 Daily peak electrical load forecasting with a multi-resolution approachYvenn Amara-Ouali, Matteo Fasiolo, Yannig Goude and Hui Yan International Journal of Forecasting, 2023, vol. 39, issue 3, 1272-1286 Abstract: In the context of smart grids and load balancing, daily peak load forecasting has become a critical activity for stakeholders in the energy industry. An understanding of peak magnitude and timing is paramount for the implementation of smart grid strategies such as peak shaving. The modelling approach proposed in this paper leverages high-resolution and low-resolution information to forecast daily peak demand size and timing. The resulting multi-resolution modelling framework can be adapted to different model classes. The key contributions of this paper are (a) a general and formal introduction to the multi-resolution modelling approach, (b) a discussion of modelling approaches at different resolutions implemented via generalised additive models and neural networks, and (c) experimental results on real data from the UK electricity market. The results confirm that the predictive performance of the proposed modelling approach is competitive with that of low- and high-resolution alternatives. Keywords: Generalised additive models; Neural networks; Peak load forecasting; Smart grids; Automated feature engineering; Multi-resolution (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:39:y:2023:i:3:p:1272-1286 DOI: 10.1016/j.ijforecast.2022.06.001 Access Statistics for this article International Journal of Forecasting is currently edited by R. J. Hyndman More articles in International Journal of Forecasting from Elsevier |
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