Sky Classification and Performance Analysis of Transparent Building Integrated Photovoltaic (BIPV) facade Using Artificial Neural Networks (ANNs) Technology
DescriptionThe transparent building integrated photovoltaic (BIPV) facade with proper daylight linked lighting controls would be an appropriate building design strategy to generate a sustainable, environment-friendly and clean energy, as well as reduce the overall building electricity use. The proposed research project analyses the energy and cost performances for cooling-dominated buildings using transparent BIPV facades. The building envelop study will include vertical facades for side-lit rooms and skylights for atria. The optimum tilted angle and orientation for such solar facades to maximize energy collection and minimize the total building electricity expenditure will be explored. By using Artificial Neural Networks (ANNs) technology, the sky types will be identified and the building energy models will be established. The investigation will be conducted based on field measurements and computer modelling. The benefits in terms of energy and cost will be examined in detail. The techniques developed can contribute and have extensive implications to the integration of active solar and passive architecture designs.
|Effective start/end date||1/01/07 → 28/09/09|