Operational scheduling of intercity passenger transportation company participating in energy and reserve markets

Abstract The electric vehicle (EV) is becoming the main mode of intercity passenger transportation. The intercity passenger transportation company (IPTC) is envisioned to participate in the electricity market to maximize the operation profit. Hence, it is necessary to study some strategic operating behaviors of the IPTC, including EV scheduling and bidding, to ensure the efficient operation of intercity passenger transport. This paper develops a decision-making tool based on a bi-level programming model for a merchant price-maker IPTC to determine the most beneficial scheduling and trading actions in the day-ahead market. The upper level of the model considers the mobility characteristics of EVs by a modified time–space network (TSN) to help the IPTC formulate intercity passenger shifts and bidding strategies. In this level, the IPTC maximizes its profit in the day-ahead market through bidding strategies, transportation scheduling, and charging/discharging arrangement at each station. In the lower level of the model, the joint energy and reserve market is cleared with maximum social welfare. The bi-level model can be transformed into an easily solved mixed-integer linear programming problem by applying the strong duality theorem and a binary expansion method to handle the nonlinear constraints of the reformulated single-level problem based on Karush-Kuhn-Tucker theorems. Finally, case studies are carried out on a modified IEEE 39-bus system and a practical 714-bus power system in China. The numerical results indicate that the IPTC tends to schedule more EVs to park in cities directly connected to congested transit lines and increase the number of discharging vehicles, resulting in the growth of the scheduled energy of discharging in these cities and thus higher profits. The different operation strategies of the IPTC are also discussed in the day-ahead market.