碳视角下基于网-车-线耦合的高速列车节能运行优化

doi:10.19595/j.cnki.1000-6753.tces.241808

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Abstract The increasing operational mileage of high-speed railways brings significant energy consumption challenges. High-speed train operation energy consumption is the primary contributor to overall energy consumption in high-speed railway operations. During high-speed train operation, the traction power supply network (network), traction drive system (train), and line operating conditions (line) comprehensively affect train energy consumption through the external power grid’s energy supply, the conversion of electrical/mechanical energy driving train motion, and changes in additional resistance. Reducing high-speed train operational energy consumption will promote energy efficiency, green, low-carbon development, and high-quality development of high-speed railways.
First, starting from the architecture of the high-speed railway traction system, the coupling relationship among the network, train, and line during energy transfer, conversion, and consumption processes is clarified. Next, combining the bi-directional system carbon emission measurement concept, the coupled carbon emission characteristics of the network-train-line system are qualitatively analyzed under two scenarios: “accounting for regenerative braking energy feedback” and “non-accounting for regenerative braking energy feedback.” Using the carbon emission factor method, a quantitative analysis method is proposed for calculating high-speed train operational carbon emissions, integrating factors such as the power grid, fuel, and passenger volume. Considering energy savings and carbon reduction, two key objectives for optimizing energy-saving train operation are defined: reducing traction energy consumption and utilizing regenerative braking energy. A single-train operation strategy is presented based on the composition of energy-saving operating conditions. In contrast, a multi-train regenerative braking energy utilization strategy is designed, incorporating an elastic buffer time utilization method. Finally, a hierarchical optimization model for energy-efficient train operation is established. Its upper layer focuses on utilizing multi-train elastic buffer time, and the lower layer addresses optimizing single-train energy-saving operation. The sine-cosine algorithm (SCA) is used to improve the deep Q network (DQN), and the SCA-DQN algorithm is proposed. Simulation analysis is conducted using data from real-world high-speed railway systems.
Simulation results show that compared with the DP, Q-learning, and DQN algorithms, the SCA-DQN algorithm improves efficiency and energy savings, achieving energy-saving and carbon reduction rates of 19.9%, 9.3%, and 1.6%, respectively. For a train running on the Xi’anbei-Huyi section of the Xi’an-Chengdu high-speed railway, the optimized energy-saving and carbon reduction rate reaches 6.36%. For trains running on the Lanzhouxi-Tianshuinan section of the Baoji-Lanzhou high-speed railway, the energy-saving and carbon reduction rates of two trains supplemented by regenerative braking energy reach 8.82% and 7.65%, respectively.

Key words： High-speed railway high-speed train network-train-line coupling energy-efficient optimization improved deep Q network

Received: 16 October 2024

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Li Xin,Zhu Chengkun. Energy-Efficient Operation Optimization of High-Speed Trains Based on Network-Train-Line Coupling Under Carbon Perspective[J]. Transactions of China Electrotechnical Society, 2025, 40(22): 7431-7448.

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