Optimization in load scheduling of a residential community using dynamic pricing

Demand side management at the utility level is facing challenges of managing the peak demands since electricity cannot be stored in bulk so the utility has to match demand at any point in time. Scheduling of electrical appliances and proper design of the electricity tariffs are some of the optimization schemes used to reduce these peaks. With proper optimization scheme, the household consumer will be motivated to either shift their loads from peaking periods or reduce their consumption. In this paper, a residential community of three houses are considered with different electric appliances. Genetic algorithm (GA) and dynamic programming (DP) based smart appliance scheduling schemes and time-of-use pricing are employed for comparative studies with demand response. The optimization control approaches are capable of solving energy optimization problem of a small community. Three types of houses, with real-world appliances, and with different power consumption are compared under energy management benchmark problem. The simulation results discuss the impact of priority of using household appliances in terms of customer comfort-level and cost minimization. The optimization performance of control approaches are also validated with several different priority conditions of household appliances.