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Prof. Dr. Özgül SALOR-DURNAMühendislik Fakültesi
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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 ...More

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A New Electric Arc Furnace Model Based on Current Waveform Synthesis from Distributions of DFT Amplitudes and Power System Frequency

Özgül SALOR-DURNA

The research work presented in this paper proposes a field-data based method for modeling the behavior of the Electric Arc Furnace (EAF) currents for a tap-to-tap period. EAF current DFT distributions and fundamental frequency histograms obtained out of previously collected EAF currents are used to develop the proposed model, which offers a model for each phase of the EAF operation: boring, melting and refining. The model is verified by comparing the THD histograms and the flicker measurements of the original and the modeled EAF current waveforms. The aim of the proposed method is to provide a ...More

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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. ...More

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Fast harmonic analysis for PHIL experiments with decentralized real-time controllers

Özgül SALOR-DURNA

This paper proposes and implements, a harmonic analysis technique used in microgrids for inverter power control when measured voltage and current signals are passed over a communication link with considerable latency. Using frequency-shifting and filtering techniques, the measurement is converted to magnitude and phase information and passed over an asynchronous communication link to another controller, where the original waveform is recovered with delay compensation. The method allows accurate power calculations and grid synchronization over distributed prosumer controllers. The proposed meth ...More

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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 ...More

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Transient event classification using pmu data with deep learning techniques and synthetically supported training-set

Özgül SALOR-DURNA

This paper presents a research work which focuses on generating synthetic data to enrich the training-set of a deep learning (DL) based classification system to classify power system transient events using PMU frequency measurements. The synthetically improved training-set is shown to increase the classification performance compared to the case when only the actual-data training-set is used. The proposed classification system helps to reveal high-frequency transient variation information out of PMU measurements collected at a relatively much lower rate, especially when a small set of training- ...More

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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 ...More

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Flicker Detection Algorithm Based on the Whole Voltage Frequency Spectrum for New Generation Lamps - Enhanced VPD Flickermeter Model and Flicker Curve

Özgül SALOR-DURNA

It is now known that disturbing light flicker originates not only solely from amplitude modulation (AM) of the fundamental amplitude and low-frequency interharmonic components as described in IEC 61000-4-15 standard but also high-frequency interharmonic components around an odd harmonic which have the same effect as low-frequency components causing flicker. Because this effect cannot be detected by the IEC flickermeter, an effective flickermeter is required In this article, a new flickermeter detects both the low- and high-frequency components robustly has been suggested. Quite close responses ...More

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Power system harmonic and interharmonic estimation using Vortex Search Algorithm

Özgül SALOR-DURNA

In this paper, a vortex search algorithm (VSA) based method designed to estimate power system harmonics and interharmonics for highly time-varying cases is presented. Time-variation in the power system is due to the nonlinear and stochastic loads such as electric arc furnaces (EAF) and it is one of the major cause of the power quality problems. The proposed algorithm is tested on both synthetic signals and also field data obtained from transmission system substations supplying EAF plants. The results are compared with other search algorithm-based methods reported in the literature and shown th ...More

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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 ...More

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Amplitude and phase estimations of power system harmonics using deep learning framework

Özgül SALOR-DURNA

In this study, a new method for the analysis of harmonic components in the power system based on a deep learning (DL) framework is introduced. In the proposed method, both amplitudes and phases of the harmonic components can be estimated accurately, unlike most of the research work in the literature, which usually focus on estimating amplitudes only. A convolutional neural network (CNN) structure is used to estimate the phases and amplitudes of harmonics, although CNN is usually used for classification. It has been shown that the proposed DL-based method can satisfactorily estimate both amplit ...More

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