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Journal articles on the topic 'Synchrophaseur'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Adewole, Adeyemi Charles, and Raynitchka Tzoneva. "Conformance Testing and Analysis of Synchrophasor Communication Message Structures and Formats for Wide Area Measurement Systems in Smart Grids." International Journal of Advances in Applied Sciences 6, no. 2 (2017): 106. http://dx.doi.org/10.11591/ijaas.v6.i2.pp106-116.

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The renewed quest for situational awareness in power systems has brought about the use of digital signal processing of power system measurements, and the transmission of such data to control centres via communication networks. At the control centres, power system stability algorithms are executed to provide monitoring, protection, and control in order to prevent blackouts. This can be achieved by upgrading the existing Supervisory Control and Data Acquisition (SCADA) systems through the deployment of newly proposed power system synchrophasor-based applications for Wide Area Monitoring, Protect

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Zseby, Tanja, Joachim Fabini, and Dipika Rani. "Synchrophasor communication." e & i Elektrotechnik und Informationstechnik 131, no. 1 (2013): 8–13. http://dx.doi.org/10.1007/s00502-013-0193-6.

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3

Kunac, Antonijo, Marin Despalatović, and Dario Šantić. "Synchrophasors Determination Based on Interpolated FFT Algorithm." Journal of Energy - Energija 69, no. 1 (2020): 7–12. http://dx.doi.org/10.37798/202069133.

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Within the standard IEEE C37.118 applications and proposed hardware structure of a phasor measurement unit (PMU) are described. This paper presents the concept of the system for measuring and transferring synchrophasors from a theoretical aspect. Synchrophasor algorithms are developed in MATLAB/Simulink for the purpose of easier verification and hardware deployment on today’s market available and affordable real time development kits. Analysis of the synchrophasor measurement process is performed gradually. Firstly, by defining the synchrophasor based on three-phase to αβ-transformation and th

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4

Kummerow, Andre, Cristian Monsalve, Christoph Brosinsky, Steffen Nicolai, and Dirk Westermann. "A Novel Framework for Synchrophasor Based Online Recognition and Efficient Post-Mortem Analysis of Disturbances in Power Systems." Applied Sciences 10, no. 15 (2020): 5209. http://dx.doi.org/10.3390/app10155209.

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Synchrophasor based applications become more and more popular in today’s control centers to monitor and control transient system events. This can ensure secure system operation when dealing with bidirectional power flows, diminishing reserves and an increased number of active grid components. Today’s synchrophasor applications provide a lot of additional information about the dynamic system behavior but without significant improvement of the system operation due to the lack of interpretable and condensed results as well as missing integration into existing decision-making processes. This study

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5

Binek, Malgorzata, Andrzej Kanicki, and Pawel Rozga. "Application of an Artificial Neural Network for Measurements of Synchrophasor Indicators in the Power System." Energies 14, no. 9 (2021): 2570. http://dx.doi.org/10.3390/en14092570.

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Dynamic phenomena in electric power systems require fast and accurate algorithms for processing signals. The processing results include synchrophasor parameters, e.g., varying amplitude, phase or frequency of sinusoidal voltage or current signals. This paper presents a novel estimation method of synchrophasor parameters that comply with the requirements of IEEE/IEC standards. The authors analyzed an algorithm for measuring the phasor magnitude by means of a selected artificial neural network (ANN), an algorithm for estimating the phasor phase and frequency that makes use of the zero-crossing m

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Castello, Paolo, Carlo Muscas, Paolo Attilio Pegoraro, and Sara Sulis. "Low-cost implementation and characterization of an active phasor data concentrator." ACTA IMEKO 8, no. 2 (2019): 21. http://dx.doi.org/10.21014/acta_imeko.v8i2.625.

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The main components of an advanced measurement system based on synchrophasor technology for the monitoring of power systems are the phasor measurement unit (PMU), which represents the ‘sensor’, and the phasor data concentrator (PDC), which collects the data forwarded by PMUs installed on the field. For the purpose of extending the benefit of synchrophasor technology from transmission grids to distribution networks, different projects are seeking to use low-cost platforms to design devices with PMU functionalities. In this perspective, in order to achieve a complete synchrophasor-based measurem

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Chen, Lei, Wei Zhao, Fuping Wang, Qing Wang, and Songling Huang. "Enhanced Interpolated Dynamic DFT Synchrophasor Estimator Considering Second Harmonic Interferences." Sensors 18, no. 9 (2018): 2748. http://dx.doi.org/10.3390/s18092748.

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In the future, phasor measurement units are expected to be applied in distribution networks (DNs) for their control and monitoring. Because of the widely used power electronic devices in DNs, harmonics are widely present in a voltage/current signal. Particularly, second harmonics have the most significant uncertainty contributions to synchrophasor estimation, which is especially true when a short cycle observation window is used for a fast response. Based on the interpolated dynamic discrete Fourier transform (IpD 2 FT), this paper introduces an enhanced IpD 2 FT (e-IpD 2 FT) synchrophasor est

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8

Castello, Paolo, Carlo Muscas, Paolo Pegoraro, and Sara Sulis. "PMU’s Behavior with Flicker-Generating Voltage Fluctuations: An Experimental Analysis." Energies 12, no. 17 (2019): 3355. http://dx.doi.org/10.3390/en12173355.

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Phasor measurement units (PMUs), which are the key components of a synchrophasor-based wide area monitoring system (WAMS), were historically conceived for transmission networks. The current trend to extend the benefits of the synchrophasor technology to distribution networks requires the PMU to also provide trustworthy information in the presence of signals that can occur in a typical distribution grid, including the presence of severe power quality (PQ) issues. In this framework, this paper experimentally investigates the performance of PMUs in the presence of one of the most important PQ phe

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9

Subramanian, Karthikeyan, and Ashok Kumar Loganathan. "Islanding Detection Using a Micro-Synchrophasor for Distribution Systems with Distributed Generation." Energies 13, no. 19 (2020): 5180. http://dx.doi.org/10.3390/en13195180.

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Distributed Generation (DG) has changed the power generation system to small-scale instead of large-scale generation. The demanding issue with the interconnection of DG is the detection of unintended islanding in a network. Several methods proposed in the literature show drawbacks such as high non-detection zones (NDZ) and higher tripping time. In this paper, the IEEE 13 bus distribution network with DGs like wind and solar power plants is integrated at two buses. Islanding is detected by utilizing data from a micro-synchrophasor located at the distribution grid and the DG. The micro-synchroph

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10

Mokeev, Alexey V., Sergey A. Piskunov, Dmitry N. Ulyanov, and Evgeniy I. Khromtsov. "Improving the efficiency and reliability of RPA systems of digital step-down substations and digital grids." E3S Web of Conferences 216 (2020): 01044. http://dx.doi.org/10.1051/e3sconf/202021601044.

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The article discusses examples of synchrophasor measurement (SPM) technology application for implementation of inherently selective protection for 35-220 kV step-down substations and 6-20 kV distribution points.

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11

Xue, Cheng, and Ruan. "Enhanced Flat Window-Based Synchrophasor Measurement Algorithm for P Class PMUs." Energies 12, no. 21 (2019): 4039. http://dx.doi.org/10.3390/en12214039.

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Accurate and fast synchrophasor measurement, especially under dynamics and distortions, is crucial for control and protection of power grid. The dynamics and distortions in the power grid may occur simultaneously, which increase the complexity of the problem. To address this issue, an enhanced flat window-based P class synchrophasor measurement algorithm (EFW-PSMA) is proposed in this paper. Firstly, an EFW is design based on the least square (LS) approach. Secondly, the EFWs are adopted as the low pass filters (LPFs) in the EFW-PSMA structure to extract the fundamental component. Finally, the

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12

BARCZENTEWICZ, Szymon. "Synchrophasor based Islanding Detection method." PRZEGLĄD ELEKTROTECHNICZNY 1, no. 11 (2015): 100–103. http://dx.doi.org/10.15199/48.2015.11.27.

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13

de la O Serna, Jose Antonio. "Synchrophasor Estimation Using Prony's Method." IEEE Transactions on Instrumentation and Measurement 62, no. 8 (2013): 2119–28. http://dx.doi.org/10.1109/tim.2013.2265436.

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14

Kundu, Pratim, and Ashok Kumar Pradhan. "Synchrophasor-Assisted Zone 3 Operation." IEEE Transactions on Power Delivery 29, no. 2 (2014): 660–67. http://dx.doi.org/10.1109/tpwrd.2013.2276071.

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15

Makram, Elham B., Megan C. Vutsinas, Adly A. Girgis, and Zheng Zhao. "Contingency analysis using synchrophasor measurements." Electric Power Systems Research 88 (July 2012): 64–68. http://dx.doi.org/10.1016/j.epsr.2012.01.002.

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16

Hojabri, Mojgan, Ulrich Dersch, Antonios Papaemmanouil, and Peter Bosshart. "A Comprehensive Survey on Phasor Measurement Unit Applications in Distribution Systems." Energies 12, no. 23 (2019): 4552. http://dx.doi.org/10.3390/en12234552.

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Synchrophasor technology opens a new window for power system observability. Phasor measurement units (PMUs) are able to provide synchronized and accurate data such as frequency, voltage and current phasors, vibration, and temperature for power systems. Thus, the utilization of PMUs has become quite important in the fast monitoring, protection, and even the control of new and complicated distribution systems. However, data quality and communication are the main concerns for synchrophasor applications. This study presents a comprehensive survey on wide-area monitoring systems (WAMSs), PMUs, data

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17

Kumar, Surender, M. K. Soni, and D. K. Jain. "Cyber Security Threats in Synchrophasor System in Wide Area Monitoring System." TELKOMNIKA Indonesian Journal of Electrical Engineering 15, no. 3 (2015): 436. http://dx.doi.org/10.11591/tijee.v15i3.1560.

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<p>Cyber security has become a critical priority for electric utilities. With the increase in the use of intelligent measuring devices like PMUs and more advanced communications and information technology in smart grid, the overall attack surface has increased. Cyber attacks against synchrophasor system critical infrastructure are detrimental to the functioning of the society as a whole. This paper presents the latest on cyber security of synchrophasor system in smart grid, specifically; it focuses on the deep understanding of the risk in terms of threats, vulnerabilities and consequence

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18

Das, Sarasij, and Tarlochan Sidhu. "Robust algorithm to estimate fault synchrophasor from fault-transient synchrophasor in phasor data concentrator." IET Generation, Transmission & Distribution 9, no. 2 (2015): 124–32. http://dx.doi.org/10.1049/iet-gtd.2014.0100.

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19

Xue, Hui, Mengjie Ruan, and Yifan Cheng. "A Fixed Length Adaptive Moving Average Filter-Based Synchrophasor Measurement Algorithm for P Class PMUs." Energies 12, no. 21 (2019): 4168. http://dx.doi.org/10.3390/en12214168.

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Accurate and fast synchrophasor measurement is the key to the wide applications of PMUs in the system-wide monitoring and reliable operation of smart grid. To address this issue, a fixed length moving average filter-based synchrophasor measurement algorithm for P class phasor measurement units (PMUs) (FA-PSMA) is proposed in this paper. Firstly, a novel fixed length adaptive moving average filter (FAMAF) is proposed. The FAMAF has an adaptive filter capability with a fixed data window length. Then, the FAMAF is applied after a phase-locked loop (PLL) for enhanced disturbance rejection capabili

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20

Agarwal, P. K., V. K. Agarwal, and Harish Rathour. "Application of PMU-Based Information in the Indian Power System." International Journal of Emerging Electric Power Systems 14, no. 1 (2013): 79–86. http://dx.doi.org/10.1515/ijeeps-2013-0019.

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Abstract SCADA/EMS system has been the most commonly used tool for real-time power system operation and control throughout the world. This system has been found to be very useful in steady-state analysis of the power system. The ever-increasing dependence of human society and every country’s economy on electrical energy calls for reliable power delivery. In order to meet these expectations, engineers across the globe have been exploring such new technologies that can improve upon the limitations of SCADA and provide dynamic visibility of the power system. A breakthrough has now been achieved i

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21

Berdin, Alexander, Dmitriy Bliznyuk, and Pavel Kovalenko. "Defining the nodal equivalent parameters using synchrophasor measurements." MATEC Web of Conferences 208 (2018): 03003. http://dx.doi.org/10.1051/matecconf/201820803003.

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The method for defining the nodal equivalent parameters of grid elements based on synchrophasor measure-ments during transients in a power system is proposed. It allows to define the topology and parameters of nodal equivalents and makes it possible to implement adaptive models for problems of power system control.

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22

Jha, Amitkumar V., Bhargav Appasani, Abu Nasar Ghazali, and Nicu Bizon. "A Comprehensive Risk Assessment Framework for Synchrophasor Communication Networks in a Smart Grid Cyber Physical System with a Case Study." Energies 14, no. 12 (2021): 3428. http://dx.doi.org/10.3390/en14123428.

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The smart grid (SG), which has revolutionized the power grid, is being further improved by using the burgeoning cyber physical system (CPS) technology. The conceptualization of SG using CPS, which is referred to as the smart grid cyber physical system (SGCPS), has gained a momentum with the synchrophasor measurements. The edifice of the synchrophasor system is its communication network referred to as a synchrophasor communication network (SCN), which is used to communicate the synchrophasor data from the sensors known as phasor measurement units (PMUs) to the control center known as the phasor

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23

Kirincic, Vedran, Srdjan Skok, and Dubravko Frankovic. "A Synchrophasor Assisted Hybrid State Estimator." Journal of Electrical Engineering 67, no. 2 (2016): 103–10. http://dx.doi.org/10.1515/jee-2016-0015.

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Abstract The paper presents a Synchrophasor Assisted Hybrid State Estimator that utilizes the conventional SCADA measurements and the synchrophasors obtained from Phasor Measurement Units (PMUs). To take advantage of the high sampling frequency of the multiple sets of synchrophasors they are preprocessed in a recursive algorithm that provides the state estimate for the power system part observable by PMUs. The results are forwarded to an iterative procedure in which they are combined with SCADA measurements. The given solution was applied on the IEEE test systems with 14, 30 and 57 buses and i

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24

CYGAN, Szymon. "Analysis of the synchrophasor estimation problem." PRZEGLĄD ELEKTROTECHNICZNY 1, no. 11 (2018): 86–90. http://dx.doi.org/10.15199/48.2018.11.20.

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25

Barchi, Grazia, David Macii, and Dario Petri. "Synchrophasor Estimators Accuracy: A Comparative Analysis." IEEE Transactions on Instrumentation and Measurement 62, no. 5 (2013): 963–73. http://dx.doi.org/10.1109/tim.2012.2236776.

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26

Sun, Kai, and Wei Kang. "Observability and Estimation Methods Using Synchrophasor." IFAC Proceedings Volumes 47, no. 3 (2014): 963–68. http://dx.doi.org/10.3182/20140824-6-za-1003.00182.

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27

Wu, Tianying, S. Arash Nezam Sarmadi, Vaithianathan Venkatasubramanian, Alex Pothen, and Ananth Kalyanaraman. "Fast SVD Computations for Synchrophasor Algorithms." IEEE Transactions on Power Systems 31, no. 2 (2016): 1651–52. http://dx.doi.org/10.1109/tpwrs.2015.2412679.

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28

Pal, Anamitra, J. S. Thorp, Taufiquar Khan, and S. Stanley Young. "Classification Trees for Complex Synchrophasor Data." Electric Power Components and Systems 41, no. 14 (2013): 1381–96. http://dx.doi.org/10.1080/15325008.2013.824048.

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29

Berdin, Alexander, and Pavel Kovalenko. "Defining the power system load frequency static response slope based on transient synchrophasor data." MATEC Web of Conferences 208 (2018): 04002. http://dx.doi.org/10.1051/matecconf/201820804002.

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The method is proposed for defining the power system load frequency static response based on synchrophasor measurements during transients accompanied by frequency deviations. The method was successfully validated involving four events resulting in frequency deviations in the Northern part of Tyumen region of up to 0.06 Hz magnitude and recorded by means of the System operator WAMS.

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30

Lee, Yunhwan, and Hwachang Song. "Decentralized Load Shedding Method Based on Voltage Stability Margin Index Using Synchrophasor Measurement Technology." Electronics 7, no. 11 (2018): 277. http://dx.doi.org/10.3390/electronics7110277.

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This study develops an analytical method for assessing the voltage stability margins of a decentralized load shedding scheme; it then examines the challenges related to the existing load shedding scheme. It also presents a practical application for implementing the proposed method, based on the synchrophasor measurement technology in modern power grid operations. By applying the concept of a continuously-computed voltage stability margin index to the configuration of the Thévenin equivalent system, the maximum transfer power could be used as an index to monitor the voltage instability phenomen

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31

Oruganti, Venkata Subrahmanya Raghavendra Varaprasad, Venkata Sesha Samba Siva Sarma Dhanikonda, Helmo Kelis Morales Paredes, and Marcelo Godoy Simões. "Enhanced Dual-Spectrum Line Interpolated FFT with Four-Term Minimal Sidelobe Cosine Window for Real-Time Harmonic Estimation in Synchrophasor Smart-Grid Technology." Electronics 8, no. 2 (2019): 191. http://dx.doi.org/10.3390/electronics8020191.

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The proliferation of nonlinear loads and integration of renewable energy sources require attention for accurate harmonic estimation along with estimation of fundamental amplitude, phase, and frequency for protection, improving power quality, and managing power effectively in a smart distribution grid. There are currently different Windowed Interpolated Fast Fourier Transform (WIFFT) algorithms for harmonic voltage estimation, but estimation of current harmonics using WIFFT is not explored sufficiently. The existing WIFFT algorithms, when used for current harmonic estimation result in low accur

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32

Magliozzi, Bernard. "Adaptive synchrophaser for reducing aircraft cabin noise and vibration." Journal of the Acoustical Society of America 99, no. 6 (1996): 3282. http://dx.doi.org/10.1121/1.414976.

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33

Popov, Alexandr I., Alexey V. Mokeev, Sergey A. Piskunov, and Andrey V. Rodionov. "Applications of synchrophasor measurement to improve the reliability and efficiency of power systems." E3S Web of Conferences 216 (2020): 01045. http://dx.doi.org/10.1051/e3sconf/202021601045.

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The article deals with the development of software and hardware systems that expand the scope of application of the synchrophasor measurement (SPM) technology. The following tasks are considered as applications: automation of 6-10 kV distribution networks with the possibility of localization a damaged cable line in case of single-phase earth faults, monitoring the state of power transformers, analyzing low-frequency oscillations in the power system.

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34

Conti, Stefania, Santi A. Rizzo, Nunzio Salerno, and Giuseppe M. Tina. "Distribution network topology identification based on synchrophasor." AIMS Energy 6, no. 2 (2018): 245–60. http://dx.doi.org/10.3934/energy.2018.2.245.

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35

Trudnowski, D. J. "Estimating Electromechanical Mode Shape From Synchrophasor Measurements." IEEE Transactions on Power Systems 23, no. 3 (2008): 1188–95. http://dx.doi.org/10.1109/tpwrs.2008.922226.

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36

Sehwail, Hussam, and Ian Dobson. "Applying Synchrophasor Computations to a Specific Area." IEEE Transactions on Power Systems 28, no. 3 (2013): 3503–4. http://dx.doi.org/10.1109/tpwrs.2013.2248957.

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37

Olken, Mel. "Key Developments: Synchrophasor Technology [From the Editor]." IEEE Power and Energy Magazine 13, no. 5 (2015): 4. http://dx.doi.org/10.1109/mpe.2015.2439935.

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38

Song, Jianhan, Emiliano Dall'Anese, Andrea Simonetto, and Hao Zhu. "Dynamic Distribution State Estimation Using Synchrophasor Data." IEEE Transactions on Smart Grid 11, no. 1 (2020): 821–31. http://dx.doi.org/10.1109/tsg.2019.2943540.

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39

de la O Serna, Jose Antonio, and Ernesto Vazquez Martinez. "Smart grids Part 2: Synchrophasor measurement challenges." IEEE Instrumentation & Measurement Magazine 18, no. 1 (2015): 13–16. http://dx.doi.org/10.1109/mim.2015.7016675.

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Ferrero, Roberto, Paolo Attilio Pegoraro, and Sergio Toscani. "Dynamic Synchrophasor Estimation by Extended Kalman Filter." IEEE Transactions on Instrumentation and Measurement 69, no. 7 (2020): 4818–26. http://dx.doi.org/10.1109/tim.2019.2955797.

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USMAN, Muhammad Usama, and M. Omar FARUQUE. "Applications of synchrophasor technologies in power systems." Journal of Modern Power Systems and Clean Energy 7, no. 2 (2018): 211–26. http://dx.doi.org/10.1007/s40565-018-0455-8.

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42

Ahmadzadeh-Shooshtari, Babak, Roozbeh Torkzadeh, Meysam Kordi, Hesamoddin Marzooghi, and Fariborz Eghtedarnia. "SG parameters estimation based on synchrophasor data." IET Generation, Transmission & Distribution 12, no. 12 (2018): 2958–67. http://dx.doi.org/10.1049/iet-gtd.2017.1989.

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A, Jothikaa, and Rajeswari R. "Estimation of synchrophasor Using Taylor Fourier Transform." IARJSET 8, no. 5 (2021): 492–99. http://dx.doi.org/10.17148/iarjset.2021.8586.

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Obushevs, A., and A. Mutule. "Application of Synchrophasor Measurements for Improving Situational Awareness of the Power System." Latvian Journal of Physics and Technical Sciences 55, no. 2 (2018): 3–10. http://dx.doi.org/10.2478/lpts-2018-0008.

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Abstract The paper focuses on the application of synchrophasor measurements that present unprecedented benefits compared to SCADA systems in order to facilitate the successful transformation of the Nordic-Baltic-and-European electric power system to operate with large amounts of renewable energy sources and improve situational awareness of the power system. The article describes new functionalities of visualisation tools to estimate a grid inertia level in real time with monitoring results between Nordic and Baltic power systems.

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Kumar, Surender, M. K Soni, and D. K Jain. "Cyber Security Threats in Synchrophasor System in Wams." International Journal of Computer Applications 115, no. 8 (2015): 17–22. http://dx.doi.org/10.5120/20172-2355.

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Kundu, Pratim, and Ashok Kumar Pradhan. "Supervisory Protection of Islanded Network Using Synchrophasor Data." IEEE Transactions on Smart Grid 10, no. 2 (2019): 1772–80. http://dx.doi.org/10.1109/tsg.2017.2777873.

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47

Konakalla, Sai Akhil R., and Raymond A. de Callafon. "Feature Based Grid Event Classification from Synchrophasor Data." Procedia Computer Science 108 (2017): 1582–91. http://dx.doi.org/10.1016/j.procs.2017.05.046.

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48

Jones, Kevin D., Anamitra Pal, and James S. Thorp. "Methodology for Performing Synchrophasor Data Conditioning and Validation." IEEE Transactions on Power Systems 30, no. 3 (2015): 1121–30. http://dx.doi.org/10.1109/tpwrs.2014.2347047.

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49

Nuthalapati, Sarma, and Arun G. Phadke. "Managing the Grid: Using Synchrophasor Technology [Guest Editorial]." IEEE Power and Energy Magazine 13, no. 5 (2015): 10–12. http://dx.doi.org/10.1109/mpe.2015.2435596.

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Zhang, Jinhuan, Haixia An, and Na Wu. "Low Frequency Oscillation Mode Estimation Using Synchrophasor Data." IEEE Access 8 (2020): 59444–55. http://dx.doi.org/10.1109/access.2020.2982979.

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