Privacy-Preserving Local Energy Trading Considering Network Fees

TL;DR

This paper introduces a privacy-preserving local energy market protocol that considers network fees and physical constraints, ensuring secure, efficient trading among 5,000 participants within minutes.

Contribution

It presents a novel secure multiparty computation-based protocol for privacy-preserving local energy trading that incorporates network fees and physical network constraints.

Findings

The protocol can efficiently handle 5,000 participants in 4.17 minutes.

It ensures privacy and security through multiparty verification and secure computation.

The approach effectively considers network fees and physical constraints in local energy markets.

Abstract

Driven by the widespread deployment of distributed energy resources, local energy markets (LEMs) have emerged as a promising approach for enabling direct trades among prosumers and consumers to balance intermittent generation and demand locally. However, LEMs involve processing sensitive participant data, which, if not protected, poses privacy risks. At the same time, since electricity is exchanged over the physical power network, market mechanisms should consider physical constraints and network-related costs. Existing work typically addresses these issues separately, either by incorporating grid-related aspects or by providing privacy protection. To address this gap, we propose a privacy-preserving protocol for LEMs, with consideration of network fees that can incite participants to respect physical limits. The protocol is based on a double-auction mechanism adapted from prior work to enable more efficient application of our privacy-preserving approach. To protect participants' data, we use secure multiparty computation. In addition, Schnorr's identification protocol is employed with multiparty verification to ensure authenticated participation without compromising privacy. We further optimise the protocol to reduce communication and round complexity. We prove that the protocol meets its security requirements and show through experimentation its feasibility at a typical LEM scale: a market with 5,000 participants can be cleared in 4.17 minutes.