Heating, ventilation and air conditioning (HVAC) systems play an essential role in demand response (DR) programs. In this paper, a fuzzy controller is designed to adjust the HVAC set-points optimally. The aims of the designed controller are multifold: to save energy, to improve user’s comfort, and reduce HVAC electricity costs. In the current research, indices such as daily energy cost, minimum and maximum home temperature, energy usage, energy usage during peak hours, and user’s comfort are proposed and discussed for the evaluation of HVAC function. In addition, the effect of different pricing schemes such as fixed pricing (FP), time-of-use pricing (TOU), and real-time pricing (RTP), are analyzed. Further, the adaptability of the proposed model enabled us to investigate users with different attitudes toward welfare and cost. Finally, the effects of set-point and dead-band width are discussed. The results show that the proposed controller reaches the pre-determined aims successfully.
