A time aggregation approach for reducing identifiability in household energy data

• More privacy friendly ways of analyzing energy data from households are necessary to further developments of digitization. • For privacy and data protection it is important to reduce identifiability of individuals and households in the data. • Anonymization is difficult to achieve, aggregation has been demonstrated to be useful to reduce identifiability. • Time aggregation of energy profiles brings privacy benefits and does significantly impact on the performance of DSM. • The example of EV charging shows that is more difficult to identify the behavior of people when time aggregation is used.