A fault-aware, explainable proximal policy optimization based intelligent control framework with neuromorphic-inspired encoding for voltage and frequency stability
Abstract High penetration of inverter-interfaced generation, faults, and sudden load changes in power systems makes them more vulnerable to voltage and frequency deviations. Traditional controllers often struggle to adapt to varying disturbance types and severities in real time. Adaptive, data-driven control methods ar...