Smart grid coordination in building HVAC systems: EMPC and the impact of forecasting

• Illustrate importance of disturbance forecasting in EMPC for HVAC applications.
• Compare and contrast various forecasting methods.
• Illustrate the impact of time varying short term averages in disturbance data.
• Assess forecasting methods within the context of EMPC.
• Propose a novel pseudo measurement based forecasting approach for use in EMPC.

Energy consumption by heating, ventilation, and air conditioning (HVAC) systems exhibits a clear correlation with electricity prices. The method of economic model predictive control (EMPC) can be used in conjunction with thermal energy storage (TES) to time-shift power consumption away from periods of high demand to periods of low energy cost. Dynamic electricity pricing and weather condition forecasts can be readily incorporated within this methodology. Unfortunately, the receding horizon nature of this control strategy makes it very susceptible to the quality of the forecasts used. To this end, the development and implementation of several forecasting methods will be discussed. Finally, the EMPC performance of these methods will be assessed on a simple building example using active TES.