Passenger-centric periodic timetable adjustment problem for the utilization of regenerative energy. (October 2022)

• Record Type: Journal Article
• Authors: Wang, Pengling; Zhu, Yongqiu; Corman, Francesco
• Is Part Of: Computers & industrial engineering. Volume 172:Part A(2022)
• Publication Date: 2022-10
• Subjects: Railway timetabling -- Utilization of regenerative energy -- Passenger satisfaction -- Multi-objective; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108578
• Languages: English
• ISSNs: 0360-8352

Abstract

Abstract: Optimizing the railway timetable to increase synchronous accelerating and braking processes can lead to an improvement in the usage of regenerative energy. However, such a synchronized timetable might result in little or unsuitable transfer connections for the passengers. This paper focuses on the optimization of railway periodic timetables, to increase usage of regenerative energy while ensuring passenger satisfaction. We work by extending the traditional Periodic Event Scheduling Problem (PESP) formulation, to address the problem of synchronization of acceleration and braking phases, (and re-used energy) and including passenger-related events (and their satisfaction). Three objectives are identified, in a resulting Mixed Integer Linear Programming (MILP) model: maximizing the overlapping times of accelerating and braking trains to achieve increased usage of regenerative energy, minimizing the total passengers' generalized travel times ( global passenger dissatisfaction), and minimizing the maximum increase in individual's generalized travel time ( local passenger dissatisfaction). A multi-step approach solves the trade-offs among three conflicting objectives. Results on a realistic case study show that the proposed approach can find optimized timetables, which compared to the currently-in-use timetable, can increase the usage of regenerative energy by over 1.5 times, save the average generalized travel time per passenger by 2 min, with only a minor increase on specific individual generalized travel time (up to 4 min). A detailed results analysis imply that to achieve a higher usage of regenerative energy, it is required to have a higher tolerance for the maximum increase in individual generalized travel time, while this is not necessary for the overall passenger generalized travel time, which can even be reduced when the maximum increase in individual generalized travel time becomes larger. Highlights: Periodic timetable model to improve regenerative energy and passenger satisfaction. Overlapping acceleration and braking processes to improve regenerative energy usage. A multi-step approach to analyze the trade-offs between three objectives. Better timetables against minimal increase of travel time for some passengers.