Abstract
The problem of residual demand prediction in electricity spot markets is considered in this paper. Hourly residual demand curves are predicted using nonparametric regressionwith functional explanatory and functional response variables. Semi-functional partial linear models are also used in this context. Forecasted values of wind energy as well as hourly price and demand are considered as linear predictors. Results from the electricity market of mainland Spain are reported. The new forecasting functional methods are compared with a naive approach.
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Aneiros-P´erez, G., Cao, R., Vilar-Fern´andez, J.M.: Functional methods for time series prediction: a nonparametric approach. To appear in Journal of Forecasting (2010)
Aneiros-P´erez, G., Vieu, P.: Semi-functional partial linear regression. Statist. Probab. Lett. 76, 1102–1110 (2006)
Aneiros-P´erez, G., Vieu, P.: Nonparametric time series prediction: A semi-functional partial linear modeling. J. Multivariate Anal. 99, 834–857 (2008)
Antoniadis, A., Paparoditis, E., Sapatinas, T.: A functional waveletkernel approach for time series prediction. J. Roy. Statist. Soc. Ser. B 68, 837–857 (2006)
Antoniadis, A., Paparoditis, E., Sapatinas, T.: Bandwidth selection for functional time series prediction. Statist. Probab. Lett. 79, 733–740 (2009)
Antoch, J., Prchal, L., De Rosa, M.R., Sarda, P. (2008). Functional linear regression with functional response: application to prediction of elecricity cosumption. In: Dabo-Niang, S., Ferraty, F. (eds.) Functional and Operatorial Statistics, pp. 23-29. Physica-Verlag, Heidelberg (2008)
Baillo, A., Ventosa, M., Rivier, M., Ramos, A.: Optimal Offering Strategies for Generation Companies Operating in Electricity Spot Markets. IEEE Transactions on Power Systems 19, 745–753 (2004)
Bosq, D.: Linear Processes in Function Spaces: Theory and Applications. Lecture Notes in Statistics, 149, Springer (2000)
Carbon, M., Delecroix, M.: Nonparametric vs parametric forecasting in time series: a computational point of view. Applied Stochastic Models and Data Analysis 9, 215–229 (1993)
Cardot, H., Dessertaine, A., Josserand E.: Semiparametric models with functional responses in a model assisted survey sampling setting. Presented at COMPSTAT 2010 (2010)
Faraway, J.: Regression analysis for a functional reponse. Technometrics 39, 254–261 (1997) 12. Ferraty, F. and Vieu, P.: Nonparametric Functional Data Analysis. Series in Statistics, Springer, New York (2006)
Gross, G., Galiana, F.D.: Short-term load forecasting. Proc. IEEE 75, 1558–1573 (1987) 14. H¨ardle, W., L¨utkepohl, H., Chen, R.: A review of nonparametric time series analysis. International Statistical Review 65, 49–72 (1997)
H¨ardle, W., Vieu, P.: Kernel regression smoothing of time series. J. Time Ser. Anal.13, 209– 232 (1992)
Hart, J. D.: Some automated methods of smoothing time-dependent data. J. Nonparametr. Stat. 6, 115–142 (1996)
Matzner-Lober, E., Gannoun, A., De Gooijer, J. G.: Nonparametric forecasting: a comparison of three kernel based methods. Commun. Stat.-Theor. M.27, 1593–1617 (1998)
Nadaraya, E. A.: On Estimating Regression. Theor. Probab. Appl. 9, 141–142 (1964)
Vilar-Fern´andez, J.M., Cao, R.: Nonparametric forecasting in time series – A comparative study. Commun. Stat. Simulat. C. 36, 311–334 (2007)
Vilar-Fern´andez, J.M., Cao, R., Aneiros-P´erez, G.: Forecasting next-day electricity demand and price using nonparametric functional methods. Preprint (2010)
Watson, G.S.: Smooth regression analysis. Sankhy¯a Ser. A26, 359–372 (1964)
Xu, L., and Baldick, R.: Transmission-constrained residual demand derivative in electricity markets. IEEE Transactions on Power Systems 22, 1563–1573 (2007)
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Aneiros, G., Cao, R., Vilar-Fernández, J.M., Muñoz-San-Roque, A. (2011). Functional Prediction for the Residual Demand in Electricity Spot Markets. In: Ferraty, F. (eds) Recent Advances in Functional Data Analysis and Related Topics. Contributions to Statistics. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2736-1_2
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DOI: https://doi.org/10.1007/978-3-7908-2736-1_2
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