A genetic algorithm for optimal power scheduling for residential energy management

Demand Response continues to gain popularity as an effective means for administering demand side management by including customer's involvement in Smart grid operations, particularly for residential energy management. Abundant recent researches have studied economic benefits both for retailers as well as customers point of view. However, working out an exact formulation for optimal management is a tedious task for large scale residential customers. This paper presents an energy management scheme for residential customers via power scheduling, assuming that an energy market prevails that publishes hourly dynamic energy prices in a day ahead fashion and the hourly demand of customers are also known day ahead. This paper presents a metaheuristic formulation that minimizes customers overall energy cost using genetic algorithm results presented herein demonstrates the efficacy of the proposed methodology.