of a distribution network. Saovapakhiran *et al.* propose to guide EVs and HEVs to the optimal charging station in order to maximize system utility in [@Saovapakhiran]. [@Wang] offers a coordinated charging strategy relying on the vehicle network communication to enhance the cooperation among mobile EVs. Compared with these papers that utilize conventional power grid to supply charging vehicles, Misra *et al.* in [@Misra] consider to use pricing to attract EVs to charge at different microgrids, which can be powered by renewable energy sources. However, the intermittent nature of renewable energy is not considered in [@Misra]. Recently, we design an online algorithm to guide EV charging at different stations, which are supplied by both on-grid energy and time-varying renewable energy [@LiYang].

As to dealing with the stochastic issue of renewable energy generation, Lyapunov optimization technique [@Georgiadis] has been applied to energy systems [@Neely1]-[@Chen] and wireless communications in smart grid [@Shah]. There are also other techniques that can be used to exploit the time-varying nature of renewable energy, such as Markov decision process in [@Zhang] and game theory in [@Maharjan]. However, the problem formulation in [@Zhang]-[@Maharjan] has to rely on the priori knowledge of the underlying stochastic process. This paper also utilizes 