Demand response with PHEV discharge in smart grid

With the development of plug-in hybrid electric vehicles (PHEVs), it is a necessary trend for residential intelligent evolution that PHEVs are widely accepted by family and can be charged at home. According to the power usage characters of home electric appliances, we divide residential appliances into PHEVs, scheduled loads (soft loads) and unscheduled loads (hard loads). PHEVs can be used as storage device when they are idle. Assuming that the price of electricity is time-varying, we propose a method to optimally charge PHEV with predicted price and schedule PHEV charge and discharge to minimize household electricity cost by supplying its electricity to soft loads. We apply a simple and efficient weighted average price prediction filter to the actual hourly-based price values with an hourly pricing program from Ameren Illinois on January, 2012, and compare the three charge patterns´ cost to choose the optimum charging mode. Two consecutive days are considered to be a model unit, and there are three kinds of situation in accordance with the state of PHEV. Simulation results show that in these three states with electricity price forecasting and residential load schedule control tactic, the electricity cost is significantly decreased by using the battery as a storage device. Meanwhile, our method can also alleviate the phenomenon of overload and secondary peak time in the smart grid.