EV Scheduling in Deregulated Energy Markets

Market penetration of electric vehicles (EVs) is growing, and the growth is expected to continue for the next decades along with decentralization of the energy market. In this paper an EV charging algorithm suitable for decentralized P2P transactive energy is implemented and compared with other traditional methods to assess its performance in cost minimization. A linear segmentation of the nonlinear EV charging characteristics is also utilized to significantly reduce runtimes. Multiple EV types and real parking lot historical data are considered to mimic real-life scenarios. Case studies are presented to illustrate the effectiveness of the algorithm and the results show a 16% reduction in overall charging costs, better than the closest counterpart by 4.5%. Moreover, the new algorithm’s runtimes never exceeded the 10-minute time limit and were less than 10% of the dynamic counterpart whose runtimes regularly exceeded the time limit when the number of EVs was the weekday normal.