Optimising energy efficiency and daylighting performance for designing vernacular architecture - A case study of Rawshan

Alelwani, Raed, Ahmad, Muhammad Waseem, Rezgui, Yacine ORCID: https://orcid.org/0000-0002-5711-8400 and Alshammari, Kaznah 2025. Optimising energy efficiency and daylighting performance for designing vernacular architecture - A case study of Rawshan. Sustainability 17 (1) , 315. 10.3390/su17010315

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Abstract

Building optimisation techniques provide a rigorous framework for exploring new optimal design solutions. In this study, a genetic algorithm (GA) was used to investigate the energy efficiency of a vernacular architectural element (Rawshan) in Saudi Arabia. Two objectives were optimised using a GA simulation enhanced: energy consumption optimisation and useful daylight illuminance (UDI) optimisation. A calibrated simulation model of a typical house in Saudi Arabia was used in the study. Several metrics, such as light interference from shadows or other windows, were considered to indicate the importance of the Rawshan. Computational studies were performed using different climatic conditions, and the results were compared with and without a Rawshan element using the weather data of Mecca, Jeddah, Riyadh, and Al-Baha. In this study, the blind thicknesses on the front and sides of the Rawshan were used as optimisation variables. The results showed that using a GA with energy consumption as an objective can reduce energy consumption. One of the methods proposed in the paper can reduce energy consumption by 3.6%, 3.6%, and 16.6% for Mecca, Riyadh, and Al-Baha, respectively. The single-objective optimisation method demonstrated that Rawshan provided sufficient UDI in four cities: Mecca, Jeddah, Riyadh, and Al-Baha. The research provided optimised values for Rawshan blind thicknesses on the front and lateral sides under different optimisation constraints. The results showed that using Rawshans in modern building architecture can reduce energy consumption and improve useful daylight illuminance.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Publisher:	MDPI
ISSN:	2071-1050
Date of First Compliant Deposit:	7 January 2025
Date of Acceptance:	27 December 2024
Last Modified:	28 Jan 2025 16:15
URI:	https://orca.cardiff.ac.uk/id/eprint/175076

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