Intelligent appliance control algorithm for optimizing user energy demand in smart homes

Advanced metering infrastructure which is an integral component of smart homes has aided in tapping the potential of the residential sector for demand side management (DSM). DSM in smart homes focus mainly on some power-intensive appliances which affect the household load profile significantly. This paper proposes an intelligent appliance control (IAC) algorithm to monitor and control the daily operation of these power-intensive appliances using their simulated load models. The proposed algorithm employs differential evolution (DE) algorithm along with a DSM strategy to limit the smart household power consumption at every half an hour to an optimum limit. The paper demonstrates the ability of the proposed algorithm in minimizing the households' monthly electricity bill, maximizing the peak load reduction and minimizing the problem of distribution transformer overloading. The paper also focuses on studying the impacts of time of use (TOU) electricity pricing on residential customers' behavior. The simulation results indicate that TOU pricing augments the benefits of the proposed algorithm both at the residential level and the distribution transformer level.