Privacy-preserving incentive mechanism for integrated demand response: A homomorphic encryption-based approach

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. • Proposed a three-level demand response model for integrated energy systems. • Developed a hierarchical incentive structure for grid-user alignment. • Improved privacy and participation with a distributed encryption algorithm.

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Publication Details

Journal
International Journal of Electrical Power & Energy Systems
Published
2024-12-13
DOI
https://doi.org/10.1016/j.ijepes.2024.110407
Citations
6
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
4.67
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article

Privacy-preserving incentive mechanism for integrated demand response: A homomorphic encryption-based approach

Ming Tang, Wen-Ting Lin, Yan Lei, Jueyou Li et al.
6 citations
International Journal of Electrical Power & Energy Systems
Blockchain Technology Applications and Security
4.67
article

Privacy-preserving incentive mechanism for integrated demand response: A homomorphic encryption-based approach

Ming Tang, Wen-Ting Lin, Yan Lei, Jueyou Li, Guo Chen, Degang Yang, Wanli Zhang
article en
6 citations

Abstract

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. • Proposed a three-level demand response model for integrated energy systems. • Developed a hierarchical incentive structure for grid-user alignment. • Improved privacy and participation with a distributed encryption algorithm.

International Journal of Electrical Power & Energy SystemsVol. 164
Chongqing Normal University (CN), Southwest University (CN), Wuhan University of Technology (CN)
Openalex Percentile: Top 5%
Blockchain Technology Applications and Security
4.67
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