Privacy of Real-Time Pricing in Smart Grid
Paper i proceeding, 2019

Installing smart meters to publish real-time electricity rates has been controversial while it might lead to privacy concerns. Dispatched rates include fine-grained data on aggregate electricity consumption in a zone and could potentially be used to infer a household's pattern of energy use or its occupancy. In this paper, we propose Blowfish privacy to protect the occupancy state of the houses connected to a smart grid. First, we introduce a Markov model of the relationship between electricity rate and electricity consumption. Next, we develop an algorithm that perturbs electricity rates before publishing them to ensure users' privacy. Last, the proposed algorithm is tested on data inspired by household occupancy models and its performance is compared to an alternative solution.


Mahrokh Ghoddousiboroujeni

Sharif University of Technology

Dominik Fay

Kungliga Tekniska Högskolan (KTH)

Christos Dimitrakakis

Chalmers, Data- och informationsteknik, Data Science

Maryam Kamgarpour

Eidgenössische Technische Hochschule Zürich (ETH)

Proceedings of the IEEE Conference on Decision and Control

07431546 (ISSN)

Vol. 2019-December 5162-5167 9029924

58th IEEE Conference on Decision and Control, CDC 2019
Nice, France,



Bioinformatik (beräkningsbiologi)

Annan elektroteknik och elektronik



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