A framework for the simultaneous control of temperature, illumination and window roller blind position is considered. The occupants are allowable to adjust their comfort preference to a strict, mild or loose level. The cost function has two parts including energy consumption and comfort dissatisfaction, each of which is expected to be minimized based on the users' comfort settings. The control strategy is Model Predictive Control (MPC) and it computes a trajectory of future manipulated variables to optimize future room temperature, illumination and outside view along with the minimum possible departure from the desired level. Weather data like solar radiation, solar illumination and outside temperature are considered in the model with the aim of taking advantage of daylight without disrupting other comfort levels. Simulation analyses were performed for the summer and winter days revealing the influence of the roller blind position on the building total energy consumption. The simulation results affirm that the proposed model can save energy by minimally changing occupants' comfort requirements during some hours of the day.
['Sareh Agheb', 'Xiaoqi Tan', 'Danny H. K. Tsang']
Model predictive control of integrated room automation considering occupants preference