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Abstract With the rapid development of photovoltaic technologies, building-integrated photovoltaic (BIPV) windows could be used to replace traditional glazing, especially semi-transparent amorphous silicon (a-Si) photovoltaic (STPV) windows which can generate electricity in situ and admit daylight into the indoor environment. The utilization of semi-transparent PV modules provides the benefit of low solar heat gain coefficient (SHGC) as a key characteristic of window products. Meanwhile, it also produces a drawback as the remaining solar energy could be converted into heat gain which increases cooling load. Due to the excellent thermal insulation performance of vacuum glazing, the integration of STPV and vacuum glazing provides the potential to achieve the best energy-efficient performance by the low solar heat gain of the PV modules and low heat losses of the vacuum glazing. However, the determination of a suitable glazing of a building in different locations must consider the climate background. In this paper, the thermal performance of the proposed vacuum photovoltaic insulated glass unit (VPV IGU) in different climate zones has been investigated. The simulation work has shown that the vacuum PV glazing can provide a significant energy saving potential in Harbin, Beijing, Wuhan and Hong Kong, which represent the severe cold, cold, hot summer and cold winter, and hot summer and warm winter regions, respectively. However, it is not suitable for the moderate climatic region like Kunming. The results have indicated the advantages of utilizing the vacuum PV glazing in different climates as well as its limitations. [ABSTRACT FROM AUTHOR]

In recent years, building-integrated photovoltaic (BIPV) windows have drawn attention from both the building industry and academic society. As a multifunctional application of photovoltaic technologies, semi-transparent BIPV panels can generate renewable energy in situ and play the role of typical windows. Unlike those PV windows made by crystalline silicon solar cells, the semi-transparent cadmium telluride (CdTe) photovoltaic (STPV) windows can admit natural daylight with a certain degree of transmittance without any shading. Therefore, it can provide better visual comfort to occupants. However, typical BIPV windows are not suitable for cold regions due to inadequate thermal insulation. To improve the thermal performance of the BIPV glazing, a novel CdTe-based vacuum PV glazing (VPV) is developed with a highly integrated three-layer structure. To fully understand the dynamic heat transfer process and thermal behaviour, this study developed a mathematical heat transfer model for the CdTe-based VPV. The dynamic heat transfer model was validated with laboratory tests. To investigate the whole year performance of the VPV, a dynamic coupling approach is proposed to integrate the transit heat transfer model with a whole building simulation model conducted by EnergyPlus to obtain more accurate simulation results. Comparing the simulation results of the decoupled and coupled methods, it was found that EnergyPlus tends to slightly underestimate the cooling energy consumption and overestimate the heating energy consumption to a considerable level. Therefore, the dynamic coupling approach is more reliable than the EnergyPlus model, especially in the heating-dominated regions. • A dynamic heat transfer model for the CdTe-based vacuum PV glazing was developed. • A validation experiment was conducted to verify the heat transfer model. • Wo coupling methods were proposed to integrate the heat transfer model with BES. • Reliable annual simulations for VPV were obtained by the dynamic co-simulation. [ABSTRACT FROM AUTHOR]

• A daylighting model and an energy simulation model of the vacuum PV glazing were developed. • The applicability and limitation of the vacuum PV glazing in different climates were investigated. • The vacuum PV glazing improves the energy performance of typical PV glazing. • The vacuum PV glazing can balance the daylighting availability and visual comfort. • The reversed and the reversible vacuum PV glazing can enhance the potential of the application. Amorphous silicon-based semi-transparent photovoltaic windows can produce renewable electricity and offer a certain amount of natural daylight for occupants. However, it has a deficiency as the absorbed solar energy would be partially transferred into additional cooling demand in summer. In this respect, a novel semi-transparent photovoltaic vacuum glazing is proposed to improve energy performance. The selection of appropriate glazing of an energy-efficient building should take into consideration the specific climate conditions. The daylighting behaviour of the glazing will also affect the daylighting performance as well as the lighting consumption. In this paper, the thermal performance, daylighting performance and overall energy performance of the proposed vacuum PV glazing in different climate regions have been investigated. A daylighting model was conducted by DAYSIM to evaluate the annual daylighting performance. It was found that the vacuum PV glazing can balance daylighting availability and visual comfort by providing sufficient daylight in the anterior half of the room and reducing daylight glare to the minimum level. The energy simulation by EnergyPlus demonstrated that the vacuum PV glazing has the energy-saving potential up to 43.4%, 66.0%, 48.8%, and 35.0% in Harbin, Beijing, Wuhan and Hong Kong, respectively. However, the applications of the vacuum glazing lead to additional cooling consumption in the moderate climate zone, such as Kunming. The results advanced the understanding on the applicability and limitation of the vacuum PV glazing in different climate backgrounds. Furthermore, the reversed and the reversible vacuum PV glazing were proposed to enhance the adaptability. The results suggest that the reversible vacuum PV glazing can act energy response in a more efficient way and fully utilize the energy-saving potential of the integration of the PV glazing and the vacuum glazing. [ABSTRACT FROM AUTHOR]

• A RADIANCE model of the vacuum PV glazing was developed and validated by laboratory tests. • An ANN daylighting prediction model was developed to reduce the simulation time. • A coupling method integrates the advanced daylighting prediction into the building energy model. • The prediction performance of the ANN model was evaluated. • More realistic results for lighting consumption were obtained by the ANN-based coupling. Window plays an essential role in the indoor environment and building energy consumption. As an innovative building integrated photovoltaic (BIPV) window, the vacuum PV glazing was proposed to provide excellent thermal performance and utilize renewable energy. However, the daylighting performance of the vacuum PV glazing and the effect on energy consumption have not been thoroughly investigated. Most whole building energy simulation used the daylighting calculation based on Daylight Factor (DF) method, which fails to address realistic calculation for direct sunlight through complex glazing materials. In this study, a RADIANCE model was developed and validated to adequately represent the daylight behaviour of a vacuum cadmium telluride photovoltaic glazing with a three-layer structure. However, RADIANCE will consume too many computational resources for a whole year simulation. Therefore, an artificial neuron network (ANN) model was trained based on the weather conditions and the RADIANCE simulation results to predict the interior illuminance. Subsequently, a preprocessing coupling method is proposed to determine the lighting consumption of a typical office with the vacuum PV glazing. The performance evaluation of the ANN model indicates that it can predict the illuminance level with higher accuracy than the daylighting calculation methods in EnergyPlus. Therefore, the ANN model can adequately address the complex daylighting response of the vacuum PV glazing. The proposed coupling method showed a more reliable outcome than the simulations sole with EnergyPlus. Furthermore, the computational cost can be reduced dramatically by the ANN daylighting prediction model in comparison with the RADIANCE model. Compared with the lighting consumption determined by the ANN-based coupling method, the two approaches in EnergyPlus, the split-flux method and the DElight method, tend to underestimate the lighting consumption by 5.3% and 9.7%, respectively. [ABSTRACT FROM AUTHOR]