Abstract: Privacy-enhancing technologies for the Smart Grid usually address either the consolidation of users’ energy consumption or the verification of billing information. The goal of this paper is to introduce iKUP, a protocol that addresses both problems simultaneously. iKUP is an efficient privacy-enhancing protocol based on DC-Nets and Elliptic Curve Cryptography as Commitment. It covers the entire cycle of power provisioning, consumption, billing, and verification. iKUP allows: (i) utility providers to obtain a consolidated energy consumption value that relates to the consumption of a user set, (ii) utility providers to verify the correctness of this consolidated value, and (iii) the verification of the correctness of the billing information by both utility providers and users. iKUP prevents utility providers from identifying individual contributions to the consolidated value and, therefore, protects the users’ privacy. The analytical performance evaluation of iKUP is validated through simulation using as input a real-world data set with over 157 million measurements collected from 6,345 smart meters. Our results show that iKUP has a worse performance than other protocols in aggregation and decryption, which are operations that happen only once per round of measurements and, thus, have a low impact in the total protocol performance. iKUP heavily outperforms other protocols in encryption, which is the most demanded cryptographic function, has the highest impact on the overall protocol performance, and it is executed in the smart meters.

Citation: F{\’a}bio Borges and Leonardo A. Martucci (2014). {iKUP} Keeps Users’ Privacy in the Smart Grid. In Proceedings of the IEEE Conference on Communications and Network Security (CNS 2014), 29–31 Oct, San Francisco, CA, USA.

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This work was presented at HAIDM 2014. The 2014 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

Abstract: Recently, many algorithms have been developed for autonomous agents to manage home energy use on behalf of their human owners. By so doing, it is expected that agents will be more efficient at, for example, choosing the best energy tariff to switch to when dynamically priced tariffs come about. However, to date, there has been no validation of such technologies in any field trial. In particular, it has not been shown whether users prefer fully autonomous agents as opposed to controlling their preferences manually. Hence, in this paper we describe a novel platform, called TariffAgent, to study notions of flexible autonomy in the context of tariff switching. TariffAgent uses real-world datasets and real-time electricity monitoring to instantiate a scenario where human participants may have to make, or delegate to their agent (in different ways), tariff switching decisions given uncertainties about their own consumption and tariff prices. We carried out a field trial with 10 participants and, from both quantitative and qualitative results, formulate novel design guidelines for systems that implement flexible autonomy.

Keywords: Human-Agent Interaction, Autonomous Agents, Flexible Autonomy, Energy, Smart Grid.

Citation: Alper Alan, Enrico Costanza, Joel Fisher, Sarvapali Ramchurn, Tom Rodden and Nicholas Jennings. A Field Study of Human-Agent Interaction for Electricity Tariff Switching.

Download: http://bit.ly/1MBoStF