Rail train operation energy-saving optimization based on improved brute-force search

Document Type

Journal Article

Publication Date

2023

Subject Area

mode - rail, mode - subway/metro, place - asia, economics - operating costs, planning - methods

Keywords

Metro train, Energy saving optimization, Brute-force search, Speed curve

Abstract

Rail train operation energy consumption mainly focuses on train traction energy consumption. Reducing train traction energy consumption in rail transit operation is significant to developing a green and low-carbon economy and reducing operation costs. The rail train operation energy-saving optimization framework is developed considering the utilization of regenerative braking energy. Firstly, three objectives of punctual arrival, fixed-point parking and minimum energy consumption are provided by train operation strategy analysis. Secondly, the improved brute-force search is developed to solve train operation energy-saving multi-objective problems. The running time, speed, distance, power, and energy consumption of operation intervals are calculated. Finally, Guangzhou Metro Line 7 is taken as an example to verify the effectiveness of the developed optimization model. The results show that the improved brute-force search method effectively finds a more energy-saving turning point under constant interval operation time and has a better energy-saving effect than two other heuristic algorithms.

Rights

Permission to publish the abstract has been given by Elsevier, copyright remains with them.

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Applied Energy Home Page:

http://www.sciencedirect.com/science/journal/03062619

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