Blockchain-Based Water-Energy Transactive Management With Spatial-Temporal Uncertainties

doi:10.1109/TSG.2022.3230693

CORC > 自动化研究所 > 中国科学院自动化研究所 > 多模态人工智能系统全国重点实验室

	Blockchain-Based Water-Energy Transactive Management With Spatial-Temporal Uncertainties
	Zhao, Pengfei 3,7; Li, Shuangqi 5,6; Hu, Paul Jen-Hwa 8; Gu, Chenghong 6; Lu, Shuai 9; Ding, Shixing 1; Cao, Zhidong 3,7; Xie, Da 2; Xiang, Yue 4
刊名	IEEE TRANSACTIONS ON SMART GRID
	2023-07-01
卷号	14 期号:4 页码:2903-2920
关键词	Blockchain spatial-temporal ambiguity set two-stage framework water-energy nexus
ISSN号	1949-3053
DOI	10.1109/TSG.2022.3230693
通讯作者	Cao, Zhidong(Zhidong.Cao@ia.ac.cn)
英文摘要	Water resources are vital to the energy conversion process but few efforts have been devoted to the joint optimization problem which is fundamentally critical to the water-energy nexus for small-scale or remote energy systems (e.g., energy hubs). Traditional water and energy trading mechanisms depend on centralized authorities and cannot preserve security and privacy effectively. Also, their transaction process cannot be verified and is subject to easy tampering and frequent exposures to cyberattacks, forgery, and network failures. Toward that end, water-energy hubs (WEHs) offers a promising way to analyse water-energy nexus for greater resource utilization efficiency. We propose a two-stage blockchain-based transactive management method for multiple, interconnected WEHs. Our method considers peer-to-peer (P2P) trading and demand response, and leverages blockchain to create a secure trading environment. It features auditing and resource transaction record management via system aggregators enabled by a consortium blockchain, and entails spatial-temporal distributionally robust optimization (DRO) for renewable generation and load uncertainties. A spatial-temporal ambiguity set is incorporated in DRO to characterize the spatial-temporal dependencies of the uncertainties in distributed renewable generation and load demand. We conduct a simulation-based evaluation that includes robust optimization and the moment-based DRO as benchmarks. The results reveal that our method is consistently more effective than both benchmarks. Key findings include i) our method reduces conservativeness with lower WEH trading and operation costs, and achieves important performance improvements by up to 6.1%; and ii) our method is efficient and requires 18.7% less computational time than the moment-based DRO. Overall, this study contributes to the extant literature by proposing a novel two-stage blockchain-based WEH transaction method, developing a realistic spatial-temporal ambiguity set to effectively hedge against the uncertainties for distributed renewable generation and load demand, and producing empirical evidence suggesting its greater effectiveness and values than several prevalent methods.
资助项目	New Generation Artificial Intelligence Development Plan of China (2015-2030)[2021ZD0111205] ; National Natural Science Foundation of China[72025404] ; National Natural Science Foundation of China[71621002] ; National Natural Science Foundation of China[71974187] ; Beijing Natural Science Foundation[L192012] ; Beijing Nova Program[Z201100006820085]
WOS关键词	CHANCE-CONSTRAINED OPTIMIZATION ; ECONOMIC-DISPATCH ; ROBUST OPTIMIZATION ; DEMAND RESPONSES ; OPERATION ; POWER ; SYSTEMS ; NEXUS ; MODEL ; MICROGRIDS
WOS研究方向	Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:001017487000033
资助机构	New Generation Artificial Intelligence Development Plan of China (2015-2030) ; National Natural Science Foundation of China ; Beijing Natural Science Foundation ; Beijing Nova Program
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/53735]
专题	多模态人工智能系统全国重点实验室
通讯作者	Cao, Zhidong
作者单位	1.Southeast Univ, Sch Cyber Sci Engn, Nanjing 211189, Peoples R China 2.Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai 200240, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100045, Peoples R China 4.Sichuan Univ, Coll Elect Engn, Chengdu 610065, Peoples R China 5.Hong Kong Polytech Univ, Dept Elect Engn, Hong Kong, Peoples R China 6.Univ Bath, Dept Elect & Elect Engn, Bath BA2 7AY, England 7.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100190, Peoples R China 8.Univ Utah, David Eccles Sch Business, Salt Lake City, UT 84112 USA 9.Southeast Univ, Sch Elect Engn, Nanjing 210096, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Pengfei,Li, Shuangqi,Hu, Paul Jen-Hwa,et al. Blockchain-Based Water-Energy Transactive Management With Spatial-Temporal Uncertainties[J]. IEEE TRANSACTIONS ON SMART GRID,2023,14(4):2903-2920.
APA	Zhao, Pengfei.,Li, Shuangqi.,Hu, Paul Jen-Hwa.,Gu, Chenghong.,Lu, Shuai.,...&Xiang, Yue.(2023).Blockchain-Based Water-Energy Transactive Management With Spatial-Temporal Uncertainties.IEEE TRANSACTIONS ON SMART GRID,14(4),2903-2920.
MLA	Zhao, Pengfei,et al."Blockchain-Based Water-Energy Transactive Management With Spatial-Temporal Uncertainties".IEEE TRANSACTIONS ON SMART GRID 14.4(2023):2903-2920.