GEFCom2012: Electric load forecasting and backcasting with semi-parametric models

Raphael Nedellec, Jairo Cugliari and Yannig Goude

International Journal of Forecasting, 2014, vol. 30, issue 2, 375-381

Abstract: We sum up the methodology of the team tololo for the Global Energy Forecasting Competition 2012: Load Forecasting. Our strategy consisted of a temporal multi-scale model that combines three components. The first component was a long term trend estimated by means of non-parametric smoothing. The second was a medium term component describing the sensitivity of the electricity demand to the temperature at each time step. We use a generalized additive model to fit this component, using calendar information as well. Finally, a short term component models local behaviours. As the factors that drive this component are unknown, we use a random forest model to estimate it.

Keywords: Demand forecasting; Forecasting competitions; Multivariate time series; Nonlinear time series; Regression (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (25)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0169207013000800
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:30:y:2014:i:2:p:375-381

DOI: 10.1016/j.ijforecast.2013.07.004

Access Statistics for this article

International Journal of Forecasting is currently edited by R. J. Hyndman

More articles in International Journal of Forecasting from Elsevier
Bibliographic data for series maintained by Catherine Liu ().