A fuzzy logic system for demand-side load management in residential buildings

Participating in demand response has significant advantages for both consumers and electricity producers, i.e., saving on high electricity prices for the user, and helping utilities in peak load curtailment. In this paper, a new concept based on fuzzy logic for demand-side load management in residential buildings is presented. The proposed fuzzy logic rule-based algorithm is developed for four important factors: current outdoor temperature, current load demand, current electricity price, and occupant presence. The approach proposed is the result of integration of wireless sensors and fuzzy logic concept. The approach is applied to existing wireless programmable thermostats to add more intelligence for load reduction in residential buildings by considering the input parameters. To gain better understanding, the wireless programmable thermostat is designed and simulated in Matlab GUI as a simulator. The results show that the system by combining the fuzzy rules reduces the temperature (load reduction) which results in better energy management and conservation in heating/cooling systems. Besides, the method is automatically able to help households to decrease their load during peak price and peak load periods. By considering the user activities in the house, it provides occupant's thermal comfort as well.