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Modeling and forecasting short-term electricity load: A comparison of methods with an application to Brazilian data

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Author Info
Soares, Lacir J.
Medeiros, Marcelo C.

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Abstract

The goal of this paper is to describe a forecasting model for the hourly electricity load in the area covered by an electric utility located in the southeast of Brazil. A different model is constructed for each hour of the day. Each model is based on a decomposition of the daily series of each hour in two components. The first component is purely deterministic and is related to trends, seasonality, and the special days effect. The second is stochastic, and follows a linear autoregressive model. Nonlinear alternatives are also considered in the second step. The multi-step forecasting performance of the proposed methodology is compared with that of a benchmark model, and the results indicate that our proposal is useful for electricity load forecasting in tropical environments.

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File URL: http://www.sciencedirect.com/science/article/B6V92-4TK2P6R-1/2/0e5855e8a3a9e634fa4700b8e2414113
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Publisher Info
Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 24 (2008)
Issue (Month): 4 ()
Pages: 630-644
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Handle: RePEc:eee:intfor:v:24:y:2008:i:4:p:630-644

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Web page: http://www.elsevier.com/locate/ijforecast

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Related research
Keywords: Short-term load forecasting Time series Seasonality Linear models SARIMA Time-series decomposition;

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This page was last updated on 2009-12-3.


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