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Energy-Social Manufacturing for Social Computing

文献类型：期刊论文

作者Zhao, Alexis Pengfei2; Li, Shuangqi1; Wang, Yanjia3; Hu, Paul Jen-Hwa4; Wu, Chenye5,6; Cao, Zhidong2; Fei, Faith Xue5,6
刊名IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
出版日期2024-04-08
页码14
关键词Blockchain security cyber-physical-social systems (CPSSs) energy management peer-to-peer trading social manufacturing (SM)
ISSN号2329-924X
DOI10.1109/TCSS.2024.3379254
通讯作者Cao, Zhidong(Zhidong.Cao@ia.ac.cn)
英文摘要This article explores social manufacturing (SM) within cyber-physical-social systems (CPSSs), leveraging artificial intelligence (AI) to revolutionize energy prosumer networks. We introduce a blockchain-enabled operation and management mechanism for energy systems, incorporating energy aggregators for efficient transaction audits and employing consortium blockchain and proof-of-work for enhanced security. Guided by social governance principles and utilizing the soft actor-critic (SAC) approach for handling renewable generation and load demand uncertainties, our method offers a resilient and cost-effective solution. Simulated case studies reveal a 16.7% reduction in audit costs and a 2.4% increase in peer-to-peer transactions, highlighting improved network synergy. Our approach also reduces redundant trading by 6.5%and cuts operational costs by up to 6%, demonstrating the effectiveness of blockchain in improving cost-efficiency and enhancing social governance and security in energy manufacturing systems. The findings of this study contribute a novel vista to the ongoing discourse in SM, illustrating the formidable potential of advanced information and AI technologies in amplifying the operational acumen of contemporary manufacturing ecosystems.
WOS关键词OPERATION ; OPTIMIZATION ; SYSTEM ; DESIGN
资助项目New Generation Artificial Intelligence Development Plan of China[2021ZD0111205] ; National Natural Science Foundation of China[72025404] ; National Natural Science Foundation of China[72293575] ; National Natural Science Foundation of China[72074209]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:001201894600001
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构New Generation Artificial Intelligence Development Plan of China ; National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/58281]  
专题舆论大数据科学与技术应用联合实验室
通讯作者Cao, Zhidong
作者单位1.Cornell Univ, Syst Engn, Ithaca, NY 14853 USA
2.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China
3.Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai 200240, Peoples R China
4.Univ Utah, David Eccles Sch Business, Salt Lake City, UT 84112 USA
5.Chinese Univ Hong Kong, Sch Sci & Engn, Shenzhen 518172, Guangdong, Peoples R China
6.Shenzhen Inst Artificial Intelligence & Robot Soc, Shenzhen 518129, Guangdong, Peoples R China
推荐引用方式
GB/T 7714		 Zhao, Alexis Pengfei,Li, Shuangqi,Wang, Yanjia,et al. Energy-Social Manufacturing for Social Computing[J]. IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS,2024:14.
APA Zhao, Alexis Pengfei.,Li, Shuangqi.,Wang, Yanjia.,Hu, Paul Jen-Hwa.,Wu, Chenye.,...&Fei, Faith Xue.(2024).Energy-Social Manufacturing for Social Computing.IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS,14.
MLA Zhao, Alexis Pengfei,et al."Energy-Social Manufacturing for Social Computing".IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS (2024):14.

入库方式： OAI收割

来源：自动化研究所

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