Energy savings and guaranteed thermal comfort in hotel rooms through nonlinear model predictive controllers

This paper presents the results obtained during the synthesis of nonlinear predictive controllers dedicated to the energy management of centralized air conditioning systems in the rooms from two city hotels. The model for predictions is based on the Radiant Time Series (RTS) method. To satisfy the thermal comfort required by the occupants, an adaptive model is considered explicitly in the economic objective function of the predictive controller. Historical records of electrical consumption from the two hotel facilities are used for comparing the performance of the controllers. Results obtained in simulation using real data as inputs show an improvement in energy consumption while maintaining the thermal comfort.