Forecasting quantiles of day-ahead electricity load
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Description
Accurate load forecasting plays a crucial role in the decision making process of many market participants, but probably is most important for the dispatch planning of an electricity market operator. Despite the competitive forecast accuracy achieved by existing point forecast models, point forecasts can only provide limited information relating to the expected level of future load. To account for the uncertainty of future load, and provide a more complete picture of the future load conditions for dispatch planning purposes, quantile forecasts can be useful. This paper proposes a computationally efficient approach to forecasting the quantiles of electricity load, which is then applied to forecasting in the National Electricity Market of Australia. The proposed model performs competitively in comparison with one industry standard and two recently proposed quantile forecasting methods. One of the main advantages of the proposed approach is the ease with the number of covariates can be expanded. This is a particularly important feature in the context of load forecasting where large numbers of important drivers are usually necessary to provide accurate load forecasts.
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ID Code: | 118702 | ||||
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Item Type: | Contribution to Journal (Journal Article) | ||||
Refereed: | Yes | ||||
ORCID iD: |
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Measurements or Duration: | 12 pages | ||||
Keywords: | Bayesian quantile regression, Load forecasting, Quantile forecasts | ||||
DOI: | 10.1016/j.eneco.2017.08.002 | ||||
ISSN: | 0140-9883 | ||||
Pure ID: | 33282605 | ||||
Divisions: | Past > QUT Faculties & Divisions > QUT Business School Current > Schools > School of Economics & Finance |
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Copyright Owner: | Consult author(s) regarding copyright matters | ||||
Copyright Statement: | This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au | ||||
Deposited On: | 06 Jun 2018 03:20 | ||||
Last Modified: | 20 Jun 2024 18:03 |
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