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Short-Term Load Forecasting: Revising How Good We Actually Are
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Title: Short-Term Load Forecasting: Revising How Good We Actually Are |
Authors: López García, Miguel VALERO, SERGIO Senabre, Carolina Gabaldon, Antonio |
Editor: IEEE |
Department: Departamentos de la UMH::Ingeniería Mecánica y Energía |
Issue Date: 2012 |
URI: https://hdl.handle.net/11000/34437 |
Abstract:
This paper proposes the use of an indicator of the
predictability of the load series along with an accuracy value
such as Mean Average Percentage Error as standard measures of
load forecasting performance. Over the last 10 years, there has
been a significant increase in load forecasting models proposed in
engineering journals. Most of these models provide a description
of the inner design of the model, the results from applying this
model to a specific data base and the conclusions drawn from this
application. However, a single accuracy value may not be
sufficient to describe the performance of the model when applied
to other data bases. The aim of this paper is to provide
researchers with a tool that is able to assess the predictability of a
load series and, therefore, contextualize the forecasting accuracy
reported. Thirteen different data bases were used to determine
its validity.
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Keywords/Subjects: Forecasting power demand performance evaluation frequency domain analysis |
Knowledge area: CDU: Ciencias aplicadas: Ingeniería. Tecnología: Ingeniería mecánica en general. Tecnología nuclear. Electrotecnia. Maquinaria |
Type of document: info:eu-repo/semantics/conferenceObject |
Access rights: info:eu-repo/semantics/closedAccess |
DOI: http://dx.doi.org/10.1109/PESGM.2012.6345392 |
Appears in Collections: Congresos, ponencias y comunicaciones
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