A Privacy-Preserving Scheme for Incentive-Based Demand Response in the Smart Grid

Yanmin Gong, Ying Cai, Yuanxiong Guo, Yuguang Fang

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

189 Citations (Scopus)

Abstract

The advanced metering infrastructure (AMI) in the smart grid provides real-time information to both grid operators and customers, exploiting the full potential of demand response (DR). However, it introduces new privacy threats to customers. Prior works have proposed privacy-preserving methods in the AMI, such as temporal or spatial aggregation. A main assumption in these works is that fine-grained data do not need to be attributable to individuals. However, this assumption does not hold in incentive-based demand response (IDR) programs where fine-grained metering data are required to analyze individual demand curtailments, and hence, need to be attributable. In this paper, we propose a privacy-preserving scheme for IDR programs in the smart grid, which enables the DR provider to compute individual demand curtailments and DR rewards while preserving customer privacy. Moreover, a customer can reveal his/her identity and prove ownership of his/her power usage profile in certain situations, such as legal disputes. We achieve both privacy and efficiency in our scheme through a combination of several cryptographic primitives, such as identity-committable signatures and partially blind signatures. As far as we know, we are the first to identify and address privacy issues for IDR programs in the smart grid.
Original languageEnglish
Article number7069275
Pages (from-to)1304-1313
JournalIEEE Transactions on Smart Grid
Volume7
Issue number3
DOIs
Publication statusPublished - 1 May 2016
Externally publishedYes

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

  • Billing
  • customer baseline (CBL)
  • data privacy
  • demand response (DR)
  • smart grid

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