Browsing by Author "Akinci, TC"

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    Spectral and statistical analysis for ferroresonance phenomenon in electric power systems
    Seker, S; Akinci, TC; Taskin, S
    This study presents our findings on the ferroresonance phenomenon for the Seyitomer-Isiklar part of the Electric Power System of 380 kV in Turkey. In this context, the power spectral density approach and Short-Time Fourier Transforms are applied to the voltage variations for phase R of the sample power network. The findings show that the ferroresonance event can be represented by the interharmonics between 50 and 250 Hz, as well as statistical properties. In addition, a histogram of the ferroresonance region shows a different characteristic from the overall data and the non-ferroresonance region. This different characteristic can be defined by an asymmetrical distribution characteristic, and its numerical measure is given by the Noise to Signal Ratio of 0.624.
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    Reverse Power Data Analysis and Feature Extraction Based Upon Continuous Wavelet Transform for Electric Power Plants
    Taskin, S; Seker, S; Irgen, B; Akinci, TC
    This study is focused on the investigating of a power plant generator in reverse power condition. For this purpose, reverse power data were collected from a Combined Heat and Power Plant generator protection relay. The reverse power conditions were evaluated by means of the time-frequency and time-scale methods. As a result of this evaluation, it can be said that the time-frequency and lime-scale properties of the signals like current, voltage, frequency, active and reactive powers were extracted with all details. Copyright (C) 2010 Praise Worthy Prize S.r.l. - All rights reserved.
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    Spectral Analysis for Current and Temperature Measurements in Power Cables
    Taskin, S; Seker, S; Karahan, M; Akinci, TC
    This research aims to detect spectral properties under thermal and current variations for power cables. Therefore, spectral diversities are exposed under current unbalances and different load conditions through the spectral analysis techniques. Also, huge load variations are easily detected from the current signals in the time-frequency plane using the short-time frequency analysis. Hence, this study presents the determination of the frequency characteristics and spectral similarities between the phase currents and thermal variations.