A microclimate-based framework for multi-objective optimization of residential building design

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Abstract
The building sector accounts for 40% of global energy consumption and 39% of carbon emissions, with climate change-induced extreme weather exacerbating energy demands and indoor habitability. Addressing this challenge is crucial for achieving the United Nations Sustainable Development Goals 11 and 13. However, existing research predominantly focuses on single-objective optimizations, lacking systematic multi-objective approaches. This study develops a synergistic optimization model integrating microclimate simulations (ENVI-MET and Grasshopper) with non-dominated sorting genetic algorithm II to simultaneously balance thermal comfort, energy consumption, and economic cost. A case study in Hebei Province, China—a temperate monsoon climate region with significant urbanization challenges—demonstrates compelling results: 2–3 °C indoor temperature reduction, 15%–20% energy savings, with only 5%–8% construction cost increase. This research provides a robust, replicable framework empowering architects and planners to optimize sustainable and climate-resilient residential building design.
Funding Information
  • the Hebei Province Major Science and Technology Support Plan Project (252D6101D)
  • Hebei Provincial Construction Science and Technology Research Project (2025-2099)

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