Breakthrough in Renewable Energy: Novel Semitransparent Photovoltaic Glazing for Low-Carbon Building Goals

Strategic Insights -

Researchers at the Hong Kong University of Science and Technology have developed a novel semitransparent photovoltaic glazing (STPV) integrated with a passive cooling film, opening up new possibilities for achieving low-carbon building goals. This innovative technology has been designed to combine experimental testing, numerical simulation, and machine learning prediction to evaluate its thermal and electrical performance. The research, supported by the RGC Early Career Scheme project and the Hong Kong Research Grants Council, demonstrates a significant improvement in energy efficiency and suggests a new technological pathway for building energy efficiency.

Key Takeaways:

  • The novel STPV glazing with integrated cooling film reduces the U-value by 44% compared to conventional STPV glazing, resulting in a 15% decrease in inner surface temperature.
  • The integration of the cooling film can reduce building air conditioning energy consumption by about 3% in Hong Kong climate.
  • Machine learning models, specifically Artificial Neural Networks (ANN), have achieved 99% prediction accuracy, outperforming Convolutional Neural Networks (CNN) models.
  • The research has identified significant correlations between the surface temperature of the STPV glazing, conversion efficiency, solar radiation intensity, and output power of the STPV glazing.
  • This innovative technology provides new solutions for the application of BIPV technology in high-density urban environments and holds considerable theoretical and practical implications for advancing low-carbon building development and renewable energy utilization.

Statistics:

  • 44% reduction in U-value of STPV glazing with integrated cooling film compared to conventional STPV glazing.
  • 15% decrease in inner surface temperature of STPV glazing with integrated cooling film.
  • 3% reduction in building air conditioning energy consumption in Hong Kong climate.
  • 99% prediction accuracy of Artificial Neural Network (ANN) model.

Sources:

  • NewsRx. New Renewable Energy Study Findings Recently Were Reported by Researchers at Hong Kong University of Science and Technology (Machine Learning Assisted Energy Performance Analysis of Semi-transparent Photovoltaic Glazing With Radiative Cooling ...). Ecology, Environment & Conservation. September 5, 2025; p 491.
  • Machine Learning Assisted Energy Performance Analysis of Semi-transparent Photovoltaic Glazing With Radiative Cooling Film. Energy and Buildings, 2025;342.
  • Elsevier Science Sa. Contact: Energy and Buildings, www.journals.elsevier.com/energy-and-buildings/
  • Hong Kong University of Science and Technology. Contact: Changying Xiang, Div Integrat Syst & Design.