A novel fault location strategy based on Bi-LSTM for MMC-HVDC systems

The integration of modular multilevel converters (MMCs) with high voltage direct current (HVDC) transmission systems is an efficient method for transporting electricity from distant renewable energy sources to demand centres. However, MMC-HVDC systems face reliability challenges during DC overcurrent faults, often caused by component failures that can lead to HVDC network shutdowns. Consequently, a reliable fault location approach is crucial for grid protection and restoration, aiding in fault isolation and alternate power flow identification. Conventional fault location methods struggle with manual protective threshold setting, susceptibility to fault resistance and noise, and the need for communication channels, resulting in signal delays. In multi-terminal HVDC networks, fault location becomes even more complex due to poor selectivity and sensitivity in traditional schemes. This study proposes a robust fault location approach based on bidirectional long short-term memory (bi-LSTM). The method offers a simplified decision-making model with low computational requirements, utilizing fault features from one end of the network, eliminating the need for a communication channel. Remarkably, this approach achieves high fault location accuracy, even with varying fault types, resistances, and noise levels, as demonstrated by an MSE of 0.006 and a percentage error below 1% in simulations conducted using a real-time simulator with MATLAB/Simulink.