Poster: Privacy-Preserving Billing for Local Energy Markets Eman Alqahtani∗and Mustafa A. Mustafa∗† ∗Department of Computer Science, The University of Manchester, Manchester, M13 9PL, UK ‡COSIC, KU Leuven, Leuven, 3001, Belgium Email: eman.alqahtani@postgrad.manchester.ac.uk, mustafa.mustafa@manchester.ac.uk Abstract—We propose a privacy-preserving billing protocol for local energy markets (PBP-LEMs) that takes into account market participants’ energy volume deviations from their bids. It enables a group of market entities to jointly compute partic- ipants’ bills in a decentralized and privacy-preserving manner. It also mitigates risks on individuals’ privacy arising from any potential internal collusion. We first propose a novel, efficient, and privacy-preserving individual billing scheme, achieving information-theoretic security, which serves as a building block. PBP-LEMs utilises this scheme, along with other techniques such as multiparty computation, Pedersen commitments and inner product functional encryption, to ensure data confidentiality and accuracy. We present three approaches, resulting in different levels of privacy and performance. We also show that PBP-LEMs is feasible for deployment in real LEMs. Index Terms—Security, Privacy, LEM, MPC I. INTRODUCTION Local energy markets (LEMs) enable prosumers – individ- uals who consume and produce – to actively participate in open markets, supporting direct trading of surplus energy with others. This contrasts with the traditional practice of selling to suppliers at feed-in-tariff (FiT), which is lower than retail market price (RP). LEMs typically require participants to submit bids before the actual trading period (e.g., 1 hour in advance). There- fore, market participants need to forecast their bid volumes, indicating the amount of energy they intend to trade. This prediction relies on historical data and estimated consumption, making it inherently prone to errors. As a result, participants may commit to trade specific energy volumes but subsequently fail to fulfill these commitments. As this failure can disrupt grid stability and increase costs, market participants should be accounted for their deviations from their committed bid volumes during the billing process. Furthermore, a market participant’s deviation may cause a different level of effect on the grid depending on what part of the grid the participant resides in. As a result, some might bear higher costs than others, not only due to their deviation amounts but also because of their specific locations on the grid. The computation and settlement of bills/rewards for partic- ipants in LEMs, while considering their deviations, requires critical private information, including individual bid volumes and meter readings per trading period. These are closely associated with individuals’ consumption patterns, posing risks to their privacy. This work was supported by EPSRC through EnnCore [EP/T026995/1] and by the Flemish Government through FWO-SBO SNIPPET [S007619]. Previous studies have addressed the privacy concerns dur- ing billing and settlement, employing techniques such as anonymization, perturbation , and homomorphic encryption. Nevertheless, only a few have considered establishing a billing mechanism based on the actual amount of energy pro- duced/consumed by LEM participants [1, 2] or to additionally account for deviations [3–5]. However, the billing process is coordinated or executed by a single honest party [1, 2, 4], disclosing some or all of the individuals private data to the party and potentially imposing a high computational cost on a single party. This raise questions about the applicability or scalability of their solutions in realistic scenarios. In contrast, solutions [3, 5] rely on a group of entities working together to compute individual bills/rewards privately. However, they are vulnerable to the risk of internal collusion, potentially leading to the disclosure of highly sensitive data. To address th