Energy Efficient Model Predictive Building Temperature Control

Abstract

<p>Sustainability considerations have placed increasing emphasis on the energy efficient operation and control of temperature control systems. It is estimated that the use of advanced control structures could lead to valuable savings in energy expenditure (up to 15-20 %) . This work considers the problem of developing a model predictive control (MPC) algorithm for temperature control in buildings. To this end, a cascade control structure was designed to regulate the room temperature subject to heat load disturbances, such as outdoor conditions or changes in the internal gains (i .e., number of people in a room). The inner loop of the cascade control structure involved controlling key variables of a vapor compression cycle (VCC), namely the superheat and supply air temperature (from the evaporator), by manipulating the compressor speed and valve opening (components in the VCC). Linear inputoutput models were appropriately identified for the VCC using a detailed first-principles model (adapted from Thermosys) for eventual utilization in a predictive control design. Then, closed loop simulations were performed by interfacing the VCC model with EnergyPlus (developed by the U.S . Department of Energy) , which was used to model realistic room temperature behavior. The control performance using a predictive controller (in the inner loop) was then evaluated against PI control.</p>