Stochastic Optimization of a Microgrid Considering Classification of Electric Vehicles

Most electric vehicles (EVs) consume energy from the main-grid or microgrid during driving. Connecting EVs to the MG will be a trend of future development. This paper proposes a stochastic programming model to deal with the optimal scheduling of MG. Different charging and discharging strategies are proposed for EVs with different mobility behavior and Monte Carlo method is used to simulate the mobility behavior. At the same time, the conditional value at risk method is applied to transfer a risk-neutral MG into a risk-averse MG, which reduce the fluctuation level of MG income and increase the conservatism. The validity of the model is verified by case study.