Residential electricity consumption is an important part of the general system. Modern trends in the use of remote communications and remote work only enhance the importance of this part.

The total amount of energy consumed and the stability of consumption are important characteristics of an individual profile. In our opinion, it is the combination of these two characteristics that is significant for the tasks of forecasting consumption and ensuring system stability.
Cases when consumption has high volumes and low stability are undesirable for both the individual consumer and the overall system. However, such cases may go unnoticed by owners.

In this presentation, we introduce a model of dynamic classification of residential electricity consumption, taking into account volume and stability. The availability of modern smart-grid technologies allows for monitoring individual consumption and obtaining time series of readings. For stability modeling, the coefficient of auto-similarity is used, which is dynamically calculated based on time series of hourly spaced readings.

The model has been successfully tested on real data of Swedish residentials (Zimmermann, J.P. (2009), End-use metering campaign in 400 households in Sweden. Assessment of the potential electricity saving. Enertech). Cases with low (0.20) and high (0.80) readings of the coefficient of auto-similarity were considered.

In our opinion, the proposed model has good prospects for implementation in practical devices for individual consumption monitoring. This can have a positive effect on reducing the cost for the individual consumer, as well as contributing to the stability of the overall system.