Multitime-Scale Optimal Dispatch of Railway FTPSS Based on Model Predictive Control

The flexible traction power supply system (FTPSS) integrates back-to-back converter, and hybrid energy storage system (HESS) and photovoltaic (PV) generation system will be an important part of the smart railway. The FTPSS not only cancels the neutral zone but also facilitates the utilization of regenerative braking (RB) and renewable energy, but the random fluctuation of PV and the sudden change of traction load will exert influence on the safe and efficient operation of the FTPSS. To improve the benefits of FTPSS and compensate for the imbalance between supply and demand in short-term operation, a multitime-scale optimal dispatch method is proposed for flexible railway energy management (FREM), which integrates day-ahead dispatch and intraday feedback correction. During the day-ahead dispatch, the minimizing operating costs problem is formulated as a mixed linear programming model by coordination between HESS, RB, and PV output. For intraday energy adjustment dispatch, a rolling optimization based on model predictive control combined with the feedback correction method is proposed, with aim of minimum operation deviation of FTPSS because of adjusting the HESS dispatch plan drew up at day-ahead. Finally, the effectiveness of the proposed FREM control strategy is verified by the detailed real case study of a railway line in China.