Model-based predictive control of office window shades

Abstract

In the automation of interior window shading devices, a control system that relies on a prediction of environmental conditions and a building's thermal response can provide savings to space-conditioning loads beyond what can be achieved using a reactive approach. The development of these control strategies can be difficult because of the uniqueness of each building. A simplified model-based predictive control (MPC) method for window shades is proposed. To this end, a control-oriented model representing the heat transfer problem in a perimeter office space was developed. The parameters of the model were estimated using the ensemble Kalman filter (EnKF). The energy-savings potential of the EnKF-based MPC approach for window shades was investigated using EnergyPlus simulations. This was accomplished by implementing the control-oriented model into the energy management system application of EnergyPlus. Simulations were conducted to assess the energy saving potential of using the EnKF-based MPC for roller blinds in a south-facing perimeter office space in Ottawa, Canada. The simulation-based results indicate the potential for about 35% reduction in electricity usage for space conditioning over manually operated interior roller blinds.