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Blockchain Technology for Smart Grids: Decentralized NIST Conceptual Model

descriptionPublicationkeyboard_double_arrow_right Article , Journal 01 Jan 2020 Austria Publisher:Institute of Electrical and Electronics Engineers (IEEE)Journal:IEEE Access, volume 8, pages 43,177-43,190 (eissn: 2169-3536,

Authors: Adedayo Aderibole; Aamna Aljarwan; Muhammad Habib Ur Rehman; Hatem H. Zeineldin; Toufic Mezher; Khaled Salah; Ernesto Damiani; +1 Authors

doi: 10.1109/access.2020.2977149

Blockchain Technology for Smart Grids: Decentralized NIST Conceptual Model

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Abstract

Blockchain technology is showing a significant potential to disrupt a number of information technology domains. One of the especially interesting areas for blockchain applications is smart grid. A number of early papers have been published in this area, however, there is no systematic analysis of the impact of blockchain technology on decentralization of smart grids. In this paper, we analyze the standard NIST conceptual model of smart grid domains with respect to the three critical blockchain features: decentralization, trust and incentive. We integrate our findings in order to produce a fully decentralized blockchain-enabled smart grid considering NIST conceptual model. The results of this paper should help smart grid developers and researchers to obtain a conceptual reference of the overall applicability of blockchain technology in smart grid domains and sub-domains. In addition this research will help to identify and guide smart grid blockchain development and research initiatives.

Country

Austria

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Keywords

blockchain, decentralization, trust, Smart grid, incentive, TK1-9971, Electrical engineering. Electronics. Nuclear engineering

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	51
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 1%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 1%