Functional Autoregressive Models: An Application to Brazilian Hourly Electricity Load

Lucélia Viviane Vaz and Getulio Borges da Silveira Filho

Brazilian Review of Econometrics, 2017, vol. 37, issue 2

Abstract: The features of the electrical demand and its response to climate variables impose three main features to the load curves: (1) strong inertia, (2) Each observation is a function and (3) cyclical movements. Based on that, we present a generalization of periodic autoregressive models for functional data with functional covariates. We also estimate a functional autoregressive model, where the periodicity of the parameters is induced by harmonic acceleration operators. Using this method, we handle annual load curves, while the first takes into account the daily load curves. We use splines to represent the smooth functions underlying the points. The estimators of the parameters embody the smoothness restrictions enforced on load curves. We compare the Root Mean Squared Error (RMSE) of our models with the RMSE of a benchmark model. We apply this framework to a dataset from the Southeast/Midwest Brazilian Interconnected Power System, from 2003/01/01 to 2011/01/20.

Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://periodicos.fgv.br/bre/article/view/62293 (text/html)

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:sbe:breart:v:37:y:2017:i:2:a:62293

Access Statistics for this article

Brazilian Review of Econometrics is currently edited by Daniel Monte

More articles in Brazilian Review of Econometrics from Sociedade Brasileira de Econometria - SBE Contact information at EDIRC.
Bibliographic data for series maintained by Núcleo de Computação da FGV EPGE ().