Scheduling Smart Home Appliances using ACO Algorithm with Different Electricity Tariff Schemes

This paper aims to minimize the electricity con-sumption costs through optimal scheduling of smart home ap-pliances. The optimization problem considers four different elec-tricity prices with dynamic energy demand profiles to determine the most suitable time to use home appliances. Those four pricing schemes are real-time price (RTP), time of use (TOU), critical peak price (CPP), and day-ahead price (DAP). Timing constraints for uninterruptible operation of specific appliances and energy constraints are modeled and the Ant Colony Optimization (ACO) algorithm is employed in the proposed framework. The optimized energy consumption profile attains minimized cost by satisfying constraints and user preferences. The simulation (MATLAB-R2017a) results and the existing results of the wind-driven optimization (WDO) algorithm and without-any scheduling al-gorithm are compared. The ACO algorithm achieves optimal scheduling and reduced electricity usage cost.