Energy-based target cost modelling for construction projects. (November 2018)

• Record Type: Journal Article
• Authors: Alwisy, Aladdin; Barkokebas, Beda; Hamdan, Samer Bu; Gül, Mustafa; Al-Hussein, Mohamed
• Is Part Of: Journal of building engineering. Volume 20(2018)
• Page Start: 387
• Page End: 399
• Publication Date: 2018-11
• Subjects: Target costing -- Target cost modelling -- Energy simulation -- Energy factors -- Energy analysis -- Artificial neural network -- Rule-based analysis; Building -- Periodicals; 690.05
• DOI: 10.1016/j.jobe.2018.06.010
• Languages: English
• ISSNs: 2352-7102

Abstract

Abstract: Energy consumption is a key performance outcome influencing both the operational cost and environmental impact of a building. Studies exploring the connection between construction project capital cost and energy performance have presented a set of tools and models capable of evaluating the influence of construction systems on energy consumption metrics; however, what is lacking in these studies is a structured framework capable of systematically meeting desired project costs. This deficiency reduces the effectiveness of existing energy paradigms during the decision-making process. This paper thus introduces an energy-based target cost modelling framework (eTC) that achieves the balance between project cost and performance metrics through the combination of target costing principles and energy analysis techniques. The introduction of standardized energy factors, utilisation of energy simulation, and implementation of statistical analysis results in the development of energy-based mathematical models capable of efficiently evaluating construction system alternatives. Rule-based analysis is then employed to automatically select the construction system(s) that yield an optimised energy consumption according to a targeted cost and defined set of performance criteria. The accuracy of the developed mathematical models in predicting the energy consumption of buildings, an inaccuracy rate of 6.18%, makes eTC a reliable cost-driven guideline for energy consumption that can help construction practitioners to enhance the energy performance of a building within a desired cost. Highlights: A methodology is presented for energy-based target cost modelling. Green building studio and eQuest are used as building energy simulation programs. General regress neural network is used to develop the energy mathematical models. Rule-based analysis is used to perform the alternative value analysis. Building specifications are optimised to improve the energy efficiency and technical performance ranking within a targeted cost.