Optimization for family energy consumption in real-time pricing environment

Abstract

In order to help consumers adapt to electricity consumption in real-time electricity pricing environment, an energy consumption scheme is proposed in this paper. This scheme focuses on the prediction, modeling and optimization for family energy consumption. A method based on support-vector machine (SVM) is used to predict the real-time price (RTP) and the optimization model divides every hour into equal time slots and thus provides more opportunities to schedule household appliances in proper working time. Then the simulation results show that the proposed optimal control model reduces the daily electricity expenditures. © 2013 Springer Science+Business Media New York.