A Dynamic Programming‐Based Cooperative Optimization Approach for Energy Consumption Reduction of Substations in AC Railway Systems

ABSTRACT

In this paper, a comprehensive method that integrates the energy optimization with the AC traction power supply modeling is proposed to achieve the energy‐saving operation in the single‐train and double‐train scenarios. Concretely, a novel non‐iterative traction power flow (TPF) method is introduced to reduce the computation time for time‐varying load flow analysis. Meanwhile, a customized dynamic programming algorithm is designed to generate the optimal speed profile based on the TPF model. In the case of multiple high‐speed trains, the optimization process enables the tracking train to maximize the utilization of regenerative braking energy (RBE) generated by the braking train. The energy cost function for the double‐train coupled system integrates the substation supply and non‐supply conditions to further enhance the energy efficiency. Finally, a real‐world case study based on the Wuhan–Guangzhou high‐speed railway is presented to demonstrate the effectiveness of proposed method. The results indicate that, compared with the traditional mechanical energy optimization schemes, the proposed method can reduce the total line‐wide energy consumption by up to 2%, mitigating the catenary voltage fluctuations, and ensuring the precise power matching during the RBE transmission phases.