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Smart Meter Privacy

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Privacy in Dynamical Systems

Abstract

The new generation electricity supply network, called the smart grid (SG), provides consumers with an active management and control of the power. By utilizing digital communications and sensing technologies which make the grid smart, SGs yield more efficient electricity transmission, reduced peak demand, improved security and increased integration of renewable energy systems compared to the traditional grid. Smart meters (SMs) are one of the core enablers of SG systems; they measure and record the high resolution electricity consumption information of a household almost in a real time basis, and report it to the utility provider (UP) at regular time intervals. SM measurements can be used for time-of-use pricing, trading user-generated energy, and mitigating load variations. However, real-time SM readings can also reveal sensitive information about the consumer’s activities which the user may not want to share with the UP, resulting in serious privacy concerns. SM privacy enabling techniques proposed in the literature can be categorized as SM data manipulation and demand shaping. While the SM data is modified before being reported to the UP in the former method, the latter requires direct manipulation of the real energy consumption by exploiting physical resources, such as a renewable energy source (RES) or a rechargeable battery (RB). In this chapter, a data manipulation privacy-enabling technique and three different demand shaping privacy-enabling techniques are presented, considering SM with a RES and an RB, SM with only an RB and SM with only a RES. Information theoretic measures are used to quantify SM privacy. Optimal energy management strategies and bounds which are obtained using control theory, specifically Markov decision processes (MDPs), and rate distortion theory are analyzed.

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Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Imperial College London, London, UK

    Ecenaz Erdemir, Deniz Gündüz & Pier Luigi Dragotti

Authors
  1. Ecenaz Erdemir
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  2. Deniz Gündüz
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  3. Pier Luigi Dragotti
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Corresponding author

Correspondence to Ecenaz Erdemir .

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Editors and Affiliations

  1. Department of Electrical and Electronic Engineering, The University of Melbourne and CSIRO’s Data61, Melbourne, VIC, Australia

    Farhad Farokhi

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Erdemir, E., Gündüz, D., Dragotti, P.L. (2020). Smart Meter Privacy. In: Farokhi, F. (eds) Privacy in Dynamical Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-0493-8_2

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