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| Capacity Optimization Configuration of Hybrid Energy Storage System for Long Steep Slope of High-Speed Railway |
| Li Xin1, Lu Jingtao1, Xiao Linrun2, Jin Zhongfu3 |
1. School of New Energy and Power Engineering Lanzhou Jiaotong University Lanzhou 730070 China;
2. School of Automatization and Electric Engineering Lanzhou Jiaotong University Lanzhou 730070 China;
3. China Railway First Survey and Design Institute Group Co. Ltd Xi'an 710043 China |
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Abstract High-speed railway trains will generate a large amount of regenerative braking energy and send it back to the traction network when they pass through the long ramp section, which will cause the voltage uplift of the traction network, harm traffic safety, and even cause economic losses to the railway enterprises. If this energy is reasonably recycled, it will be beneficial to reduce the energy consumption of high-speed rail, low-carbon transportation, energy conservation, and emission reduction, and achieve the ‘3060’ dual carbon target, which is more conducive to train safety. Studies have shown that it is a good method to recover regenerative braking energy by ground hybrid energy storage system, but it needs to be reasonably configured. Therefore, this paper presents a segmented configuration scheme and capacity optimization model for a hybrid energy storage system. The improved simulated annealing algorithm based on Levy flight (LESA) is used to optimize the capacity of the hybrid energy storage system on a long ramp of a high-speed railway.
Firstly, the characteristics of regenerative braking power are analyzed from each and all day respectively. On this basis, considering the capacity requirements of the energy storage system, the energy is combined with the same type in chronological order to form the action segment, analyze the feasibility of the utilization of regenerative braking energy, and determine the recovery range. Accordingly, considering the respective characteristics of different media of the hybrid energy storage system, the energy recovery method with the threshold Pth as the boundary condition is formulated, the segmented configuration scheme of the hybrid energy storage system is established, and the economic indicators are calculated. Secondly, in the aspect of optimization algorithm, because the traditional simulated annealing algorithm (SA) has low efficiency, Levy flight is used to generate the initial solution, and it is constantly memorized and updated in the process of algorithm solution. An improved simulated annealing algorithm based on Levy flight (LESA) is proposed. This method can reduce the number of times to enter the Metropolis criterion, and is closer to the optimal solution under a limited number of iterations, improving the efficiency of the algorithm. Finally, according to the actual operation data of a long steep slope of Xi'an-Chengdu high-speed railway, two kinds of configuration schemes are analyzed.
The analysis results of regenerative braking power show that the single braking power is low and has small fluctuation. Moreover, in the analysis of the whole day conditions, the power curve has obvious stratification, and the energy of the low-power section is more enriched than the high-power section. In the feasibility analysis of regenerative braking energy utilization, a total of 36 braking sections and 36 traction sections were obtained. The first 35 times were included in the configuration calculation range considering the discharge demand. According to the actual operation data, through the given configuration scheme, optimization model, and LESA algorithm, the results of optimal configuration are obtained: Scheme 1 of recovering low-power energy with battery, the daily cumulative recovery power reaches 1 1673.48 kW·h; scheme 2 of recovering low-power energy with supercapacitors has a daily cumulative recovery of 9 191.15 kW·h. The configuration results obtained by the LESA algorithm are better than the 11 290.35 kW·h and 9 131.24 kW·h calculated by the SA algorithm.
The improved simulated annealing algorithm based on the Levy flight presented in this paper has better and more stable results than the traditional SA under the finite number of iterations, which solves the solving efficiency problem of the original algorithm to a certain extent. After optimized configuration, the hybrid energy storage system can recover a large amount of regenerative braking energy during its life, and the recovered electricity accounts for 16.3 % of the traction power consumption, which has a high recycling significance.
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Received: 22 June 2022
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2023, Vol. 38 
