Demand Response Potential Evaluation of Aggregated High-Speed Trains Toward Power System Operation

Abstract

The integration of a high proportion of intermittent renewable energy sources and the continuous fluctuation of loads in power systems have created an urgent need for flexible reserves. It has been demonstrated both theoretically and experimentally that high-speed trains (HSTs), with booming electricity consumption, can flexibly change their speed to achieve real-time power climbing, reduction, or even feedback from the train to the grid. In this paper, the flexibility of HSTs is investigated from a power system-oriented perspective, and the demand response (DR) potential of HSTs is exploited based on the kinematics and dynamics equations of trains. The lagging power rebound (LPR) effect after the DR period of HSTs is enclosed for the first time, and a duration-capacity-speed-LPR index system is established to quantify the DR performance of HSTs. Considering the operation requirements of both power and railway systems, a novel operation optimization model for aggregated HSTs is proposed to calculate their maximum DR potential. In the proposed model, the LPR of HSTs is constrained to ensure power system security, and the minimum distance limit between HSTs sharing the same railway is also included to ensure railway safety. In addition, an adaptive solution method based on pseudo-spectral is used to solve the optimization model. This approach balances the requirement for calculation speed in the power system with the need for temporal accuracy in the railway system. Finally, the proposed model and technique are verified using a 3-railway 6-HST system.