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Privacy Measures and Storage Technologies for Battery-Based Load Hiding - an Overview and Experimental Study

Authors:

Vadim Arzamasov,

Rebecca Schwerdt,

Shahab Karrari,

Tien Bach NguyenAuthors Info & Claims

e-Energy '20: Proceedings of the Eleventh ACM International Conference on Future Energy Systems

Pages 178 - 195

https://doi.org/10.1145/3396851.3398320

Published: 18 June 2020 Publication History

Abstract

Large-scale smart meter roll-outs all over the world are one effect of the ongoing energy transition. This poses a significant risk to consumer's privacy. Battery based load hiding (BBLH)---where an energy storage system is employed to obscure actual demand patterns---is one possibility to still retain privacy. In recent years many different BBLH algorithms have been proposed. But although most of them were assessed with some formally defined privacy measure, the current state of the art sorely lacks any comparability.

We give an overview of privacy measures proposed for this scenario, available storage technologies, and datasets used for the assessment of BBLH. Furthermore, we conduct a study of how these factors influence the ratings of several state-of-the-art BBLH algorithms. Our results illustrate the need for standardization as well as further research into meaningful privacy measures. Achieving this is necessary for private households to make an informed decision on which BBLH algorithm is best for their specific situation.

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Cited By

Karrari SLudwig NDe Carne GNoe M(2022)Sizing of Hybrid Energy Storage Systems Using Recurring Daily PatternsIEEE Transactions on Smart Grid10.1109/TSG.2022.315686013:4(3290-3300)Online publication date: Jul-2022
https://doi.org/10.1109/TSG.2022.3156860
Haji Mirzaee PShojafar MCruickshank HTafazolli R(2022)Smart Grid Security and Privacy: From Conventional to Machine Learning Issues (Threats and Countermeasures)IEEE Access10.1109/ACCESS.2022.317425910(52922-52954)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3174259

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Privacy Measures and Storage Technologies for Battery-Based Load Hiding - an Overview and Experimental Study

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Smart grid provides significant enhancement to the reliability and efficiency of the electricity systems, but the real-time consumption information exposes user's privacy. To tackle this challenging issue, we present a novel privacy-preserving scheme. ...

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e-Energy '20: Proceedings of the Eleventh ACM International Conference on Future Energy Systems

June 2020

601 pages

ISBN:9781450380096

DOI:10.1145/3396851

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGEnergy: ACM Special Interest Group on Energy Systems and Informatics

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 June 2020

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Research-article
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Refereed limited

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Deutsche Forschungsgemeinschaft

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e-Energy '20

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SIGEnergy

e-Energy '20: The Eleventh ACM International Conference on Future Energy Systems

June 22 - 26, 2020

Virtual Event, Australia

Acceptance Rates

e-Energy '20 Paper Acceptance Rate 77 of 173 submissions, 45%;

Overall Acceptance Rate 160 of 446 submissions, 36%

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Cited By

Karrari SLudwig NDe Carne GNoe M(2022)Sizing of Hybrid Energy Storage Systems Using Recurring Daily PatternsIEEE Transactions on Smart Grid10.1109/TSG.2022.315686013:4(3290-3300)Online publication date: Jul-2022
https://doi.org/10.1109/TSG.2022.3156860
Haji Mirzaee PShojafar MCruickshank HTafazolli R(2022)Smart Grid Security and Privacy: From Conventional to Machine Learning Issues (Threats and Countermeasures)IEEE Access10.1109/ACCESS.2022.317425910(52922-52954)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3174259

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