4.7 Article

Techno-economic assessment of building energy efficiency systems using behavioral change: A case study of an edge-based micro-moments solution

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 331, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2021.129786

Keywords

Energy efficiency; Behavioral change; Anomaly detection; Recommendation generation; Business model; Market drivers/barriers

Funding

  1. Qatar National Research Fund (Qatar Foundation) [10-0130-170288]

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Energy efficiency based on behavioral change has gained interest, but lacks techno-economic analysis. This paper proposes the first techno-economic assessment of a behavioral change-based building energy efficiency solution. The technical assessment introduces a novel edge-based solution, analyzes energy data using machine learning tools, and evaluates application scenarios. The economic assessment examines marketability potential and provides recommended actions for commercialization.
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; (H) analyzing energy data using machine learning tools and micro-moments, and producing intelligent, personalized, and explainable action recommendations; and (Hi) 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.

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