Computational approach to extend the air-conditioning usage to adaptive comfort: Adaptive-Comfort-Control-Implementation Script

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.

Automated summary

The study introduces a computational approach, ACCIS, to extend air-conditioning usage to adaptive comfort, aiming to achieve energy savings. Results from a case study showed that adaptive setpoint temperatures could save up to 83% of energy. ACCIS allows for unlimited simulations with high customization properties, making it a powerful tool for energy efficiency.