The Impact of Occupancy-Driven Models on Cooling Systems in Commercial Buildings

Cooling systems play a key role in maintaining human comfort inside buildings. The challenges that are facing conventional cooling the rapid growth of total energy and annual electricity consumption commercial This is even more significant countries with an arid climate, where typically working 80% year. Thus, there has been growing interest developing smart control models to assign optimal setpoints recent years. In present work, we propose occupancy-based model based on non-linear optimization algorithm efficiently reduce costs. utilizes Monte-Carlo method determine approximate occupancy schedule for building thermal zones. We compare our proposed three different strategies, namely: always-on thermostat, schedule-based model, rule-based occupancy-driven model. Unlike these algorithms, approach white-box considers thermodynamic relationships system find setpoints. For comparison, case studies five cities around world were investigated. Our findings illustrate able noticeably Significantly, located severe hot regions, such as Doha Phoenix, can be reduced by 14.71% 15.19%, respectively.