TY - GEN
T1 - Applications of Digital Twins for Demand Side Recommendation Scheme with Consumer Comfort Constraints
AU - Onile, Abiodun E.
AU - Belikov, Juri
AU - Petlenkov, Eduard
AU - Levron, Yoash
N1 - Publisher Copyright:
© 2023 IEEE European Union.
PY - 2023
Y1 - 2023
N2 - The next evolution of traditional energy systems towards smart grid will require end-consumers to actively participate and make informed decisions regarding their energy usage. Industry 4.0 facilitates such progress by allowing more advanced analytics and creating means for end-consumers and distributed grid assets to be modelled as their Digital twins (DT) equivalents, paving the way for asset-level analytics. Note-worthily, consumers’ comfort is crucial towards promotion of easy adoption of such models from consumers’ perspectives. This study presents the application of hybrid DT and multiagent reinforcement learning models for real-time estimation of end-consumers future energy behaviors while generating actionable recommendation feedback for improving their energy efficiency and enhancing end-user comfort.
AB - The next evolution of traditional energy systems towards smart grid will require end-consumers to actively participate and make informed decisions regarding their energy usage. Industry 4.0 facilitates such progress by allowing more advanced analytics and creating means for end-consumers and distributed grid assets to be modelled as their Digital twins (DT) equivalents, paving the way for asset-level analytics. Note-worthily, consumers’ comfort is crucial towards promotion of easy adoption of such models from consumers’ perspectives. This study presents the application of hybrid DT and multiagent reinforcement learning models for real-time estimation of end-consumers future energy behaviors while generating actionable recommendation feedback for improving their energy efficiency and enhancing end-user comfort.
KW - Consumer comfort
KW - Demand side recommender system
KW - Distributed power systems
KW - Hybrid digital twins
KW - Industry 5.0
UR - http://www.scopus.com/inward/record.url?scp=85187273842&partnerID=8YFLogxK
U2 - 10.1109/ISGTEUROPE56780.2023.10407399
DO - 10.1109/ISGTEUROPE56780.2023.10407399
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AN - SCOPUS:85187273842
T3 - IEEE PES Innovative Smart Grid Technologies Conference Europe
BT - Proceedings of 2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023
T2 - 2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023
Y2 - 23 October 2023 through 26 October 2023
ER -
