Recently, the energy saving potential from using setpoint temperatures based on adaptive comfort has been studied. This study proposes a computational approach, the Adaptive-Comfort-Control-Implementation Script (ACCIS), to extend the air-conditioning usage to adaptive comfort. ACCIS transforms PMV-based into adaptive setpoint building energy models according to both an Input Data File (IDF) and the setup specified by the user. Originally, ACCIS was an Energy Management System (EMS) script, but available functions have been extended, and ACCIS has been nested in an ease-to-use Python package called Adaptive Comfort Control Implemented Model (“accim”). A case study has been tested, whose results showed that adaptive setpoint temperatures could achieve an 83% of energy savings. However, its most powerful attribute is that it allows many simulations to be run with no limit because of both its high customisation properties and the fact that it allows the same IDF to be run with various EPW files.

最近，已经研究了使用基于自适应舒适度的设定点温度的节能潜力。本研究提出了一种计算方法，即自适应舒适控制实施脚本 (ACCIS)，以将空调使用扩展到自适应舒适度。ACCIS 根据输入数据文件 (IDF) 和用户指定的设置，将基于 PMV 的建筑能源模型转换为自适应设定点建筑能源模型。最初，ACCIS 是一个能源管理系统 (EMS) 脚本，但已经扩展了可用功能，并且 ACCIS 已嵌套在一个易于使用的 Python 包中，称为自适应舒适控制实现模型（“ accim”）。一个案例研究已经过测试，其结果表明自适应设定点温度可以实现 83% 的节能。然而，它最强大的属性是它允许无限制地运行许多模拟，因为它具有高度的自定义属性，并且允许使用不同的 EPW 文件运行相同的 IDF。