Journal paper about influence of data granularity on smart meter privacy

Through smart metering load profiles are measured per household. However, besides the desired information also personal data can be inferred from these load profiles which has led to privacy concerns. As a simple example, turning on the microwave can be seen as an increase in consumed power of about 1500W, turning it off leads to a decrease of 1500W. Together with the timestamps of the measurements, also the on-duration is known. A longer duration could be a very strong hint for a subsequent meal. If such events are viewed for longer time periods, personal habits can be inferred.

Privacy is expected to increase with longer intervals between measurements of load curves. This paper studies the impact of data granularity on the possibility to determine appliance use. It is shown that when the measurement time interval exceeds half the on-time of an appliance, the appliance use detection
rate declines. The results for a sample household are visualized in an easily understandable form: if an appliance can not be determined at a given measurement interval, the corresponding entry is colored green.privacyFmeasure_house1_fontSize12The analysis shows quite good news: with the currently planned time interval of 15 minutes, typically only light switching events can be recognized.


  • [PDF] [DOI] G. Eibl and D. Engel, “Influence of Data Granularity on Smart Meter Privacy,” IEEE Transactions on Smart Grid, vol. 6, iss. 2, p. 930–939, 2015.
    author = {G\"{u}nther Eibl and Dominik Engel},
    title = {Influence of Data Granularity on Smart Meter Privacy},
    journal = {IEEE Transactions on Smart Grid},
    year = {2015},
    volume = {6},
    number = {2},
    pages = {930--939},
    month = {March},
    doi = {10.1109/TSG.2014.2376613},
    pdf = {},
    url = {},