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Short-term load forecasting

Gross, G., Galiana, F.D.·1987·Proceedings of the IEEE

Abstract

This paper discusses the state of the art in short-term load forecasting (STLF), that is, the prediction of the system load over an interval ranging from one hour to one week. The paper reviews the important role of STLF in the on-line scheduling and security functions of an energy management system (EMS). It then discusses the nature of the load and the different factors influencing its behavior. A detailed classification of the types of load modeling and forecasting techniques is presented. Whenever appropriate, the classification is accompanied by recommendations and by references to the literature which support or expand the discussion. The paper also presents a lengthy discussion of practical aspects for the development and usage of STLF models and packages. The annotated bibliography offers a representative selection of the principal publications in the STLF area.

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Metadata

Authors
Gross, G., & Galiana, F. D.
Venue
Proceedings of the IEEE
Published
1987
Volume
75
Issue
12
Pages
1558-1573
ISSN
0018-9219 (ISSN-L)
OpenAlex
W2067576900
Cited by
878
References
0
FWCI
6.65
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Short-term load forecasting. https://app.cochat.ai/papers/10.1109/proc.1987.13927
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Gross, G., & Galiana, F. D. (1987). Short-term load forecasting. Proceedings of the IEEE. https://doi.org/10.1109/proc.1987.13927

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.