人因－能效”协同的高铁站智慧化热环境设计方法

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Abstract： Current thermal environment designs for high-speed railway stationsare predominantlybased onsteady-stateassumptionsand confined to single spaces.Suchapproaches fail to meet passengers' actual needsandconsequentlyresultinreduced thermal comfort and diminished building energy efficiency.This study proposes an intelligent thermal environmentdesignmethodology for high-speed railwaystations，aiming tosynergisticallyoptimizepassengerthermal comfort and building energy performance.The proposed approach employsartificial intelligence （Al） techniquestoestablishadatadriven“perception-prediction-optimization"workflow.It integrates human perception data with energy consumption information to construct predictive models of thermal comfort and energy efficiency， whileapplying intelligentoptimizationalgorithmstoimproveboth simultaneously.Validation throughareal-world case studyof a large high-speed railway station ina cold region demonstrates that the proposed method can improve thermal comfort by up to 67.40% and reduce energy consumption by 34.75% .Theresearch findings provide a scientific foundation for revising thermal environment design standards in high-speed railway stations and present a transferable framework and technical pathway for Al-enabled thermal environment design in public buildings.

Keywords：High-speed railwaystations;Artificial intelligence;Thermal comfort; Energy use intensity; Thermal environment design

引言：

随着全球气候危机加剧，实现2050年全球二氧化碳净零排放已成为国际社会日益强化的政治共识与行动目标[1]。（剩余13631字）