Personal Information

  • Doctoral Supervisor
  • Master Tutor
  • (Associate Professor)
  • Name (Pinyin):

    Zhao Chuangyao
  • School/Department:

    Xi'an University of Architecture and Technology
  • Education Level:

    PhD student
  • Gender:

    Male
  • Contact Information:

    cyzhao@xauat.edu.n
  • Degree:

    Doctoral Degree in Engineering
  • Professional Title:

    Associate Professor
  • Status:

    Employed
  • Academic Titles:

    Associate Professor
  • Alma Mater:

    Xi'an Jiaotong University
  • Discipline:

    Heating, Gas Supply, Ventilating and Air Conditioning Engineering
    Engineering Thermophysics

Other Contact Information

  • Email:

Research Focus

Home >Research Focus

Building energy-saving technologies

  Building energy-saving technologies focus on systematically reducing lifecycle energy consumption and carb on emissions through passive design optimization (e.g., high-performance building envelopes, natural ventilation/daylighting), active system upgrades (high-efficiency HVAC, smart energy management), and renewable energy integration (solar, geothermal heat pumps, building-integrated photovoltaics). For existing building retrofits, key strategies include external wall insulation (vacuum insulation panels, aerogel composites), window replacement (low-emissivity glass, thermally broken aluminum frames), equipment efficiency enhancement (magnetic levitation chillers, variable-frequency heat pumps), and smart energy system reconstruction (digital twin monitoring, demand-response control), supported by policy incentives (e.g., China’s Green Retrofitting Standards for Existing Buildings), financial tools (green loans, energy performance contracting), and user behavior guidance. These efforts aim to transform high-energy-consuming buildings into near-zero-energy structures, exemplified by Germany’s Passivhaus retrofits and China’s Northern Clean Heating Project. Future challenges involve cost-sharing mechanisms, compatibility of energy efficiency with historic preservation, and AI-driven personalized energy-saving optimization.

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