Work

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

Year: 2024

Type: article

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. • Swiss electricity demand is estimated from load curves and public socioeconomic data. • A 4.8% energy saving in winter 2022 is observed compared to the pre-COVID-19 period. • Model reveals differences in the savings behavior of three consumer groups over time. • The method enables real-time monitoring and savings opportunities for practitioners. • The scaling method can be easily adapted for use in different regions or countries.

Source: Applied Energy

DOI: 10.1016/j.apenergy.2024.124537