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Volumn 107, Issue , 2013, Pages 191-208

Forecasting models for wind speed using wavelet, wavelet packet, time series and Artificial Neural Networks

Author keywords

ANN; ARIMA; Hybrid model; Signal decomposition; Wind speed forecasting; Wind speed predictions

Indexed keywords

FORECASTING; NEURAL NETWORKS; RADIAL BASIS FUNCTION NETWORKS; TIME SERIES ANALYSIS; WIND POWER;

EID: 84875115854     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2013.02.002     Document Type: Article
Times cited : (311)

References (40)
  • 1
    • 81855186989 scopus 로고    scopus 로고
    • Development of offshore wind power in China
    • Jinjin C. Development of offshore wind power in China. Renew Sustain Energy Rev 2011, 15(9):5013-5020.
    • (2011) Renew Sustain Energy Rev , vol.15 , Issue.9 , pp. 5013-5020
    • Jinjin, C.1
  • 2
    • 78650577402 scopus 로고    scopus 로고
    • An integrated control method for a wind farm to reduce frequency deviations in a small power system
    • Kaneko T., Uehara A., Senjyu T., Yona A., Urasaki N. An integrated control method for a wind farm to reduce frequency deviations in a small power system. Appl Energy 2011, 88(4):1049-1058.
    • (2011) Appl Energy , vol.88 , Issue.4 , pp. 1049-1058
    • Kaneko, T.1    Uehara, A.2    Senjyu, T.3    Yona, A.4    Urasaki, N.5
  • 3
    • 84864827118 scopus 로고    scopus 로고
    • Wind speed and wind energy forecast through Kalman filtering of numerical weather prediction model
    • Cassola F., Burlando M. Wind speed and wind energy forecast through Kalman filtering of numerical weather prediction model. Appl Energy 2012, 99:154-166.
    • (2012) Appl Energy , vol.99 , pp. 154-166
    • Cassola, F.1    Burlando, M.2
  • 4
    • 84864797603 scopus 로고    scopus 로고
    • Performance analysis of four modified approaches for wind speed forecasting
    • Zhang W.Y., Wu J., Wang J.Z., Zhao W.G., Shen L. Performance analysis of four modified approaches for wind speed forecasting. Appl Energy 2012, 99:324-333.
    • (2012) Appl Energy , vol.99 , pp. 324-333
    • Zhang, W.Y.1    Wu, J.2    Wang, J.Z.3    Zhao, W.G.4    Shen, L.5
  • 5
    • 78650562310 scopus 로고    scopus 로고
    • ARMA based approaches for forecasting the tuple of wind speed and direction
    • Erdem E., Shi J. ARMA based approaches for forecasting the tuple of wind speed and direction. Appl Energy 2011, 88:1405-1414.
    • (2011) Appl Energy , vol.88 , pp. 1405-1414
    • Erdem, E.1    Shi, J.2
  • 6
    • 84862213628 scopus 로고    scopus 로고
    • Comparison of two new ARIMA-ANN and ARIMA-Kalman hybrid methods for wind speed prediction
    • Liu H., Tian H.Q., Li Y.F. Comparison of two new ARIMA-ANN and ARIMA-Kalman hybrid methods for wind speed prediction. Appl Energy 2012, 98:415-424.
    • (2012) Appl Energy , vol.98 , pp. 415-424
    • Liu, H.1    Tian, H.Q.2    Li, Y.F.3
  • 7
    • 78149358777 scopus 로고    scopus 로고
    • Comprehensive evaluation of ARMA-GARCH(-M) approaches for modeling the mean and volatility of wind speed
    • Liu H.P., Erdem E., Shi J. Comprehensive evaluation of ARMA-GARCH(-M) approaches for modeling the mean and volatility of wind speed. Appl Energy 2011, 88(3):724-732.
    • (2011) Appl Energy , vol.88 , Issue.3 , pp. 724-732
    • Liu, H.P.1    Erdem, E.2    Shi, J.3
  • 8
    • 79952454042 scopus 로고    scopus 로고
    • Multiple architecture system for wind speed prediction
    • Bouzgou H., Benoudjit N. Multiple architecture system for wind speed prediction. Appl Energy 2011, 88(7):2463-2471.
    • (2011) Appl Energy , vol.88 , Issue.7 , pp. 2463-2471
    • Bouzgou, H.1    Benoudjit, N.2
  • 9
    • 84860255082 scopus 로고    scopus 로고
    • Forecasting wind speed with recurrent neural networks
    • Cao Q., Ewing B.T., Thompson M.A. Forecasting wind speed with recurrent neural networks. Eur J Oper Res 2012, 221(1):148-154.
    • (2012) Eur J Oper Res , vol.221 , Issue.1 , pp. 148-154
    • Cao, Q.1    Ewing, B.T.2    Thompson, M.A.3
  • 10
    • 84865557377 scopus 로고    scopus 로고
    • Very short-term wind speed forecasting with Bayesian structural break model
    • Jiang Y., Song Z., Kusiak A. Very short-term wind speed forecasting with Bayesian structural break model. Renew Energy 2013, 50:637-647.
    • (2013) Renew Energy , vol.50 , pp. 637-647
    • Jiang, Y.1    Song, Z.2    Kusiak, A.3
  • 11
    • 79961127156 scopus 로고    scopus 로고
    • Multi-step forecasting for wind speed using a modified EMD-based artificial neural network model
    • Guo Z.H., Zhao W.G., Lu H.Y., Wang J.Z. Multi-step forecasting for wind speed using a modified EMD-based artificial neural network model. Renew Energy 2012, 37(1):241-249.
    • (2012) Renew Energy , vol.37 , Issue.1 , pp. 241-249
    • Guo, Z.H.1    Zhao, W.G.2    Lu, H.Y.3    Wang, J.Z.4
  • 13
    • 79959733948 scopus 로고    scopus 로고
    • A case study on a hybrid wind speed forecasting method using BP neural network
    • Guo Z.H., Wu J., Lu H.Y., Wang J.Z. A case study on a hybrid wind speed forecasting method using BP neural network. Knowl Based Syst 2011, 24(7):1048-1056.
    • (2011) Knowl Based Syst , vol.24 , Issue.7 , pp. 1048-1056
    • Guo, Z.H.1    Wu, J.2    Lu, H.Y.3    Wang, J.Z.4
  • 14
    • 78649814612 scopus 로고    scopus 로고
    • Prediction of wind speed time series using modified Taylor Kriging method
    • Liu H.P., Shi J., Erdem E. Prediction of wind speed time series using modified Taylor Kriging method. Energy 2010, 35(12):4870-4879.
    • (2010) Energy , vol.35 , Issue.12 , pp. 4870-4879
    • Liu, H.P.1    Shi, J.2    Erdem, E.3
  • 15
    • 84859416828 scopus 로고    scopus 로고
    • Evaluation of hybrid forecasting approaches for wind speed and power generation time series
    • Shi J., Guo J.M., Zheng S.T. Evaluation of hybrid forecasting approaches for wind speed and power generation time series. Renew Sustain Energy Rev 2012, 16(5):3471-3480.
    • (2012) Renew Sustain Energy Rev , vol.16 , Issue.5 , pp. 3471-3480
    • Shi, J.1    Guo, J.M.2    Zheng, S.T.3
  • 17
    • 79551493206 scopus 로고    scopus 로고
    • A new hybrid iterative method for short term wind speed forecasting
    • Amjady N., Keynia F., Zareipour H. A new hybrid iterative method for short term wind speed forecasting. Eur Trans Electr Power 2011, 21:581-595.
    • (2011) Eur Trans Electr Power , vol.21 , pp. 581-595
    • Amjady, N.1    Keynia, F.2    Zareipour, H.3
  • 18
    • 84892452723 scopus 로고    scopus 로고
    • Adaptive neurofuzzy short-term wind-speed forecasting for Egypt's East-Coast
    • Salim O.M., Zohdy M.A., Dorrah H.T., Kamel A.M. Adaptive neurofuzzy short-term wind-speed forecasting for Egypt's East-Coast. Int J Sustain Energy 2012, 10.1080/14786451.2011.630468.
    • (2012) Int J Sustain Energy
    • Salim, O.M.1    Zohdy, M.A.2    Dorrah, H.T.3    Kamel, A.M.4
  • 19
    • 78049513565 scopus 로고    scopus 로고
    • Very short-term wind speed prediction: a new artificial neural network-Markov chain model
    • Kani S.A.P., Ardehali M.M. Very short-term wind speed prediction: a new artificial neural network-Markov chain model. Energy Convers Manage 2011, 52(1):738-745.
    • (2011) Energy Convers Manage , vol.52 , Issue.1 , pp. 738-745
    • Kani, S.A.P.1    Ardehali, M.M.2
  • 20
    • 78650944534 scopus 로고    scopus 로고
    • Fine tuning support vector machines for short-term wind speed forecasting
    • Zhou J.Y., Shi J., Li G. Fine tuning support vector machines for short-term wind speed forecasting. Energy Convers Manage 2011, 52(4):1990-1998.
    • (2011) Energy Convers Manage , vol.52 , Issue.4 , pp. 1990-1998
    • Zhou, J.Y.1    Shi, J.2    Li, G.3
  • 21
    • 84859070373 scopus 로고    scopus 로고
    • Application of auto-regressive models to UK wind speed data for power system impact studies
    • Hill D.C., McMillan D., Bell K.R.W., Infield D. Application of auto-regressive models to UK wind speed data for power system impact studies. IEEE Trans Sustain Energy 2012, 3(1):134-141.
    • (2012) IEEE Trans Sustain Energy , vol.3 , Issue.1 , pp. 134-141
    • Hill, D.C.1    McMillan, D.2    Bell, K.R.W.3    Infield, D.4
  • 22
    • 80052530027 scopus 로고    scopus 로고
    • Short-term wind power forecasting using Ridgelet neural network
    • Amjady N., Keynia F., Zareipour H. Short-term wind power forecasting using Ridgelet neural network. Electr Power Syst Res 2011, 81(12):2099-2107.
    • (2011) Electr Power Syst Res , vol.81 , Issue.12 , pp. 2099-2107
    • Amjady, N.1    Keynia, F.2    Zareipour, H.3
  • 23
    • 79959557168 scopus 로고    scopus 로고
    • Wind power prediction by a new forecast engine composed of modified hybrid neural network and enhanced particle swarm optimization
    • Amjady N., Keynia F., Zareipour H. Wind power prediction by a new forecast engine composed of modified hybrid neural network and enhanced particle swarm optimization. IEEE Trans Sustain Energy 2011, 2(3):265-276.
    • (2011) IEEE Trans Sustain Energy , vol.2 , Issue.3 , pp. 265-276
    • Amjady, N.1    Keynia, F.2    Zareipour, H.3
  • 24
    • 79959375425 scopus 로고    scopus 로고
    • Assessment of the benefits of numerical weather predictions in wind power forecasting based on statistical methods
    • Maria Grazia De Giorgi, Ficarella A., Tarantino M. Assessment of the benefits of numerical weather predictions in wind power forecasting based on statistical methods. Energy 2011, 36(7):3968-3978.
    • (2011) Energy , vol.36 , Issue.7 , pp. 3968-3978
    • Maria Grazia De, G.1    Ficarella, A.2    Tarantino, M.3
  • 25
    • 84860890595 scopus 로고    scopus 로고
    • Data mining and wind power prediction: a literature review
    • Colaka I., Sagiroglub S., Yesilbudakc M. Data mining and wind power prediction: a literature review. Renew Energy 2012, 46:241-247.
    • (2012) Renew Energy , vol.46 , pp. 241-247
    • Colaka, I.1    Sagiroglub, S.2    Yesilbudakc, M.3
  • 26
    • 79951847299 scopus 로고    scopus 로고
    • Short-term wind power generation forecasting: direct versus indirect ARIMA-based approaches
    • Shi J., Qu X., Zeng S. Short-term wind power generation forecasting: direct versus indirect ARIMA-based approaches. Int J Green Energy 2011, 8(1):100-112.
    • (2011) Int J Green Energy , vol.8 , Issue.1 , pp. 100-112
    • Shi, J.1    Qu, X.2    Zeng, S.3
  • 27
    • 84859036543 scopus 로고    scopus 로고
    • AWNN-assisted wind power forecasting using feed-forward neural network
    • Bhaskar K., Singh S.N. AWNN-assisted wind power forecasting using feed-forward neural network. IEEE Trans Sustain Energy 2012, 3(2):306-315.
    • (2012) IEEE Trans Sustain Energy , vol.3 , Issue.2 , pp. 306-315
    • Bhaskar, K.1    Singh, S.N.2
  • 28
    • 79959826777 scopus 로고    scopus 로고
    • Estimation of wind speed profile using adaptive neuro-fuzzy inference system (ANFIS)
    • Mohandes M., Rehman S., Rahman S.M. Estimation of wind speed profile using adaptive neuro-fuzzy inference system (ANFIS). Appl Energy 2011, 88(11):4024-4032.
    • (2011) Appl Energy , vol.88 , Issue.11 , pp. 4024-4032
    • Mohandes, M.1    Rehman, S.2    Rahman, S.M.3
  • 29
    • 33646342226 scopus 로고    scopus 로고
    • Day-ahead price forecasting of electricity markets by a new fuzzy neural network
    • Amjady N. Day-ahead price forecasting of electricity markets by a new fuzzy neural network. IEEE Trans Power Syst 2006, 21(2):887-896.
    • (2006) IEEE Trans Power Syst , vol.21 , Issue.2 , pp. 887-896
    • Amjady, N.1
  • 30
    • 33646399473 scopus 로고    scopus 로고
    • Neural networks approach to forecast several hour ahead electricity prices and loads in deregulated market
    • Mandal P., Senjyu T., Funabashi T. Neural networks approach to forecast several hour ahead electricity prices and loads in deregulated market. Energy Convers Manage 2006, 47(15-16):2128-2142.
    • (2006) Energy Convers Manage , vol.47 , Issue.15-16 , pp. 2128-2142
    • Mandal, P.1    Senjyu, T.2    Funabashi, T.3
  • 31
    • 70349972130 scopus 로고    scopus 로고
    • An effort to optimize similar days parameters for ANN based electricity price forecasting
    • Mandal P., Srivastava A.K., Park J.W. An effort to optimize similar days parameters for ANN based electricity price forecasting. IEEE Trans Ind Appl 2009, 45(5):1888-1896.
    • (2009) IEEE Trans Ind Appl , vol.45 , Issue.5 , pp. 1888-1896
    • Mandal, P.1    Srivastava, A.K.2    Park, J.W.3
  • 32
    • 0024700097 scopus 로고
    • A theory for multiresolution signal decomposition: the wavelet representation
    • Mallat S.G. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans Pattern Anal Mach Intell 1989, 11(7):674-693.
    • (1989) IEEE Trans Pattern Anal Mach Intell , vol.11 , Issue.7 , pp. 674-693
    • Mallat, S.G.1
  • 33
    • 84859917661 scopus 로고    scopus 로고
    • Convolution wavelet packet transform and its applications to signal processing
    • Zhao X.Z., Ye B.Y. Convolution wavelet packet transform and its applications to signal processing. Digital Signal Process 2010, 20(5):1352-1364.
    • (2010) Digital Signal Process , vol.20 , Issue.5 , pp. 1352-1364
    • Zhao, X.Z.1    Ye, B.Y.2
  • 34
    • 0033351402 scopus 로고    scopus 로고
    • Convergence analysis of the Quickprop method. In: IEEE international joint conference on neural networks
    • Vrahatis MN, Magoulas GD, Plagianakos VP. Convergence analysis of the Quickprop method. In: IEEE international joint conference on neural networks; 1999. p. 1209-14.
    • (1999) , pp. 1209-1214
    • Vrahatis, M.N.1    Magoulas, G.D.2    Plagianakos, V.P.3
  • 35
    • 84943274699 scopus 로고
    • A direct adaptive method for faster backpropagation learning: the RPROP algorithm. In: IEEE international conference on neural networks
    • Riedmiller M, Braun H. A direct adaptive method for faster backpropagation learning: the RPROP algorithm. In: IEEE international conference on neural networks; 1993. p. 586-91.
    • (1993) , pp. 586-591
    • Riedmiller, M.1    Braun, H.2
  • 36
    • 76949104606 scopus 로고    scopus 로고
    • Feedforward neural network trained by BFGS algorithm for modeling plasma etching of silicon carbide
    • Xia J.H., Rusli, Kumta A.S. Feedforward neural network trained by BFGS algorithm for modeling plasma etching of silicon carbide. IEEE Trans Plasma Sci 2010, 38(2):142-148.
    • (2010) IEEE Trans Plasma Sci , vol.38 , Issue.2 , pp. 142-148
    • Xia, J.H.1    Rusli2    Kumta, A.S.3
  • 37
    • 0141501530 scopus 로고    scopus 로고
    • Neuro-fuzzy methods for nonlinear system identification
    • BabuŠka R., Verbruggen H. Neuro-fuzzy methods for nonlinear system identification. Annu Rev Control 2003, 27:73-85.
    • (2003) Annu Rev Control , vol.27 , pp. 73-85
    • Babuška, R.1    Verbruggen, H.2
  • 38
    • 0027601884 scopus 로고
    • ANFIS: adaptive-network-based fuzzy inference systems
    • Jang J.S.R. ANFIS: adaptive-network-based fuzzy inference systems. IEEE Trans Syst Man Cybernet 1993, 23(3):665-685.
    • (1993) IEEE Trans Syst Man Cybernet , vol.23 , Issue.3 , pp. 665-685
    • Jang, J.S.R.1
  • 39
    • 0034286972 scopus 로고    scopus 로고
    • A comparison of various forecasting techniques applied to mean hourly wind speed time series
    • Sfetsos A. A comparison of various forecasting techniques applied to mean hourly wind speed time series. Renew Energy 2000, 21(1):23-35.
    • (2000) Renew Energy , vol.21 , Issue.1 , pp. 23-35
    • Sfetsos, A.1
  • 40
    • 84875122561 scopus 로고    scopus 로고
    • A review of wind power and wind speed forecasting methods with different time horizons. In: IEEE north American power symposium
    • Soman SS, Zareipour H, Malik O, Mandal P. A review of wind power and wind speed forecasting methods with different time horizons. In: IEEE north American power symposium; 2010. p. 1-8.
    • (2010) , pp. 1-8
    • Soman, S.S.1    Zareipour, H.2    Malik, O.3    Mandal, P.4


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