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

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 t...

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Detalles Bibliográficos
Autores principales: Li, Zhihu, Xu, Haiqing, Zhai, Feng, Zhao, Bing, Xu, Meng, Guo, Zhenwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9695595/
https://www.ncbi.nlm.nih.gov/pubmed/36433614
http://dx.doi.org/10.3390/s22229020
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author Li, Zhihu
Xu, Haiqing
Zhai, Feng
Zhao, Bing
Xu, Meng
Guo, Zhenwei
author_facet Li, Zhihu
Xu, Haiqing
Zhai, Feng
Zhao, Bing
Xu, Meng
Guo, Zhenwei
author_sort Li, Zhihu
collection PubMed
description 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.
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spelling pubmed-96955952022-11-26 A Privacy-Preserving, Two-Party, Secure Computation Mechanism for Consensus-Based Peer-to-Peer Energy Trading in the Smart Grid Li, Zhihu Xu, Haiqing Zhai, Feng Zhao, Bing Xu, Meng Guo, Zhenwei Sensors (Basel) Article 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. MDPI 2022-11-21 /pmc/articles/PMC9695595/ /pubmed/36433614 http://dx.doi.org/10.3390/s22229020 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Li, Zhihu
Xu, Haiqing
Zhai, Feng
Zhao, Bing
Xu, Meng
Guo, Zhenwei
A Privacy-Preserving, Two-Party, Secure Computation Mechanism for Consensus-Based Peer-to-Peer Energy Trading in the Smart Grid
title A Privacy-Preserving, Two-Party, Secure Computation Mechanism for Consensus-Based Peer-to-Peer Energy Trading in the Smart Grid
title_full A Privacy-Preserving, Two-Party, Secure Computation Mechanism for Consensus-Based Peer-to-Peer Energy Trading in the Smart Grid
title_fullStr A Privacy-Preserving, Two-Party, Secure Computation Mechanism for Consensus-Based Peer-to-Peer Energy Trading in the Smart Grid
title_full_unstemmed A Privacy-Preserving, Two-Party, Secure Computation Mechanism for Consensus-Based Peer-to-Peer Energy Trading in the Smart Grid
title_short A Privacy-Preserving, Two-Party, Secure Computation Mechanism for Consensus-Based Peer-to-Peer Energy Trading in the Smart Grid
title_sort privacy-preserving, two-party, secure computation mechanism for consensus-based peer-to-peer energy trading in the smart grid
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9695595/
https://www.ncbi.nlm.nih.gov/pubmed/36433614
http://dx.doi.org/10.3390/s22229020
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