Profit Maximization for Plug-In Electric Taxi With Uncertain Future Electricity Prices

This paper investigates the optimal charging strategy for a plug-in electric taxi (PET) to maximize its operating profit by choosing proper charging slots, subject to uncertain electricity prices and time-varying incomes. As PET consumes more electricity and possesses different charging behaviors from the widely studied private electric vehicles, this problem deserves special treatment. First, in order to tackle the uncertain electricity prices, a simple thresholding method is proposed to determine the optimal charging slot, where the thresholds are computed via a backward induction algorithm. Then, the properties that reveal the insights of the algorithm are presented. Then, several practical factors are included in algorithm design to approach a more realistic solution, such as an accurate battery model, the additional power consumption of driving PET to charging station, and the battery loss during charging and discharging processes. Numerical results show that the proposed algorithm is able to improve the profit and significantly reduce the expense.