Multi-objective energy management of smart homes considering uncertainty in wind power forecasting

Abstract

Smart homes are one of the effective parts of a smart grid. A residential smart grid operates properly when each of smart homes is managed appropriately. The energy management system of a home has to simultaneously manage the operational time of appliances and how to use the energy of an electric vehicle and home renewable distributed generation units like a wind turbine. So, the energy management of smart homes in a residential smart grid is studied in this paper. The wind turbine is considered as the energy source of the smart home while the electric vehicle can operate as a producer/consumer unit in discharge/charge mode. The uncertainty model of wind turbine and electric vehicles are also considered in the proposed method for energy managing. The real-time pricing tariff is utilized for applying the demand response program. The electricity cost of consumers and the peak to average rate of demand are formulated to achieve the best schedule of devices of smart homes. Multi-objective dragonfly algorithm is utilized for optimizing the technical and economic objective functions. After finding the optimal Pareto front, the analytical hierarchy process method is used to select the best operational schedule of smart homes. The proposed method is evaluated in a sample smart grid. Numerical results show that the proposed management method has considerable efficiency in improving the performance of the smart grid.