Privacy-preserving incentive mechanism for integrated demand response: A homomorphic encryption-based approach - Wen-Ting Lin; Guo Chen; Jueyou Li; Yan Lei; Wanli Zhang; Degang Yang; Tingzhen Ming (International Journal of Electrical Power & Energy Systems)
Demand response is crucial for stabilizing smart grids by promoting flexible energy consumption. However, current demand response models largely rely on single- or bi-level frameworks, which lack the structure to effectively propagate incentives from the grid to integrated energy system service providers and, ultimately, to multi-energy users. Additionally, privacy concerns in collecting and transmitting user energy preferences can reduce user participation in demand response. This study addresses these challenges by proposing a three-level demand response model for integrated energy systems, structured to align grid and integrated energy system objectives through a hierarchical incentive system. Using a Stackelberg game framework, the model coordinates interactions among the grid, integrated energy system service providers, and multi-energy users, ensuring efficient incentive distribution across all levels. To further protect privacy and encourage participation, a fully distributed algorithm incorporating homomorphic encryption is employed. Simulation results indicate that the proposed three-level mechanism enhances demand response performance by aligning user actions with grid objectives, outperforming traditional bi-level models.