In Kuwait, where the government subsidizes approximately 95% of residential electricity bills, most of the country’s energy consumption is for residential use. In particular, air-conditioning (AC) systems for cooling, which are used throughout the year, are responsible for residential electric energy consumption. This study aimed to reduce the amount of energy consumed for cooling purposes by developing a thermal comfort-based controller. Our study commenced by using a simulation model to investigate the possibility of energy reduction when using the predicted mean vote (PMV) for optimal control. The result showed that control optimization would enable the cooling energy consumption to be reduced by 33.5%. The influence of six variables on cooling energy consumption was then analyzed to develop a thermal comfort-based controller. The analysis results showed that the indoor air temperature was the most influential factor, followed by the mean radiant temperature, the metabolic rate, and indoor air velocity. The thermal comfort-based controller-version 1 (TCC-V1) was developed based on the analysis results and experimentally evaluated to determine the extent to which the use of the controller would affect the energy consumed for cooling. The experiments showed that the implementation of TCC-V1 control made it possible to reduce the electric energy consumption by 39.5% on a summer representative day. The results of this study indicate that it is possible to improve indoor thermal comfort while saving energy by using the thermal comfort-based controller in residential buildings in Kuwait.
Bibliographical noteFunding Information:
Funding: This research was funded by the Korea Institute of Energy Technology Evaluation and Planning and the Republic of Korea Ministry of Trade, Industry & Energy (grant number 20168510011550).
© 2019 by the authors.
All Science Journal Classification (ASJC) codes
- Renewable Energy, Sustainability and the Environment
- Energy Engineering and Power Technology
- Energy (miscellaneous)
- Control and Optimization
- Electrical and Electronic Engineering