Probabilistic load forecasting for the low voltage network : forecast fusion and daily peaks
Gilbert, Ciaran and Browell, Jethro and Stephen, Bruce (2023) Probabilistic load forecasting for the low voltage network : forecast fusion and daily peaks. Sustainable Energy, Grids and Networks, 34. 100998. ISSN 2352-4677 (https://doi.org/10.1016/j.segan.2023.100998)
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Abstract
Short-term forecasts of energy consumption are invaluable for operation of energy systems, including low voltage electricity networks. However, network loads are challenging to predict when highly desegregated to small numbers of customers, which may be dominated by individual behaviours rather than the smooth profiles associated with aggregate consumption. Furthermore, distribution networks are challenged almost entirely by peak loads, and tasks such as scheduling storage and/or demand flexibility maybe be driven by predicted peak demand, a feature that is often poorly characterised by general-purpose forecasting methods. Here we propose an approach to predict the timing and level of daily peak demand, and a data fusion procedure for combining conventional and peak forecasts to produce a general-purpose probabilistic forecast with improved performance during peaks. The proposed approach is demonstrated using real smart meter data and a hypothetical low voltage network hierarchy comprising feeders, secondary and primary substations. Fusing state-of-the-art probabilistic load forecasts with peak forecasts is found to improve performance overall, particularly at smart-meter and feeder levels and during peak hours, where improvement in terms of CRPS exceeds 10%.
ORCID iDs
Gilbert, Ciaran ORCID: https://orcid.org/0000-0001-6114-7880, Browell, Jethro and Stephen, Bruce ORCID: https://orcid.org/0000-0001-7502-8129;-
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Item type: Article ID code: 83875 Dates: DateEvent30 June 2023Published18 January 2023Published Online9 January 2023AcceptedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering > Production of electric energy or power
Technology > Electrical engineering. Electronics Nuclear engineering > Electrical apparatus and materials > Electric networksDepartment: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 26 Jan 2023 15:08 Last modified: 12 Dec 2024 14:15 URI: https://strathprints.strath.ac.uk/id/eprint/83875