Paper 2024/1562

Fully Privacy-preserving Billing Models for Peer-to-Peer Electricity Trading Markets

Abstract

Peer-to-peer energy trading markets enable users to exchange electricity, directly offering them increased financial benefits. However, discrepancies often arise between the electricity volumes committed to in trading auctions and the volumes actually consumed or injected. Solutions designed to address this issue often require access to sensitive information that should be kept private. This paper presents a novel, fully privacy-preserving billing protocol designed to protect users' sensitive consumption and production data in the context of billing protocols for energy trading. Leveraging advanced cryptographic techniques, including fully homomorphic encryption (FHE) and pseudorandom zero sharing (PRZS), our protocol ensures robust security and confidentiality while addressing the critical issue of managing discrepancies between promised and actual electricity volumes. The proposed protocol guarantees that users' sensitive information remains inaccessible to external parties, including the trading platform and billing server. By utilizing FHE, the protocol allows computations on encrypted data without compromising privacy, while PRZS ensures secure aggregation of individual discrepancies of each household. This combination of cryptographic primitives maintains data privacy and enhances billing accuracy, even when fluctuations in energy supply and demand occur. We analyze real-time consumption and production data from 100 households to experimentally validate the effectiveness and efficiency of our billing model. By implementing a flexible framework compatible with any billing method, we demonstrate that our protocol can accurately compute individual bills for 100 households in approximately 0.17 seconds.