Comfort, carbon emissions, and cost of building envelope and photovoltaic arrangement optimization through a two-stage model

Zhan, Jin; He, Wenjing; Huang, Jianxiang

doi:10.1016/j.apenergy.2023.122423

Cited by 14 publications

(2 citation statements)

References 54 publications

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“…Photovoltaic panels, as a renewable energy source, can reduce energy consumption in buildings by converting sunlight into electricity (U.S. EIA 2022). Different studies indicated the importance of photovoltaic panels (Zhan et al, 2024;Samarasinghalage et al 2022); for instance, studies in China have shown that net-zero energy buildings can be achieved by integrating photovoltaic systems (BIPV) on the rooftops of lowrise residential buildings (Liu et al 2019;Feng et al 2023). Similarly, a study by Sorgato et al (2018) conducted in six Brazilian cities found that these systems could meet the net energy consumption requirements of 4-story office buildings.…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of building envelope parameters and adopting PV panels to reduce reliance on local generators in hot-dry climate

Ibrahim,

Zangana,

Dehghanifarsani

2024

Int. J. Renew. Energy Dev.

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The growing energy demand, associated with the inability of the current infrastructure to satisfy this demand, has presented numerous challenges in Iraq's electricity sector. As a result, there has been an increased dependence on local diesel generators to mitigate power outages in homes. However, these generators raise environmental concerns and are associated with high operating CO₂ emissions. Here, using the DesignBuilder and EnergyPlus simulation software, the effectiveness of different building envelope modifications and photovoltaic panels as alternative energy sources was examined. Specifically, the impact of wall and roof insulation, window glazing, and shading devices on energy efficiency was analyzed. The results indicated that roof insulation is the most effective in reducing energy consumption by 28.8%, followed by wall insulation by 13.01%, while the effect of windows glazing and shading devices was insignificant. Furthermore, the installation of solar panels led to a significant reduction in energy demand by 53.6%, thereby decreasing operating carbon dioxide emissions and providing a practical alternative to the use of local generators. Our study offers valuable insights into the design of energy-efficient residential buildings in hot and dry climates. It highlights the importance of selecting appropriate building materials and integrating renewable energy sources, presenting a more environmentally effective solution to mitigate energy shortages.

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Section: Introductionmentioning

confidence: 99%

Effectiveness of building envelope parameters and adopting PV panels to reduce reliance on local generators in hot-dry climate

Ibrahim,

Zangana,

Dehghanifarsani

2024

Int. J. Renew. Energy Dev.

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“…As studies continue to report on green design analyses for various structural systems and the application of different optimisation techniques, research in structural optimisation considering environmental impacts remains an active area. Recently, there has been increased research interest on green structural design in approaches using heuristic techniques such as GA, SA, evolutionary computation, and differential evolution, as well as machine learning applications (Zhan et al, 2024;Chen et al, 2023;Farahzadi & Kioumarsi, 2023;Kaveh et al, 2020;Eleftheriadis et al, 2018;Kanyilmaz et al, 2022;Gan et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Green Design Model Based on Costs, Co2 Emissions and Serviceability for High-Rise Buildings With a Mega-Structure System

Choi,

Lee,

Hong

et al. 2024

Journal of Civil Engineering and Management

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In light of growing environmental concerns, the reduction of CO2 emissions is increasingly vital. Particularly in the construction industry, a major contributor to global carbon emissions, addressing this issue is critical for environmental sustainability and mitigating the accelerating impacts of climate change. This study proposes the Optimal Green Design Model for Mega Structures (OGDMM) to optimise CO2 emissions, cost-effectiveness, and serviceability in highrise buildings with mega structures. The OGDMM examines the impact of each material and structural design of main members on these three critical aspects. Analytical results for high-rise buildings (120–200 m, slenderness ratio: 2.0–8.0) demonstrate that OGDMM can reduce CO2 emissions and costs by an average of 4.67% and 3.97%, respectively, without compromising serviceability. To ensure comprehensive evaluation, this study introduces five new evaluation indicators encompassing environmental, economic, and serviceability performances of high-rise buildings. Based on these criteria, optimised structural designs for high-rise buildings are classified into four categories according to slenderness ratio, leading to the formulation of corresponding design guidelines. The model’s applicability is further validated through its application to a 270-m-tall high-rise building in Korea, showing reductions in CO2 emissions and costs by 8.99% and 18.50%, respectively, while maintaining structural serviceability.

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Controllable cross-building multi-objective optimisation for NZEBs: A framework Utilising parametric generation and intelligent algorithms

Liu,

Fang,

Cui

et al. 2024

Applied Energy

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Comfort, carbon emissions, and cost of building envelope and photovoltaic arrangement optimization through a two-stage model

Cited by 14 publications

References 54 publications

Effectiveness of building envelope parameters and adopting PV panels to reduce reliance on local generators in hot-dry climate

Effectiveness of building envelope parameters and adopting PV panels to reduce reliance on local generators in hot-dry climate

Multi-Objective Green Design Model Based on Costs, Co2 Emissions and Serviceability for High-Rise Buildings With a Mega-Structure System

Controllable cross-building multi-objective optimisation for NZEBs: A framework Utilising parametric generation and intelligent algorithms

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