Thesis (Senior Honors)
Space cooling of buildings consumes an estimated 6% of US energy per year and releases a comparable proportion of the country's greenhouse gases. Operable window shading has the potential to significantly reduce greenhouse gas emissions by limiting solar heat gain through windows, thereby reducing a building’s cooling load. In computational models, shades controlled using environmental parameters, particularly window heat flux, demonstrate greater reductions in heat gain than shades controlled by illumination, time of day, or other methods. However, the performance of shading when controlled by sensors in the field is unknown, and previous studies indicate that sensor noise may negate the promising effects of heat flux-controlled shading. This thesis explores the relationship between heat flux sensor noise and shading performance. A MATLAB interface is used to control shades in a series of EnergyPlus models, and net window heat gain is examined over a range of noise levels. This reveals that heat flux-controlled shading is far more effective than conventional controls, even with large amounts of noise. The performance of heat flux controls is assessed for the months of May, July, and October in seven cities representing arid, semi-arid, continental, and Mediterranean climates across the United States. Heat flux-controlled shades consistently outperform conventionally controlled shades in every location and season with noise at and even above anticipated levels, suggesting that inexpensive heat flux sensing has excellent potential to reduce cooling loads, diminish air-conditioning needs, and improve comfort in diverse climates.
Dartmouth Digital Commons Citation
Danis, Jackson, "Heat Flux Sensing for Actuation of Shading in Green Buildings" (2021). ENGS 88 Honors Thesis (AB Students). 27.