Transparent Electricity Pricing with Privacy
Daniel Reijsbergen, Zheng Yang, Aung Maw, Tien Tuan Anh Dinh, Jianying, Zhou

TL;DR
This paper proposes a privacy-preserving transparent dynamic pricing scheme for smart grids that incentivizes efficient consumption, prevents data tampering, and ensures user privacy using cryptographic techniques.
Contribution
It introduces a novel privacy-preserving pricing protocol (PPTP) with formal security guarantees, addressing trust, tampering, and privacy challenges in smart grid billing.
Findings
Protocols are secure against tampering and privacy breaches.
Implementation demonstrates practical performance at scale.
Protocols effectively detect data tampering by the retailer.
Abstract
Smart grids leverage data from smart meters to improve operations management and to achieve cost reductions. The fine-grained meter data also enable pricing schemes that simultaneously benefit electricity retailers and users. Our goal is to design a practical dynamic pricing protocol for smart grids in which the rate charged by a retailer depends on the total demand among its users. Realizing this goal is challenging because neither the retailer nor the users are trusted. The first challenge is to design a pricing scheme that incentivizes consumption behavior that leads to lower costs for both the users and the retailer. The second challenge is to prevent the retailer from tampering with the data, for example, by claiming that the total consumption is much higher than its real value. The third challenge is data privacy, that is, how to hide the meter data from adversarial users. To…
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Taxonomy
TopicsSmart Grid Security and Resilience · Smart Grid Energy Management · Blockchain Technology Applications and Security
