Large-scale prediction of solar irradiation, shading impacts, and energy generation on building Façade through urban morphological indicators: A machine learning approach

Energy and Buildings, Год журнала: 2024, Номер unknown, С. 114797 - 114797

Опубликована: Сен. 1, 2024

Язык: Английский

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Effect of urban morphology on microclimate and building cluster energy consumption in cold regions of China

Sustainable Cities and Society, Год журнала: 2024, Номер unknown, С. 105838 - 105838

Опубликована: Сен. 1, 2024

Язык: Английский

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Weather clustering for machine learning-based hourly building energy prediction models at design phase

Energy and Buildings, Год журнала: 2025, Номер unknown, С. 115308 - 115308

Опубликована: Янв. 1, 2025

Язык: Английский

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The CEEMDAN-EWT-CNN-GRU-SVM Model: A Robust Framework for Decomposing Non-Stationary Time Series, Extracting Data features, and Predicting Solar Radiation

Results in Engineering, Год журнала: 2025, Номер unknown, С. 104267 - 104267

Опубликована: Фев. 1, 2025

Язык: Английский

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Development of data-driven estimation models of village carbon emissions by built form factors: The study in Huaihe River Basin, China

Building and Environment, Год журнала: 2025, Номер unknown, С. 112846 - 112846

Опубликована: Март 1, 2025

Язык: Английский

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Deep learning for sensible cooling and heating loads associated with solar panels of residential buildings in arid climate

Smart and Sustainable Built Environment, Год журнала: 2025, Номер unknown

Опубликована: Март 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.

Язык: Английский

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Optimizing Energy Efficiency: Louver Systems for Sustainable Building Design

Buildings, Год журнала: 2025, Номер 15(7), С. 1183 - 1183

Опубликована: Апрель 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.

Язык: Английский

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An Overview of the Research on the Correlation between Solar Energy Utilization Potential and Spatial Morphology

Results in Engineering, Год журнала: 2024, Номер 24, С. 103444 - 103444

Опубликована: Ноя. 17, 2024

Язык: Английский

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Evaluating cities' solar potential using geographic information systems: A review

Renewable and Sustainable Energy Reviews, Год журнала: 2024, Номер 209, С. 115112 - 115112

Опубликована: Ноя. 20, 2024

Язык: Английский

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Energy yield of solar PV in 34 Indonesian cities with respect to various roof pitches and orientations

International Journal of Environmental Science and Technology, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 20, 2024

Язык: Английский

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