Operational parameters of air handling units (AHUs) play an important role in the energy and comfort performance of commercial buildings. Current guidelines to determine these parameters are based on heuristics and are not informed by formal optimization. This paper presents a building performance optimization method to derive sequence of operations for multi-zone AHUs. To this end, 27 variants of a generic EnergyPlus office building model are built representing three levels of occupancy, envelope, and HVAC capacity scenarios. The supply temperature, morning start time, and economizer settings of the model are optimized for the 27 scenarios by using a genetic algorithm. The results highlight that optimal supply temperature setpoints transition from ∼12°C to a range of ∼16°C to ∼20°C over an outdoor temperature range of ∼20°C to ∼0°C. Energy savings are estimated as ∼20% relative to a reference case with a constant supply temperature and preheating/precooling period.

空气处理机组（AHU）的运行参数在商业建筑的能源和舒适性能中起着重要作用。当前确定这些参数的准则是基于试探法，而不是正式的优化方法。本文提出了一种建筑性能优化方法来推导多区域AHU的操作顺序。为此，构建了一个普通的EnergyPlus办公楼模型的27个变体，分别代表了三个级别的占用，围护和HVAC容量方案。通过使用遗传算法，针对27种情况优化了模型的供应温度，早晨开始时间和省煤器设置。结果突出表明，在约20°C至约0°C的室外温度范围内，最佳电源温度设定点从约12°C转变为约16°C至约20°C的范围。