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Exploiting design thinking to improve energy efficiency of buildings

descriptionPublicationkeyboard_double_arrow_right Article , Journal 01 Apr 2020 Australia Publisher:Elsevier BVJournal:Energy, volume 197, page 117,141 (issn: 0360-5442,

Authors: Tushar, Wayes; Lan, Lan; Withanage, Chathura; Sng, Hui En Karen; Yuen, Chau; Wood, Kristin L.; Saha, Tapan Kumar;

doi: 10.1016/j.energy.2020.117141

Exploiting design thinking to improve energy efficiency of buildings

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Abstract

This paper studies an interdisciplinary approach for improving building energy efficiency. In particular, the proposed approach integrates design innovation (DI) techniques, existing energy audit methods (EAM), and data-driven & engineering modeling techniques (DET) in the process of sustainable smart energy system design. From this perspective, DI methods are extended and modified to suit the content of sustainable smart energy system design and a DI 4D (Discover, Define, Develop and Deliver) framework is introduced to guide the design process. The motivation behind and the implementation procedure of each of the DI phases is explained separately, and the process of integrating DI methods, EAM and DET in developing a sustainable smart energy system is demonstrated. The proposed approach is deployed within the campus of a tertiary education institution to show its effectiveness in designing a smart sustainable energy system.

Country

Australia

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Keywords

690, 670, 2208 Electrical and Electronic Engineering, 2205 Civil and Structural Engineering, 2210 Mechanical Engineering, Pollution, General Energy, 2215 Building and Construction, 2310 Pollution, 2209 Industrial and Manufacturing Engineering

Impact byBIP!

	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).	17
	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%