AI-based hybrid power quality control system for electrical railway using single phase PV-UPQC with Lyapunov optimization.

ABSTRACT: This research paper presents an advanced AI-driven hybrid power quality management system for electrical railways that addresses critical challenges in 25 kV AC traction networks through a novel integration of single-phase PV-UPQC with ANN-Lyapunov control architecture. The system effectively manages voltage unbalance exceeding 2%, high THD, voltage variations of ± 10%, and poor power factor through a dual-approach methodology combining ANN-based reference signal generation with Lyapunov optimization, enabling dynamic parameter tuning and real-time load adaptation. MATLAB/Simulink simulations validate the system's superior performance, demonstrating significant improvements, including voltage unbalance reduction from 1.5 to 0.8%, THD reduction below 1%, unity power factor correction, 40% f

SUBMITTER: Nishad DK 

PROVIDER: S-EPMC11751446 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature