메뉴 건너뛰기




Volumn 31, Issue , 2014, Pages 762-777

Current status and future advances for wind speed and power forecasting

Author keywords

Offshore forecasting; Probabilistic forecasting; Regional forecasting; Spatial correlation forecasting; Wind power; Wind speed

Indexed keywords

SPEED; WIND EFFECTS; WIND POWER;

EID: 84892960976     PISSN: 13640321     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rser.2013.12.054     Document Type: Review
Times cited : (619)

References (149)
  • 1
    • 84893019151 scopus 로고    scopus 로고
    • United States Department of Energy. 20% Wind energy by 2030; 2008
    • United States Department of Energy. 20% Wind energy by 2030; 2008
  • 3
    • 79961126223 scopus 로고    scopus 로고
    • Current methods and advances in forecasting of wind power generation
    • A.M. Foley, P.G. Leahy, A. Marvuglia, and E.J. McKeogh Current methods and advances in forecasting of wind power generation Renew Energy 37 2012 1 8
    • (2012) Renew Energy , vol.37 , pp. 1-8
    • Foley, A.M.1    Leahy, P.G.2    Marvuglia, A.3    McKeogh, E.J.4
  • 12
    • 84860890595 scopus 로고    scopus 로고
    • Data mining and wind power prediction: A literature review
    • I. Colak, S. Sagiroglu, and M. Yesilbudak Data mining and wind power prediction: a literature review Renew Energy 46 2012 241 247
    • (2012) Renew Energy , vol.46 , pp. 241-247
    • Colak, I.1    Sagiroglu, S.2    Yesilbudak, M.3
  • 14
    • 79952073578 scopus 로고    scopus 로고
    • Impact of wind power forecasting error bias on the economic operation of autonomous power systems
    • A.G. Tsikalakis, N.D. Hatziargyriou, Y.A. Katsigiannis, and P.S. Georgilakis Impact of wind power forecasting error bias on the economic operation of autonomous power systems Wind Energy 12 2009 315 331
    • (2009) Wind Energy , vol.12 , pp. 315-331
    • Tsikalakis, A.G.1    Hatziargyriou, N.D.2    Katsigiannis, Y.A.3    Georgilakis, P.S.4
  • 15
    • 34548657445 scopus 로고    scopus 로고
    • Distributed generation as a balancing resource for wind generation
    • DOI 10.1049/iet-rpg:20070017
    • J. Kennedy, B. Fox, and D.J. Morrow Distributed generation as a balancing resource for wind generation Renew Power Gener, IET 1 2007 167 174 (Pubitemid 47403810)
    • (2007) IET Renewable Power Generation , vol.1 , Issue.3 , pp. 167-174
    • Kennedy, J.1    Fox, B.2    Morrow, D.J.3
  • 18
    • 84883254341 scopus 로고    scopus 로고
    • Impact of wind forecast error statistics upon unit commitment
    • C. Lowery, and M. O'Malley Impact of wind forecast error statistics upon unit commitment IEEE Trans Sustain Energy 3 2012 760 768
    • (2012) IEEE Trans Sustain Energy , vol.3 , pp. 760-768
    • Lowery, C.1    O'Malley, M.2
  • 20
    • 2942575891 scopus 로고    scopus 로고
    • Benefits for wind energy in electricity markets from using short term wind power prediction tools; A simulation study
    • J. Usaola, O. Ravelo, G. González, F. Soto, M.C. Dávila, and B. Díaz-Guerra Benefits for wind energy in electricity markets from using short term wind power prediction tools; a simulation study Wind Eng. 28 2004 119 127
    • (2004) Wind Eng. , vol.28 , pp. 119-127
    • Usaola, J.1    Ravelo, O.2    González, G.3    Soto, F.4    Dávila, M.C.5    Díaz-Guerra, B.6
  • 22
    • 77951497638 scopus 로고    scopus 로고
    • Wind power forecasting in U.S.Electricity markets
    • A. Botterud, J. Wang, V. Miranda, and R.J. Bessa Wind power forecasting in U.S. electricity markets Electr J 23 2010 71 82
    • (2010) Electr J , vol.23 , pp. 71-82
    • Botterud, A.1    Wang, J.2    Miranda, V.3    Bessa, R.J.4
  • 23
    • 33751372426 scopus 로고    scopus 로고
    • The role of wind forecasting in grid operations & reliability
    • DOI 10.1109/TDC.2005.1547203, 1547203, Proceedings - 2005 IEEE/PES Transmission and DistributionConference and Exhibition - Asia and Pacific
    • Smith JC, Ahlstrom ML, Zavadil RM, Sadjadpour A, Philbrick CR. The role of wind forecasting in utility system operation. In: Proceedings of the 2009 IEEE power and energy society general meeting; 2009. p. 1-5. (Pubitemid 44131214)
    • (2005) Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference , vol.2005 , pp. 1-5
    • Ahlstrom, M.L.1    Zavadil, R.M.2
  • 28
    • 33645659220 scopus 로고    scopus 로고
    • The future of wind forecasting and utility operations
    • Jones L Ahlstrom, R. Zavadil, and W. Grant The future of wind forecasting and utility operations Power Energy Mag, IEEE 3 2005 57 64
    • (2005) Power Energy Mag, IEEE , vol.3 , pp. 57-64
    • Ahlstrom, J.L.1    Zavadil, R.2    Grant, W.3
  • 29
    • 33751372426 scopus 로고    scopus 로고
    • The role of wind forecasting in grid operations & reliability
    • DOI 10.1109/TDC.2005.1547203, 1547203, Proceedings - 2005 IEEE/PES Transmission and DistributionConference and Exhibition - Asia and Pacific
    • Ahlstrom ML, Zavadil RM. The role of wind forecasting in grid operations & reliability. In: Proceedings of the 2005 IEEE/PES transmission and distribution conference and exhibition: Asia and Pacific; 2005. p. 1-5. (Pubitemid 44131214)
    • (2005) Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference , vol.2005 , pp. 1-5
    • Ahlstrom, M.L.1    Zavadil, R.M.2
  • 33
    • 0035280497 scopus 로고    scopus 로고
    • Short-term prediction of local wind conditions
    • DOI 10.1016/S0167-6105(00)00079-9, PII S0167610500000799
    • L. Landberg Short-term prediction of local wind conditions J Wind Eng Ind Aerodyn 89 2001 235 245 (Pubitemid 32235784)
    • (2001) Journal of Wind Engineering and Industrial Aerodynamics , vol.89 , Issue.3-4 , pp. 235-245
    • Landberg, L.1
  • 34
    • 0033086885 scopus 로고    scopus 로고
    • Short-term prediction of the power production from wind farms
    • DOI 10.1016/S0167-6105(98)00192-5, PII S0167610598001925
    • L. Landberg Short-term prediction of the power production from wind farms J Wind Eng Ind Aerodyn 80 1999 207 220 (Pubitemid 30024264)
    • (1999) Journal of Wind Engineering and Industrial Aerodynamics , vol.80 , Issue.1-2 , pp. 207-220
    • Landberg, L.1
  • 35
    • 0005581003 scopus 로고    scopus 로고
    • A mathematical look at a physical power prediction model
    • L. Landberg A mathematical look at a physical power prediction model Wind Energy 1 1998 23 28
    • (1998) Wind Energy , vol.1 , pp. 23-28
    • Landberg, L.1
  • 41
    • 77949570119 scopus 로고    scopus 로고
    • A hybrid statistical method to predict wind speed and wind power
    • H. Liu, H.-Q. Tian, C. Chen, and Y.-f. Li A hybrid statistical method to predict wind speed and wind power Renew Energy 35 2010 1857 1861
    • (2010) Renew Energy , vol.35 , pp. 1857-1861
    • Liu, H.1    Tian, H.-Q.2    Chen, C.3    Li, Y.-F.4
  • 45
    • 78650562310 scopus 로고    scopus 로고
    • ARMA based approaches for forecasting the tuple of wind speed and direction
    • E. Erdem, and J. Shi ARMA based approaches for forecasting the tuple of wind speed and direction Appl Energy 88 2011 1405 1414
    • (2011) Appl Energy , vol.88 , pp. 1405-1414
    • Erdem, E.1    Shi, J.2
  • 48
    • 34548079535 scopus 로고    scopus 로고
    • Variable selection for wind power prediction using particle swarm optimization
    • DOI 10.1145/1276958.1277361, Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference
    • Jursa R. Variable selection for wind power prediction using particle swarm optimization. In: Proceedings of the 9th annual conference on genetic and evolutionary computation; 2007. p. 2059-65. (Pubitemid 47291845)
    • (2007) Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference , pp. 2059-2065
    • Jursa, R.1
  • 49
    • 79959557168 scopus 로고    scopus 로고
    • Wind power prediction by a new forecast engine composed of modified hybrid neural network and enhanced particle swarm optimization
    • N. Amjady, F. Keynia, and H. Zareipour Wind power prediction by a new forecast engine composed of modified hybrid neural network and enhanced particle swarm optimization IEEE Trans Sustain Energy 2 2011 265 276
    • (2011) IEEE Trans Sustain Energy , vol.2 , pp. 265-276
    • Amjady, N.1    Keynia, F.2    Zareipour, H.3
  • 50
    • 80052530027 scopus 로고    scopus 로고
    • Short-term wind power forecasting using ridgelet neural network
    • N. Amjady, F. Keynia, and H. Zareipour Short-term wind power forecasting using ridgelet neural network Electr Power Syst Res 81 2011 2099 2107
    • (2011) Electr Power Syst Res , vol.81 , pp. 2099-2107
    • Amjady, N.1    Keynia, F.2    Zareipour, H.3
  • 51
    • 77953137822 scopus 로고    scopus 로고
    • On comparing three artificial neural networks for wind speed forecasting
    • G. Li, and J. Shi On comparing three artificial neural networks for wind speed forecasting Appl Energy 87 2010 2313 2320
    • (2010) Appl Energy , vol.87 , pp. 2313-2320
    • Li, G.1    Shi, J.2
  • 52
    • 78649276197 scopus 로고    scopus 로고
    • Output prediction of wind power generation system using complex-valued neural network
    • Kitajima T, Yasuno T. Output prediction of wind power generation system using complex-valued neural network. In: Proceedings of the 2010 SICE annual conference; 2010. p. 3610-3.
    • (2010) Proceedings of the 2010 SICE Annual Conference , pp. 3610-3613
    • Kitajima, T.1    Yasuno, T.2
  • 53
    • 77958190421 scopus 로고    scopus 로고
    • Very short-term wind power forecasting with neural networks and adaptive Bayesian learning
    • R. Blonbou Very short-term wind power forecasting with neural networks and adaptive Bayesian learning Renew Energy 36 2011 1118 1124
    • (2011) Renew Energy , vol.36 , pp. 1118-1124
    • Blonbou, R.1
  • 54
    • 78649450621 scopus 로고    scopus 로고
    • Short-term wind power forecasting in Portugal by neural networks and wavelet transform
    • J.P.S. Catalão, H.M.I. Pousinho, and V.M.F. Mendes Short-term wind power forecasting in Portugal by neural networks and wavelet transform Renew Energy 36 2011 1245 1251
    • (2011) Renew Energy , vol.36 , pp. 1245-1251
    • Catalão, J.P.S.1    Pousinho, H.M.I.2    Mendes, V.M.F.3
  • 55
    • 84859036543 scopus 로고    scopus 로고
    • AWNN-assisted wind power forecasting using feed-forward neural network
    • K. Bhaskar, and S.N. Singh AWNN-assisted wind power forecasting using feed-forward neural network IEEE Trans Sustain Energy 3 2012 306 315
    • (2012) IEEE Trans Sustain Energy , vol.3 , pp. 306-315
    • Bhaskar, K.1    Singh, S.N.2
  • 56
    • 79961127156 scopus 로고    scopus 로고
    • Multi-step forecasting for wind speed using a modified EMD-based artificial neural network model
    • Z. Guo, W. Zhao, H. Lu, and J. Wang Multi-step forecasting for wind speed using a modified EMD-based artificial neural network model Renew Energy 37 2012 241 249
    • (2012) Renew Energy , vol.37 , pp. 241-249
    • Guo, Z.1    Zhao, W.2    Lu, H.3    Wang, J.4
  • 57
    • 84863508830 scopus 로고    scopus 로고
    • A hybrid model for wind speed prediction using empirical mode decomposition and artificial neural networks
    • H. Liu, C. Chen, H.-q. Tian, and Y.-f. Li A hybrid model for wind speed prediction using empirical mode decomposition and artificial neural networks Renew Energy 48 2012 545 556
    • (2012) Renew Energy , vol.48 , pp. 545-556
    • Liu, H.1    Chen, C.2    Tian, H.-Q.3    Li, Y.-F.4
  • 58
    • 84869882813 scopus 로고    scopus 로고
    • Generalized feed-forward based method for wind energy prediction
    • A.N. Celik, and M. Kolhe Generalized feed-forward based method for wind energy prediction Appl Energy 101 2013 582 588
    • (2013) Appl Energy , vol.101 , pp. 582-588
    • Celik, A.N.1    Kolhe, M.2
  • 59
    • 84856532432 scopus 로고    scopus 로고
    • Performance evaluation and accuracy enhancement of a day-ahead wind power forecasting system in China
    • P. Zhao, J. Wang, J. Xia, Y. Dai, Y. Sheng, and J. Yue Performance evaluation and accuracy enhancement of a day-ahead wind power forecasting system in China Renew Energy 43 2012 234 241
    • (2012) Renew Energy , vol.43 , pp. 234-241
    • Zhao, P.1    Wang, J.2    Xia, J.3    Dai, Y.4    Sheng, Y.5    Yue, J.6
  • 60
    • 84871712040 scopus 로고    scopus 로고
    • Kernel ridge regression with active learning for wind speed prediction
    • F. Douak, F. Melgani, and N. Benoudjit Kernel ridge regression with active learning for wind speed prediction Appl Energy 103 2013 328 340
    • (2013) Appl Energy , vol.103 , pp. 328-340
    • Douak, F.1    Melgani, F.2    Benoudjit, N.3
  • 61
    • 33947303690 scopus 로고    scopus 로고
    • An advanced statistical method for wind power forecasting
    • DOI 10.1109/TPWRS.2006.889078
    • G. Sideratos, and N.D. Hatziargyriou An advanced statistical method for wind power forecasting IEEE Trans Power Syst 22 2007 258 265 (Pubitemid 46437735)
    • (2007) IEEE Transactions on Power Systems , vol.22 , Issue.1 , pp. 258-265
    • Sideratos, G.1    Hatziargyriou, N.D.2
  • 62
    • 78650402541 scopus 로고    scopus 로고
    • Hybrid wavelet-PSO-ANFIS approach for short-term wind power forecasting in Portugal
    • J.P.S. Catala, H.M.I. Pousinho, and V.M.F. Mendes Hybrid wavelet-PSO-ANFIS approach for short-term wind power forecasting in Portugal IEEE Trans Sustain Energy 2 2011 50 59
    • (2011) IEEE Trans Sustain Energy , vol.2 , pp. 50-59
    • Catala, J.P.S.1    Pousinho, H.M.I.2    Mendes, V.M.F.3
  • 63
    • 77955279506 scopus 로고    scopus 로고
    • Hour-ahead wind power and speed forecasting using simultaneous perturbation stochastic approximation (SPSA) algorithm and neural network with fuzzy inputs
    • Y.-Y. Hong, H.-L. Chang, and C.-S. Chiu Hour-ahead wind power and speed forecasting using simultaneous perturbation stochastic approximation (SPSA) algorithm and neural network with fuzzy inputs Energy 35 2010 3870 3876
    • (2010) Energy , vol.35 , pp. 3870-3876
    • Hong, Y.-Y.1    Chang, H.-L.2    Chiu, C.-S.3
  • 66
    • 78649814612 scopus 로고    scopus 로고
    • Prediction of wind speed time series using modified Taylor Kriging method
    • H. Liu, J. Shi, and E. Erdem Prediction of wind speed time series using modified Taylor Kriging method Energy 35 2010 4870 4879
    • (2010) Energy , vol.35 , pp. 4870-4879
    • Liu, H.1    Shi, J.2    Erdem, E.3
  • 68
    • 67349211771 scopus 로고    scopus 로고
    • Forecasting the wind generation using a two-stage network based on meteorological information
    • F. Shu, J.R. Liao, R. Yokoyama, C. Luonan, and L. Wei-Jen Forecasting the wind generation using a two-stage network based on meteorological information IEEE Trans Energy Convers 24 2009 474 482
    • (2009) IEEE Trans Energy Convers , vol.24 , pp. 474-482
    • Shu, F.1    Liao, J.R.2    Yokoyama, R.3    Luonan, C.4    Wei-Jen, L.5
  • 69
    • 78751705514 scopus 로고    scopus 로고
    • Quaternion-valued short-term joint forecasting of three-dimensional wind and atmospheric parameters
    • C.C. Took, G. Strbac, K. Aihara, and D.P. Mandic Quaternion-valued short-term joint forecasting of three-dimensional wind and atmospheric parameters Renew Energy 36 2011 1754 1760
    • (2011) Renew Energy , vol.36 , pp. 1754-1760
    • Took, C.C.1    Strbac, G.2    Aihara, K.3    Mandic, D.P.4
  • 70
    • 74449091026 scopus 로고    scopus 로고
    • Application of Bayesian model averaging in modeling long-term wind speed distributions
    • G. Li, and J. Shi Application of Bayesian model averaging in modeling long-term wind speed distributions Renew Energy 35 2010 1192 1202
    • (2010) Renew Energy , vol.35 , pp. 1192-1202
    • Li, G.1    Shi, J.2
  • 71
    • 84865557377 scopus 로고    scopus 로고
    • Very short-term wind speed forecasting with Bayesian structural break model
    • Y. Jiang, Z. Song, and A. Kusiak Very short-term wind speed forecasting with Bayesian structural break model Renew Energy 50 2013 637 647
    • (2013) Renew Energy , vol.50 , pp. 637-647
    • Jiang, Y.1    Song, Z.2    Kusiak, A.3
  • 72
    • 84864797603 scopus 로고    scopus 로고
    • Performance analysis of four modified approaches for wind speed forecasting
    • W. Zhang, J. Wu, J. Wang, W. Zhao, and L. Shen Performance analysis of four modified approaches for wind speed forecasting Appl Energy 99 2012 324 333
    • (2012) Appl Energy , vol.99 , pp. 324-333
    • Zhang, W.1    Wu, J.2    Wang, J.3    Zhao, W.4    Shen, L.5
  • 73
    • 61649090211 scopus 로고    scopus 로고
    • Short-term prediction of wind farm power: A data mining approach
    • A. Kusiak, Z. Haiyang, and S. Zhe Short-term prediction of wind farm power: a data mining approach IEEE Trans Energy Convers 24 2009 125 136
    • (2009) IEEE Trans Energy Convers , vol.24 , pp. 125-136
    • Kusiak, A.1    Haiyang, Z.2    Zhe, S.3
  • 74
    • 77955202511 scopus 로고    scopus 로고
    • Prediction of wind farm power ramp rates: A data-mining approach
    • H. Zheng, and A. Kusiak Prediction of wind farm power ramp rates: a data-mining approach J Sol Energy Eng 131 2009 031011 031018
    • (2009) J Sol Energy Eng , vol.131 , pp. 031011-031018
    • Zheng, H.1    Kusiak, A.2
  • 75
    • 65249086722 scopus 로고    scopus 로고
    • Wind farm power prediction: A data-mining approach
    • A. Kusiak, H. Zheng, and Z. Song Wind farm power prediction: a data-mining approach Wind Energy 12 2009 275 293
    • (2009) Wind Energy , vol.12 , pp. 275-293
    • Kusiak, A.1    Zheng, H.2    Song, Z.3
  • 76
    • 84871722288 scopus 로고    scopus 로고
    • A frequency domain approach to characterize and analyze wind speed patterns
    • J. Jung, and K.-S. Tam A frequency domain approach to characterize and analyze wind speed patterns Appl Energy 103 2013 435 443
    • (2013) Appl Energy , vol.103 , pp. 435-443
    • Jung, J.1    Tam, K.-S.2
  • 77
    • 11944258430 scopus 로고    scopus 로고
    • To combine or not to combine: Selecting among forecasts and their combinations
    • DOI 10.1016/j.ijforecast.2004.05.002, PII S0169207004000494
    • M. Hibon, and T. Evgeniou To combine or not to combine: selecting among forecasts and their combinations Int J Forecast. 21 2005 15 24 (Pubitemid 40101336)
    • (2005) International Journal of Forecasting , vol.21 , Issue.1 , pp. 15-24
    • Hibon, M.1    Evgeniou, T.2
  • 78
    • 31744451232 scopus 로고    scopus 로고
    • Short-term prediction of wind energy production
    • DOI 10.1016/j.ijforecast.2005.05.003, PII S0169207005000622
    • I. Sánchez Short-term prediction of wind energy production Int J Forecast 22 2006 43 56 (Pubitemid 43174790)
    • (2006) International Journal of Forecasting , vol.22 , Issue.1 , pp. 43-56
    • Sanchez, I.1
  • 80
    • 79952454042 scopus 로고    scopus 로고
    • Multiple architecture system for wind speed prediction
    • H. Bouzgou, and N. Benoudjit Multiple architecture system for wind speed prediction Appl Energy 88 2011 2463 2471
    • (2011) Appl Energy , vol.88 , pp. 2463-2471
    • Bouzgou, H.1    Benoudjit, N.2
  • 82
    • 80052205596 scopus 로고    scopus 로고
    • Online clustering for wind speed forecasting based on combination of RBF neural network and persistence method
    • Xiao Q, Cong J, Jun W. Online clustering for wind speed forecasting based on combination of RBF neural network and persistence method. In: Proceedings of the 2011 chinese control and decision conference (CCDC); 2011. p. 2798-802.
    • (2011) Proceedings of the 2011 Chinese Control and Decision Conference (CCDC) , pp. 2798-2802
    • Xiao, Q.1    Cong, J.2    Jun, W.3
  • 83
    • 84859416828 scopus 로고    scopus 로고
    • Evaluation of hybrid forecasting approaches for wind speed and power generation time series
    • J. Shi, J. Guo, and S. Zheng Evaluation of hybrid forecasting approaches for wind speed and power generation time series Renew Sustain Energy Rev 16 2012 3471 3480
    • (2012) Renew Sustain Energy Rev , vol.16 , pp. 3471-3480
    • Shi, J.1    Guo, J.2    Zheng, S.3
  • 84
    • 77954315872 scopus 로고    scopus 로고
    • Wind speed forecasting in three different regions of Mexico, using a hybrid ARIMA-ANN model
    • E. Cadenas, and W. Rivera Wind speed forecasting in three different regions of Mexico, using a hybrid ARIMA-ANN model Renew Energy 35 2010 2732 2738
    • (2010) Renew Energy , vol.35 , pp. 2732-2738
    • Cadenas, E.1    Rivera, W.2
  • 85
    • 84862213628 scopus 로고    scopus 로고
    • Comparison of two new ARIMA-ANN and ARIMA-Kalman hybrid methods for wind speed prediction
    • H. Liu, H.-q. Tian, and Y.-f. Li Comparison of two new ARIMA-ANN and ARIMA-Kalman hybrid methods for wind speed prediction Appl Energy 98 2012 415 424
    • (2012) Appl Energy , vol.98 , pp. 415-424
    • Liu, H.1    Tian, H.-Q.2    Li, Y.-F.3
  • 86
    • 79751505649 scopus 로고    scopus 로고
    • Bayesian adaptive combination of short-term wind speed forecasts from neural network models
    • G. Li, J. Shi, and J. Zhou Bayesian adaptive combination of short-term wind speed forecasts from neural network models Renew Energy 36 2011 352 359
    • (2011) Renew Energy , vol.36 , pp. 352-359
    • Li, G.1    Shi, J.2    Zhou, J.3
  • 88
    • 79952183962 scopus 로고    scopus 로고
    • A corrected hybrid approach for wind speed prediction in Hexi Corridor of China
    • Z. Guo, J. Zhao, W. Zhang, and J. Wang A corrected hybrid approach for wind speed prediction in Hexi Corridor of China Energy 36 2011 1668 1679
    • (2011) Energy , vol.36 , pp. 1668-1679
    • Guo, Z.1    Zhao, J.2    Zhang, W.3    Wang, J.4
  • 90
    • 71849115521 scopus 로고    scopus 로고
    • Uncertainty analysis of wind energy potential assessment
    • S.-D. Kwon Uncertainty analysis of wind energy potential assessment Appl Energy 87 2010 856 865
    • (2010) Appl Energy , vol.87 , pp. 856-865
    • Kwon, S.-D.1
  • 93
    • 1642310555 scopus 로고    scopus 로고
    • Correlation of wind speed between neighboring measuring stations
    • D.A. Bechrakis, and P.D. Sparis Correlation of wind speed between neighboring measuring stations IEEE Trans Energy Convers 19 2004 400 406
    • (2004) IEEE Trans Energy Convers , vol.19 , pp. 400-406
    • Bechrakis, D.A.1    Sparis, P.D.2
  • 94
    • 2942570109 scopus 로고    scopus 로고
    • A fuzzy model for wind speed prediction and power generation in wind parks using spatial correlation
    • I.G. Damousis, M.C. Alexiadis, J.B. Theocharis, and P.S. Dokopoulos A fuzzy model for wind speed prediction and power generation in wind parks using spatial correlation IEEE Trans Energy Convers 19 2004 352 361
    • (2004) IEEE Trans Energy Convers , vol.19 , pp. 352-361
    • Damousis, I.G.1    Alexiadis, M.C.2    Theocharis, J.B.3    Dokopoulos, P.S.4
  • 96
    • 78650968145 scopus 로고    scopus 로고
    • Influence of the input layer signals of ANNs on wind power estimation for a target site: A case study
    • S. Velázquez, J.A. Carta, and J.M. Matías Influence of the input layer signals of ANNs on wind power estimation for a target site: a case study Renew Sustain Energy Rev 15 2011 1556 1566
    • (2011) Renew Sustain Energy Rev , vol.15 , pp. 1556-1566
    • Velázquez, S.1    Carta, J.A.2    Matías, J.M.3
  • 104
    • 34548156412 scopus 로고    scopus 로고
    • Non-parametric probabilistic forecasts of wind power: Required properties and evaluation
    • DOI 10.1002/we.230
    • P. Pinson, H.A. Nielsen, J.K. Møller, H. Madsen, and G.N. Kariniotakis Non-parametric probabilistic forecasts of wind power: required properties and evaluation Wind Energy 10 2007 497 516 (Pubitemid 350273129)
    • (2007) Wind Energy , vol.10 , Issue.6 , pp. 497-516
    • Pinson, P.1    Nielsen, H.Aa.2    Moller, J.K.3    Madsen, H.4    Kariniotakis, G.N.5
  • 105
    • 80755122841 scopus 로고    scopus 로고
    • Time-adaptive quantile-copula for wind power probabilistic forecasting
    • R.J. Bessa, V. Miranda, A. Botterud, Z. Zhou, and J. Wang Time-adaptive quantile-copula for wind power probabilistic forecasting Renew Energy 40 2012 29 39
    • (2012) Renew Energy , vol.40 , pp. 29-39
    • Bessa, R.J.1    Miranda, V.2    Botterud, A.3    Zhou, Z.4    Wang, J.5
  • 106
    • 14344258897 scopus 로고    scopus 로고
    • On-line assessment of prediction risk for wind power production forecasts
    • DOI 10.1002/we.114
    • P. Pinson, and G. Kariniotakis On-line assessment of prediction risk for wind power production forecasts Wind Energy 7 2004 119 132 (Pubitemid 40290421)
    • (2004) Wind Energy , vol.7 , Issue.2 , pp. 119-132
    • Pinson, P.1    Kariniotakis, G.2
  • 107
    • 33244496469 scopus 로고    scopus 로고
    • Using quanti le regression to extend an existing wind power forecasting system With probabilistic forecasts
    • DOI 10.1002/we.180
    • H.A. Nielsen, H. Madsen, and T.S. Nielsen Using quantile regression to extend an existing wind power forecasting system with probabilistic forecasts Wind Energy 9 2006 95 108 (Pubitemid 43281988)
    • (2006) Wind Energy , vol.9 , Issue.1-2 , pp. 95-108
    • Nielsen, H.A.1    Madsen, H.2    Nielsen, T.S.3
  • 108
    • 14344255817 scopus 로고    scopus 로고
    • Probabilistic wind power forecasts using local quantile regression
    • DOI 10.1002/we.107
    • J.B. Bremnes Probabilistic wind power forecasts using local quantile regression Wind Energy 7 2004 47 54 (Pubitemid 40290428)
    • (2004) Wind Energy , vol.7 , Issue.1 , pp. 47-54
    • Bremnes, J.B.1
  • 110
    • 84867988966 scopus 로고    scopus 로고
    • Probabilistic wind power forecasting using radial basis function neural networks
    • G. Sideratos, and N.D. Hatziargyriou Probabilistic wind power forecasting using radial basis function neural networks IEEE Trans Power Syst 27 2012 1788 1796
    • (2012) IEEE Trans Power Syst , vol.27 , pp. 1788-1796
    • Sideratos, G.1    Hatziargyriou, N.D.2
  • 114
    • 61749097513 scopus 로고    scopus 로고
    • Skill forecasting from ensemble predictions of wind power
    • P. Pinson, H.A. Nielsen, H. Madsen, and G. Kariniotakis Skill forecasting from ensemble predictions of wind power Appl Energy 86 2009 1326 1334
    • (2009) Appl Energy , vol.86 , pp. 1326-1334
    • Pinson, P.1    Nielsen, H.A.2    Madsen, H.3    Kariniotakis, G.4
  • 115
    • 70049094192 scopus 로고    scopus 로고
    • Wind power density forecasting using ensemble predictions and time series models
    • J.W. Taylor, P.E. McSharry, and R. Buizza Wind power density forecasting using ensemble predictions and time series models IEEE Trans Energy Convers 24 2009 775 782
    • (2009) IEEE Trans Energy Convers , vol.24 , pp. 775-782
    • Taylor, J.W.1    McSharry, P.E.2    Buizza, R.3
  • 118
    • 78751515195 scopus 로고    scopus 로고
    • Spatio-temporal analysis and modeling of short-term wind power forecast errors
    • J. Tastu, P. Pinson, E. Kotwa, H. Madsen, and H.A. Nielsen Spatio-temporal analysis and modeling of short-term wind power forecast errors Wind Energy 14 2011 43 60
    • (2011) Wind Energy , vol.14 , pp. 43-60
    • Tastu, J.1    Pinson, P.2    Kotwa, E.3    Madsen, H.4    Nielsen, H.A.5
  • 120
    • 67650021306 scopus 로고    scopus 로고
    • Characterizing wind power forecast uncertainty with numerical weather prediction spatial fields
    • N. Cutler, J. Kepert, H. Outhred, and I. MacGill Characterizing wind power forecast uncertainty with numerical weather prediction spatial fields Wind Eng 32 2008 509 524
    • (2008) Wind Eng , vol.32 , pp. 509-524
    • Cutler, N.1    Kepert, J.2    Outhred, H.3    Macgill, I.4
  • 121
    • 78650561071 scopus 로고    scopus 로고
    • Error analysis of short term wind power prediction models
    • M.G. De Giorgi, A. Ficarella, and M. Tarantino Error analysis of short term wind power prediction models Appl Energy 88 2011 1298 1311
    • (2011) Appl Energy , vol.88 , pp. 1298-1311
    • De Giorgi, M.G.1    Ficarella, A.2    Tarantino, M.3
  • 124
    • 13244257007 scopus 로고    scopus 로고
    • Forecasting offshore wind speeds above the North Sea
    • DOI 10.1002/we.140
    • J. Tambke, M. Lange, U. Focken, J.-O. Wolff, and J.A.T. Bye Forecasting offshore wind speeds above the North Sea Wind Energy 8 2005 3 16 (Pubitemid 40183781)
    • (2005) Wind Energy , vol.8 , Issue.1 , pp. 3-16
    • Tambke, J.1    Lange, M.2    Focken, U.3    Wolff, J.-O.4    Bye, J.A.T.5
  • 126
    • 79959858370 scopus 로고    scopus 로고
    • Influence of local wind speed and direction on wind power dynamics - Application to offshore very short-term forecasting
    • C. Gallego, P. Pinson, H. Madsen, A. Costa, and A. Cuerva Influence of local wind speed and direction on wind power dynamics - application to offshore very short-term forecasting Appl Energy 88 2011 4087 4096
    • (2011) Appl Energy , vol.88 , pp. 4087-4096
    • Gallego, C.1    Pinson, P.2    Madsen, H.3    Costa, A.4    Cuerva, A.5
  • 129
    • 33645031359 scopus 로고    scopus 로고
    • Standardizing the performance evaluation of shortterm wind power prediction models
    • H. Madsen, P. Pinson, G. Kariniotakis, H.A. Nielsen, and T. Nielsen Standardizing the performance evaluation of shortterm wind power prediction models Wind Eng 29 2005 475 489
    • (2005) Wind Eng , vol.29 , pp. 475-489
    • Madsen, H.1    Pinson, P.2    Kariniotakis, G.3    Nielsen, H.A.4    Nielsen, T.5
  • 132
    • 84864827118 scopus 로고    scopus 로고
    • Wind speed and wind energy forecast through Kalman filtering of numerical weather prediction model output
    • F. Cassola, and M. Burlando Wind speed and wind energy forecast through Kalman filtering of numerical weather prediction model output Appl Energy 99 2012 154 166
    • (2012) Appl Energy , vol.99 , pp. 154-166
    • Cassola, F.1    Burlando, M.2
  • 136
    • 34548176991 scopus 로고    scopus 로고
    • Combination of deterministic and probabilistic meteorological models to enhance wind farm power forecasts
    • Lueder von B. Combination of deterministic and probabilistic meteorological models to enhance wind farm power forecasts. J Phys: Conf Ser. 2007;75:012050.
    • (2007) J Phys: Conf ser , vol.75 , pp. 012050
    • Von, L.B.1
  • 137
    • 78650937809 scopus 로고    scopus 로고
    • An adaptive framework based on multi-model data fusion for one-day-ahead wind power forecasting
    • A. Vaccaro, P. Mercogliano, P. Schiano, and D. Villacci An adaptive framework based on multi-model data fusion for one-day-ahead wind power forecasting Electr Power Syst Res 81 2011 775 782
    • (2011) Electr Power Syst Res , vol.81 , pp. 775-782
    • Vaccaro, A.1    Mercogliano, P.2    Schiano, P.3    Villacci, D.4
  • 138
    • 0036504289 scopus 로고    scopus 로고
    • Short-term prediction of the aggregated power output of wind farms - A statistical analysis of the reduction of the prediction error by spatial smoothing effects
    • DOI 10.1016/S0167-6105(01)00222-7, PII S0167610501002227
    • U. Focken, M. Lange, K. Mönnich, H.-P. Waldl, H.G. Beyer, and A. Luig Short-term prediction of the aggregated power output of wind farms - a statistical analysis of the reduction of the prediction error by spatial smoothing effects J Wind Eng Ind Aerodyn 90 2002 231 246 (Pubitemid 34315977)
    • (2002) Journal of Wind Engineering and Industrial Aerodynamics , vol.90 , Issue.3 , pp. 231-246
    • Focken, U.1    Lange, M.2    Monnich, K.3    Waldl, H.-P.4    Beyer, H.G.5    Luig, A.6
  • 139
    • 84892994468 scopus 로고    scopus 로고
    • A study of the reduction of the regional aggregated wind power forecast error by spatial smoothing effects in the Maritimes Canada
    • Yu H, Liuchen C. A study of the reduction of the regional aggregated wind power forecast error by spatial smoothing effects in the Maritimes Canada. In: Proceedings of the 2010 IEEE electric power and energy conference (EPEC); 2010. p. 1-6.
    • (2010) Proceedings of the 2010 IEEE Electric Power and Energy Conference (EPEC) , pp. 1-6
    • Yu, H.1    Liuchen, C.2
  • 143
    • 79961128617 scopus 로고    scopus 로고
    • Nested ensemble NWP approach for wind energy assessment
    • S. Al-Yahyai, Y. Charabi, A. Al-Badi, and A. Gastli Nested ensemble NWP approach for wind energy assessment Renew Energy 37 2012 150 160
    • (2012) Renew Energy , vol.37 , pp. 150-160
    • Al-Yahyai, S.1    Charabi, Y.2    Al-Badi, A.3    Gastli, A.4
  • 144
    • 75049083283 scopus 로고    scopus 로고
    • Wind forecasts for wind power generation using the Eta model
    • L. Lazić, G. Pejanović, and M. Živković Wind forecasts for wind power generation using the Eta model Renew Energy 35 2010 1236 1243
    • (2010) Renew Energy , vol.35 , pp. 1236-1243
    • Lazić, L.1    Pejanović, G.2    Živković, M.3
  • 146
    • 33244483663 scopus 로고    scopus 로고
    • Short-term wind forecasting using off-site observations
    • DOI 10.1002/we.179
    • K.A. Larson, and K. Westrick Short-term wind forecasting using off-site observations Wind Energy 9 2006 55 62 (Pubitemid 43281984)
    • (2006) Wind Energy , vol.9 , Issue.1-2 , pp. 55-62
    • Larson, K.A.1    Westrick, K.2
  • 147
    • 79959375425 scopus 로고    scopus 로고
    • Assessment of the benefits of numerical weather predictions in wind power forecasting based on statistical methods
    • M.G. De Giorgi, A. Ficarella, and M. Tarantino Assessment of the benefits of numerical weather predictions in wind power forecasting based on statistical methods Energy 36 2011 3968 3978
    • (2011) Energy , vol.36 , pp. 3968-3978
    • De Giorgi, M.G.1    Ficarella, A.2    Tarantino, M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.