A Privacy-Preserving, Two-Party, Secure Computation Mechanism for Consensus-Based Peer-to-Peer Energy Trading in the Smart Grid.

P2P negotiation mechanism blockchain consensus + innovation method homomorphic encryption secure computation smart contract two-party zero-knowledge proof

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
21 Nov 2022
Historique:
received: 22 08 2022
revised: 14 11 2022
accepted: 14 11 2022
entrez: 26 11 2022
pubmed: 27 11 2022
medline: 30 11 2022
Statut: epublish

Résumé

Consumers in electricity markets are becoming more proactive because of the rapid development of demand-response management and distributed energy resources, which boost the transformation of peer-to-peer (P2P) energy-trading mechanisms. However, in the P2P negotiation process, it is a challenging task to prevent private information from being attacked by malicious agents. In this paper, we propose a privacy-preserving, two-party, secure computation mechanism for consensus-based P2P energy trading. First, a novel P2P negotiation mechanism for energy trading is proposed based on the consensus + innovation (C + I) method and the power transfer distribution factor (PTDF), and this mechanism can simultaneously maximize social welfare and maintain physical network constraints. In addition, the C + I method only requires a minimum set of information to be exchanged. Then, we analyze the strategy of malicious neighboring agents colluding to attack in order to steal private information. To defend against this attack, we propose a two-party, secure computation mechanism in order to realize safe negotiation between each pair of prosumers based on Paillier homomorphic encryption (HE), a smart contract (SC), and zero-knowledge proof (ZKP). The energy price is updated in a safe way without leaking any private information. Finally, we simulate the functionality of the privacy-preserving mechanism in terms of convergence performance, computational efficiency, scalability, and SC operations.

Identifiants

pubmed: 36433614
pii: s22229020
doi: 10.3390/s22229020
pmc: PMC9695595
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Open Research Fund of Key Laboratory of Cryptography of Zhejiang Province
ID : ZCL21007
Organisme : Populus Euphratica Found grand number
ID : CCF- HuaweiBC2021009
Organisme : 2020 Industrial Internet Innovation and Development Project - For the Power Industry Industrial Internet Network Trust Support Platform Project
ID : JL71-20-017

Auteurs

Zhihu Li (Z)

China Electric Power Research Institute, Beijing 100081, China.

Haiqing Xu (H)

State Grid Corporation of China, Beijing 100031, China.

Feng Zhai (F)

China Electric Power Research Institute, Beijing 100081, China.
School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China.

Bing Zhao (B)

China Electric Power Research Institute, Beijing 100081, China.

Meng Xu (M)

China Electric Power Research Institute, Beijing 100081, China.

Zhenwei Guo (Z)

Hangzhou Innovative Institute, Beihang University, Hangzhou 310051, China.
Key Laboratory of Cryptography of Zhejiang Province, Hangzhou Normal University, Hangzhou 311121, China.

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Classifications MeSH