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Z. He, S. Gao, X. Chen, J. Zhang, Z. Bo and Q. Qian, “Study of a New Method for Power System Transients Classification Based on Wavelet Entropy and Neural Network,” International Journal of Electrical Power & Energy Systems, Article in Press, 2010. doi:10.1016/j.ijepes.2010.10.001

has been cited by the following article:

• TITLE: Wavelet Entropy Based Algorithm for Fault Detection and Classification in FACTS Compensated Transmission Line

  AUTHORS: Amany M. El-Zonkoly, Hussein Desouki

  KEYWORDS: FACTS, SSSC, UPFC, Wavelet Transform, Entropy Calculation

  JOURNAL NAME: Energy and Power Engineering, Vol.3 No.1, February 25, 2011

  ABSTRACT: Distance protection of transmission lines including advanced flexible AC transmission system (FACTS) de-vices has been a very challenging task. FACTS devices of interest in this paper are static synchronous series compensators (SSSC) and unified power flow controller (UPFC). In this paper, a new algorithm is proposed to detect and classify the fault and identify the fault position in a transmission line with respect to a FACTS device placed in the midpoint of the transmission line. Discrete wavelet transformation and wavelet entropy calculations are used to analyze during fault current and voltage signals of the compensated transmission line. The proposed algorithm is very simple and accurate in fault detection and classification. A variety of fault cases and simulation results are introduced to show the effectiveness of such algorithm.