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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control)
Ashwani Kumar Chandel
National Institute of Technology Hamirpur
Computer Science & IT

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Transient Stability Enhancement of the Power System with Wind Generation Sujith Mohandas; Ashwani Kumar Chandel
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 9, No 2: August 2011
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v9i2.697

Abstract

 Transient stability analysis of a power system with wind generation has been addressed in this paper. The effects of automatic voltage regulators, power system stabilizers, and static synchronous compensators on transient stability of a power system are investigated. Various simulation results show that addition of power system stabilizer and static synchronous compensators reduce the rotor angle oscillations. However, the static synchronous compensator shows better damping characteristics and improves the stability of the wind integrated system. It has been established that the static synchronous compensator damps out the speed oscillations in the shaft of the constant speed wind turbine. A transient impact index has been proposed to prove that the static compensator damps out the rotor oscillations.
Inverse S-Transform Based Decision Tree for Power System Faults Identification Srikanth Pullabhatla; Ashwani Kumar Chandel; Anil Naik Kanasottu
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 9, No 1: April 2011
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v9i1.674

Abstract

 In this paper a decision tree based identification of power system faults has been proposed. The key input values to the decision tree are the performance indices calculated from the maximum values of unfiltered inverse Stockwell transform (MUNIST) technique. A wide range of techniques including Stockwell transform (ST) have been used for the identification of power system faults. However, the signatures produced by these techniques are not unique and sometimes lead to misinterpretation of faults. Consequently, a decision tree based on the inverse Stockwell transform method is proposed in the present paper to automatically identify both the symmetrical and unsymmetrical power system faults. The method is able to determine both sudden and gradual changes in the signal caused by different power system faults. The technique is very accurate and produces unique signatures compared to the existing techniques. The results obtained show the efficacy of the proposed technique. 
Co-Authors Anil Naik Kanasottu Srikanth Pullabhatla Sujith Mohandas