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

Zongyi Xing, Zhenyu Zhang, Jian Guo, Yong Qin and Limin Jia

Applied Energy, 2023, vol. 330, issue PA, No S0306261922016026

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.

Keywords: Metro train; Energy saving optimization; Brute-force search; Speed curve (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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DOI: 10.1016/j.apenergy.2022.120345

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