Multi-Objective Optimization-Driven Research on Rural Residential Building Design in Inner Mongolia Region

Energies, Journal Year: 2025, Volume and Issue: 18(7), P. 1867 - 1867

Published: April 7, 2025

According to the China Building Energy Consumption and Carbon Emissions Research Report (2023), construction industry accounts for 36.3% of total societal energy consumption, with residential buildings contributing significantly due their extensive coverage high operational frequency. Addressing efficiency carbon reduction in this sector is critical achieving national sustainability goals. This study proposes an optimization methodology rural dwellings Inner Mongolia, focusing on reducing demand while enhancing indoor thermal comfort daylight performance. A parametric model was developed using Grasshopper, (PPD), Useful Daylight Illuminance (UDI) simulated through Ladybug Honeybee tools. Key parameters analyzed include building morphology, envelope structures, environments, followed by systematic components. To refine multi-objective inputs, a specialized wall database established, enabling categorization dynamic visualization material properties methods. Comparative analysis demonstrated 22.56% 19.26% decrease occupant dissatisfaction 25.44% improvement UDI values post-optimization. The proposed framework provides scientifically validated approach improving environmental adaptability cold-climate architecture.

Language: Английский

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Revealing the Driving Factors of Household Energy Consumption in High-Density Residential Areas of Beijing Based on Explainable Machine Learning

Buildings, Journal Year: 2025, Volume and Issue: 15(7), P. 1205 - 1205

Published: April 7, 2025

This study explores the driving factors of household energy consumption in high-density residential areas Beijing and proposes targeted energy-saving strategies. Data were collected through field surveys, questionnaires, interviews, covering 16 influencing across household, building, environment, transportation categories. A hyperparameter-optimized ensemble model (XGBoost, RF, GBDT) was employed, with XGBoost combined genetic algorithm tuning performing best. SHAP analysis revealed that key varied by season but included floor level, daily travel distance, building age, greening rate, water bodies, age. The findings inform strategies such as optimizing workplace–residence layout, improving insulation, increasing green spaces, promoting community programs. provides refined data support for management areas, enhances application technologies, encourages low-carbon lifestyles. By effectively reducing carbon emissions during operational phase it contributes to urban development China’s “dual carbon” goals.

Language: Английский

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Comprehensive Cost–Energy Evaluation of Wall Insulation for Diverse Orientations and Seasonal Usages

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(18), P. 8239 - 8239

Published: Sept. 12, 2024

An optimization study on thermal insulation applied to building exteriors has been performed in this research. Solar radiation considered while obtaining optimum thicknesses for various directions. Analyses have conducted not only the cardinal directions (south, north, west, and east) but also intermediate (southeast, northeast, northwest, southwest). received by vertical walls cooling heating degree day values computed according This research examines most suitable different seasonal usage scenarios, considering cooling, heating, annual energy demands. Variations cost savings, savings rates, payback periods, demands, wall orientations presented. Additionally, correlations providing total based thickness each direction scenarios determined. The results indicate that incoming solar varies from 52.08 W/m2 111.82 across orientations, range 23.48 USD/m2 24.56 USD/m2, with rates between 69.8% 70.3%. Payback periods 5.94 6.05 years. Depending orientation, vary 4.52 5.02 cm 1.56 2.09 5.92 6.08 requirements. demands ranged 54.8 MJ/m2 58.38 MJ/m2, varied 10.91 12.08 depending orientation. It concluded ideal meeting orientation building’s use purpose.

Language: Английский

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How Does Digital Economy Influence Green Mobility for Sustainable Development? Moderating Effect of Policy Instruments

Sustainability, Journal Year: 2024, Volume and Issue: 16(21), P. 9316 - 9316

Published: Oct. 26, 2024

The role of green mobility as a low-carbon lifestyle in carbon reduction and sustainable development cannot be ignored. digital economy effectively promotes for energy use the broader setting significant data era development. This study utilizes panel 264 cities China from 2011 to 2021 construct two-way fixed-effects regression model analyze impact on residents’ indirect mechanism two policy tools, transportation pilot emissions trading, theoretical empirical aspects. results show that economic helps promote mobility. In addition, implementation pilots trading policies has strengthened promoting findings remain after introducing robustness tests such “smart city” exogenous shock policies. A heterogeneity suggests effect residents is more economically developed human capital-rich areas. contributes literature by providing evidence urban demonstrating moderating effects instruments, thereby offering practical insights policymakers aiming reduce pollution enhance

Language: Английский

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