Real-time estimates of Swiss electricity savings using streamed smart meter data
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Date
2025-01-01
Publication Type
Journal Article
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yes
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Abstract
The gas crisis of 2022 put pressure on electricity prices in Europe, prompting the Swiss government to launch a national energy-saving campaign. To effectively quantify potential savings and guide timely decision-making, this campaign called for rigorous near-real-time modeling of changes in electricity consumption habits. The proposed approach estimates national electricity consumption at an hourly resolution across three consumer categories using thousands of streamed smart-meter load curves. These curves are aggregated to produce a national consumption estimate using scaling factors that account for differences among Swiss distributors. These factors are derived by regressing historical annual consumption against public socio-economic variables. The obtained national load curve is adjusted for the influence of weather conditions, the calendar and global trends, in order to compare different periods with a reference scenario. Such external effects are modeled with splines using Generalized Additive Models, trained on a 5-year dataset, to precisely measure each contribution on the national consumption and evaluate the consumers’ response to the saving plan. The results indicate a reduction of approximately 4.8% of the adjusted electricity consumption during winter 2022–2023, equivalent to an average monthly savings of 246 GWh, distributed across residential, service, and industrial sectors.
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Publication status
published
Editor
Book title
Journal / series
Volume
377
Pages / Article No.
124537
Publisher
Elsevier
Event
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Energy policy; Energy saving; Smart meters; Generalised additive models
Organisational unit
09752 - McKenna, Russell / McKenna, Russell
02286 - Swiss Data Science Center (SDSC) / Swiss Data Science Center (SDSC)