Transient-based fault identification algorithm using parametric models for meshed HVDC grids

•A fault detection and identification algorithm for meshed HVDC is proposed.•A parametric model of DC fault behavior is developed .•The algorithm computes a maximum likelihood estimate of the fault parameters.•The method can selectively identify faults using very few measurements. This paper addresses the problem of fault identification in meshed HVDC grids once an abnormal behavior has been detected. A parametric single-ended fault identification algorithm is proposed. The method is able to determine whether the line monitored by a relay is faulty or not using a very short observation window. When a fault is suspected, the proposed algorithm estimates the fault distance and impedance using a parametric model describing the voltage and current evolution just after the fault occurrence. This model combines phenomenological (knowledge-based) and behavioral (black-box) parts to represent the fault propagation and to account for ground effects and various losses. The identification of the faulty line is then based on the size of the confidence region of the obtained estimate. The performance of the algorithm for a three-node meshed grid is studied using Electro-Magnetic Transient (EMT) simulations. On the considered grid model, the current and voltage need to be observed during less than 0.2 ms to get a sufficiently accurate estimate of the fault characteristics and identify consistently the faulty line.