A Study on the application of simulation-based simplified PMV regression model in office buildings

Recently, the Korean Government enacted a new law aimed at reducing energy losses in buildings throughout Seoul. According to the regulation, buildings over a certain size must keep the indoor temperature above 26 ℃ during the summer season and below 20 ℃ in the winter season. However, these energy-savings were accompanied by thermal discomfort for occupants who work indoors, thus leading to reduced work efficiency. In order to address these problems, several recently published studies have investigated thermal comfort controls that can reduce air-conditioning energy use while also satisfying the thermal comfort needs of occupants. However, thermal comfort controls can prove more difficult to monitor than temperature controls due to the way the existing regulation is written, with far more variables involved in the former. This creates additional costs for multiple measuring sensors, additional time required for monitoring, and an overall greater likelihood for errors. Thus, this study used EnergyPlus, a program with high accuracy for thermal comfort control prediction, to model an actual office building. A PMV regression analysis was conducted for this model based on a database of PMV variables. PMV regression model simplification was completed through sensitivity analysis, and the Energy Management System (EMS) in EnergyPlus was used to establish a simplified PMV regression analysis-based thermal comfort control.