This paper investigates the potential of residential heating, ventilation and air conditioning systems to contribute to dynamic demand-side management. Thermal models for seven houses in Austin, Texas are developed with the goal of using them in a planning based demand-side management methodology. The thermal models form the base to determine the flexibility present in these houses with respect to cooling requirements. The linear models are shown to be reasonably accurate when used to predict indoor temperature changes. Furthermore, the resulting prediction errors can be largely attributed to human behavior. The considered thermal models are integrated in a planning-based demand-side management methodology while accounting for such prediction errors. The resulting methodology is capable of flattening the load profile of the considered houses considerably.
|Publisher||IEEE Power & Energy Society|
|Conference||2016 IEEE PES Innovative Smart Grid Technologies, ISGT 2016|
|Period||6/09/16 → 9/09/16|
- Residential Control
- Demand Side Management
- HVAC systems