Intelligent Control of FACTS Devices for Co-Optimized Transient Stability and Voltage Security in Power Transmission Systems: A Comprehensive Review

Abstract

Modern power transmission systems increasingly operate under stressed conditions characterised by load growth, reduced operating margins, ageing infrastructure, and extensive integration of converter-interfaced generation. These conditions strengthen the coupling between transient rotor-angle stability and voltage security and increase the need for coordinated fast reactive-power support. This review examines intelligent control strategies for shunt Flexible AC Transmission Systems (FACTS), with emphasis on Static Var Compensators (SVCs) and static synchronous compensators (STATCOMs), for co-optimised improvement of transient stability and voltage security. Conventional proportional-integral and lead-lag controllers are assessed alongside artificial neural networks, fuzzy logic controllers, and adaptive neuro-fuzzy inference systems. The reviewed evidence indicates that intelligent controllers offer improved adaptability under nonlinear and time-varying operating conditions and can support simultaneous reduction of rotor-angle deviations, mitigation of voltage dips, and faster post-fault voltage recovery. Hybrid neuro-fuzzy approaches show particularly balanced performance across multiple evaluation criteria, although their practical deployment remains constrained by data dependency, training complexity, generalisation to unseen operating states, communication delays, measurement noise, cybersecurity risks, and limited real-time validation. The review therefore highlights the need for hybrid AI and model-based control, coordinated multi-FACTS architectures, standardised benchmarking, cybersecurity-aware design, and hardware-in-the-loop validation to support reliable deployment in renewable-rich, low-inertia power systems globally.