Wind power prediction considering nonlinear atmospheric disturbances

Energies

Volumn 8, Issue 1, 2015, Pages 475-489

  Zhang, Yagang ^a,b   Yang, Jingyun ^a   Wang, Kangcheng ^a   Wang, Zengping ^a  

^a NORTH CHINA ELECTRIC POWER UNIVERSITY   (China)

^b UNIVERSITY OF SOUTH CAROLINA   (United States)

Author keywords

Artificial neural network; Atmospheric disturbance; Lorenz system; Wind energy; Wind speed and power prediction

Indexed keywords

FORECASTING; NEURAL NETWORKS; PERTURBATION TECHNIQUES; SPEED; WIND; WIND EFFECTS; WIND POWER;

ARTIFICIAL NEURAL NETWORK MODELS; ATMOSPHERIC DISTURBANCE; DISTURBANCE VARIABLES; GUIDING SIGNIFICANCES; LORENZ SYSTEM; POWER PREDICTIONS; WIND POWER PREDICTIONS; WIND SPEED PREDICTION;

WEATHER FORECASTING;

EID: 84949115984     PISSN: None     EISSN: 19961073     Source Type: Journal    
DOI: 10.3390/en8010475     Document Type: Article

References (27)

1. Global Wind Energy Council (GWEC). Available online: http://www.gwec.net/global-figures/ graphs/ (accessed on 9 March 2014).
2. Hu, J.M., Wang, J.Z., Zeng, G.W. A hybrid forecasting approach applied to wind speed time series. Renew. Energy 2013, 60, 185-194.
3. Zhang, W.Y., Wang, J.J., Wang, J.Z., Zhao, Z.B., Tian, M. Short-term wind speed forecasting based on a hybrid model. Appl. Soft. Comput. 2013, 13, 3225-3233.
4. Wang, X.C., Guo, P., Huang, X.B. A review of wind power forecasting models. Energy Proced. 2011, 12, 770-778.
5. Foley, A.M., Leahy, P.G., Marvuglia, A., Mckeogh, E.J. Current methods and advances in forecasting of wind power generation. Renew. Energy 2011, 37, 1-8.
6. Chen, Z.H., Xu, Y., Xu, P.H., Yang, H.Q., Xiong, S.Q. Principle of Wind Power Prediction Technology and Business Systems, 1st ed., China Meteorological Press: Beijing, China, 2013; pp. 18-41.
7. Bouzgou, H., Benoudjit, N. Multiple architecture system for wind speed prediction. Appl. Energy 2011, 88, 2463-2471.
8. Yesilbudak, M., Sagiroglu, S., Colak, I. A new approach to very short term wind speed prediction using k-nearest neighbor classification. Energy Convers. Manag. 2013, 69, 77-86.
9. Liu, H., Tian, H.Q., Chen, C., Li, Y.F. A hybrid statistical method to predict wind speed and wind power. Renew. Energy 2010, 35, 1857-1861.
10. Tascikaraoglu, A., Uzunoglu, M. A review of combined approaches for prediction of short-term wind speed and power. Renew. Sustain. Energy Rev. 2014, 34, 243-254.
11. Gan, M., Ding, M., Huang, Y.Z., Dong, X.P. The effect of different state sizes on Mycielski approach for wind speed prediction. J. Wind Eng. Ind. Aerodyn. 2012, 109, 89-93.
12. Martinez-Morales, J.D., Palacios, E., Velazquez-Carrillo, G.A. Wavelet neural networks for predicting engine emissions. Proced. Technol. 2013, 7, 328-335.
13. Zhou, J.Y., Shi, J., Li, G. Fine tuning support vector machines for short-term wind speed forecasting. Energy Convers. Manag. 2011, 52, 1990-1998.
14. Monfared, M., Rastegar, H., Kojabadi, H.M. A new strategy for wind speed forecasting using artificial intelligent methods. Renew. Energy 2008, 34, 845-848.
15. 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 2010, 98, 415-424.
16. Sheela, K.G., Deepa, S.N. Neural network based hybrid computing model for wind speed prediction. Neurocomputing 2013, 122, 425-429.
17. Liu, H., Tian, H.Q., Pan, D.F., Li, Y.F. Forecasting models for wind speed using wavelet, wavelet packet, time series and artificial neural networks. Appl. Energy 2013, 107, 191-208.
18. Zhang, Y., Wang, J.X., Wang, X.F. Review on probabilistic forecasting of wind power generation. Renew. Sustain. Energy Rev. 2014, 32, 255-270.
19. Guo, Z.H., Chi, D.Z., Wu, J., Zhang, W.Y. A new wind speed forecasting strategy based on the chaotic time series modelling technique and the Apriori algorithm. Energy Convers. Manag. 2014, 84, 140-151.
20. Zhang, Y.G., Yang, J.Y., Wang, K.C., Wang, Y.D. Lorenz wind disturbance model based on grey generated components. Energies 2014, 7, 7178-7193.
21. Liu, B.Z., Peng, J.H. Nonlinear Dynamics, 1st ed., Higher Education Press: Beijing, China, 2007; pp. 120-143.
22. Lorenz, E.N. The Butterfly Effect; Premio Felice Pietro Chisesi e Caterina Tomassoni award lecture; University of Rome: Rome, Italy, 2008.
23. Lorenz, E.N. Deterministic nonperiodic flow. J. Atmos. Sci. 1963, 20, 130-141.
24. Algaba, A., Fernandez-Sanchez, F., Merino, M., Rodriguez-Luis, A.J. Comments on 'Global dynamics of the generalized Lorenz systems having invariant algebraic surfaces'. Phys. D Nonlinear Phenom. 2014, 266, 80-82.
25. Moghtadaei, M., Hashemi Golpayegani, M.R. Complex dynamic behaviors of the complex Lorenz system. Sci. Iran. D 2012, 19, 733-738.
26. Lorenz, E.N. The Essence of Chaos, 1st ed., China Meteorological Press: Beijing, China, 1997; pp. 127-137.
27. Saltzman, B. Finite amplitude free convection as an initial value problem-I. J. Atmos. Sci. 1962, 19, 329-341.