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| A High Impedance Fault Detection Method for Flexible DC Distribution Network |
| Wang Xiaowei1, 2, Gao Jie3, Wu Lei2, Song Guobing2, Wei Yanfang1 |
1. School of Electrical Engineering and Automation Henan Polytechnic UniversityJiaozuo 454000 China;
2. School of Electrical Engineering Xi’anJiaotong University Xi’an 710049 China;;
3. Wenzhou Power Supply Company Zhejiang Electric Power Company Wenzhou 325000 China |
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Abstract Flexible DC distribution network has acquired more interest and development in recent years, with the emergency of lots of renewable energy and direct current (DC) loads, as for the high impedance fault (HIF) detection in flexible DC distribution network, it not gathers attention from the industry and research community. Hence, this paper proposed an improved complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method. Firstly, it utilizes CEEMDAN to extract the first intrinsic mode function component (IMF1) of transient zero mode current (TZMC), and obtainedthe mutation singular point by calculating one order differences among IMF1, then, it distinguishes fault stage from normal condition (NC) to calculate the slopes near the singular point, and compare slopes with start threshold. Secondly, uses Prony algorithm to identify the IMF1 parameters, which including characteristic frequency component (CFC) and DC component, besides, calculates the energy ratio between CFC and DC to distinguish small impedance fault (SIF), medium impedance fault (MIF), high impedance fault (HIF) and load switching (LS). Lots of simulation experiments and field data prove that the paper can detect HIF effectively, and has some advantages compared with other methods in feature extraction, detection accuracy and calculation speed and so on.
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Received: 01 July 2018
Published: 17 July 2019
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2019, Vol. 34 
