-535.
    • (2013) Materials & Design , vol.51 , pp. 530-535
    • Taghizadeh, S.1
  • 17
    • 34250762015 scopus 로고    scopus 로고
    • Application of artificial neural networks for the wind speed prediction of target station using reference stations data
    • Bilgili M, Sahin B, Yasar A. Application of artificial neural networks for the wind speed prediction of target station using reference stations data. Renewable Energy, 2007. 32(14): p. 2350-2360.
    • (2007) Renewable Energy , vol.32 , Issue.14 , pp. 2350-2360
    • Bilgili, M.1    Sahin, B.2    Yasar, A.3
  • 19
    • 79952453503 scopus 로고    scopus 로고
    • Energy Research Center of the Netherlands (ECN), ECN-E-09-016, Petten, The Netherlands, Tech. Rep
    • Sanderse B. "Aerodynamics of wind turbine wakes." Energy Research Center of the Netherlands (ECN), ECN-E-09-016, Petten, The Netherlands, Tech. Rep(2009).
    • (2009) Aerodynamics of Wind Turbine Wakes
    • Sanderse, B.1
  • 23
    • 84869870630 scopus 로고    scopus 로고
    • An application of the actuator disc model for wind turbine wakes calculations
    • Castellani F, Vignaroli A. "An application of the actuator disc model for wind turbine wakes calculations." Applied Energy (2012).
    • (2012) Applied Energy
    • Castellani, F.1    Vignaroli, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.