Abstract
Rural dwellings in China’s cold regions face significant challenges related to energy consumption, thermal comfort, and daylight, with a projected substantial increase in energy demand in the future. Scientifically optimized design during the early planning stages can significantly enhance indoor thermal and daylight conditions, effectively reducing energy consumption. This study focuses on Shandong Province to comprehensively analyze the optimization of geometry and envelope design of rural dwellings in China’s cold regions. It employs a multi-objective optimization method, integrating genetic algorithms with dynamic energy simulations, to minimize total energy demand while ensuring thermal comfort and sufficient daylight. Utilizing the Octopus plugin in Grasshopper, in conjunction with EnergyPlus, Ladybug, and Honeybee, this research optimizes and analyzes the impact of various design variables on energy consumption, thermal comfort and daylight, including room depth, window-to-wall ratio in different orientations, thermal performance of the envelope, and related glass material parameters. The results indicate that the selected variables have significant energy-saving potential. Compared to the case study building, the optimized solutions can reduce total energy demand by over 62.41%, with the highest savings rate reaching 88.75%. This study emphasizes the importance of integrated design and optimization strategies in enhancing the sustainability of rural dwellings. It proposes both cost-free and cost-included optimization schemes: the former maximizes the energy-saving, thermal comfort and daylight potential of the selected variables, while the latter is more practically feasible considering the economic constraints of rural areas. The proposed optimization schemes provide multiple reference solutions and theoretical foundations for users of rural dwellings in China’s cold regions.
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