Demand response potential of residential HVAC loads considering users preferences

Abstract

Domestic Heating Ventilation and Air-Conditioning (HVAC) loads are among the most flexible residential loads for possible demand response (DR) applications. This paper aims at assessing the DR potential of HVAC loads in smart grids considering users' temperature preferences. For doing so, at first, a mathematical formulation is developed to evaluate the flexibility of HVAC loads. The model, by adjusting the HVAC load, intends to either maximize or minimize electricity consumption during specific hours of a day while the user thermal comfort is intact. The proposed model is then applied to a medium massive structure house in Helsinki, Finland. The study is performed for different seasons and the associated DR potential is evaluated. The simulation results showcase the significant potential of HVAC loads in both consumption reduction and load increment. It is shown that the DR potential can be significantly affected by temperature dead-bands representing consumers' willingness to accept change in their comfort. It is also demonstrated that installing even a small thermal storage capacity may lead to a greater value-added DR potential.

Sizing Hydrogen Energy Storage in Consideration of Demand Response in Highly Renewable Generation Power Systems

“…The space heating model, a two capacity thermal model, has already been introduced by Ali et al [16] and does not constitute an original contribution of this work. However, the thermodynamic model is repeated for the sake of completeness.…”

“…However, the intermittent and uncertain nature of solar and wind generation has led to considerable uncertainty as to how to balance energy demand with production [3]. For instance, 16 GWh of solar generation and 358 GWh of wind generation was curtailed in Germany in 2012 [4]. Curtailment is a natural response to preserve the capability of the system at times of excess production.…”

Increasing the Benefit from Cost-Minimizing Loads via Centralized Adjustments

“…Constraints (2) and (3) model the evolution of the indoor (T a ) and the building mass (T m ) temperature, respectively. These constraints represent a two-capacity building thermal model capturing the thermal dynamics of a detached house [14]. Parameters A1-A4 and B1-B3 are obtained by discretizing the continuous dynamics as done in [15].…”

“…The adjusted heating power (E A ) given in Equation (13) is a sum of the forecasted heating load and the positive and negative adjustments. Equation (14) contains the heating load model and Equation (15) sets the allowed indoor temperature band for the control. The constraints (14) and (15) principally define the possible changes in the indoor temperature due to the adjustments.…”

“…Equation (14) contains the heating load model and Equation (15) sets the allowed indoor temperature band for the control. The constraints (14) and (15) principally define the possible changes in the indoor temperature due to the adjustments. Similarly, Equations (16)- (18) define the consumption if the aggregator's regulation bid is activated.…”