Open AccessJoint optimization combining the capacity of subway on‐board energy storage device and timetable
Author(s) -
Wang Xiaowen,
Sun Pengfei,
Wang Qingyuan,
Ding Juxia,
Feng Xiaoyun
Publication year - 2023
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/itr2.12248
Subject(s) - train , computer science , heuristic , mathematical optimization , dynamic programming , energy (signal processing) , linear programming , energy storage , capacity optimization , joint (building) , constraint (computer aided design) , simulation , engineering , algorithm , power (physics) , statistics , physics , mathematics , quantum mechanics , architectural engineering , mechanical engineering , cartography , artificial intelligence , geography
On‐board energy storage devices (OESD) and energy‐efficient train timetabling (EETT) are considered two effective ways to improve the usage rate of regenerative braking energy (RBE) of subway trains. EETT is less costly but has lower ceilings, whereas OESD, although expensive, maximizes the reuse of RBE. To make the RBE usage rate of the train group reach the required target, a typical problem is how to use the OESD with the minimum capacity to reduce the cost. With this consideration, this paper proposes an optimization method that combines EETT and OESD. In this method, the joint optimization of timetable and OESD capacity allocation in case OESDs of different capacities can be carried between trains is considered to further improve the optimization. A non‐linear programming model is built to minimize the total OESD capacity of the train group under the constraint of reaching target RBE usage. An efficient heuristic algorithm is designed to simultaneously obtain the optimal timetable and the matching capacity allocation scheme of OESDs. Finally, some simulation cases based on real‐line data are designed to verify the effectiveness of the method.