Optimal Residential Load Control Comparison Using Linear Programming and Simulated Annealing for Energy Scheduling

Many tariffs are used for electricity pricing. Electricity bills can be reduced by choosing the optimal working hours of appliances and for appropriate tariffs in smart homes. In this study, Linear Programming (LP) and Simulated Annealing (SA) methods are realized and compared each other to find minimum bill. The multi-time tariffs that have different energy unit prices at different times of the day are preferred. Energy Management System (EMS) shifts time slots of some appliances to cheap energy unit prices. Optimal load control is applied to prevent high peak demand because there may be overload in system because of shifting of working hours of appliances. Mathematical model of the problem is constructed and LP method is solved by GAMS and SA technique is realized by C# program. The cost table consisting of the energy unit prices of each time slots is used as input. Optimum electricity cost, working hours of the appliances and peak to average ratio are achieved by two different solutions and the results are compared. According to result, LP gives lower cost than SA.