Electricity demand loads modeling using AutoRegressive Moving Average (ARMA) models

S.Sp. Pappas, L. Ekonomou, D.Ch. Karamousantas, G.E. Chatzarakis, S.K. Katsikas and P. Liatsis

Energy, 2008, vol. 33, issue 9, 1353-1360

Abstract: This study addresses the problem of modeling the electricity demand loads in Greece. The provided actual load data is deseasonilized and an AutoRegressive Moving Average (ARMA) model is fitted on the data off-line, using the Akaike Corrected Information Criterion (AICC). The developed model fits the data in a successful manner. Difficulties occur when the provided data includes noise or errors and also when an on-line/adaptive modeling is required. In both cases and under the assumption that the provided data can be represented by an ARMA model, simultaneous order and parameter estimation of ARMA models under the presence of noise are performed. The produced results indicate that the proposed method, which is based on the multi-model partitioning theory, tackles successfully the studied problem. For validation purposes the produced results are compared with three other established order selection criteria, namely AICC, Akaike's Information Criterion (AIC) and Schwarz's Bayesian Information Criterion (BIC). The developed model could be useful in the studies that concern electricity consumption and electricity prices forecasts.

Keywords: Adaptive multi-model filtering; Electricity demand load; ARMA; Order selection; Parameter estimation; Kalman filter (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (81)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:33:y:2008:i:9:p:1353-1360

DOI: 10.1016/j.energy.2008.05.008

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