Real-time estimates of Swiss electricity savings using streamed smart meter data

Alessandro Mari, Carl Remlinger, Roberto Castello, Guillaume Obozinski, Silvia Quarteroni, Fabian Heymann and Matthias Galus

Applied Energy, 2025, vol. 377, issue PC, No S0306261924019202

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.

Keywords: Energy policy; Energy saving; Smart meters; Generalised additive models (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.apenergy.2024.124537

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