Zone-Based Privacy-Preserving Billing for Local Energy Market Based on Multiparty Computation

TL;DR

This paper introduces a privacy-preserving billing protocol for local energy markets using multiparty computation, ensuring accurate billing while protecting participant privacy and demonstrating high efficiency for large user bases.

Contribution

It presents a novel zone-based billing model that incorporates location data and energy deviations, utilizing multiparty computation for decentralised, privacy-preserving calculations.

Findings

Billing for 5000 users completed in less than nine seconds

Honest-majority model outperforms dishonest-majority in efficiency

Protocol maintains privacy and accuracy in energy billing

Abstract

This paper proposes a zone-based privacy-preserving billing protocol for local energy markets that takes into account energy volume deviations of market participants from their bids. Our protocol incorporates participants' locations on the grid for splitting the deviations cost. The proposed billing model employs multiparty computation so that the accurate calculation of individual bills is performed in a decentralised and privacy-preserving manner. We also present a security analysis as well as performance evaluations for different security settings. The results show superiority of the honest-majority model to the dishonest majority in terms of computational efficiency. They also show that the billing can be executed for 5000 users in less than nine seconds in the online phase for all security settings, demonstrating its feasibility to be deployed in real local energy markets.