Optimization of energy-efficient residential building design in Japan: A climate-responsive approach under current and future scenarios

• Investigates energy-efficient residential building designs across Japan’s diverse climatic zones. • Employs genetic algorithm to optimize thermal resistance and window-to-wall ratios. • Assesses building energy performance under current and future climate scenarios. • Reveals significant regional differences in heating and cooling energy demands. • Contributes to Japan's carbon neutrality goals with region-specific optimization strategies. Japan’s 2050 carbon neutrality goal demands optimized residential building energy efficiency amid diverse climates and future warming, intensified by polar amplification and urban heat island (UHI) effects. This study investigates climate-responsive designs for a 120.08 m² two-story residential model across ten Japanese cities—Sapporo, Akita, Sendai, Tokyo, Nagoya, Toyohashi, Osaka, Fukuoka, Kagoshima, and Naha—under current (2020s) and future (2080s) scenarios. Using high-resolution EnergyPlus weather data and a Genetic Algorithm (GA) in Python with the Distributed Evolutionary Algorithms in Python (DEAP) library, window-to-wall ratio (WWR) and R-values for roofs, walls, and windows were optimized to minimize energy use while maintaining thermal comfort per ISO 7730 (Predicted Mean Vote, PMV, -0.5 to +0.5). Results reveal regional contrasts: Sapporo’s heating drops 15,251 kWh annually with enhanced insulation (R roof = 6.0 m²K/W), while Naha’s cooling rises 3585 kWh, mitigated by higher WWR (0.45) for ventilation. Temperate Tokyo balances both, reducing energy by 6851 kWh with WWR = 0.29. This pioneering approach, among the first to integrate UHI and polar amplification into a GA-based optimization framework for Japanese climates, spans Japan’s climatic diversity, achieving energy savings and comfort through tailored designs—e.g., advanced glazing cuts southern peak loads by 23–27 %. Unlike static-focused studies, it offers future-adaptive guidelines, bridging simulation and practical design under evolving climates. This work advances sustainable architecture, supporting Japan’s low-carbon transition by providing region-specific strategies for long-term building performance and informing energy-efficient urban planning and policy development.

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Publication Details

Journal
Energy Nexus
Published
2025-11-21
DOI
https://doi.org/10.1016/j.nexus.2025.100605
Primary Topic
Building Energy and Comfort Optimization
Type
article
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article

Optimization of energy-efficient residential building design in Japan: A climate-responsive approach under current and future scenarios

Zhe Tian, Craig Farnham, Zhichao Jiao, Xiong Xiao et al.
Energy Nexus
Building Energy and Comfort Optimization
article

Optimization of energy-efficient residential building design in Japan: A climate-responsive approach under current and future scenarios

Zhe Tian, Craig Farnham, Zhichao Jiao, Xiong Xiao, Jiale Chai, Jihui Yuan, Zhengsong Lin, Yan Ding, Xiangfei Kong, Xiaochen Yang, Kazuo Emura
article en

Abstract

• Investigates energy-efficient residential building designs across Japan’s diverse climatic zones. • Employs genetic algorithm to optimize thermal resistance and window-to-wall ratios. • Assesses building energy performance under current and future climate scenarios. • Reveals significant regional differences in heating and cooling energy demands. • Contributes to Japan's carbon neutrality goals with region-specific optimization strategies. Japan’s 2050 carbon neutrality goal demands optimized residential building energy efficiency amid diverse climates and future warming, intensified by polar amplification and urban heat island (UHI) effects. This study investigates climate-responsive designs for a 120.08 m² two-story residential model across ten Japanese cities—Sapporo, Akita, Sendai, Tokyo, Nagoya, Toyohashi, Osaka, Fukuoka, Kagoshima, and Naha—under current (2020s) and future (2080s) scenarios. Using high-resolution EnergyPlus weather data and a Genetic Algorithm (GA) in Python with the Distributed Evolutionary Algorithms in Python (DEAP) library, window-to-wall ratio (WWR) and R-values for roofs, walls, and windows were optimized to minimize energy use while maintaining thermal comfort per ISO 7730 (Predicted Mean Vote, PMV, -0.5 to +0.5). Results reveal regional contrasts: Sapporo’s heating drops 15,251 kWh annually with enhanced insulation (R roof = 6.0 m²K/W), while Naha’s cooling rises 3585 kWh, mitigated by higher WWR (0.45) for ventilation. Temperate Tokyo balances both, reducing energy by 6851 kWh with WWR = 0.29. This pioneering approach, among the first to integrate UHI and polar amplification into a GA-based optimization framework for Japanese climates, spans Japan’s climatic diversity, achieving energy savings and comfort through tailored designs—e.g., advanced glazing cuts southern peak loads by 23–27 %. Unlike static-focused studies, it offers future-adaptive guidelines, bridging simulation and practical design under evolving climates. This work advances sustainable architecture, supporting Japan’s low-carbon transition by providing region-specific strategies for long-term building performance and informing energy-efficient urban planning and policy development.

Energy NexusVol. 20
Tianjin University (CN), Nanjing Forestry University (CN), Hebei University of Technology (CN), Osaka Metropolitan University (JP)
Openalex Percentile: Top 62%
Building Energy and Comfort Optimization
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