In this article, a multitimescale operation (MTO) strategy is proposed for the railway flexible traction power system (FTPS) with photovoltaic (PV) and battery-ultracapacitor (UC) hybrid energy storage systems (HESSs). The strategy can fully exploit the HESS flexibility to coordinate the reduction of the whole-day maximum power demand (MPD) and the real-time source-load power mismatch regulation, minimizing daily operational costs. It is a tri-stage framework, integrating the day-ahead and intraday rolling optimization (IRO) stages and the rule-based real-time stage. For the first time, the traction load power uncertainty caused by the train-timetable deviations is considered. A scenario-based day-ahead optimization (SDAO) model is established to dispatch the large-capacity battery to shave MPD against source-load prediction errors. Second, a threshold-based real-time allocation (TRTA) method of high-power UCs is proposed to relieve seconds-scale power mismatch. The charge/discharge threshold enables short-time energy scheduling via UC. Then, a scenario-based IRO (SIRO) method is developed, incorporating the day-ahead decisions and the real-time stage’s counterpart model. It rollingly corrects the day-ahead battery plan and optimizes the UC’s thresholds for real-time operations, further considering short-time uncertainties. Finally, numerical tests demonstrate the effectiveness of the proposed MTO strategy in minimizing daily operation costs against uncertainty, saving about 6% of cost compared to existing studies.
Multitimescale Optimal Operation for Hybrid Energy Storage of Flexible Traction Power Systems Considering Uncertain Train Timetable Deviations
IEEE Transactions on Transportation Electrification ; 11 , 2 ; 6640-6653
2025-04-01
3267240 byte
Article (Journal)
Electronic Resource
English
Systematic analyses of train run deviations from the timetable
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