Impact of Energy Efficient Design Parameters on Energy Consumption in Hot-Humid Climate Zones

Yakut, Melik Ziya; ESEN, Sinem

doi:10.17515/resm2019.156ic2809

Cited by 1 publication

(2 citation statements)

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“…Assessing the performance of the most common simulating and modeling applications for green building energy consumption [18].…”

Section: Aim Methods Findings and Limitationsmentioning

confidence: 99%

“…Suitable energy analysis software can not only provide accurate analysis results, but it can also improve the efficiency of the analysis. In order to find suitable software for the energy performance of a building, Al Ka'bi [18] evaluated the performance of the most common simulating and modeling applications for green building energy consumption. They compared and ranked the building energy analysis performance of 10 of the most common energy in the unifying criteria, and the final ranked result in descending order was as follows: (1) TRNSYS, (2) Ecotect, (3) Autodesk-GBS, (4) EnergyPlus, (5) IES-VE, (6) IDAICE, (7) VIP-Energy, (8) DesignBuilder, (9) eQUEST, and (10) RIUSKA.…”

Section: Aim Methods Findings and Limitationsmentioning

confidence: 99%

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Using Regression Model to Develop Green Building Energy Simulation by BIM Tools

et al. 2022

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Energy consumption in the building sector poses a huge burden in terms of global energy and pollution. Recent advancements in building information modelling and simulating building energy performance (BEP) have provided opportunities for energy optimization. The use of building information modelling (BIM) also has increased significantly in the last decade based on the requirement to accommodate and manage data in buildings. By using the data, some building information modelling tools have developed the function of energy analysis. This paper aims to identify design parameters critical to BEP to assist architects in the initial stages of building design and to investigate their relationship. The outcomes of the prototype model’s energy simulations were then used to construct multilinear regression models. For the rest of the independent building design variables, linear regression models are used to analyse the relationship between it and energy consumption. It was concluded that, in the same building conditions, diamond-shaped buildings have the highest energy consumption, while triangle-shaped buildings showed the most efficient energy performance through energy simulations for seven fundamental prototype building models based on Autodesk Kits, Green Building Studio (GBS) with a Doe-2 engine. In addition, the developed regression models are validated to within 10% error via a case study of the ABS building. At the end of this paper, recommendations are provided on energy optimisation for the initial stages of building design. The parametric analysis of design variables in this study contributed to the total energy consumption at the early phases of design and recommendations on energy optimization.

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“…Assessing the performance of the most common simulating and modeling applications for green building energy consumption [18].…”

Section: Aim Methods Findings and Limitationsmentioning

confidence: 99%

Section: Aim Methods Findings and Limitationsmentioning

confidence: 99%