Techno-economic assessment of building energy efficiency systems using behavioral change: A case study of an edge-based micro-moments solution
Author | Himeur, Yassine |
Author | Alsalemi, Abdullah |
Author | Bensaali, Faycal |
Author | Amira, Abbes |
Author | Varlamis, Iraklis |
Author | Bravos, George |
Author | Sardianos, Christos |
Author | Dimitrakopoulos, George |
Available date | 2022-12-29T07:34:45Z |
Publication Date | 2022 |
Publication Name | Journal of Cleaner Production |
Resource | Scopus |
Abstract | Energy efficiency based on behavioral change has attracted increasing interest in recent years, although, solutions in this area lack much needed techno-economic analysis. That is due to the absence of both prospective studies and consumer awareness. To close such gap, this paper proposes the first techno-economic assessment of a behavioral change-based building energy efficiency solution, to the best of the authors' knowledge. From the one hand, the technical assessment is conducted through (i) introducing a novel edge-based energy efficiency solution; (ii) analyzing energy data using machine learning tools and micro-moments, and producing intelligent, personalized, and explainable action recommendations; and (iii) proceeding with a technical evaluation of four application scenarios, i.e., data collection, data analysis and anomaly detection, recommendation generation, and data visualization. On the other hand, economic assessment is performed by examining the marketability potential of the proposed solution via a market and research analysis of behavioral change-based systems for energy efficiency applications. Also, various factors impacting the commercialization of the final product are investigated before providing recommended actions to ensure its potential marketability via conducting a Go/No-Go evaluation. In conclusion, the proposed solution is designed at a low cost and can save up to 28%-68% of the consumed energy, which results in a Go decision to commercialize the technology. 2021 Elsevier Ltd |
Sponsor | This paper was made possible by National Priorities Research Program (NPRP) grant No. 10-0130-170288 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. |
Language | en |
Publisher | Elsevier |
Subject | Anomaly detection Behavioral change Business model Energy efficiency Market drivers/barriers Recommendation generation |
Type | Article |
Volume Number | 331 |
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Electrical Engineering [2649 items ]