Multi-Frequency bands based Pole-to-Ground fault detection method for MMC-Based radial DC distribution systems. (October 2022)

• Record Type: Journal Article
• Authors: Yang, Changqing; Lin, Shuyue; Guo, Moufa
• Is Part Of: International journal of electrical power & energy systems. Volume 141(2022)
• Publication Date: 2022-10
• Subjects: Faulty feeder detection -- Multi-frequency bands -- Pole-to-ground fault -- Radial DC distribution systems -- Transient zero-mode current; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2022.108250
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: A faulty feeder detection method is proposed based on the characteristics of transient zero-mode current in multi-frequency bands. The fault current is analyzed in frequency domain. The proposed method avoided the misidentification caused by using fixed bands and avoided the complicated threshold setting. The proposed method improved the disturbance rejection capability of the protection scheme. The simulation results of the proposed method indicated its excellent robustness. Abstract: In a small-current grounding system, the pole-to-ground fault may cause the voltage drop in the fault pole and the voltage rise in the other poles. In flexible DC distribution systems, Severe voltage variation may shorten the insulation lifetime of the equipment, which leads to great concerns on the safety issue. In addition, the existence of high transition resistance degrades the accuracy of fault detection methods, thus further affecting the reliability of the system. Therefore, it is essential to explore an advanced technology for faulty feeder detection. This study proposes a faulty feeder detection method based on the characteristics of transient zero-mode current (TZMC) in multi-frequency bands. The change rate of zero-mode voltage is applied as the protection activation criterion. Then, the characteristic matrix is constructed via computing the fuzzy entropy of TZMC in each frequency band. Finally, the faulty feeder can be identified by conducting fuzzy C-means on the characteristic matrix. This proposed method is tested through simulations on the PSCAD/EMTDC platform, which successfully demonstrates its outstanding adaptability, reliability, and accuracy.