A Predictive Nighttime Ventilation Algorithm to Reduce Energy Use and Peak Demand in an Office Building  

作　　者：Hatef Aria Hashem Akbari 

机构地区：[1]Department of Building, Civil and Environmental Engineering, Concordia University, Montreal H3G1M6, Canada

出　　处：《Journal of Energy and Power Engineering》2013年第10期1821-1830,共10页能源与动力工程（美国大卫英文）

摘　　要：The effect of two nighttime ventilation strategies on cooling and heating energy use is investigated for a prototype office building in several northern America climates, using hourly building energy simulation software （DOE2.1E）. The strategies include： scheduled-driven nighttime ventilation and a predictive method for nighttime ventilation. The maximum possible energy savings and peak demand reduction in each climate is analyzed as a function of ventilation rate, indoor-outdoor temperature difference, and building thermal mass. The results show that nighttime ventilation could save up to 32% cooling energy in an office building, while the total energy and peak demand savings for the fan and cooling is about 13% and 10%, respectively. Consequently, finding the optimal control parameters for the nighttime ventilation strategies is very important. The performance of the two strategies varies in different climates. The predictive nighttime ventilation worked better in weather conditions with fairly smooth transition from heating to cooling season.

关 键 词：Nighttime ventilation predictive control energy and peak demand savings thermal mass building energy simulations. 

分 类 号：TU243[建筑科学—建筑设计及理论] TK511.2[动力工程及工程热物理—热能工程]