Optimal Residential Load Scheduling in Dynamic Tariff Environment

Abstract

The optimal scheduling of appliances under real time pricing can potentially provide advantages to consumer as well as to utility. Demand Side Management (DSM) is a key challenging area in smart grid. The main responsibility of a DSM system is to schedule the appliances in an optimal way to reduce the electricity cost while considering the consumer requirements. Optimal scheduling of appliances will reduce the peak demand and improve the power system efficiency. This paper studies the DSM strategies for residential consumers, where the customer provides the desired operation for each shiftable electricity appliance which is accompanied with time limits. The use of Intelligent Decision Support Systems has become vital for load scheduling which supports consumers to respond to dynamic tariff environment. The paper discusses how the Exact method, Genetic algorithm and the Mixed integer linear programming are applicable in load scheduling. Next, we proposed two novel approaches to optimize the load scheduling, namely Vacant Power Method and Prior Ranking Method. Furthermore, a comparative analysis of these DSM strategies were performed considering the electricity cost and the processing time.