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 byaccurately partitioningtwo-phase loads’ occurrence region withhigh probability, and 2)dynamically adjustingthe 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, theinsightof the compensation principle and theadvanceddesign 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, anexquisitepower regulation unit indigitalsense is created, contributing to thesystem-levelapplication of smart railway systems.