Pattern-based local linear regression models for short-term load forecasting

Electric Power Systems Research

Volumn 130, Issue , 2016, Pages 139-147

  Dudek, Grzegorz ^a  

^a CZESTOCHOWA UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

Linear regression; Partial least squares regression; Patterns of seasonal cycles; Short term load forecasting; Time series

Indexed keywords

ELECTRIC POWER PLANT LOADS; FORECASTING; LEAST SQUARES APPROXIMATIONS; LINEAR REGRESSION; PRINCIPAL COMPONENT ANALYSIS; TIME SERIES;

APPLICATION EXAMPLES; EXPONENTIAL SMOOTHING; FORECASTING PROBLEMS; LOCAL LINEAR REGRESSION; PARTIAL LEAST SQUARES REGRESSION; PRINCIPAL COMPONENTS; SEASONAL CYCLE; SHORT TERM LOAD FORECASTING;

REGRESSION ANALYSIS;

EID: 84942163884     PISSN: 03787796     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.epsr.2015.09.001     Document Type: Article

References (29)

1. R. Weron Modeling and Forecasting Electricity Loads and Prices 2006 Wiley Chichester
2. J.W. Taylor, and R.D. Snyder Forecasting intraday data with multiple seasonal cycles using parsimonious seasonal exponential smoothing Omega 40 6 2012 748 757
3. J.W. Taylor Short-term load forecasting with exponentially weighted methods IEEE Trans. Power Syst. 27 1 2012 458 464
4. J. Nowicka-Zagrajek, and R. Weron Modeling electricity loads in California: ARMA models with hyperbolic noise Signal Process. 82 2002 1903 1915
5. C.-M. Lee, and C.-N. Ko Short-term load forecasting using lifting scheme and ARIMA models Expert Syst. Appl. 38 2011 5902 5911
6. H.S. Hippert, and J.W. Taylor An evaluation of Bayesian techniques for controlling model complexity and selecting inputs in a neural network for short-term load forecasting Neural Netw 23 2010 386 395
7. N. Amjady, and F. Keynia Short-term load forecasting of power systems by combination of wavelet transform and neuro-evolutionary algorithm Energy 34 2009 46 57
8. Y. Chen, P.B. Luh, C. Guan, Y. Zhao, L.D. Michel, M.A. Coolbeth, P.B. Friedland, and S.J. Rourke Short-term load forecasting: similar day-based wavelet neural networks IEEE Trans. Power Syst. 25 1 2010 322 330
9. Hao Quan, D. Srinivasan, and A. Khosravi Short-term load and wind power forecasting using neural network-based prediction intervals IEEE Trans. Neural Netw. Learn. Syst. 25 2 2014 303 315 10.1109/TNNLS.2013.2276053
10. Z. Yun, Z. Quan, S. Caixin, L. Shaolan, L. Yuming, and S. Yang RBF neural network and ANFIS-based short-term load forecasting approach in real-time price environment IEEE Trans. Power Syst. 23 3 2008 853 858
11. M. Hanmandlu, and B.K. Chauhan Load forecasting using hybrid models IEEE Trans. Power Syst. 26 1 2011 20 29
12. H. Mao, X.-J. Zeng, G. Leng, Y.-J. Zhai, and J.A. Keane Short-term and midterm load forecasting using a bilevel optimization model IEEE Trans. Power Syst. 24 2 2009 1080 1090
13. D.K. Chaturvedi, A.P. Sinha, and O.P. Malik Short term load forecast using fuzzy logic and wavelet transform integrated generalized neural network Int. J. Electr. Power Energy Syst. 67 2015 230 237
14. Q. Wu Power load forecasts based on hybrid PSO with Gaussian and adaptive mutation and Wv-SVM Expert Syst. Appl. 37 2010 194 201
15. E. Ceperic, V. Ceperic, and A. Baric A Strategy for short-term load forecasting by support vector regression machines IEEE Trans. Power Syst. 28 4 2013 4356 4364
16. M. De Felice Short-term load forecasting with neural network ensembles: a comparative study IEEE Comput. Intell. Mag. 6 3 2011 47 56
17. Rui Zhang, Zhao Yang Dong, Yan Xu, Ke Meng, and Kit Po Wong Short-term load forecasting of Australian National Electricity Market by an ensemble model of extreme learning machine IET Gener. Transm. Distrib. 7 4 2013 391 397
18. G. Dudek Artificial immune system for forecasting time series with multiple seasonal cycles Trans. Comput. Collec. Intell. XI LNCS 8065 2013 176 197
19. G. Dudek Pattern similarity-based methods for short-term load forecasting - Part 1: Principles Appl. Soft Comput. 37 2015 277 287 10.1016/j.asoc.2015.08.040 ISSN 1568-4946
20. S. Chatterjee, and A.S. Hali Regression Analysis by Example 2006 John Wiley & Sons, Inc. Hoboken, New Jersey
21. N. Draper, and H. Smith Applied Regression Analysis 1981 Wiley New York
22. T. Hastie, R. Tibshirani, and J. Friedman The Elements of Statistical Learning. Data Mining, Inference, and Prediction 2009 Springer-Verlag New York
23. R. Rosipal, and N. Kramer Overview and recent advances in partial least squares Subspace, Latent Structure and Feature Selection LNCS 3940 2006 Springer Berlin Heidelberg 34 51
24. R.J. Hyndman, A.B. Koehler, J.K. Ord, and R.D. Snyder Forecasting with Exponential Smoothing: The State Space Approach 2008 Springer, - Springer series in statistics Berlin/London
25. R.J. Hyndman, and Y. Khandakar Automatic time series forecasting: the forecast package for R J. Stat. Softw. 27 3 2008 1 22
26. G. Dudek Forecasting time series with multiple seasonal cycles using neural networks with local learning Artificial Intelligence and Soft Computing, ICAISC 2013, LNCS vol. 7894 2010 Springer Berlin Heidelberg 52 63
27. F.D. Foresee, and M.T. Hagan Gauss-Newton approximation to Bayesian regularization Proc. Inter. Joint Conference on Neural Networks 1997 1930 1935
28. G. Dudek Short-term load forecasting based on kernel conditional density estimation Przegl. Elektrotech. Electr. Rev. 86 8 2010 164 167
29. G. Dudek Pattern-Similarity Machine Learning Models for Short-Term Load Forecasting 2012 Academic Publishing House "Exit" Warsaw (in Polish)