Bilateral privacy-preserving energy sharing in network-constrained models via homomorphic encryption-based distributed optimization

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dc.contributor.authorWang, Hongli
dc.contributor.authorYang, Jun
dc.contributor.authorLi, Gaojunjie
dc.contributor.authorWu, Fuzhang
dc.contributor.authorXie, Lilong
dc.contributor.authorLiao, Fengran
dc.contributor.authorJia, Legang
dc.contributor.authorNgamroo, Issarachai
dc.date.accessioned2026-08-06T10:55:28Z
dc.date.available2026-08-06T10:55:28Z
dc.date.issued2026-05-01
dc.description.abstractThe proliferation of distributed energy enables prosumers to participate in local trading, yet privacy concerns and network constraints hinder market implementation. This paper proposes a bilateral privacy-preserving energy sharing mechanism that secures sensitive data while enforcing grid operational limits. We develop a prosumer decision model incorporating utility functions and transfer distance factors. To resolve privacy-coordination conflicts, a distributed optimization framework compatible with nonlinear models is designed by integrating gradient descent and dual ascent. This framework guarantees convergence under problem convexity and Lagrangian gradient existence. Furthermore, a homomorphic encryption scheme is integrated to enable dual-blind computations, which prevents plaintext disclosure to either prosumers or the operator while maintaining network safety. Theoretical analysis confirms the scheme's correctness and computational tractability. Numerical simulations on IEEE 14-bus and 33-bus systems validate the mechanism regarding convergence, bilateral privacy protection, and social welfare enhancement. Finally, the algorithm's scalability is demonstrated through penalty-based acceleration, which meets the practical deployment requirements of modern power system.
dc.identifier.citationElectric Power Systems Research, 254, 2026
dc.identifier.doi10.1016/j.epsr.2026.112719
dc.identifier.issn03787796
dc.identifier.other2-s2.0-105027638503
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/18089
dc.sourceElectric Power Systems Research
dc.subjectDistributed algorithms
dc.subjectEnergy sharing
dc.subjectHomomorphic encryption
dc.subjectPrivacy
dc.subjectProsumer
dc.titleBilateral privacy-preserving energy sharing in network-constrained models via homomorphic encryption-based distributed optimization
dc.typeArticle

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