Smart grid

Electrical engineering

Physics

Cryptography

Identity (music)

Demand response

Computer network

Mathematics

Data aggregator

Information privacy

Engineering

Mathematical analysis

Economics

Microeconomics

Wireless sensor network

Acoustics

Grid

Electricity

Geometry

Incentive

Load management

Computer science

Scheme (mathematics)

Metering mode

Computer security

Mechanical engineering

IEEE Transactions on Smart Grid

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.

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