Random Forest-Equilibrium Optimizer based HVDC Fault Diagnosis with Renewable Energy Integration

In today's full use of renewable energy, high voltage direct current (HVDC) transmission also plays an important role. In order to solve the problem caused by the coupling between the poles of HVDC transmission lines, a fault pole selection scheme using unipolar electrical quantities is proposed. The electromagnetic coupling between the poles of HVDC transmission lines is particularly obvious under lightning strikes and unstable action of renewable energy power supply. The fault of one pole will induce transient electrical quantities on the perfect pole line at the same time, which may cause the maloperation of the protection of the perfect pole line, resulting in the bipolar outage when the unipolar fault occurs, affecting the safe and stable operation of the sending and receiving power grids. Therefore, the correct judgment of the fault pole plays an important role. In this paper, the fault pole identification model is composed of random forest and equilibrium optimizer, and the fault pole selection is effectively judged by using the actual data saved by China Southern Power Grid Extra High Voltage (EHV) Company in recent years. A fault pole diagnosis method based on Random Forest-Equilibrium Optimizer is proposed.