A real scene 3D Model-Driven sunlight analysis method for complex building roofs DOI
Jinghai Xu, M. Qi, Haoran Jing

et al.

Energy and Buildings, Journal Year: 2024, Volume and Issue: 325, P. 115051 - 115051

Published: Nov. 13, 2024

Language: Английский

Large-scale prediction of solar irradiation, shading impacts, and energy generation on building Façade through urban morphological indicators: A machine learning approach DOI Creative Commons
Hongying Zhao, Chengyang Liu, Rebecca Yang

et al.

Energy and Buildings, Journal Year: 2024, Volume and Issue: unknown, P. 114797 - 114797

Published: Sept. 1, 2024

Language: Английский

Citations

6
Effect of urban morphology on microclimate and building cluster energy consumption in cold regions of China DOI
Peng Cui,

Jiaqi Lu,

Yutong Wu

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: unknown, P. 105838 - 105838

Published: Sept. 1, 2024

Language: Английский

Citations

4
Weather clustering for machine learning-based hourly building energy prediction models at design phase DOI Creative Commons
Dongxue Zhan, Shaoxiang Qin, Liangzhu Wang

et al.

Energy and Buildings, Journal Year: 2025, Volume and Issue: unknown, P. 115308 - 115308

Published: Jan. 1, 2025

Language: Английский

Citations

0
The CEEMDAN-EWT-CNN-GRU-SVM Model: A Robust Framework for Decomposing Non-Stationary Time Series, Extracting Data features, and Predicting Solar Radiation DOI Creative Commons
Sharareh Pourebrahim, Akram Seifi,

Mohammad Ehteram

et al.

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104267 - 104267

Published: Feb. 1, 2025

Language: Английский

Citations

0
Development of data-driven estimation models of village carbon emissions by built form factors: The study in Huaihe River Basin, China DOI
Zhixin Li, Siyao Wang, Hong Zhang

et al.

Building and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 112846 - 112846

Published: March 1, 2025

Language: Английский

Citations

0
Deep learning for sensible cooling and heating loads associated with solar panels of residential buildings in arid climate DOI
Abdulbasit Almhafdy, Amal A. Al-Shargabi

Smart and Sustainable Built Environment, Journal Year: 2025, Volume and Issue: unknown

Published: March 11, 2025

Purpose This study aims to develop accurate prediction models for heating and cooling demands in buildings equipped with solar panels. By integrating renewable energy technologies, the goal is design nearly energy-neutral that significantly reduce consumption enhance overall efficiency. Design/methodology/approach The research utilizes deep learning address variables building design, an area previous studies have not fully explored. A dataset from arid climate regions was used train test two predict output. evaluation focused on how well predicted needs, as amount of panels would need generate order meet these demands. approach represents advancement over methodologies by techniques context climates, where efficiency a critical concern. Findings developed this were highly predicting both requirements output suggests can effectively support energy-efficient buildings, ensuring provide enough cover building’s needs. Originality/value introduces novel method panel performance characteristics consumption, moving beyond traditional reliance environmental factors. It optimizes management systems enhancing accuracy applicability. use optimization ensures precise flexible predictions, providing holistic solution design. findings useful insights architects builders looking create zero-energy advancing field green technologies.

Language: Английский

Citations

0
Optimizing Energy Efficiency: Louver Systems for Sustainable Building Design DOI Creative Commons
Waseem Iqbal, Irfan Ullah, Asif Hussain

et al.

Buildings, Journal Year: 2025, Volume and Issue: 15(7), P. 1183 - 1183

Published: April 3, 2025

As the global focus on sustainability intensifies, architects and engineers are increasingly seeking innovative passive strategies to improve building energy efficiency. Among these strategies, strategic integration of louvers has garnered significant attention due their potential optimize envelope performance reduce consumption. Louvers effectively manage solar heat gain, mitigating impact extreme temperatures indoor spaces. Consequently, reliance active HVAC systems, leading notable savings a decreased carbon footprint. This paper presents comprehensive review role in enhancing efficiency, highlighting designs, improvement suggestions. Moreover, this article addresses challenges related louver design, such as balancing trade-off between gain daylighting how configurations for specific types. Approaches overcome challenges, including advanced modeling techniques parametric also explored assist designers achieving most energy-efficient outcomes.

Language: Английский

Citations

0
An Overview of the Research on the Correlation between Solar Energy Utilization Potential and Spatial Morphology DOI Creative Commons
Dexin Li, Xianghong Cui, Long Shi

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: 24, P. 103444 - 103444

Published: Nov. 17, 2024

Language: Английский

Citations

2
Evaluating cities' solar potential using geographic information systems: A review DOI
Paweł Drozd, Jacek Kapica, Jakub Jurasz

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2024, Volume and Issue: 209, P. 115112 - 115112

Published: Nov. 20, 2024

Language: Английский

Citations

1
Energy yield of solar PV in 34 Indonesian cities with respect to various roof pitches and orientations DOI
Beta Paramita, Rizki A. Mangkuto, Abdi Gunawan Djafar

et al.

International Journal of Environmental Science and Technology, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 20, 2024

Language: Английский

Citations

1