Técnicas Big Data para la predicción de la demanda y precio eléctrico
- Laura Melgar García 1
- José Francisco Torres Maldonado 2
- Alicia Troncoso 2
- José Cristóbal Riquelme Santos 3
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1
Universidad IE
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2
Universidad Pablo de Olavide
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3
Universidad de Sevilla
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ISSN: 0422-2784
Year of publication: 2024
Issue Title: Digitalización y electrificación
Issue: 431
Pages: 119-130
Type: Article
More publications in: Economía industrial
Sustainable development goals
Abstract
Electricity demand forecasting is a fundamental component of supply chain planning in the energy sector, in the stages of generation, storage and distribution of energy. Storing electricity is a challenge, so the balance between electricity demand and supply is continuously being sought. This makes the electricity price market volatile and difficult to predict. In this paper, several Big Data prediction techniques for electricity demand and price data in Spain are proposed with the main objective of improving the efficiency of the supply chain management. Specifically, this research addresses these problems by making use of Machine Learning and Deep Learning models. The performance results demonstrate the good behavior of the models.
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