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Bulunan: 5 Adet 0.001 sn
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Erişime Açık

Waveform Correlation Based Harmonic Voltage Contribution Determination of Iron and Steel Plants Supplied From PCC

Özgül SALOR-DURNA

This paper presents a new waveform correlation based method which determines the individual harmonic voltage contributions of Electric Arc Furnace (EAF) plants supplied from a point of common coupling (PCC). The method is based on the waveform correlation computations between the PCC voltage and the feeder current at the individual harmonic frequency. PCCs supplying multiple EAF plants usually suffer from high voltage harmonic components due to their operation principles. A relationship between the correlation coefficient of the PCC voltage and the feeder current waveforms, and the harmonic vo ...Daha fazlası

Erişime Açık

Deep Learning Based Predictive Compensation of Flicker, Voltage Dips, Harmonics and Interharmonics in Electric Arc Furnaces

Özgül SALOR-DURNA

In this research work, deep machine learning-based methods together with a novel data augmentation are developed for predicting flicker, voltage dip, harmonics, and interharmonics originating from highly time-varying electric arc furnace (EAF) currents and voltage. The aim with the prediction is to counteract both the response and reaction time delays of active power filters (APFs) specifically designed for electric arc furnaces (EAF). Multiple synchronous reference frame (MSRF) analysis is used to decompose the frequency components of the EAF current and voltage waveforms into dqo components. ...Daha fazlası

Erişime Açık

Harmonic Contribution Detection of Iron and Steel Plants Based on Correlation of Time-Synchronized Current and Voltage Signals

Özgül SALOR-DURNA

In this research work, a new harmonic responsibility measure is proposed to extract the amount of harmonic responsibility of each plant supplied from the point of common coupling (PCC). The proposed method uses a function of the correlation coefficients between the voltage and current signals measured synchronously at the PCC. After the verification of the method on synthetic data generated in simulation environment, field data measurements of voltage and current are used to test the practicability of the proposed method. Harmonic contributions of the iron and steel (I&S) plants obtained using ...Daha fazlası

Erişime Açık

Statistical Models of EAF Harmonics Developed for Harmonic Estimation Directly from Waveform Samples Using Deep Learning Framework

Özgül SALOR-DURNA

In this research work, a deep learning (DL)-based method for the fast and accurate analysis of current harmonics of electric arc furnaces (EAF) is proposed. For such a system, a large amount of EAF current data is required for the training phase of the DL-based structure, which is not only a thorny but also an expensive procedure. Hence, the second focus of this research work is to gain the ability to generate EAF currents with realistic harmonic contents based on a much smaller amount of field data of EAF currents. For this purpose, EAF current data, recorded at a transformer substation suppl ...Daha fazlası

Erişime Açık

Deep-Learning-Based Harmonics and Interharmonics Predetection Designed for Compensating Significantly Time-Varying EAF Currents

Özgül SALOR-DURNA

In this article, a new approach to compensate both the response and reaction times of active power filters (APF) for special cases of highly time-varying harmonics and interharmonics of electric arc furnace (EAF) currents is proposed. Instead of using the classical approach of taking a window of past current samples and analyzing the data, future samples of EAF currents are predetected using a deep learning (DL)-based method and then analyzed, which provides the opportunity to make real-time analysis. This can also serve the needs of other possible APF applications. Two different methods for p ...Daha fazlası

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