Short-term wind power forecasting using adaptive neuro-fuzzy inference system combined with evolutionary particle swarm optimization, wavelet transform and mutual information
Tài liệu tham khảo
Haque, 2012, A new strategy for prediction short-term wind speed soft computing models, Renew Sustain Energy Rev, 16, 4563, 10.1016/j.rser.2012.05.042
Zhao, 2011, Performance evaluation and accuracy enhancement of a day-ahead wind power forecasting in China, Renew Energy, 43, 234, 10.1016/j.renene.2011.11.051
Skittides, 2014, Wind forecasting using principal component analysis, Renew Energy, 69, 365, 10.1016/j.renene.2014.03.068
Foley, 2012, Current methods and advances in forecasting of wind power generation, Renew Energy, 37, 1, 10.1016/j.renene.2011.05.033
Amjady, 2011, Short-term wind power forecasting using ridgelet neural network, Electr Power Syst Res, 81, 2099, 10.1016/j.epsr.2011.08.007
Khalid, 2012, A method for short-term wind power prediction with multiple observation points, IEEE Trans Power Syst, 27, 579, 10.1109/TPWRS.2011.2160295
Colak, 2012, Data mining and wind power prediction: a literature review, Renew Energy, 46, 241, 10.1016/j.renene.2012.02.015
Mandal, 2014, Forecasting aggregated wind power production of multiple wind farms using hybrid wavelet-PSO-NNs, Int J Energy Res, 38, 1654, 10.1002/er.3171
Haque, 2013, A novel hybrid approach based on wavelet transform and fuzzy ARTMAP networks for predicting wind farm power production, IEEE Trans Ind Appl, 49, 2253, 10.1109/TIA.2013.2262452
Sideratos, 2012, Wind power forecasting focused on extreme power system events, IEEE Trans Sustain Energy, 3, 445, 10.1109/TSTE.2012.2189442
Botterud, 2012, Wind power trading under uncertainty in LMP markets, IEEE Trans Power Syst, 27, 894, 10.1109/TPWRS.2011.2170442
Albadi, 2010, Overview of wind power intermittency impacts on power systems, Elect Power Syst Res, 80, 627, 10.1016/j.epsr.2009.10.035
Liu, 2013, Short-term wind speed forecasting using wavelet transform and support vector machines optimized by genetic algorithm, Renew Energy, 62, 592, 10.1016/j.renene.2013.08.011
Shi, 2014, Hybrid forecasting model for very-short term wind power forecasting based on grey relational analysis and wind speed distribution features, IEEE Trans Smart Grid, 5, 521, 10.1109/TSG.2013.2283269
The National Energy Strategy 2020 for Portugal–ENE2020. [English Version]. http://www.renewable.pt/en/.
Sideratos, 2012, Probabilistic wind power forecasting using radial basis function neural network, IEEE Trans Power Syst, 27, 1788, 10.1109/TPWRS.2012.2187803
Wan, 2014, Optimal prediction intervals of wind power generation, IEEE Trans Power Syst, 29, 1166, 10.1109/TPWRS.2013.2288100
Liu, 2012, Short-term wind-power prediction based on wavelet transform-support vector machine and statistic-characteristics analysis, IEEE Trans Ind Appl, 48, 1136, 10.1109/TIA.2012.2199449
Catalão, 2011, Hybrid intelligent approach for short–term wind power forecasting in Portugal, IET Renew Power Gener, 5, 251, 10.1049/iet-rpg.2009.0155
Peng, 2012, A hybrid strategy of short term wind power prediction, Renew Energy, 50, 590, 10.1016/j.renene.2012.07.022
Costa, 2008, A review of the young history of wind power short-term prediction, Renew Sustain Energy Rev, 12, 1725, 10.1016/j.rser.2007.01.015
Wang, 2011, A review of wind power forecasting models, Energy Proc, 12, 770, 10.1016/j.egypro.2011.10.103
Amjady, 2011, Wind power prediction by a new forecast engine composed of modified hybrid neural network and enhanced particle swarm optimization, IEEE Trans Sustain Energy, 2, 265, 10.1109/TSTE.2011.2114680
Togelou, 2012, Wind power forecasting in the absence of historical data, IEEE Trans Sustain Energy, 3, 416, 10.1109/TSTE.2012.2188049
Prasad, 2009, Some of the design and methodology considerations in wind resource assessment, IET Renew Power Gener, 3, 53, 10.1049/iet-rpg:20080030
Ma, 2009, A review on the forecasting of wind speed and generated power, Renew Sustain Energy Rev, 13, 915, 10.1016/j.rser.2008.02.002
Kavassery, 2009, Day-ahead wind speed forecasting using f-ARIMA models, Renew Energy, 34, 1388, 10.1016/j.renene.2008.09.006
Nielsen, 1998, A new reference for wind power forecasting, Wind Energy, 1, 29, 10.1002/(SICI)1099-1824(199809)1:1<29::AID-WE10>3.0.CO;2-B
Catalão, 2009, An artificial neural network approach for short-term wind power forecasting in Portugal, Eng Intell Syst Electr Eng Commun, 17, 5
Rosado, 2009, Comparison of two new short-term wind-power forecasting systems, Renew Energy, 34, 1848, 10.1016/j.renene.2008.11.014
Catalão, 2011, Short-term wind power forecasting in Portugal by neural network and wavelet transform, Renew Energy, 36, 1245, 10.1016/j.renene.2010.09.016
Bhaskar, 2012, AWNN-assisted wind power forecasting using feed-forward neural network, IEEE Trans Sustain Energy, 3, 306, 10.1109/TSTE.2011.2182215
Pousinho, 2011, Application of adaptive neuro-fuzzy inference for wind power short–term forecasting, IEEJ Trans Elect Electr Eng, 6, 571, 10.1002/tee.20697
Sideratos, 2007, An advanced statistical method for wind power forecasting, IEEE Trans Power Syst, 22, 258, 10.1109/TPWRS.2006.889078
Jursa, 2008, Short-term wind power forecasting using evolutionary algorithms for the automated specification of artificial intelligence models, Int J. Forecast, 24, 694, 10.1016/j.ijforecast.2008.08.007
Catalão, 2011, Hybrid Wavelet-PSO-ANFIS approach for short-term wind power forecasting in Portugal, IEEE Trans Sustain Energy, 2, 50
Amjady, 2010, Electricity market price spike analysis by a hybrid data model and feature selection technique, Electr Power Syst Res, 80, 318, 10.1016/j.epsr.2009.09.015
Amjady, 2009, Design of input vector for day-ahead price forecasting of electricity markets, Expert Syst Appl, 36, 12281, 10.1016/j.eswa.2009.04.059
Wang, 2006, Short-term load forecasting based on mutual information and artificial neural network, Adv Neural Networks, 3972, 1246
Amjady, 2009, Day-ahead price forecasting of electricity markets by mutual information technique and cascaded neuro-evolutionary algorithm, IEEE Trans Power Syst, 24, 306, 10.1109/TPWRS.2008.2006997
Cai, 2009, An efficient gene selection algorithm based on mutual information, Neurocomputing, 72, 991, 10.1016/j.neucom.2008.04.005
Eynard, 2011, Wavelet-based multi-resolution analysis and artificial neural networks, for forecasting temperature and thermal power consumption, Eng Appl Art Intell, 24, 501, 10.1016/j.engappai.2010.09.003
Prakash, 2011, Disturbance detection in grid-connected distributed generation system using wavelet transform and S-transform, Electr Power Syst Res, 81, 805, 10.1016/j.epsr.2010.11.011
Amjady, 2009, Short-term loads forecasting of power systems by combining wavelet transform and neuro-evolutionary algorithm, Energy, 34, 46, 10.1016/j.energy.2008.09.020
Miranda, 2006, New experiments with EPSO-evolutionary particle swarm optimization, 162
Chen, 2008, An evolutionary particle swarm algorithm for multi-objective optimization”, 3269
Abdelhalim, 2007, Hardware software partitioning using particle swarm optimization technique, 189
Miranda, 2009, Improving power system reliability calculation efficiency with EPSO variants, IEEE Trans Power Syst, 24, 1772, 10.1109/TPWRS.2009.2030397
Yun, 2008, RBF neural network and ANFIS-based short-term load forecasting approach in real-time price environment, IEEE Trans Power Syst, 23, 853, 10.1109/TPWRS.2008.922249
Jang, 1993, ANFIS: adaptive-network-based fuzzy inference system, IEEE Trans Syst Man Cybern, 23, 665, 10.1109/21.256541
REN Web Site. http://www.ren.pt. [Portuguese version]. 2014.
Giebel, 2007
Emst, 2010
