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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Renewable and Sustai...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Renewable and Sustainable Energy Reviews
Article . 2016 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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End user perceptions toward smart grid technology: Acceptance, adoption, risks, and trust

Authors: Pedro Ponce; Arturo Molina; Kenneth Polasko;

End user perceptions toward smart grid technology: Acceptance, adoption, risks, and trust

Abstract

Abstract Although smart grid technology has been extensively accepted, social factors influence the performance of smart grid systems. This smart technology will enable the automated monitoring and control of the power delivery system, increase the capacity of the power delivery system, and enhance the performance and connectivity of end users. However, the perceptions of end users are a key factor for adoption of this technology. When end users do not fully accept the smart grid, the operation of the smart grid is not satisfactory. Most literature has concentrated on the technological aspects of smart grids; a technological solution may be defined as one that requires a change only in the developed technology, demanding little or no change in human values or ideas of morality about the usage of electrical energy. However, the solutions to the problems of implementing smart grid technology are not to be found only in technological aspects. This paper presents experimental scenarios that use signal detection theory (SDT), a well-known tool in psychology research, to capture the perceptions of end users about smart grid technology. If the perceptions of end users are positive, the performance of the smart grid is improved. End user criteria can be analyzed using SDT. In addition, fuzzy logic type 2 is suggested as a way to increase the descriptive power of fuzzy signal detection theory. To obtain end user perceptions, several experimental scenarios were created using a didactic smart grid system designed by Delorenzo Group Italy. End users were faced with real situations that enabled determination of their perceptions about the smart grid technology. Experimental results of end users׳ perceptions of smart grid technology are shown using SDT, fuzzy detection theory, and fuzzy detection theory type 2. The results show that end users have a conservative criterion because they are not entirely confident in the intelligent technology provided by the smart grid; this conservative criterion limits smart grid performance.

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    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).
    47
    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 10%
    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 10%
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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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
47
Top 10%
Top 10%
Top 10%