Open AccessAnalysis of Symmetrical and Unsymmetrical Faults Using the EEMD and Scale-Dependent Intrinsic Entropies
Author(s) -
Wei-Tai Hsu,
Chia-Wei Huang
Publication year - 2022
Publication title -
fluctuation and noise letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.268
H-Index - 29
eISSN - 1793-6780
pISSN - 0219-4775
DOI - 10.1142/s0219477522500316
Subject(s) - hilbert–huang transform , electric power system , computer science , entropy (arrow of time) , correlation coefficient , fault (geology) , algorithm , spectral density , signal (programming language) , power grid , transmission system , power (physics) , transmission (telecommunications) , physics , machine learning , telecommunications , filter (signal processing) , quantum mechanics , seismology , computer vision , programming language , geology
The rapid and accurate diagnosis of power grid faults plays a vital role in speeding up the process of accident handling and system recovery and ensuring the safe operation of the power system. This paper proposes to apply the ensemble empirical mode decomposition (EEMD) method and scale-related intrinsic entropy to diagnose the type of fault for the transmission line. First, the electrical data collected by the power system is decomposed by using the EEMD method. Then by eliminating some intrinsic mode functions, the signal is reconstructed by inspecting the correlation coefficient. Finally, the complexity of the reconstructed signal is calculated by using the scale-dependent intrinsic entropy. Since the scale-dependent intrinsic entropy reflects the complexity of one-dimensional time series, it is susceptible to signal changes. The complexity is helpful in the power system for fault signal analysis. The results show the combined method’s effectiveness and practicability through failure analysis using the IEEE 14-bus system as the simulation model.