Multi-resolution load curve representation with privacy-preserving aggregation

The availability of individual load curves per household in the smart grid end-user domain combined with nonintrusive load monitoring to infer personal data from these load curves has led to privacy concerns. Two types of approaches show high potential to resolve this issue: (i) secure aggregation and (ii) multi-resolution representation with conditional access. In this paper a combination of these two principle approaches is proposed. It is shown formally that secure aggregation and wavelet-based multi-resolution representation are compatible. Furthermore, it is shown that that the wavelet transformation is compatible with existing privacy-preserving protocols and can be used to extend them with additional degrees of freedom. An implementation of the proposed approach is used for evaluation of feasibility in a low-cost embedded environment.