[1]
|
Chang, W.Y. (2013) Short-Term Wind Power Forecasting Using EPSO Based Hybrid Method. Energies, 6, 4879-4896.
http://dx.doi.org/10.3390/en6094879
|
[2]
|
Chang, W.Y. (2013) Comparison of Three Short Term Wind Power Forecasting Systems. Advanced Materials Research, 684, 671-675. http://dx.doi.org/10.4028/www.scientific.net/AMR.684.671
|
[3]
|
Chang, W.Y. (2013) An RBF Neural Network Combined with OLS Algorithm and Genetic Algorithm for Short-Term Wind Power Forecasting. Journal of Applied Mathematics, 2013, Article ID: 971389, 9 p.
|
[4]
|
Sideratos, G. and Hatziargyriou, N.D. (2007) An Advanced Statistical Method for Wind Power Forecasting. IEEE Transactions on Power Systems, 22, 258-265. http://dx.doi.org/10.1109/TPWRS.2006.889078
|
[5]
|
Ma, L., Luan, S.Y., Jiang, C.W., Liu, H L. and Zhang, Y. (2009) A Review on the Forecasting of Wind Speed and Generated Power. Renewable and Sustainable Energy Reviews, 13, 915-920.
http://dx.doi.org/10.1016/j.rser.2008.02.002
|
[6]
|
Lange, M. and Focken, U. (2008) New Developments in Wind Energy Forecasting. Proceedings of the 2008 IEEE Power and Energy Society General Meeting, Pittsburgh, 20-24 July 2008, 1-8.
|
[7]
|
Wang, X.C., Guo, P. and Huang, X.B. (2011) A Review of Wind Power Forecasting Models. Energy Procedia, 12, 770-778. http://dx.doi.org/10.1016/j.egypro.2011.10.103
|
[8]
|
Zhao, D.M., Zhu, Y.C. and Zhang, X. (2011) Research on Wind Power Forecasting in Wind Farms. Proceedings of the 2011 IEEE Power Engineering and Automation Conference, Wuhan, 8-9 September 2011, 175-178.
http://dx.doi.org/10.1109/PEAM.2011.6134829
|
[9]
|
Zhao, X., Wang, S.X. and Li, T. (2011) Review of Evaluation Criteria and Main Methods of Wind Power Forecasting. Energy Procedia, 12, 761-769. http://dx.doi.org/10.1016/j.egypro.2011.10.102
|
[10]
|
Wu, Y.K. and Hon, J.S. (2007) A Literature Review of Wind Forecasting Technology in the World. Proceedings of the IEEE Conference on Power Tech, Lausanne, 1-5 July 2007, 504-509.
|
[11]
|
Soman, S.S., Zareipour, H., Malik, O. and Mandal, P. (2010) A Review of Wind Power and Wind Speed Forecasting Methods with Different Time Horizons. Proceedings of the 2010 North American Power Symposium, Arlington, 26-28 September 2010, 1-8. http://dx.doi.org/10.1109/NAPS.2010.5619586
|
[12]
|
Bhaskar, K. and Singh, S.N. (2012) AWNN-Assisted Wind Power Forecasting Using Feed-Forward Neural Network. IEEE Transactions on Sustainable Energy, 3, 306-315. http://dx.doi.org/10.1109/TSTE.2011.2182215
|
[13]
|
Firat, U., Engin, S.N., Saraclar, M. and Ertuzun, A.B. (2010) Wind Speed Forecasting Based on Second Order Blind Identification and Autoregressive Model. Proceedings of the 9th International Conference on Machine Learning and Applications, Washington, 12-14 December 2010, 618-621.
|
[14]
|
Erdem, E. and Shi, J. (2011) ARMA Based Approaches for Forecasting the Tuple of Wind Speed and Direction. Applied Energy, 88, 1405-1414. http://dx.doi.org/10.1016/j.apenergy.2010.10.031
|
[15]
|
Li, L.L., Li, J.H., He, P.J. and Wang, C.S. (2011) The Use of Wavelet Theory and ARMA Model in Wind Speed Prediction. Proceedings of the 1st International Conference on Electric Power Equipment-Switching Technology, Xi’an, 23-27 October 2011, 395-398.
|
[16]
|
Palomares-Salas, J.C., de la Rosa, J.J.G., Ramiro, J.G., Melgar, J., Aguera, A. and Moreno, A. (2009) ARIMA vs. Neural Networks for Wind Speed Forecasting. Proceedings of the IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, Hong Kong, 11-13 May 2009, 129-133.
|
[17]
|
Miranda, M.S. and Dunn, R.W. (2006) One-Hour-Ahead Wind Speed Prediction Using a Bayesian Methodology. Proceedings of the 2006 IEEE Power Engineering Society General Meeting, Montreal, 18-22 June 2006, 1-6.
|
[18]
|
Alexiadis, M.C., Dokopoulos, P.S., Sahsamanoglou, H.S. and Manousaridis, I.M. (1998) Short-Term Forecasting of Wind Speed and Related Electrical Power. Solar Energy, 63, 61-68. http://dx.doi.org/10.1016/S0038-092X(98)00032-2
|
[19]
|
Alexiadis, M.C., Dokopoulos, P.S. and Sahsamanoglou, H.S. (1999) Wind Speed and Power Forecasting Based on Spatial Correlation Models. IEEE Transactions on Energy Conversion, 14, 836-842.
http://dx.doi.org/10.1109/60.790962
|
[20]
|
Barbounis, T.G. and Theocharis, J.B. (2007) A Locally Recurrent Fuzzy Neural Network with Application to the Wind Speed Prediction Using Spatial Correlation. Neurocomputing, 70, 1525-1542.
http://dx.doi.org/10.1016/j.neucom.2006.01.032
|
[21]
|
Wu, Y.K., Lee, C.Y., Tsai, S.H. and Yu, S.N. (2010) Actual Experience on the Short-Term Wind Power Forecasting at Penghu-From an Island Perspective. Proceedings of the 2010 International Conference on Power System Technology, Hangzhou, 24-28 October 2010, 1-8. http://dx.doi.org/10.1109/POWERCON.2010.5666092
|
[22]
|
Sfetsos, A. (2002) A Novel Approach for the Forecasting of Mean Hourly Wind Speed Time Series. Renewable Energy, 27, 163-174. http://dx.doi.org/10.1016/S0960-1481(01)00193-8
|
[23]
|
Chang, W.Y. (2013) Application of Back Propagation Neural Network for Wind Power Generation Forecasting. International Journal of Digital Content Technology and its Application, 7, 502-509.
|
[24]
|
More, A. and Deo, M.C. (2003) Forecasting Wind with Neural Networks. Marine Structures, 16, 35-49.
http://dx.doi.org/10.1016/S0951-8339(02)00053-9
|
[25]
|
Chang, W.Y. (2013) Wind Energy Conversion System Power Forecasting Using Radial Basis Function Neural Network. Applied Mechanics and Materials, 284-287, 1067-1071.
http://dx.doi.org/10.4028/www.scientific.net/AMM.284-287.1067
|
[26]
|
Guo, Z.H., Zhao, W.G., Lu, H.Y. and Wang, J.Z. (2012) Multi-Step Forecasting for Wind Speed Using a Modified EMD-Based Artificial Neural Network Model. Renewable Energy, 37, 241-249.
http://dx.doi.org/10.1016/j.renene.2011.06.023
|
[27]
|
Li, G. and Shi, J. (2010) On Comparing Three Artificial Nneural Networks for Wind Speed Forecasting. Applied Energy, 87, 2313-2320. http://dx.doi.org/10.1016/j.apenergy.2009.12.013
|
[28]
|
Yang, Z.L., Liu, Y.Q. and Li, C.R. (2011) Interpolation of Missing Wind Data Based on ANFIS. Renewable Energy, 36, 993-998. http://dx.doi.org/10.1016/j.renene.2010.08.033
|
[29]
|
Zeng, J.W. and Qiao, W. (2011) Support Vector Machine-Based Short-Term Wind Power Forecasting. Proceedings of the IEEE/PES Power Systems Conference and Exposition, Phoenix, 20-23 March 2011, 1-8.
|
[30]
|
Zhou, J.Y., Shi, J. and Li, G. (2011) Fine Tuning Support Vector Machines for Short-Term Wind Speed Forecasting. Energy Conversion and Management, 52, 1990-1998. http://dx.doi.org/10.1016/j.enconman.2010.11.007
|
[31]
|
Xia, J.R., Zhao, P. and Dai, Y.P. (2010) Neuro-Fuzzy Networks for Short-Term Wind Power Forecasting. Proceedings of the International Conference on Power System Technology, Hangzhou, 24-28 October 2010, 1-5.
http://dx.doi.org/10.1115/1.859612
|
[32]
|
Jursa, R. and Rohrig, K. (2008) Short-Term Wind Power Forecasting Using Evolutionary Algorithms for the Automated Specification of Artificial Intelligence Models. International Journal of Forecasting, 24, 694-709.
http://dx.doi.org/10.1016/j.ijforecast.2008.08.007
|
[33]
|
Zhao, P., Wang, J.F., Xia, J.R., Dai, Y.P., Sheng, Y.X. and Yue, J. (2012) Performance Evaluation and Accuracy Enhancement of a Day-Ahead Wind Power Forecasting System in China. Renewable Energy, 43, 234-241.
http://dx.doi.org/10.1016/j.renene.2011.11.051
|
[34]
|
Shi, J., Guo, J.M. and Zheng, S.T. (2012) Evaluation of Hybrid Forecasting Approaches for Wind Speed and Power Generation Time Series. Renewable and Sustainable Energy Reviews, 16, 3471-3480.
http://dx.doi.org/10.1016/j.rser.2012.02.044
|
[35]
|
Guo, Z.H., Wu, J., Lu, H.Y. and Wang, J.Z. (2011) A Case Study on a Hybrid Wind Speed Forecasting Method Using BP Neural Network. Knowledge-Based Systems, 24, 1048-1056. http://dx.doi.org/10.1016/j.knosys.2011.04.019
|
[36]
|
Catalão, J.P.S., Pousinho, H.M.I. and Mendes, V.M.F. (2011) Short-Term Wind Power Forecasting in Portugal by Neural Networks and Wavelet Transform. Renewable Energy, 36, 1245-1251.
http://dx.doi.org/10.1016/j.renene.2010.09.016
|
[37]
|
Ernst, B., Oakleaf, B., Ahlstrom, M.L., Lange, M., Moehrlen, C., Lange, B., Focken, U. and Rohrig, K. (2007) Predicting the Wind. IEEE Power and Energy Magazine, 5, 78-89. http://dx.doi.org/10.1109/MPE.2007.906306
|
[38]
|
Foley, A.M., Leahy, P.G., Marvuglia, A. and McKeogh, E.J. (2012) Current Methods and Advances in Forecasting of Wind Power Generation. Renewable Energy, 37, 1-8. http://dx.doi.org/10.1016/j.renene.2011.05.033
|