A Novel Power Programming Strategy for Railway Power Regulation With Dynamic Exploration

Intelligent power regulation is a prominent feature of smart railway systems; to enhance the grid-connected performance of railway loads while economically determining the size of power regulating units, this paper proposes a novel computation-efficient power programming strategy for railway power flow controller (RPFC) to implement power regulation in a.c. railway systems. Two key methods are developed: 1) determining two-phase loads’ PF-P & PF-PF combination model by accurately partitioning two-phase loads’ occurrence region with high probability , and 2) dynamically adjusting the exploring region of two-phase PFs for every load point in 1); in those methods, the intrinsic two-phase PF-PF and PF-P distribution properties of real train loads are fully considered (Note: “P” and “PF” stated above present active power and power factor respectively). In addition, the insight of the compensation principle and the advanced design capacity visualization scheme of RPFC are discussed with emphasis. Finally, a comprehensive performance investigation is carried out to validate the correctness of the proposed method. In this process, an exquisite power regulation unit in digital sense is created, contributing to the system-level application of smart railway systems.