Frequency domain methods applied to forecasting electricity markets

Energy Economics

Volumn 31, Issue 5, 2009, Pages 727-735

  Trapero, Juan R ^a   Pedregal, Diego J ^b  

^a LANCASTER UNIVERSITY   (United Kingdom)

^b UNIVERSITY OF CASTILLA LA MANCHA   (Spain)

Author keywords

Electricity markets; Forecasting; Frequency domain; State Space systems; Unobserved Components models

Indexed keywords

ARIMA MODELS; DIRECT USE; ELECTRICITY MARKET; ELECTRICITY MARKETS; FORECASTING ELECTRICITY; FREQUENCY DOMAIN; FREQUENCY DOMAINS; FREQUENCY-DOMAIN METHODS; HUMAN INTERVENTION; LOAD DEMAND; PJM INTERCONNECTION; SIGNAL EXTRACTION; STATE SPACE SYSTEMS; UNOBSERVED COMPONENTS MODELS;

COMMERCE; FEATURE EXTRACTION; FREQUENCY DOMAIN ANALYSIS; SIGNAL PROCESSING; TIME DOMAIN ANALYSIS; TIME SERIES;

ELECTRIC LOAD FORECASTING;

ELECTRICITY; ENERGY MARKET; FORECASTING METHOD; NUMERICAL MODEL; TIME SERIES ANALYSIS;

EID: 67650759743     PISSN: 01409883     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eneco.2009.03.002     Document Type: Article

References (34)

1. Abraham A., and Nath B. A neuro-fuzzy approach for modeling electricity demand in Victoria. Applied Sof Computing Journal 1 (2001) 127-138
2. Bryson A., and Ho Y. Applied Optimal Control, Optimization, Estimation and Control (1969), Blaisdell Publishing Company
3. Bujosa M., Garcia-Ferrer A., and Young P.C. Linear dynamic harmonic regression. Computational Statistics & Data Analysis 52 (2007) 999-1024
4. Cancelo J.R., Espasa A., and Grafe R. Forecasting the electricity load from one day to one week ahead for the Spanish system operator. International Journal of Forecasting (2008) 10.1016/j.ijforecast.2008.07.005
5. Conejo A., Contreras J., Espínola R., and Plazas M. Forecasting electricity prices for a day-ahead pool-based electricity energy market. International Journal of Forecasting 21 (2005) 435-462
6. Conejo A., Plazas M., Espínola R., and Molina A. Day-ahead electricity price forecasting using the wavelet transform and ARIMA models. IEEE Transactions on Power Systems 20 2 (2005) 1035-1042
7. Darbellay G., and Slama M. Forecasting the short-term demand for electricity-do neural networks stad a better chance?. International Journal of Forecasting 16 (2000) 71-83
8. Dordonnat V., Koopman S., Ooms M., Dessertaine A., and Collet J. An hourly periodic state space model for modelling French national electricity load. International Journal of Forecasting (2008) 10.1016/j.ijforecast.2008.08.010
9. Fan Y., Liang Q., and Wei Y.M. A generalized pattern matching approach for multi-step prediction of crude oil price. Energy Ecomics 30 (2008) 889-904
10. Gómez V., and Maravall A. Automatic Modelling Methods for Univariate Series (2001), J. Wiley and Sons, New York 202-246 Ch. 7
11. González-Romera E., Jaramillo-Moran M., and Carmona-Fernández D. Monthly electric energy demand forecasting based on trend extraction. IEEE Transactions on Power Systems 21 4 (2006) 1946-1953
12. Harvey A. Forecasting Structural Time Series Models and the Kalman Filter (1989), Cambridge University Press
13. Harvey A.C., and Koopman S.J. Forecasting hourly electricity demand using time-varying splines. Journal of the American Statistical Association 88 (1993) 1228-1242
14. Kalman R.E. A new approach to linear filtering and prediction problems. ASME Transactions. Journal Basic Engineering 83-D (1960) 95-108
15. Kay S., and Marple S. Spectral Analysis, A Modern Perspective. Proc. IEEE vol. 69 (1981) 1380-1419
16. Knittel C.R., and Roberts M.R. An empirical examination of restructured electricity prices. Energy economics 27 (2005) 791-817
17. Li G., Liu C.C., Lawarree J., Gallanti M., and Venturini A. State-of-the-art of electricity price forecasting. Proc. 2nd CIGRE/IEEE Power Eng. Soc. Int. Symp., San Antonio, TX, Oct. 5-7 (2005)
18. Ljung G.M., and Box G.E.P. On a measure of lack of fit in time series models. Biometrika 65 (1978) 297-303
19. Metaxiotis K., Kagiannas A., Askounis D., and Psarras J. Artificial intelligence in short term electric load forecasting: a state-of-the-art survey for the researcher. Energy Conversion and Management 44 (2003) 1525-1534
20. Nogales F., Contreras J., Conejo A., and Espínola R. Forecasting next-day electricity prices by time series models. IEEE Transactions on Power Systems 17 2 (2002) 342-348
21. Pardo A., Meneu V., and Valor E. Temperature and seasonality influences on Spanish electricity load. Energy Economics 24 (2002) 55-70
22. Pedregal D., and Young P. Modulated cycles, a new approach to modelling seasonal/cyclical behaviour in unobserved component models. International Journal of Forecasting 22 (2006) 189-194
23. Pedregal D.J., and Young P.C. Statistical approaches to modelling and forecasting time series. Companion to Economic Forecasting Blackwell Publishers, Ch. 4 (2002) 69-104
24. Schwartz G. Estimating the dimension of a model. Annals of Statistics 6 (1978) 461-464
25. Shahidehpour M., Yamin H., and Li Z. Market Operations in Electric Power Systems: Forecasting, Scheduling, and Risk Management (2002), John Wiley and Sons, New York
26. Sheblé G.B. Computational Auction Mechanisms for Restructured Power Industry Operation (1999), Kluwer, Norwell, MA
27. Song K., Ha S., Park J., Kweon D., and Kim K. Hybrid load forecasting method with analysis of temperature sensitivities. IEEE Transactions on Power Systems 21 2 (2006) 869-876
28. Taylor C.J., Pedregal D.J., Young P.C., and Tych W. Environmental time series analysis and forecasting with the captain toolbox. Enviromental Modelling & Software 22 6 (2007) 797-814
29. Taylor J., and Buizza R. Using weather ensemble predictions in electricity demand forecasting. International Journal of Forecasting 19 1 (2003) 57-70
30. Taylor J., Menezes L., and McSharry P. A comparison of univariate methods for forecasting electricity demand up to a day ahead. International Journal of Forecasting 22 (2006) 1-16
31. West M., and Harrison J. Bayesian Forecasting and Dynamic Models (1989), Springer-Verlag
32. Young P., Pedregal D., and Tych W. Dynamic harmonic regression. Journal of Forecasting 18 (1999) 369-394
33. Zhang L., Luh P., and Kasiviswanathan K. Energy clearing price prediction and confidence interval estimation with cascaded neural networks. IEEE Transactions on Power Systems 18 1 (2003) 99-105
34. Zhou M., Yan Z., Ni Y., Li G., and Nie Y. Electricity price forecasting with confidence-interval estimation through an extended ARIMA approach. Generation, Transmission and Distribution 153 (2006) 187-195