Charging scheduling of enterprise private parking-lot with renewable power: A simulation method based on markov decision processes

With the development of renewable energy and electric vehicles (EVs), using renewable energy charging for EVs becomes an effective way to reduce environment pollution. In this paper, we study a charging scheduling problem in the enterprise private parking-lot considering the uncertainties of renewable energy and charging demand of EVs. In this model, the stochastic multistage decision problem is described as Markov decision processes (MDPs). In addition, a simulation-based dynamic programming (SBDP) method is proposed to get the optimal strategy and expected cost of purchasing electricity from the power grid. Finally, a real case study is analyzed. The results show that the method is applicable to various scale of EVs well and the cost of electricity purchasing has been reduced in the range of 9% and 47% depending on the scale of charging piles.