Modelling the Load Curve of Aggregate Electricity Consumption Using Principal Components

Matteo Manera () and Angelo Marzullo
Additional contact information
Angelo Marzullo: Enifin, Eni S.p.A., Milano, Italy

No 2003.95, Working Papers from Fondazione Eni Enrico Mattei

Abstract: Since oil is a non-renewable resource with a high environmental impact, and its most common use is to produce combustibles for electricity, reliable methods for modelling electricity consumption can contribute to a more rational employment of this hydrocarbon fuel. In this paper we apply the Principal Components (PC) method to modelling the load curves of Italy, France and Greece on hourly data of aggregate electricity consumption. The empirical results obtained with the PC approach are compared with those produced by the Fourier and constrained smoothing spline estimators. The PC method represents a much simpler and attractive alternative to modelling electricity consumption since it is extremely easy to compute, it significantly reduces the number of variables to be considered, and generally increases the accuracy of electricity consumption forecasts. As an additional advantage, the PC method is able to accommodate relevant exogenous variables such as daily temperature and environmental factors, and it is extremely versatile in computing out-of-sample forecasts.

Keywords: Electricity; Load curves; Principal components; Fourier estimator; Constrained smoothing estimator; Temperature; Non-renewable resources; Hydrocarbon fuels; Environment (search for similar items in EconPapers)
JEL-codes: C51 C53 Q30 Q40 (search for similar items in EconPapers)
Date: 2003-10
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://feem-media.s3.eu-central-1.amazonaws.com/w ... oads/NDL2003-095.pdf (application/pdf)

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:fem:femwpa:2003.95

Access Statistics for this paper

More papers in Working Papers from Fondazione Eni Enrico Mattei Contact information at EDIRC.
Bibliographic data for series maintained by Alberto Prina Cerai ( this e-mail address is bad, please contact ).