Fault Detection and Protection Strategy for Multi-Terminal HVDC Grids Using Wavelet Analysis

Jashandeep Kaur, Manilka Jayasooriya (), Muhammad Naveed Iqbal, Kamran Daniel, Noman Shabbir () and Kristjan Peterson
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Jashandeep Kaur: Department of Engineering, Staffordshire University, Stoke on Trent ST4 2DE, UK
Manilka Jayasooriya: Department of Engineering, Staffordshire University, Stoke on Trent ST4 2DE, UK
Muhammad Naveed Iqbal: Department of Engineering, Staffordshire University, Stoke on Trent ST4 2DE, UK
Kamran Daniel: Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia
Noman Shabbir: Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia
Kristjan Peterson: Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia

Energies, 2025, vol. 18, issue 5, 1-19

Abstract: The growing demand for electricity, integration of renewable energy sources, and recent advances in power electronics have driven the development of HVDC systems. Multi-terminal HVDC (MTDC) grids, enabled by Voltage Source Converters (VSCs), provide increased operational flexibility, including the ability to reverse power flow and independently control both active and reactive power. However, fault propagation in DC grids occurs more rapidly, potentially leading to significant damage within milliseconds. Unlike AC systems, HVDC systems lack natural zero-crossing points, making fault isolation more complex. This paper presents the implementation of a wavelet-based protection algorithm to detect faults in a four-terminal VSC-HVDC grid, modelled in MATLAB and SIMULINK. The study considers several fault scenarios, including two internal DC pole-to-ground faults, an external DC fault in the load branch, and an external AC fault outside the protected area. The discrete wavelet transform, using Symlet decomposition, is applied to classify faults based on the wavelet entropy and sharp voltage and current signal variations. The algorithm processes the decomposition coefficients to differentiate between internal and external faults, triggering appropriate relay actions. Key factors influencing the algorithm’s performance include system complexity, fault location, and threshold settings. The suggested algorithm’s reliability and suitability are demonstrated by the real-time implementation. The results confirmed the precise fault detection, with fault currents aligning with the values in offline models. The internal faults exhibit more entropy than external faults. Results demonstrate the algorithm’s effectiveness in detecting faults rapidly and accurately. These outcomes confirm the algorithm’s suitability for a real-time environment.

Keywords: fault detection; HVDC; wavelet analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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