4.6 Article

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

期刊

INTERNATIONAL JOURNAL OF FORECASTING
卷 24, 期 4, 页码 630-644

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ELSEVIER SCIENCE BV
DOI: 10.1016/j.ijforecast.2008.08.003

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Short-term load forecasting; Time series; Seasonality; Linear models; SARIMA; Time-series decomposition

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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. (C) 2008 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

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