Daylight-electrical-thermal coupling model for real-time zero-energy potential analysis of vacuum-photovoltaic glazing

Abstract

Windows are considered as the main culprit of heat loss in buildings and the development of advanced glazing is a global necessity. Vacuum integrated photovoltaic (VPV) glazing was proven to have great air conditioning energy-saving potential, while there is a lack of real-time zero-energy potential evaluation that considers the interaction between thermal, power and daylight performances. Given this context, a daylight-electrical-thermal coupling model was developed using Python language for VPV glazing to evaluate its overall performance for optimal design towards real-time zero-energy goal. The coupling model integrated the numerical heat transfer model, electrical model, as well as decision tree and random forest algorithms for glare and illuminance prediction. All models were validated through full-scale outdoor experiments and showed acceptable errors between experimental and simulated data. Based on that, key parameters affecting the performance of the VPV glazing, namely PV coverage, emissivity of Low-E coating, pillar separation, and inner window shades were determined through sensitivity analysis. A case study of optimal design of the VPV glazing in hot summer and cold winter zone in China showed that VPV glazing with a PV coverage of 40%, a coating emissivity of 0.068, and a pillar separation of 90 mm can achieve 67% zero-energy hours throughout the year. This study can provide a validated coupled model for performance evaluation and optimization of VPV glazing for engineering applications.