smart charge and discharge planning of electric vehicles in the parking in a price responsive smart grid environment

Reduce the use of electric vehicles in addition to environmental concerns, can reduce the peak and fill the valley daily load characteristic of network. In other words, in the context of smart grids, electric vehicles battery can charge and discharge planning process to improve the load characteristics. with the emergence of smart grids and using advanced metering infrastructure (AMI), customers are instantaneously aware of prices therefore it is expected that the demand side customers change their consumption patterns according to the forecasted prices by interrupting, shifting or even locally generating the load. This response pattern is causing massive changes in network load curve. In this article, a multistage model using neural networks and ANFIS to forecast the day-ahead load of price-responsive smart grid environments have been provided. Then, smart charge and discharge planning of electric vehicles in the parking according to the forecasted load curve of next day In considering smart charge and discharge operation strategy, a Complete probabilistic model of the car parking area is provided. The probabilistic model is based on a new hybrid optimization algorithm consists of sequential Monte Carlo simulation and imperialist competitive algorithm. Finally, the proposed model applied to four sample days data from the years 2014-2013 of the NSW electricity market in Australia and determined smart charge and discharge planning of electric vehicles in the parking in price responsive of smart grid environment.