Multisegmented Intelligent Solution for MT-HVDC Grid Protection

Fault detection continues to be a relevant and ongoing topic in multiterminal High Voltage Direct Current (MT-HVDC) grid protection. In MT-HVDC grids, however, high DC-fault currents result from failure of complex protective threshold traditional protection schemes, making Source Converter (VSC) vulnerable such potent transient currents. this innovative single-ended DC scheme, multiple time window segments are used consider the effects period across limiting inductors at each end link. Multiple 0–0.8, 0.8–1.5, 1.5–3.0 ms reduce relay improve sensitivity fault impedance while requiring minimal computational effort. It employs feature extraction tools as Stationary Wavelet Transform Random Search (RS)-based Artificial Neural Networks (ANNs) for detecting transmission line faults within networks. Its goal is accuracy reliability relays various events. Simulations showed that proposed algorithms could effectively identify any input data segment detect up 500 ohms. Accuracy first 100% 200 ohms, whereas second third show 400 addition, they maintain stability even under external disturbances.