Work

A time aggregation approach for reducing identifiability in household energy data

Year: 2025

Type: article

Abstract: • 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.

Source: Utilities Policy

DOI: 10.1016/j.jup.2025.101900

Authors: S. van Schendel, I.A.M. Varenhorst

Institutions: Erasmus University Rotterdam, University of Twente

Language: English

Topic: Smart Grid Energy Management

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Climate action

Open Access status: hybrid

Estimated APC paid: $2,950