Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Forecasting hourly electricity demand in Spain using a revised version of the Cancelo Espasa Model
Year:2017
Research Areas
  • Engineering,
  • Information technology and adata processing,
  • Electric engineers, electronic and automatic (eil)
Information
Abstract
The management of an electrical system requires knowing the energy demand well in advance. A common practice is to model the hourly time series of electricity demand. The strong daily seasonality has led many authors to estimate a different model for each hour of the day. This article presents a new approach that assembles the 24 hourly series in a periodic autoregressive moving-average model. The identification and estimation of a periodic model of order 24 presents enormous complexity. In this paper we present a theoretical result that greatly simplifies this task. The paper presents an original method of estimating the periodic model that takes advantage of the existing implementation of estimating univariate ARIMA models and describes their application in the prediction of the next hours. The new methodology includes two additional contributions: (1) a very exhaustive and complex intervention system that allows the reduction of prediction errors occurring during non-working days, and (2) a meticulous model of the non-linear temperature effect using regression spline techniques. The method is currently being used by the Spanish System Operator (\emph{Red El\'{e}ctrica de Espa\~{n}a}, REE) to make hourly forecasts of electricity demand from one to ten days ahead.
International
Si
Congress
20th IIF Workshop | Predictive Energy Analytics in the Big Data World Cairns, Australia 22-23 June 2017
960
Place
Cairns, Australia
Reviewers
Si
ISBN/ISSN
0000-0000
Start Date
22/06/2017
End Date
23/06/2017
From page
1
To page
37
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Participants
  • Autor: Eduardo Caro Huertas (UPM)
  • Autor: Jesus Juan Ruiz (UPM)
  • Autor: Francisco Javier Cara Cañas (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Estadística computacional y Modelado estocástico
  • Departamento: Ingeniería de Organización, Administración de Empresas y Estadística
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