AWNN-Assisted wind power forecasting using feed-forward neural network

IEEE Transactions on Sustainable Energy

Volumn 3, Issue 2, 2012, Pages 306-315

  Bhaskar, Kanna ^a   Singh, S N ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY KANPUR   (India)

Author keywords

Adaptive wavelet neural network (AWNN); feed forward neural network (FFNN); multiresolution analysis; wind speed and wind power forecast

Indexed keywords

ADAPTIVE WAVELET NEURAL NETWORK; ALLOCATION PROBLEMS; BENCHMARK MODELS; ECONOMIC SCHEDULING; ELECTRICITY MARKET; FEED-FORWARD NEURAL NETWORK (FFNN); MULTI-RESOLUTIONS; NONLINEAR MAPPINGS; NUMERICAL WEATHER PREDICTION; POWER OUT PUT; POWER PRODUCER; SYSTEM OPERATOR; TWO STAGE; UNIT COMMITMENTS; WIND GENERATION; WIND POWER FORECASTING; WIND POWER PENETRATION; WIND POWER PREDICTIONS; WIND SPEED; WIND SPEED AND WIND POWER FORECAST; WIND SPEED-UP;

NEURAL NETWORKS; SCHEDULING; SIGNAL PROCESSING; WAVELET DECOMPOSITION; WIND EFFECTS; WIND POWER;

WEATHER FORECASTING;

EID: 84859036543     PISSN: 19493029     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSTE.2011.2182215     Document Type: Article

References (33)

1. Global Wind Energy Outlook Report 2010 [Online]. Available: http://www. gwec. net/fileadmin/documents/Publications/GWEO%202010%20final. pdf
2. G. Giebel, L. Landberg, G. Kariniotakis, and R. Brownsword, "State-of-the-art on methods and software tools for short-term prediction of wind energy production, " in Proc. Eur. Wind Energy Conf. and Exhibition (EWEC), Madrid, Spain, 2003.
3. T. S. Nielsen, H. MadsenJ, and J. Tøfting, "Experiences with statistical methods for wind power prediction, " in Proc. Eur. Wind Energy Conf. (EWEC), 1999, pp. 1066-1069.
4. T. S. Nielsen, H. MadsenJ, and J. Tøfting, WPPT, a tool for on-line wind power prediction International Energy Agency, Wind Forecasting Techniques Tech. Rep., 2000.
5. T. Barbounis, J. Theocharis, M. Alexiadis, and P. Dokopoulos, "Longterm wind speed and power forecasting using local recurrent neural network models, " IEEE Trans. Energy Convers., vol. 21, no. 1, pp. 273-284, Mar. 2006. (Pubitemid 43280545)
6. G. Sideratos and N. Hatziargyriou, "An advanced statisticalmethod for wind power forecasting, " IEEE Trans. Power Syst., vol. 22, no. 1, pp. 258-265, Feb. 2007. (Pubitemid 46437735)
7. Y. K. Wu and J. S. Hong, "A literature review of wind forecasting technology in the world, " in Proc. IEEE Power Tech., Lausanne, 2007, pp. 504-509.
8. C. Monteiro, R. Bessa, V. Miranda, A. Botterud, J. Wang, and G. Conzelmann, Wind Power Forecasting: State-of-the-art 2009 ARGONNE National Laboratory Deliverable Report Nov. 2009.
9. G. N. Kariniotakis, G. S. Stavrakakis, and E. F. Nogaret, "Wind power forecasting using advanced neural networks models, " IEEE Trans. Energy Convers., vol. 11, no. 4, pp. 762-767, Dec. 1996. (Pubitemid 126771432)
10. A. Y. Alanis, L. J. Ricalde, and E. N. Sanchez, "High order neural networks for wind speed time series prediction, " in Proc. Int. Joint Conf. on Neural Networks, 2009, pp. 76-80.
11. I. Damousis, M. Alexiadis, J. Theocharis, and P. Dokopoulos, "A fuzzy model for wind speed prediction and power generation in wind parks using spatial correlation, " IEEE Trans. Energy Convers., vol. 19, no. 2, pp. 352-361, Jun. 2004.
12. M. Alexiadis, P. Dokopoulos, and H. Sahsamanoglou, "Wind speed and power forecasting based on spatial correlation models, " IEEE Trans. Energy Convers., vol. 14, no. 3, pp. 836-842, Sep. 1999. (Pubitemid 30528670)
13. J. P. S. Catalao, 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, vol. 2, no. 1, pp. 50-59, Jan. 2011.
14. M. Milligan, M. Schwartz, and Y. Wan, "Statistical wind power forecasting for U. S. wind farms, " in Proc. 17th Conf. Probability and Statistics in the Atmospheric Sciences American Meteorological Society Annual Meeting, Seattle, WA, Jan. 2004.
15. R. G. Kavasseri and K. Seetharaman, "Day-ahead wind speed forecasting using f-ARIMA models, " Renew. Energy, vol. 34, no. 5, pp. 1388-1393, 2009.
16. H. Zhou, J. Fang, and M. Huang, "Numerical analysis of application GARCH to short-term wind power forecasting, " in Proc. Int. Conf. Power System Technology (POWERCON), 2010, pp. 1-6.
17. S. Gao, Y. He, and H. Chen, "Wind speed forecast for wind farms based on ARMA-ARCH model, " in Proc. Int. Conf. Sustainable Power Generation and Supply (SUPERGEN), 2009, pp. 1-4.
18. A. Kusiak, H. Zheng, and Z. Song, "Short-termprediction of wind farm power: A data mining approach, " IEEE Trans. Energy Convers., vol. 24, no. 1, pp. 125-136, Mar. 2009.
19. Z. Songlin, M. Meiqin, and L. chang, "Forecasting of wind speed based on wavelet analysis and support vector machine, " in Proc. Int. Conf. Power Electronics for Distributed Generation Systems (PEDG), 2010, pp. 864-867.
20. Q. Zhang and A. Benveniste, "Wavelet networks, " IEEE Trans. Neural Netw., vol. 3, no. 6, pp. 889-898, Nov. 1992. (Pubitemid 23580843)
21. J. Zhang, G. G. Walter, Y. Miao, and W. N. W. Lee, "Wavelet neural networks for function learning, " IEEE Trans. Signal Process., vol. 43, no. 6, pp. 1485-1497, Jun. 1995.
22. S. A. Billings and H. L. Wei, "A new class of wavelet networks for nonlinear system identification, " IEEE Trans. Neural Netw., vol. 16, no. 4, pp. 862-874, Jul. 2005. (Pubitemid 41064318)
23. S. S. Iyenger, E. C. Cho, and V. V. Phoha, Foundation of Wavelet Networks and Applications. Boca Raton, FL: Chapman & Hall, 2002.
24. N. M. Pindoriya, S. N. Singh, and S. K. Singh, "An adaptive wavelet neural network-based energy price forecasting in electricity markets, " IEEE Trans. Power Syst., vol. 23, no. 3, pp. 1423-1432, Aug. 2008.
25. I. Daubechies, "The wavelet transform, time-frequency localization and signal analysis, " IEEE Trans. Inf. Theory, vol. 36, no. 5, pp. 961-1005, Sep. 1990. (Pubitemid 20738359)
26. S. G. Mallat, "A theory for multiresolution signal decomposition: The wavelet representation, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 11, no. 7, pp. 674-693, Jul. 1989.
27. D. Parcival and A. Walden, Wavelet Methods for Time Series Analysis. Cambridge, U. K. : Cambridge Univ. Press, 2000.
28. M. Unser, "Texture classification and segmentation using wavelet frames, " IEEE Trans. Image Process., vol. 4, no. 11, pp. 1549-1560, Nov. 1995.
29. S. Haykin, Neural Netwoks a Comprehensive Foundation. Englewood Cliffs, NJ: Prentice-Hall, 1999.
30. K. L. Ho, Y. Y. Hsu, and C. C. Yang, "Short term load forecasting using amultilayer neural network with an adaptive learning algorithm, " IEEE Trans. Power Syst., vol. 7, no. 1, pp. 141-149, Feb. 1992.
31. H. Madsen, P. Pinson, G. Kariniotakis, H. A. Nielsen, and T. S. Nielsen, "Standardizing the performance evaluation of short-term wind power prediction models, " Wind Eng., vol. 29, no. 6, pp. 475-489, 2005.
32. National Renewable Energy Laboratory [Online]. Available: http://www. nrel. gov/wind/integrationdatasets/eastern/data. html
33. G. K. Kariniotakis et al., "Next generation short-term forecasting of wind power-Overview of the ANEMOS project, " in Proc. Eur. Wind Energy Conf. (EWEC), Athens, Greece, 2006.