Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/54372
Title: Avaliação da capacidade preditiva de modelos ARIMA e VAR-VEC: o caso da demanda por energia elétrica no Rio Grande do Sul
Other Titles: Evaluation of the predictive capacity of ARIMA and VAR-VEC models: the case of electricity demand in Rio Grande do Sul
Keywords: Séries temporais
Modelo Box-Jenkins
Modelo de vetores autorregressivos
Modelo de correção de erros vetoriais
Time series
Box-Jenkins model
Autoregressive vector model
Error correction vector model
Issue Date: 2022
Publisher: Universidade Nove de Julho (UNINOVE)
Citation: NUNES, G. dos S. et al. Avaliação da capacidade preditiva de modelos ARIMA e VAR-VEC: o caso da demanda por energia elétrica no Rio Grande do Sul. Exacta, [S.l.], v. 20, n. 2, p. 307-335, abr./jun. 2022. DOI: 10.5585/exactaep.2021.17357.
Abstract: This paper presents the modelling of electricity demand in State of Rio Grande do Sul for the three main consumer sectors: residential, commercial and industrial, through the autoregressive vector model, complemented by the error correction vector model. In this approach, we also considered information regarding energy tariff, GDP, appliances and electrical material and equipment prices. The predictive capacity of all fitted models was compared to the Box-Jenkins framework, specifically, with the autoregressive integrated moving average (ARIMA) models. All models were fitted using data from 1971 to 2010, and their validation were performed from 2011 up to 2017. In general, for all three consumer sections, the best predictive capacity was returned by the ARIMA models. Nevertheless, the other models performed better on one-step-ahead predictions.
URI: http://repositorio.ufla.br/jspui/handle/1/54372
Appears in Collections:DES - Artigos publicados em periódicos



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