LAPSE:2023.35898
Published Article
LAPSE:2023.35898
Consumer Preferences for Smart Energy Services Based on AMI Data in the Power Sector
May 26, 2023
Advanced metering infrastructure (AMI) is becoming increasingly popular as an efficient means of energy demand management. By collecting energy data through AMI, it is possible to provide users with information that can induce them to change their behavior. To ensure that AMI continues to expand and to encourage the use of energy data, it is important to increase consumer participation and analyze their preferred service attributes. This study utilized a choice experiment to analyze consumer preferences for and acceptance of smart energy services based on AMI data. The results of a mixed logit model estimation show that consumers prefer the electricity information service for individual households and the social safety-net service among convergence services. A scenario analysis confirms that monetary compensation to offset any additional charges is important to maintain the level of consumer acceptance. These empirical findings offer insights for policymakers and companies seeking to develop policies and similar services.
Keywords
choice experiment, smart energy service, stated preference techniques, willingness to pay
Suggested Citation
Lee HJ, Chung BJ, Huh SY. Consumer Preferences for Smart Energy Services Based on AMI Data in the Power Sector. (2023). LAPSE:2023.35898
Author Affiliations
Lee HJ: Department of Future Energy Convergence, Seoul National University of Science & Technology, 232 Gongreung-Ro, Nowon-Gu, Seoul 01811, Republic of Korea
Chung BJ: Research Center of Electrical and Information Technology, Seoul National University of Science & Technology, 232 Gongreung-Ro, Nowon-Gu, Seoul 01811, Republic of Korea [ORCID]
Huh SY: Department of Future Energy Convergence, Seoul National University of Science & Technology, 232 Gongreung-Ro, Nowon-Gu, Seoul 01811, Republic of Korea [ORCID]
Journal Name
Energies
Volume
16
Issue
9
First Page
3961
Year
2023
Publication Date
2023-05-08
Published Version
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en16093961, Publication Type: Journal Article
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LAPSE:2023.35898
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doi:10.3390/en16093961
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May 26, 2023
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CC BY 4.0
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[v1] (Original Submission)
May 26, 2023
 
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May 26, 2023
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Original Submitter
Calvin Tsay
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