研究目的
To evaluate the potential for saving and generating energy in buildings using semi-transparent photovoltaic windows, focusing on the interaction among air conditioning energy consumption, lighting energy consumption, and energy generation in southwest China.
研究成果
STPV windows demonstrate significant energy saving potential, with up to 29% savings on sunny days in experimental tests and up to 54% in simulations for Kunming. The technology reduces cooling loads but may slightly increase heating and lighting consumption due to shading effects. It is most effective in regions with high solar radiation like Lhasa and Kunming.
研究不足
The study is limited to specific climatic conditions in southwest China and may not generalize to other regions. The experimental setup uses simplified building models, and real-world applications could have additional variables. The energy saving potential varies with weather conditions, and cloudy days showed increased lighting consumption.
1：Experimental Design and Method Selection:
The study involved building two identical test units (3m x 3m x 3m) with one fitted with double-skin STPV windows and the other with conventional windows. A three-factor model (lighting-heat-electricity) was established using Thermal balance model, Daylighting model, and Sandia PV model in EnergyPlus for simulation.
2：Sample Selection and Data Sources:
The test rig was built in Chengdu, China, and simulations were conducted for four cities (Lhasa, Kunming, Guiyang, Chengdu) representing different climates. Data included solar radiation, temperature, and energy consumption metrics.
3：List of Experimental Equipment and Materials:
Key instruments included outdoor multi-channel PV test equipment (Ceyear AV6595A), solar radiation test equipment (AV87110), weather station (J.t), multi-channel data recorder (J.t), thermocouples (J.t), light meter (J.t), and electricity recorder (BULL). Materials included double-skin STPV windows produced with Hanergy Company and conventional windows.
4：Experimental Procedures and Operational Workflow:
Experiments were conducted from June to August, measuring air conditioning and lighting electricity consumption, illuminance, temperature, and PV generation. Data was collected at 1-minute intervals. Simulations validated the model using ASHRAE guidelines.
5：Data Analysis Methods:
Data was analyzed to compare energy consumption and generation, using metrics like mean bias error (MBE) and coefficient of variation of root mean square error (Cv(RMSE)) for model validation.
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