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The process of Synchronization between two buses in a power system plays a vital role, especially during blackstart or bulk power system restoration period. The synchronization process is primarily monitored in the presence of experienced personnel at the substation level, which might not control or even predict the after effects of synchronization as soon as the synchronizing breaker between the two buses respective to the two islands is closed. However, with the advent of phasor measurement units (PMUs) providing time synchronized synchrophasor data, synchroscope functionality can now be implemented at a centralized remote control platform, usually the control room of the specific utility. This thesis presents a technique along with the actual implementation of such a PMU Synchroscope analytic developed as a part of the Department of Energy sponsored open and Extensible Control and Analytics platform for synchrophasor data (openECA project). The challenges faced to realize this functionality at the centralized remote location along with methods to overcome these hurdles have been discussed in the document. Additional features in comparison to the conventional synchroscope device are also added to facilitate a smoother and successful synchronization, reducing error on behalf of the user /operator and thus, facilitating a faster power system restoration. / Master of Science / Successful and proper synchronization between different nodes of a power system is one of the most crucial stages of restoring power after a major wide area electricity outage. Improper synchronization may lead to additional system outages and might delay the restoration process. In this regards, it is desired to perform this vital task at the electric utility’s central remote control room. This thesis develops an application to perform the successful reconnection between two nodes of a system overcoming the various challenges and incorporating system delays. The application designed is based on real-time measurements and is integrated with an open source framework platform for ease of the user.

Transmission line reactance is an important parameter in carrying out stability studies. The model proposed here utilizes available real time synchrophasor data and information about the generation in the ERCOT grid to determine the Thevenin equivalent reactance of a line. Synchrophasors provide the advantage of synchronized measurements of phase angles which are essential in determining the transmission line reactance. This thesis provides the results of applying this model to estimate the Thevenin equivalent line reactance between McDonald Observatory in West Texas and The University of Texas at Austin. / text

M. Tech. Electrical Engineering. / Discusses that most real-time applications of synchronised phasor measurement units in power system stability studies are done using RTDS simulator, hardware PMUs and PTP hardware modules with GPS providing the time reference. The major drawbacks of this configuration are both technical and economical. The technical limitations are related to the possible number of outputs that can be used to interface PMU devices, which can be very limited; and also the possible limits on small-time step computation due to the big number of output signals. The economic constraints are mainly due to cost: for a research laboratory, only a limited number of units can be acquired due to budgeting issues. To overcome these difficulties, the realisation of an entirely software-based synchrophasor measurement unit, presents an attractive approach. Such a unit will be capable of deliveringreal-time data by acquiring the voltage and current signals from the Matlab/Simulink simulator, low cost software environment PMUs computing real-time phasors of voltage and current and software only PTP synchronisation protocol. The unit delivers synchrophasors for the application of power system SE and small signal stability analysis, but also taking into consideration the accuracy of the synchronisation protocol on the application of power system SE and small signal stability analysis.

Synchronized phasor measurements, or synchrophasors, allow the measurement of voltage phase angle and frequency, and through the comparison of two or more phasor the stability of the grid can be studied. The acquisition of synchrophasors in possible using Phasor Measurement Units (PMUs) and Global Positioning System Technology (GPS). The purpose of this research is to study synchrophasor events in the Western Electricity Coordinating Council (WECC) grid. Several studies have been made in the Texas grid, and that allows a comparison of events in both grids. During this study, five different types of synchrophasor events were observed. The first type of events, which consist of a change in phase angle difference value followed by damped oscillations has also been observed in the Texas grid; however, the other 4 types of events are not common occurrences in the Texas grid. The characteristics of each of the five types of synchrophasor events have been analyzed in this thesis. / text

The operation and control of the power system in an efficient way is important in order to keep the system secure, reliable and economical. With advancements in smart grid, several new algorithms have been developed for improved operation and control. These algorithms need to be extensively tested and validated in real time before applying to the real electric power grid. This work focuses on the development of a real time test bed for testing and validating power system control algorithms, hardware devices and cyber security vulnerability. The test bed developed utilizes several hardware components including relays, phasor measurement units, phasor data concentrator, programmable logic controllers and several software tools. Current work also integrates historian for power system monitoring and data archiving. Finally, two different power system test cases are simulated to demonstrate the applications of developed test bed. The developed test bed can also be used for power system education.

An increase in demand for electric power has forced utility transmission systems to continuously operate under stressed conditions, which are close to instability limits. Operating power systems under such conditions along with inadequate reactive power reserves initiates a sequence of voltage instability points and can ultimately lead to a system voltage collapse. Significant research have been focused on time-synchronized measurements of power systems which can be used to frequently determine the state of a power system and can lead to a more robust protection, control and operation performance. This thesis discusses the applicability of two voltage stability synchrophasor-based indices from literature to analyze the stability of a power system. Various load flow scenarios were conducted on the BPA 10-Bus system and the IEEE 39-Bus System using PowerWorld Simulator. The two indices were analyzed and compared against each other along with other well-known methods. Results show that their performances are coherent to each other regarding to voltage stability of the system; the indices can also predict voltage collapse as well as provide insight on other locations within the system that can contribute to instability.

ABSTRACT Designing Anti-Islanding Detection Using the Synchrophasor Vector Processor Ruth Huang The need for distributed generation (DG) has become more and more popular because of the adverse effects of fossil fuels and the fear of running out of fossil fuels. By having DG, there are less transmission losses, voltage support, controllability of the system, decreased costs in transmission and distribution, power quality improvement, energy efficiency, and reduced reserve margin. The adverse effects of DG are voltage flicker, harmonics, and islanding. Islanding occurs when the DG continues to energize the power system when the main utility is disconnected. Detecting islanding is important for personnel safety, speedy restoration, and equipment protection. This paper describes the different islanding methods currently used and the benefits of combining two passive islanding detection methods, under/over voltage detection and voltage phase jump detection methods, using the synchrophasor vector processor (SVP).

Real-time monitoring of electromechanical oscillations is of great significance for power system operators; to this aim, software solutions (algorithms) that use synchrophasor measurements have been developed for this purpose. This thesis investigates different approaches for improving mode estimation process by offering new methods and deepening the understanding of different stages in the mode estimation process. One of the problems tackled in this thesis is the selection of synchrophasor signals used as the input for mode estimation. The proposed selection is performed using a quantitative criterion that is based on the variance of the critical mode estimate. The proposed criterion and associated selection method, offer a systematic and quantitative approach for PMU signal selection. The thesis also analyzes methods for model order selection used in mode estimation. Further, negative effects of forced oscillations and non-white noise load random changes on mode estimation results have been addressed by exploiting the intrinsic power system property that the characteristics of electromechanical modes are predominately determined by the power generation and transmission network. An improved accuracy of the mode estimation process can be obtained by intentionally injecting a probing disturbance. The thesis presents an optimization method that finds the optimal spectrum of the probing signals. In addition, the probing signal with the optimal spectrum is generated considering arbitrary time domain signal constraints that can be imposed by various probing signal generating devices. Finally, the thesis provides a comprehensive description of a practical implementation of a real-time mode estimation tool. This includes description of the hardware, software architecture, graphical user interface, as well as details of the most important components such as the Statnett’s SDK that allows easy access to synchrophasor data streams. / <p>The Doctoral Degrees issued upon completion of the programme are issued by Comillas Pontifical University, Delft University of Technology and KTH Royal Institute of Technology. The invested degrees are official in Spain, the Netherlands and Sweden, respectively.</p><p>QC 20160218</p> / FP7 iTesla

The research topics presented in this dissertation focus on validation of customer-level voltage synchrophasor data for transmission system analysis, detection and categorization of power system events as measured by phasor measurement units (PMUs), and identification of the influence of power system conditions (wind power, daily and seasonal load variation) on low-frequency oscillations. Synchrophasor data can provide information across entire power systems but obtaining the data, handling the large dataset and developing tools to extract useful information from it is a challenge. To overcome the challenge of obtaining data, an independent synchrophasor network was created by taking synchrophasor measurements at customer-level voltage. The first objective is to determine if synchrophasor data taken at customer-level voltage is an accurate representation of power system behavior. The validation process was started by installing a transmission level (69 kV) PMU. The customer-level voltage measurements were validated by comparison of long term trends and low-frequency oscillations estimates. The techniques best suited for synchrophasor data analysis were identified after a detailed study and comparison. The same techniques were also applied to detect power system events resulting in the creation of novel categories for numerous events based on shared characteristics. The numerical characteristics for each category and the ranges of each numerical characteristic for each event category are identified. The final objective is to identify trends in power system behavior related to wind power and daily and seasonal variations by utilizing signal processing and statistical techniques. / text