Publication

Abstract : In today’s smart grid era, ensuring fair energy distribution while protecting participants’ data privacy is a critical challenge, particularly in Peer-to-Peer (P2P) energy trading environments. To address this challenge, this paper presents a privacy-preserving energy management model that ensures fair energy allocation based on participants’ reported information. By identifying the demand-to-supply ratio, the proposed model classifies the market operation mode either buyers’ mode or sellers’ mode and manages energy accordingly. The model employs a quorum-based architecture that integrates SHA-256 encryption and Shamir’s Secret Sharing scheme to safeguard participants’ private data against potential cyber-attacks such as Man-in-the-Middle (MitM) and False Data Injection Attacks (FDIA). Simulation results demonstrate that once the system operator receives the valid threshold shares, the original information can be successfully reconstructed. Furthermore, the simulation also indicates that the proposed model not only improves grid stress by up to 76.60% during peak hours but also transforms the grid’s role from an energy taker to an energy contributor.