Consensus reaching with heterogeneous user preferences, private input and privacy-preservation output

被引:1
|
作者
Le Cadre, Helene [1 ]
Bedo, Jean-Sebastien [2 ]
机构
[1] VITO EnergyVille, Thor Sci Pk, B-3600 Genk, Belgium
[2] Orange, Ave Bourget, Evere, Belgium
来源
关键词
Matching markets; Preferences; Nash equilibrium; Privacy; Consensus ADMM; PEER-TO-PEER; STABILITY;
D O I
10.1016/j.orp.2019.100138
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
This paper deals with a generic problem of matching agents with underlying preferences while guaranteeing a certain level of privacy is met. As a general framework, we consider consumers and prosumers who trade energy on a platform. Consumers buy energy to the platform to maximize their usage benefit while minimizing the cost paid to the platform. Prosumers, who have the possibility to generate energy, self-consume part of it to maximize their usage benefit and sell the rest to the platform to maximize their revenue. Inspired by a variant of the Hotelling model, product differentiation is introduced and consumers can specify preferences regarding locality and green origin of their supply. The consumers and prosumers problems being coupled through a matching probability, we provide analytical characterization of the resulting Nash equilibrium, and conditions for existence and uniqueness. Assuming supply shortages occur on the platform, we reformulate the local market clearing problem as a consensus problem that we solve using Consensus Alternating Direction Method of Multipliers (C-ADMM), enabling minimal information exchanges between prosumers and consumers. C-ADMM complexity is recalled and strategy proofness is analysed. The algorithm is then run on a case study made of 300 prosumers from New South Wales in Australia, equipped with solar panels. We consider privacy-preservation output against a centralized benchmark approach, and evaluate C-ADMM computational time under three scenarios with an increasing number of agents. Regarding economic analysis, we observe that it is more profitable for prosumers than for consumers to be flexible within a local energy community, and that belonging to a local energy community incentivizes them to reduce their demands by comparison with their initial targets. Furthermore, the expectation to make a substantial profit is a main driver for prosumers' engagement within a community; whereas for consumers, the green origin of the supply is determinant.
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页数:17
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  • [1] Incremental ADMM with Privacy-Preservation for Decentralized Consensus Optimization
    Ye, Yu
    Chen, Hao
    Xiao, Ming
    Skoglund, Mikael
    Poor, H. Vincent
    [J]. 2020 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT), 2020, : 209 - 214
  • [2] User Authentication Scheme with Privacy-Preservation for Multi-Server Environment
    Wang, Ren-Chiun
    Juang, Wen-Shenq
    Lei, Chin-Laung
    [J]. IEEE COMMUNICATIONS LETTERS, 2009, 13 (02) : 157 - 159
  • [3] Preservation of patterns and input-output privacy
    Bu, Shaofeng
    Lakshmanan, Laks V. S.
    Ng, Raymond T.
    Ramesh, Ganesh
    [J]. 2007 IEEE 23RD INTERNATIONAL CONFERENCE ON DATA ENGINEERING, VOLS 1-3, 2007, : 671 - +
  • [4] An Efficient Hybrid Signcryption Scheme With Conditional Privacy-Preservation for Heterogeneous Vehicular Communication in VANETs
    Ali, Ikram
    Lawrence, Tandoh
    Omala, Anyembe Andrew
    Li, Fagen
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2020, 69 (10) : 11266 - 11280
  • [5] User Preferences for Interdependent Privacy Preservation Strategies in Social Media
    Necaise, Aaron
    Tanni, Tangila Islam
    Williams, Aneka
    Solihin, Yan
    Kapadia, Apu
    Amon, Mary Jean
    [J]. Proceedings of the ACM on Human-Computer Interaction, 2023, 7 (CSCW2)
  • [6] Large-scale k-means clustering with user-centric privacy-preservation
    Sakuma, Jun
    Kobayashi, Shigenobu
    [J]. KNOWLEDGE AND INFORMATION SYSTEMS, 2010, 25 (02) : 253 - 279
  • [7] A Passive Attack Authentication Scheme for User Privacy-Preservation in LBS: A Case in Opportunistic Mobile Networks
    Adu-Gyamfi, D.
    Zhang, F. L.
    Takyi, A.
    Addy, N. A. M.
    Anku, N. E. L.
    [J]. INTERNATIONAL CONFERENCE ON POWER ELECTRONICS AND ENERGY ENGINEERING (PEEE 2015), 2015, : 275 - 280
  • [8] Large-scale k-means clustering with user-centric privacy-preservation
    Jun Sakuma
    Shigenobu Kobayashi
    [J]. Knowledge and Information Systems, 2010, 25 : 253 - 279
  • [9] Sport Location-Based User Clustering With Privacy-Preservation in Wireless IoT-Driven Healthcare
    Zhang, Qiyun
    Zhang, Yuan
    Li, Caizhong
    Yan, Chao
    Duan, Yucong
    Wang, Hao
    [J]. IEEE ACCESS, 2021, 9 : 12906 - 12913
  • [10] Distributed event-triggered estimation for dynamic average consensus: A perturbation-injected privacy-preservation scheme
    Yi, Xiaojian
    Xu, Tao
    [J]. INFORMATION FUSION, 2024, 108