Ozgul Salor

Multipurpose Platform for Power System Monitoring and Analysis With Sample Grid Applications

This paper is devoted to the design and implementation of a multipurpose platform (MPP) for power system monitoring and analysis. This MPP is a novel device, which combines the abilities of a power quality (PQ) analyzer, an event logger, a synchronized phasor measurement unit, and an interarea oscillation identifier, all in one device. The multiple functions of the proposed MPP can serve the needs of the power system operators (SOs) as a wide-area monitoring system to observe the states and stability of the power system, and as a PQ analyzer to monitor the PQ events and parameters, permanently. Furthermore, the algorithms of flicker and harmonic current contributions at a point of common coupling can be embedded on this MPP, to determine the individual contributions of different loads supplied from the same bus. The operational features of the developed MPP have been tested on the Turkish electricity transmission system and its interfaces with the distribution system by installing 450 MPPs and integrating them with a monitoring and control center. The proposed all-in-one MPP can therefore meet the multiple requirements of the power SOs to serve the needs of modern electricity markets and convert an ordinary electricity system to a smart grid.

Data Mining Framework for Power Quality Event Characterization of Iron and Steel Plants

In this paper, a power quality (PQ) knowledge discovery and modeling framework has been developed for both temporal and spatial PQ event data collected from transformer substations supplying iron and steel (I&S) plants. PQ event characteristics of various I&S plants have been obtained based on clustering and rule discovery techniques. The data are collected by the PQ analyzers, which detect the voltage sags, swells, and interruptions according to the IEC Standard 61000-4-30. The constructed clustering strategy ensures feasible system monitoring by reducing unmanageable number of PQ events collected by the distributed PQ measurement systems into event clusters count. An abstraction for event representation has been developed, through which representative feature bags are constructed for each event to be used in the similarity decisions. The developed model has been applied satisfactorily to PQ event data obtained from 15 major transformer substations supplying heavy industry zones of the transmission system up to a five-year time period and from two additional transformer substations supplying some other industrial zones, for comparison purposes. The developed PQ data mining framework, which is used to identify PQ event distributions based on the event descriptions given in the IEEE Std. 1159, provides a useful analysis and evaluation infrastructure for taking countermeasures against the most probable event occurrences, specific to those feeders of I&S plant transformer substations.

Correlation Between Multiple Electric Arc Furnace Operations and Unscheduled Power Flows in the Interconnection Lines at the Eastern Cross Border of ENTSO-E

In this paper, the correlation between unscheduled power flows in the interconnection lines at the eastern cross border of the European Network of Transmission System Operators for Electricity (ENTSO-E) and multiple electric arc furnace (EAF) operations in Turkey has been assessed. Turkey is interconnected to ENTSO-E at the eastern cross border via Greece and Bulgaria, with a 400-MW export and a 550-MW import agreement. In order to determine the degree of the relationship between the unscheduled power exchange between Turkey and Europe, and the multiple high-power EAF operations, Pearson correlation method has been employed. For this purpose, time-synchronized data of active power consumption have been collected from 17 major EAF plants during 1 week with a time resolution of 3 s, by using custom-design, synchronized power-quality (PQ) analyzers. A total peak-power consumption of nearly 1.5 GW of multiple EAF loads has been recorded. The results obtained have been evaluated by the use of the National Power Quality Monitoring System of Turkey, which continuously monitors the power flows in the interconnection lines of the ENTSO-E by PQ analyzers. The rate of change in total EAF power consumptions higher than 200 MW in less than 15 s against the rate of change in area control error (ACE) index is found to be closely correlated to each other, with a Pearson correlation coefficient (CC) of 0.8. Since the response of the frequency restoration reserve of power plants is much slower, such rapid fluctuations in the power consumption of multiple EAFs collectively result in uncontrollable power flows in the interconnection lines at the eastern cross border of ENTSO-E.

State-Estimation-Based Determination of Harmonic Current Contributions of Iron and Steel Plants Supplied from PCC

In this paper, a state-estimation-based method is proposed to determine harmonic current contributions of iron and steel (IS hence, it provides accurate harmonic contributions of the electric arc furnace (EAF) plants.

Online characterization of interharmonics and harmonics of AC electric arc furnaces by multiple synchronous reference frame analysis

In this paper, a multiple synchronous reference frame (MSRF) analysis framework is developed to determine the positive- and negative-sequence components of all interharmonic and harmonic currents produced by alternating current electric arc furnace (AC EAF) installations, which can be considered as balanced but asymmetrical three-phase, three-wire loads on the power system. The aim of developing the MSRF analysis framework is twofold; deep understanding of the EAF characteristics, and fast and accurate generation of reference signals to the controllers of the advanced technology compensation systems such as active power filters (APFs), synchronous static compensators (STATCOMs), and energy storage systems (ESS), which may successfully compensate interharmonics, harmonics, and flicker. Online characterization of interharmonics and harmonics by MSRF analysis utilizes continuously measured line currents and line voltages on the medium-voltage side of the EAF transformer at a sampling rate of 25.6-kHz per data channel. It has been shown by offline computations that compensation of the sequence components of interharmonics and harmonics of the EAF currents obtained by the proposed framework, reduces the short-term flicker values at the point of common coupling by up to 10-fold. The proposed MSRF analysis framework has been successfully verified by comparing the frequency spectrums of the EAF currents with Fourier analysis results based on one-cycle sliding windows of 10-cycle duration.

Classification of power quality events using deep learning on event images

In this paper, a new method for the classification of power quality (PQ) events of the electricity networks based on deep learning approach is presented. In contrast with the existing PQ event data analysis techniques, sampled voltage data of the PQ events are not used, but image files of the three-phase PQ event data are analyzed by taking the advantage of the success of the deep leaning approach on image-file-classification. Therefore, the novelty of the proposed approach is that, image files of the voltage waveforms of the three phases of the power grid are classified. PQ events obtained from four transformer substations of the electricity transmission system for a year are used for training and testing the proposed classification method. DIGITS deep learning platform of NVIDIA is employed for the application of the deep learning algorithm on PQ event data images. It is shown that the test data can be classified with 100% accuracy. The proposed work is believed to serve the needs of the future smart grid applications, which are fast and automatic analysis of the electricity grid and taking automatic countermeasures against potential PQ events.

Harmonics and interharmonics analysis of electrical arc furnaces based on spectral model optimization with high resolution windowing

In this paper, a spectral model optimization based method for the analysis of harmonics and interharmonics produced by electric arc furnace (EAF) installations is presented. Detecting the changes occurring in the frequency spectrum of the EAF voltages fast and accurately has crucial importance to eliminate the undesired effects of harmonics and interharmonics using advanced technology compensation systems such as active power filters, synchronous static compensators, energy storage systems, and etc. The aim of the research work presented here is to reduce the spectral leakage effects experienced by Fourier analysis based methods by estimating the spectral model parameters using nonlinear least squares. The Fourier spectrum of the signal is used as apriori information; however, the proposed model does not suffer from the spectral leakage problems encountered by the Fourier analysis based methods in case of fundamental frequency variation, which frequently occurs in the existence of EAF plants in an electrical system. Moreover, the proposed model permits frequency detection at a much higher resolution than the Fourier analysis based methods. The proposed method has been tested on both synthetic and field data and it has been shown that it is able to detect frequency components and the corresponding amplitudes and phases of harmonics and interharmonics with high accuracy for EAF plants.

Correlation between multiple electric arc furnace operations and unscheduled power flows in the interconnection lines at the eastern cross border of ENTSO-E

In this paper, the correlation between unscheduled power flows in the interconnection lines at the eastern cross border of the European Network of Transmission System Operators for Electricity (ENTSO-E) and multiple electric arc furnace (EAF) operations in Turkey, has been assessed. Turkey is interconnected to ENTSO-E at the eastern cross border via Greece and Bulgaria, with a 400 MW export and a 550 MW import agreement. In order to determine the degree of the relationship between the unscheduled power exchange between Turkey and Europe, and the multiple high power EAF operations, Pearson correlation method has been employed. For this purpose, time-synchronized data of active power consumption have been collected from 17 major EAF plants during one week with a time resolution of three seconds, by using custom-design, synchronized power quality analyzers. A total peak power consumption of nearly 1.5 GW of multiple EAF loads has been recorded. The results obtained have been evaluated by the use of the National Power Quality Monitoring System of Turkey, which continuously monitors the power flows in the interconnection lines of the ENTSO-E by power quality analyzers. The rate of change of total EAF power consumptions higher than 200 MW for less than 15-s duration against the rate of change of area control error (ACE) index are found to be closely correlated to each other, with a Pearson correlation coefficient of 0.8. Since the response of the frequency restoration reserve of power plants is much slower, such rapid fluctuations in the power consumption of multiple EAFs collectively result in uncontrollable power flows in the interconnections lines at the eastern cross border of ENTSO-E.

Data mining framework for power quality event characterization of iron and steel plants

In this paper, a power quality (PQ) knowledge discovery and modeling framework has been developed for both temporal and spatial PQ event data collected from transformer substations supplying iron and steel (I&S) plants. PQ event characteristics of various I&S plants have been obtained based on clustering and rule discovery techniques. The data are collected by the PQ analyzers, which detect the voltage sags, swells, and interruptions according to the IEC Standard 61000-4-30. The constructed clustering strategy ensures feasible system monitoring by reducing unmanageable number of PQ events collected by the distributed PQ measurement systems into event clusters count. An abstraction for event representation has been developed, through which representative feature bags are constructed for each event to be used in the similarity decisions. The developed model has been applied satisfactorily to PQ event data obtained from 15 major transformer substations supplying heavy industry zones of the transmission system up to a five-year time period and from two additional transformer substations supplying some other industrial zones, for comparison purposes. The developed PQ data mining framework, which is used to identify PQ event distributions based on the event descriptions given in the IEEE Std. 1159, provides a useful analysis and evaluation infrastructure for taking countermeasures against the most probable event occurrences, specific to those feeders of I&S plant transformer substations.

Exponential smoothing of multiple reference frame components with GPUs for real-time detection of time-varying harmonics and interharmonics of EAF currents

In this research work, a multiple synchronous reference frame (MSRF) based analysis method used together with exponential smoothing (ES) to accurately obtain the time-varying harmonics and interharmonics of electric arc furnace (EAF) currents, is proposed. The proposed method has been implemented on NVIDIA Geforce GTX 960 graphics card for the parallel processing of all harmonics and interharmonics so that real-time processing of the EAF currents obtained from a measurement point of the electricity transmission system is possible. To obtain the best possible accuracy for the EAF current harmonics and interharmonics estimation, the ES window size has been optimized specific to each harmonic and interharmonic frequency component. It has been shown on field data that the implemented system is capable of successfully estimating all harmonics up to the 50th and all interharmonics at 5Hz resolution in real-time. Moreover, active filtering of certain harmonics and interharmonics has been achieved in the simulation environment and it has been shown that successful real-time filtering of any harmonic and interharmonic component is possible with the proposed MSRF+ES method. Hence, it can be concluded that the proposed system can be used to generate reference signals for the controllers of the new technology compensation systems such as active power filters.