Parametric-Based Multi-Objective Optimization Workflow: Daylight and Energy Performance Study of Hospital Building in Algeria

Soumaya Besbas (), Francesco Nocera (), Noureddine Zemmouri, Mohamed Amine Khadraoui and Asma Besbas
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Soumaya Besbas: Laboratory of Design and Modeling of Architectural Forms and Ambiances (LACOMOFA), Department of Architecture, Mohamed Khider University, Biskra 07000, Algeria
Francesco Nocera: Department of Civil Engineering and Architecture, University of Catania, Via Santa Sofia, 64, 95123 Catania, Italy
Noureddine Zemmouri: Laboratory of Design and Modeling of Architectural Forms and Ambiances (LACOMOFA), Department of Architecture, Mohamed Khider University, Biskra 07000, Algeria
Mohamed Amine Khadraoui: Laboratory of Construction Engineering and Architecture (LGCA), Abderrahmane Mira University, Bejaia 06000, Algeria
Asma Besbas: Laboratory of Smart Computing (LINFI), Mohamed Khider University, Biskra 07000, Algeria

Sustainability, 2022, vol. 14, issue 19, 1-20

Abstract: Daylight is an important factor that significantly contributes to patients’ healing, with a reduction in the length of stay in the hospital. It can strongly affect energy consumption negatively or positively through lighting control strategies. Therefore, the case of healthcare buildings is very particular and sensitive, especially under extreme climate conditions as in hot and arid regions. The present study aims to determine a balance between daylight use and energy consumption through a parametric-based optimization of the external shading system in a typical hospital room in Biskra. This paper demonstrates how the implementation of parametric design with evolutionary algorithms is considered a reliable strategy to reach optimum solutions in building performance problems. The daylight performance is investigated based on multi-objective optimization to minimize the Energy Use Intensity “EUI”, while maximizing Spatial Daylight Autonomy “sDA” and Useful Daylight Illuminance “UDI”. A simulation model was developed via Grasshopper, which was employed with the use of Ladybug, Honeybee, and Octopus plug-ins. The results revealed that the adaptive facade system can improve indoor daylight levels and energy performance simultaneously compared to the conventional shading system. The presented framework may be used as a reference model, which can enhance opportunities to solve complex design problems in the early design stages and suggest recommendations for sustainable building design.

Keywords: parametric analysis; multi-objective optimization; daylight; energy consumption; hospital building; hot and arid climate (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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