A Hybrid DC Fault Primary Protection Algorithm for Multi-Terminal HVdc Systems

TL;DR

This paper introduces a hybrid fault detection algorithm for multi-terminal HVdc systems that improves detection accuracy, robustness, and coverage across various fault types and scenarios using sensor data processing and adaptive detector selection.

Contribution

It presents a novel hybrid primary protection algorithm that adaptively selects the best fault detector for multi-terminal HVdc systems, enhancing detection capabilities and robustness.

Findings

Successfully detects all major fault types including P2P, P2G, and external faults.

Provides wide coverage for faults at various locations and impedances.

Demonstrates improved robustness to noisy measurements in simulations.

Abstract

Protection against dc faults is one of the main technical hurdles faced when operating converter-based HVdc systems. Protection becomes even more challenging for multi-terminal dc (MTdc) systems with more than two terminals/converter stations. In this paper, a hybrid primary fault detection algorithm for MTdc systems is proposed to detect a broad range of failures. Sensor measurements, i.e., line currents and dc reactor voltages measured at local terminals, are first processed by a top-level context clustering algorithm. For each cluster, the best fault detector is selected among a detector pool according to a rule resulting from a learning algorithm. The detector pool consists of several existing detection algorithms, each performing differently across fault scenarios. The proposed hybrid primary detection algorithm: i) detects all major fault types including pole-to-pole (P2P), pole-to-ground (P2G), and external dc fault; ii) provides a wide detection region covering faults with various fault locations and impedances; iii) is more robust to noisy sensor measurements compared to the existing methods. Performance and effectiveness of the proposed algorithm are evaluated and verified based on time-domain simulations in the PSCAD/EMTDC software environment. The results confirm satisfactory operation, accuracy, and detection speed of the proposed algorithm under various fault scenarios.