Optimizing Urban Block Morphology for Energy Efficiency and Photovoltaic Utilization: Case Study of Wuhan DOI Creative Commons

Ruoyao Wang,

Yanyan Huang, Guoliang Zhang

и другие.

Buildings, Год журнала: 2025, Номер 15(7), С. 1118 - 1118

Опубликована: Март 29, 2025

With global carbon emissions continuing to rise and urban energy demands growing steadily, understanding how block morphology impacts building photovoltaic (PV) efficiency consumption has become crucial for sustainable development climate change mitigation. Current research primarily focuses on individual optimization, while block-scale coupling relationships between PV utilization remain underexplored. This study developed an integrated prediction optimization tool using deep learning physical simulation assess design parameters (building morphology, orientation, layout) affect performance. Through a methodology combining modeling, potential assessment, simulation, the quantified parameters, utilization, consumption. Results demonstrate that appropriate forms layouts reduce shadow obstruction, enhance system capability, simultaneously improve reducing The provides improved accuracy, enabling planners scientifically maximize generation minimize use. Extensive experimental validation demonstrates model analytical methods proposed in this will help break through limitations of research, making PV-energy analysis at scale possible, providing scientific basis achieving low-carbon transformation sector.

Язык: Английский

AI-Driven Green Building Technology Innovation: Knowledge Structure, Evolution Trends, Research Paradigms and Future Prospects DOI Creative Commons
Wu Jie, Qinge Wang, Zhenxu Guo

и другие.

Buildings, Год журнала: 2025, Номер 15(10), С. 1754 - 1754

Опубликована: Май 21, 2025

The rapidly evolving domain of artificial intelligence (AI) is significantly influencing the green building (GB) sector, acting as a catalyst for technology innovation (GBTI). Notably, unlike AI applications in buildings (AI-in-GB), AI-driven GBTI positions central force, promoting and leading novel technological breakthroughs. Although research has been conducted AI-in-GB, there remains lack in-depth analysis on advancements. To address this gap, study comprehensively reviews existing GBTI, systematically organizing analyzing knowledge structure, thematic evolution, paradigms, potential future directions. This conducts bibliometric analyses 151 publications sourced from Scopus using VOSviewer CiteSpace, capturing temporal characteristics, hotspots, frontiers area. Additionally, based dynamic topic modeling, analyzes 86 representative articles, identifying three key themes their evolution trends, elucidating framework within field. Through further discussion, reveals four core paradigms proposes directions, providing theoretical support guidance its continued development. first to focus contributing comprehensive understanding expanding GBTI.

Язык: Английский

Процитировано

0
The impact of urban canyon illumination levels on visual comfort and energy consumption in buildings: A case study of Kermanshah DOI

Mahtab Yarmoradi,

Nazanin Nasrollahi

Energy and Buildings, Год журнала: 2025, Номер unknown, С. 115510 - 115510

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0
Optimizing Urban Block Morphology for Energy Efficiency and Photovoltaic Utilization: Case Study of Wuhan DOI Creative Commons

Ruoyao Wang,

Yanyan Huang, Guoliang Zhang

и другие.

Buildings, Год журнала: 2025, Номер 15(7), С. 1118 - 1118

Опубликована: Март 29, 2025

With global carbon emissions continuing to rise and urban energy demands growing steadily, understanding how block morphology impacts building photovoltaic (PV) efficiency consumption has become crucial for sustainable development climate change mitigation. Current research primarily focuses on individual optimization, while block-scale coupling relationships between PV utilization remain underexplored. This study developed an integrated prediction optimization tool using deep learning physical simulation assess design parameters (building morphology, orientation, layout) affect performance. Through a methodology combining modeling, potential assessment, simulation, the quantified parameters, utilization, consumption. Results demonstrate that appropriate forms layouts reduce shadow obstruction, enhance system capability, simultaneously improve reducing The provides improved accuracy, enabling planners scientifically maximize generation minimize use. Extensive experimental validation demonstrates model analytical methods proposed in this will help break through limitations of research, making PV-energy analysis at scale possible, providing scientific basis achieving low-carbon transformation sector.

Язык: Английский

Процитировано

0