Print Email Facebook Twitter Integration of real-time traffic management and train control for rail networks Title Integration of real-time traffic management and train control for rail networks: Part 2: Extensions towards energy-efficient train operations Author Luan, X. (TU Delft Transport Engineering and Logistics) Wang, Y. (Beijing Jiaotong University) De Schutter, B.H.K. (TU Delft Team Bart De Schutter) Meng, Lingyun (Beijing Jiaotong University) Lodewijks, G. (University of New South Wales) Corman, F. (ETH Zürich) Date 2018 Abstract We study the integration of real-time traffic management and train control by using mixed-integer nonlinear programming (MINLP) and mixed-integer linear programming (MILP) approaches. In Part 1 of the paper (Luan et al., 2018), three integrated optimization problems, namely the PNLP problem (NLP: nonlinear programming), the PPWA problem (PWA: piecewise affine), and the PTSPO problem (TSPO: train speed profile option), have been developed for real-time traffic management that inherently include train control. A two-level approach and a custom-designed two-step approach have been proposed to solve these optimization problems. In Part 2 of the paper, aiming at energy-efficient train operation, we extend the three proposed optimization problems by introducing energy-related formulations. We first evaluate the energy consumption of a train motion. A set of nonlinear constraints is first proposed to calculate the energy consumption, which is further reformulated as a set of linear constraints for the PTSPO problem and approximated by using a piecewise constant function for the PNLP and PPWA problems. Moreover, we consider the option of regenerative braking and present linear formulations to calculate the utilization of the regenerative energy obtained through braking trains. We focus on two objectives, i.e., delay recovery and energy efficiency, through using a weighted-sum formulation and an ε-constraint formulation. With these energy-related extensions, the nature of the three optimization problems remains same to Part 1. In numerical experiments conducted based on the Dutch test case, we consider the PNLP approach and the PTSPO approach only and compare their performance with the inclusion of the energy-related aspects; the PPWA approach is neglected due to its bad performance, as evaluated in Part 1. According to the experimental results, the PTSPO approach still yields a better performance within the required computation time. The trade-off between train delay and energy consumption is investigated. The results show the possibility of reducing train delay and saving energy at the same time through managing train speed, by up to 4.0% and 5.6% respectively. In our case study, applying regenerative braking leads to a 22.9% reduction of the total energy consumption. Subject Energy efficient train operationIntegrated optimizationReal-time traffic managementRegenerative brakingTrain control To reference this document use: http://resolver.tudelft.nl/uuid:e679f5d7-2df0-4db6-9f6c-37f735444b27 DOI https://doi.org/10.1016/j.trb.2018.06.011 Embargo date 2020-07-18 ISSN 0191-2615 Source Transportation Research. Part B: Methodological, 115, 72-94 Bibliographical note Accepted Author Manuscript Part of collection Institutional Repository Document type journal article Rights © 2018 X. Luan, Y. Wang, B.H.K. De Schutter, Lingyun Meng, G. Lodewijks, F. Corman Files PDF Luan_et_al._Part2.pdf 1.68 MB Close viewer /islandora/object/uuid:e679f5d7-2df0-4db6-9f6c-37f735444b27/datastream/OBJ/view