Modelling Fluctuations of Electricity Consumption

Christian Beck (together with international collaborators) is analysing measured data for electricity consumption in households (as well as frequency fluctuations in power grids), and constructing stochastic models that can be used to estimate demand trends and fluctuations in the consumer pattern, ultimately enabling a better prediction of electricity demand patterns on various time scales. This can be used to avoid switching on ‘dirty’ power stations at periods of high demand, and in the long-term these types of data-driven forecasting methods for demand patterns can help to reduce the carbon footprint.

The dynamics of power consumption constitutes an essential building block for planning and operating sustainable energy systems. Whereas variations in the dynamics of renewable energy generation are reasonably well studied, a deeper understanding of the variations in consumption dynamics is still missing. In one of his recent papers published in Nature Communications (2022),  Christian Beck (together with an international team of collaborators) has analysed highly resolved residential electricity consumption data of Austrian, German and UK households and developed a generally applicable data-driven load model. This research offers a better understanding of consumer demand dynamics, and provides general tools for disentangling mean demand and fluctuations for any given system, going beyond the standard load profile. These insights on the demand dynamics can support planning and operating future-compliant (micro) grids in maintaining supply-demand balance.

For more details, see M. Anvari, E. Proedrou, B. Schaefer, C. Beck, H. Kantz, and M. Timme, Nature Commun. 13, 4593 (2022)

Renewable energy resources (wind, solar) as well as consumer demand fluctuations create a complex pattern of fluctuations in modern power grids