Dissertations / Theses on the topic 'PMU-Phasor Measurement System'

Phasor Measurement Units (PMUs) are widely acknowledged as one of the most significant developments in the field of real-time monitoring of power system. By aligning time stamps of voltage and current phasor measurements, which are consistent with Coordinated Universal Time (UTC), a coherent picture of the power system state can be achieved through either direct measurements or simple linear calculations. With the growing number of PMUs installed or planned to be installed in the near future, both utilities and research institutions are looking for novel applications of synchrophasor measurements from these widely installed PMUs. In this dissertation, the author proposes two new PMUs measurements applications: three-phase instrument transformer calibration, and three-phase line parameter calculation with instrument transformers. First application is to calibrate instrument transformers. Instrument transformers are the main sensors used in power systems. They provide isolation between high voltage level of primary side and metering level of the secondary side. All the monitoring and measuring systems obtain input signals from the secondary side of instrument transformers. That means when instrument transformers are not accurate, all the measurements used in power system are inaccurate. The most important job of this dissertation is to explore a method to automatically calibrate all the instrument transformers in the power system based on real-time synchrophasor measurements. The regular instrument transformer calibration method requires the instrument transformer to be out of service (offline) and calibrated by technicians manually. However, the error of instrument transformer changes when environment changes, and connected burden. Therefore, utilities are supposed to periodically calibrate instrument transformers at least once a year. The high labor and economic costs make traditional instrument transformer calibration method become one of the urgent problems in power industry. In this dissertation we introduce a novel, low cost and easy method to calibrate three-phase instrument transformers. This method only requires one three-phase voltage transformer at one bus calibrated in advance. All other instrument transformers can be calibrated by this method as often as twice a day, based on the synchrophasor measurements under different load scenarios. Second application is to calculate line parameters during calibrating instrument transformers. The line parameters, line impedance and line shunt admittance, as needed by utilities are generated by the computer method. The computer method is based on parameters, such as the diameter, length, material characteristics, the distance among transmission line, the distance to ground and so on. The formulas to calculate line parameters have been improved and re-modeled from time to time in order to increase the accuracy. However, in this case, the line parameters are still inaccurate due to various reasons. The line parameters errors do affect the instrument transformers calibration results (with 5% to 10% error). To solve this problem, we present a new method to calculate line parameters and instrument transformers in the same processing step. This method to calibrate line parameter and instrument transformers at the same time only needs one pre-calibrated voltage transformer and one pre-calibrated current transformer in power system. With the pre-calibrated instrument transformers, the line parameter as well as the ratio correction factors of all the other instrument transformers can be solved automatically. Simulation results showed the errors between calculated line parameters and the real line parameter, the errors between calibrated ratio correction factors and the real ratio correction factors are of the order of 10e-10 per unit. Therefore, high accuracy line parameters as well as perfectly calibrated instrument transformers can be obtained by this new method. This method can run automatically every day. High accuracy and dynamic line parameters will significantly improve power system models. It will also increase the reliability and speed of the relay system, enhance the accuracy of power system analysis, and benefit all other researches using line parameters. New methods of calculating line parameter and the instrument transformer calibrations will influence the whole power industry significantly.<br>Ph. D.

Recent large-scale blackouts revealed that power systems around the world are far from the stability and reliability requirement as they suppose to be. The post-event analysis clarifies that one major reason of the interconnection blackout is lack of wide area information. Frequency dynamics is one of the most important parameters of an electrical power system. In order to understand power system dynamics effectively, accurately measured wide-area frequency is needed. The idea of building an Internet based real-time GPS synchronized wide area Frequency Monitoring Network (FNET) was proposed to provide the imperative dynamic information for the large-scale power grids and the implementation of FNET has made the synchronized observations of the entire US power network possible for the first time. The FNET system consists of Frequency Disturbance Recorders (FDR), which work as the sensor devices to measure the real-time frequency at 110V single-phase power outlets, and an Information Management System (IMS) to work as a central server to process the frequency data. The device comparison between FDR and commercial PMU (Phasor Measurement Unit) demonstrate the advantage of FNET. The web visualization tools make the frequency data available for the authorized users to browse through Internet. The research work addresses some preliminary observations and analyses with the field-measured frequency information from FNET. The original algorithms based on the frequency response characteristic are designed to process event detection, localization and unbalanced power estimation during frequency disturbances. The analysis of historical cases illustrate that these algorithms can be employed in real-time level to provide early alarm of abnormal frequency change to the system operator. The further application is to develop an adaptive under frequency load shedding scheme with the processed information feed in to prevent further frequency decline in power systems after disturbances causing dangerous imbalance between the load and generation.<br>Ph. D.

This study takes advantage of wide area measurements to propose a centralized nonlinear controller that acts on power system stabilizers, to cooperatively increase the damping of problematic small signal oscillations all over the system. The structure based on decision trees results in a simple, efficient, and dependable methodology that imposes much less computational burden than other nonlinear design approaches, making it a promising candidate for actual implementation by utilities and system operators. Details are given to utilize existing stabilizers while causing minimum changes to the equipment, and warranting improvement or at least no detriment of current system behavior. This enables power system stabilizers to overcome their inherent limitation to act only on the basis of local measurements to damp a single target frequency. This study demonstrates the implications of this new input on mathematical models, and the control functionality that is made available by its incorporation to conventional stabilizers. In preparation of the case of study, a heuristic dynamic reduction methodology is introduced that preserves a physical equivalent model, and that can be interpreted by any commercial software package. The steps of this method are general, versatile, and of easy adaptation to any particular power system model, with the aggregated value of producing a physical model as final result, that makes the approach appealing for industry. The accuracy of the resulting reduced network has been demonstrated with the model of the Central American System.<br>Ph. D.

Phasor Measurement Units (PMUs) are widely acknowledged as one of the most promising developments in the field of real-time monitoring of power systems. By aligning the time stamps of voltage and current phasor measurements that are consistent with Coordinated Universal Time (UTC), a coherent picture of the power system state can be achieved through either direct measurements or simple linear calculations. With the growing number of PMUs planned for installation in the near future, both utilities and research institutions are looking for the best solutions to the placement of units as well as to the applications that make the most of phasor measurements. This dissertation explores a method for optimal PMU placement as well as two applications of synchronized phasor measurements in state estimation. The pre-processing PMU placement method prepares the system data for placement optimization and reduces the size of the optimization problem. It is adaptive to most of the optimal placement methods and can save a large amount of computational effort. Depth of un-observability is one of the criteria to allow the most benefit out of a staged placement of the units. PMUs installed in the system provide synchronized phasor measurements that are highly beneficial to power system state estimations. Two related applications are proposed in the dissertation. First, a post-processing inclusion of phasor measurements in state estimators is introduced. This method avoids the revision of the existing estimators and is able to realize similar results as mixing phasor data with traditional SCADA with a linear afterwards step. The second application is a method to calibrate instrument transformers remotely using phasor measurements. Several scans of phasor measurements are used to accomplish estimating system states in conjunction with complex instrument transformer correction factors. Numerical simulation results are provided for evaluation of the calibration performance with respect to the number of scans and load conditions. Conducting theoretical and numerical analysis, the methods and algorithms developed in this dissertation are aimed to strategically place PMUs and to incorporate phasor measurements into state estimators effectively and extensively for better system state monitoring. Simulation results show that the proposed placement method facilitates approaching the exact optimal placement while keep the computational effort low. Simulation also shows that the use of phasor measurement with the proposed instrument transformer correction factors and proposed state estimation enhancement largely improves the quality of state estimations.<br>Ph. D.

Master of Science<br>Department of Electrical and Computer Engineering<br>Noel N. Schulz<br>As the size of electric power systems are increasing, the techniques to protect, monitor and control them are becoming more sophisticated. Government, utilities and various organizations are striving to have a more reliable power grid. Various research projects are working to minimize risks on the grid. One of the goals of this research is to discuss a robust and accurate state estimation (SE) of the power grid. Utilities are encouraging teams to change the conventional way of state estimation to real time state estimation. Currently most of the utilities use traditional centralized SE algorithms for transmission systems. Although the traditional methods have been enhanced with advancement in technologies, including PMUs, most of these advances have remained localized with individual utility state estimation. There is an opportunity to establish a coordinated SE approach integration using PMU data across a system, including multiple utilities and this is using Distributed State Estimation (DSE). This coordination will minimize cascading effects on the power system. DSE could be one of the best options to minimize the required communication time and to provide accurate data to the operators. This project will introduce DSE techniques with the help of PMU data for a system snapshot. The proposed DSE algorithm will split the traditional central state estimation into multiple local state estimations and show how to reduce calculation time compared with centralized state estimation. Additionally these techniques can be implemented in micro-grid or islanded system.

The dissertation research investigates estimating of power system static and dynamic states (e.g. rotor angle, rotor speed, mechanical power, voltage magnitude, voltage phase angle, mechanical reference point) as well as identification of synchronous generator parameters. The research has two focuses: i. Synchronous generator dynamic model states and parameters estimation using real-time PMU data. ii.Integrate PMU data and conventional measurements to carry out static state estimation. The first part of the work focuses on Phasor Measurement Unit (PMU) data-based synchronous generator states and parameters estimation. In completed work, PMU data-based synchronous generator model identification is carried out using Unscented Kalman Filter (UKF). The identification not only gives the states and parameters related to a synchronous generator swing dynamics but also gives the states and parameters related to turbine-governor and primary and secondary frequency control. PMU measurements of active power and voltage magnitude, are treated as the inputs to the system while voltage phasor angle, reactive power, and frequency measurements are treated as the outputs. UKF-based estimation can be carried out at real-time. Validation is achieved through event play back to compare the outputs of the simplified simulation model and the PMU measurements, given the same input data. Case studies are conducted not only for measurements collected from a simulation model, but also for a set of real-world PMU data. The research results have been disseminated in one published article. In the second part of the research, new state estimation algorithm is designed for static state estimation. The algorithm contains a new solving strategy together with simultaneous bad data detection. The primary challenge in state estimation solvers relates to the inherent non-linearity and non-convexity of measurement functions which requires using of Interior Point algorithm with no guarantee for a global optimum solution and higher computational time. Such inherent non-linearity and non-convexity of measurement functions come from the nature of power flow equations in power systems. The second major challenge in static state estimation relates to the bad data detection algorithm. In traditional algorithms, Largest Normalized Residue Test (LNRT) has been used to identify bad data in static state estimation. Traditional bad data detection algorithm only can be applied to state estimation. Therefore, in a case of finding any bad datum, the SE algorithm have to rerun again with eliminating found bad data. Therefore, new simultaneous and robust algorithm is designed for static state estimation and bad data identification. In the second part of the research, Second Order Cone Programming (SOCP) is used to improve solving technique for power system state estimator. However, the non-convex feasible constraints in SOCP based estimator forces the use of local solver such as IPM (interior point method) with no guarantee for quality answers. Therefore, cycle based SOCP relaxation is applied to the state estimator and a least square estimation (LSE) based method is implemented to generate positive semi-definite programming (SDP) cuts. With this approach, we are able to strengthen the state estimator (SE) with SOCP relaxation. Since SDP relaxation leads the power flow problem to the solution of higher quality, adding SDP cuts to the SOCP relaxation makes Problem’s feasible region close to the SDP feasible region while saving us from computational difficulty associated with SDP solvers. The improved solver is effective to reduce the feasible region and get rid of unwanted solutions violate cycle constraints. Different Case studies are carried out to demonstrate the effectiveness and robustness of the method. After introducing the new solving technique, a novel co-optimization algorithm for simultaneous nonlinear state estimation and bad data detection is introduced in this dissertation. ${\ell}_1$-Norm optimization of the sparse residuals is used as a constraint for the state estimation problem to make the co-optimization algorithm possible. Numerical case studies demonstrate more accurate results in SOCP relaxed state estimation, successful implementation of the algorithm for the simultaneous state estimation and bad data detection, and better state estimation recovery against single and multiple Gaussian bad data compare to the traditional LNRT algorithm.

The future power grid will effectively utilize renewable energy resources and distributed generation to respond to energy demand while incorporating information technology and communication infrastructure for their optimum operation. This dissertation contributes to the development of real-time techniques, for wide-area monitoring and secure real-time control and operation of hybrid power systems. To handle the increased level of real-time data exchange, this dissertation develops a supervisory control and data acquisition (SCADA) system that is equipped with a state estimation scheme from the real-time data. This system is verified on a specially developed laboratory-based test bed facility, as a hardware and software platform, to emulate the actual scenarios of a real hybrid power system with the highest level of similarities and capabilities to practical utility systems. It includes phasor measurements at hundreds of measurement points on the system. These measurements were obtained from especially developed laboratory based Phasor Measurement Unit (PMU) that is utilized in addition to existing commercially based PMU’s. The developed PMU was used in conjunction with the interconnected system along with the commercial PMU’s. The tested studies included a new technique for detecting the partially islanded micro grids in addition to several real-time techniques for synchronization and parameter identifications of hybrid systems. Moreover, due to numerous integration of renewable energy resources through DC microgrids, this dissertation performs several practical cases for improvement of interoperability of such systems. Moreover, increased number of small and dispersed generating stations and their need to connect fast and properly into the AC grids, urged this work to explore the challenges that arise in synchronization of generators to the grid and through introduction of a Dynamic Brake system to improve the process of connecting distributed generators to the power grid. Real time operation and control requires data communication security. A research effort in this dissertation was developed based on Trusted Sensing Base (TSB) process for data communication security. The innovative TSB approach improves the security aspect of the power grid as a cyber-physical system. It is based on available GPS synchronization technology and provides protection against confidentiality attacks in critical power system infrastructures.

Given the ability of the Phasor Measurement Unit (PMU) to directly measure the system state and the increasing implementation of PMUs across the electric power industry, a natural expansion of state estimation techniques would be one that employed the exclusive use of PMU data. Dominion Virginia Power and the Department of Energy (DOE) are sponsoring a research project which aims to implement a three phase linear tracking state estimator on Dominionâ s 500kV network that would use only PMU measurements to compute the system state. This thesis represents a portion of the work completed during the initial phase of the research project. This includes the initial development and testing of two applications: the three phase linear state estimator and the topology processor. Also presented is a brief history of state estimation and PMUs, traditional state estimation techniques and techniques with mixed phasor data, a development of the linear state estimation algorithms and a discussion of the future work associate with this research project.<br>Master of Science

This thesis develops a robust methodology for on-line identification of power system dynamic signature based on incoming system responses from Phasor Measurement Units (PMUs) in Wide Area Measurement Systems (WAMS). Data mining techniques are used in the methodology to convert real-time monitoring data into transient stability information and the pattern of system dynamic behaviour in the event of instability. The future power system may operate closer to its stability limit in order to improve its efficiency and economic value. The changing types and patterns of load and generation are resulting in highly variable operating conditions. Corrective control and stabilisation is becoming a potentially viable option to enable safer system operation. In the meantime, the number of WAMS projects and PMUs is rising, which will significantly improve the system situational awareness. The combination of all these factors means that it is of vital importance to exploit a new and efficient Transient Stability Assessment (TSA) tool in order to use real-time PMU data to support decisions for corrective control actions. Data mining has been studied as the innovative solution and considered as promising. This work contributes to a number of areas of power systems stability research, specifically around the data driven approach for real-time emergency mode TSA. A review of past research on on-line TSA using PMU measurements and data mining is completed, from which the Decision Tree (DT) method is found to be the most suitable. This method is implemented on the test network. A DT model is trained and the sensitivity of its prediction accuracy is assessed according to a list of network uncertainties. Results showed that DT is a useful tool for on-line TSA for corrective control approach. Following the implementation, a generic probabilistic framework for the assessment of the prediction accuracy of data mining models is developed. This framework is independent of the data mining technique. It performs an exhaustive search of possible contingencies in the testing process and weighs the accuracies according to the realistic probability distribution of uncertain system factors, and provides the system operators with the confidence level of the decisions made under emergency conditions. After that, since the TSA for corrective control usually focuses on transient stability status without dealing with the generator grouping in the event of instability, a two-stage methodology is proposed to address this gap and to identify power system dynamic signature. In this methodology, traditional binary classification is used to identify transient stability in the first stage; Hierarchical Clustering is used to pre-define patterns of unstable dynamic behaviour; and different multiclass classification techniques are investigated to identify the patterns in the second stage. Finally, the effects of practical issues related to WAMS on the data mining methodologies are investigated. Five categories of issues are discussed, including measurement error, communication noise, wide area signal delays, missing measurements, and a limited number of PMUs.

For decades, researchers have sought to make the North American power system as reliable as possible with many security measures in place to include redundancy. Yet the increasing number of blackouts and failures have highlighted the areas that require improvement. Meeting the increasing demand for energy and the growing complexity of the loads are two of the main challenges faced by the power grid. In order to prepare for contingencies and maintain a secure state, power engineers must perform simulations using steady state and dynamic models of the system. The results from the contingency studies are only as accurate as the models of the grid components. The load components are generally the most difficult to model since they are controlled by the consumer. This study focuses on developing static and dynamic load models using advanced mathematical approximation algorithms and wide area measurement devices, which will improve the accuracy of the system analysis and hopefully decrease the frequency of blackouts. The increasing integration of phasor measurement units (PMUs) into the power system allows us to take advantage of synchronized measurements at a high data rate. These devices are capable of changing the way we manage online security within the Energy Management System (EMS) and can enhance our offline tools. This type of data helps us redevelop the measurement-based approach to load modeling. The static ZIP load model composition is estimated using a variation of the method of least squares, called bounded-variable least squares. The bound on the ZIP load parameters allows the measurement matrix to be slightly correlated. The ZIP model can be determined within a small range of error that won't affect the contingency studies. Machine learning is used to design the dynamic load model. Neural network training is applied to fault data obtained near the load bus and the derived network model can estimate the load parameters. The neural network is trained using simulated data and then applied to real PMU measurements. A PMU algorithm was developed to transform the simulated measurements into a realistic representation of phasor data. These new algorithms will allow us to estimate the load models that are used in contingency studies.<br>Ph. D.

Master of Science<br>Department of Electrical and Computer Engineering<br>Shelli Starrett<br>Variability in power systems is increasing due to pushing the system to limits for economic purposes, the inclusion of new energy sources like wind turbines and photovoltaic, and the introduction of new types of loads such as electric vehicle chargers. In this new environment, system monitoring and control must keep pace to insure system stability and reliability on a wide area scale. Phasor measurement unit technology implementation is growing and can be used to provide input signals to new types of control. Fuzzy logic based power system stabilizer (PSS) controllers have also been shown effective in various studies. This thesis considers several choices of input signals, composed assuming phasor measurement availability, for fuzzy logic-based controllers. The purpose of the controller is to damp power systems’ low frequency oscillations. Nonlinear transient simulation results for a 4-machine two-area system and 50 machine system are used to compare the effects of input choice and controller type on damping of system oscillations. Reactive power in the system affects voltage, which in turn affects system damping and dynamic stability. System stability and damping can be enhanced by deploying SVC controllers properly. Different types of power system variables play critical role to damp power swings using SVC controller. A fuzzy logic based static var compensator (SVC) was used near a generator to damp these electromechanical oscillations using different PMU-acquired inputs. The goal was again improve dynamic stability and damping performance of the system at local and global level. Nonlinear simulations were run to compare the damping performance of different inputs on the 50 machine system.

The strain on modern electrical power system operation has led to an ever increasing utilization of new Information Communication Technology (ICT) systems to enhance the reliability and efficiency of grid operation. Among these proposals, Phasor Measurement Unit (PMU)-based Wide-Area Monitoring and Control (WAMC) systems have been recognized as one of the enablers of “Smart Grid”, particularly at the transmission level, due to their capability to improve the real-time situational awareness of the grid. These systems differ from the conventional Supervisory Control And Data Acquisition (SCADA) systems in that they provide globally synchronized measurements at high resolutions. On the other hand, the WAMC systems also impose several stringent requirements on the underlying ICT systems, including performance, security, and availability, etc. As a result, the functionality of the WAMC applications is heavily, but not exclusively, dependent on the capabilities of the underlying ICT systems. This tight coupling makes it difficult to fully exploit the benefits of the synchrophasor technology without the proper design and configuration of ICT systems to support the WAMC applications. The strain on modern electrical power system operation has led to an ever increasing utilization of new Information Communication Technology (ICT) systems to enhance the reliability and efficiency of grid operation. Among these proposals, Phasor Measurement Unit (PMU)-based Wide-Area Monitoring and Control (WAMC) systems have been recognized as one of the enablers of “Smart Grid”, particularly at the transmission level, due to their capability to improve the real-time situational awareness of the grid. These systems differ from the conventional Supervisory Control And Data Acquisition (SCADA) systems in that they provide globally synchronized measurements at high resolutions. On the other hand, the WAMC systems also impose several stringent requirements on the underlying ICT systems, including performance, security, and availability, etc. As a result, the functionality of the WAMC applications is heavily, but not exclusively, dependent on the capabilities of the underlying ICT systems. This tight coupling makes it difficult to fully exploit the benefits of the synchrophasor technology without the proper design and configuration of ICT systems to support the WAMC applications. In response to the above challenges, this thesis addresses the dependence of WAMC applications on the underlying ICT systems. Specifically, two of the WAMC system data quality attributes, latency and completeness, are examined together with their effects on a typical WAMC application, PMU-based wide-area damping systems. The outcomes of this research include quantified results in the form of PMU communication delays and data frame losses, and probability distributions that can model the PMU communication delays. Moreover, design requirements are determined for the wide-area damping systems, and three different delay-robust designs for this WAMC application are validated based on the above results. Finally, a virtual PMU is developed to perform power system and communication network co-simulations. The results reported by this thesis offer a prospect for better predictions of the performance of the supporting ICT systems in terms of PMU data latency and completeness. These results can be further used to design and optimize the WAMC applications and their underlying ICT systems in an integrated manner. This thesis also contributes a systematic approach to design the wide-area damping system considering the PMU data latency and completeness. Finally, the developed virtual PMU, as part of a co-simulation platform, provides a means to investigate the dependence of WAMC applications on the capabilities of the underlying ICT systems in a cost-efficient manner.<br><p>QC 20131015</p>

Enabling islanded operation of power distribution networks will greatly improve the reliability of supply for customers. Measurement devices such as Phasor Measurement Units (PMUs) are required to protect and control the islanded network. PMUs are widely used in transmission network. This thesis examines whether existing PMUs meet the performance requirements to enable islanded distribution network operation.

The role played by phasor measurement units (PMU) in power grid monitoring systems today showcases the importance and usefulness of this device. There is a significant challenge regarding the design and implementation of PMUs today. This challenge stems from the closed source philosophy employed by commercial PMU vendors who strongly protect their hardware and software designs keeping it away from researchers. This philosophy has motivated a number of researchers to develop their own PMU devices. This thesis presents the design and implementation of a PMU device utilizing off-the- shelf components to estimate power system parameters such as voltage magnitude, phase angle and frequency with key design information extracted from the OpenPMU group and the IEEE C37.118-2011 standard. The functionality of the PMU was tested by performing important power system experiments which compared measured result of voltage magnitude, phase angle and frequency of a balanced three phase signal from a rapid prototyping system with estimated results from PMU. The conducted experiments confirmed that the PMU could estimate voltage magnitude, phase angle and frequency approximately equivalent to the measured quantities of the input signal.<br>February 2016

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.<br>text

The modern day power system is witnessing a tremendous change. There has been a rapid rise in the distributed generation, along with this the deregulation has resulted in a more complex system. The power demand is on a rise, the generation and trans-mission infrastructure hasn't yet adapted to this growing demand. The economic and operational constraints have forced the system to be operated close to its design limits, making the system vulnerable to disturbances and possible grid failure. This makes the study of voltage stability of the system important more than ever. Generally, voltage stability studies are carried on a single phase equivalent system assuming that the system is perfectly balanced. However, the three phase power system is not always in balanced state. There are a number of untransposed lines, single phase and double phase lines. This thesis deals with three phase voltage stability analysis, in particular the voltage stability index known as L-Index. The equivalent single phase analysis for voltage stability fails to work in case of any unbalance in the system or in presence of asymmetrical contingency. Moreover, as the system operators are giving importance to synchrophasor measurements, PMUs are being installed throughout the system. Hence, the three phase voltages can be obtained, making three phase analysis easier. To study the effect of unbalanced system on voltage stability a three phase L-Index based on traditional L-Index has been proposed. The proposed index takes into consideration the unbalance resulting due to untransposed transmission lines and unbalanced loads in the system. This index can handle any unbalance in the system and is much more realistic. To obtain bus voltages during unbalanced operation of the system a three phase decoupled Newton Raphson load ow was used. Reactive power distribution in a system can be altered using generators voltage set-ting, transformers OLTC settings and SVC settings. All these settings are usually in balanced mode i.e. all the phases have the same setting. Based on this reactive power optimization using LP technique on an equivalent single phase system is proposed. This method takes into account generator voltage settings, OLTC settings of transformers and SVC settings. The optimal settings so obtained are applied to corresponding three phase system. The effectiveness of the optimal settings during unbalanced scenario is studied. This method ensures better voltage pro les and decrease in power loss. Case studies of the proposed methods are carried on 12 bus and 24 bus EHV systems of southern Indian grid and a modified IEEE 30 bus system. Both balanced and unbalanced systems are studied and the results are compared.

The modern day power system is witnessing a tremendous change. There has been a rapid rise in the distributed generation, along with this the deregulation has resulted in a more complex system. The power demand is on a rise, the generation and trans-mission infrastructure hasn't yet adapted to this growing demand. The economic and operational constraints have forced the system to be operated close to its design limits, making the system vulnerable to disturbances and possible grid failure. This makes the study of voltage stability of the system important more than ever. Generally, voltage stability studies are carried on a single phase equivalent system assuming that the system is perfectly balanced. However, the three phase power system is not always in balanced state. There are a number of untransposed lines, single phase and double phase lines. This thesis deals with three phase voltage stability analysis, in particular the voltage stability index known as L-Index. The equivalent single phase analysis for voltage stability fails to work in case of any unbalance in the system or in presence of asymmetrical contingency. Moreover, as the system operators are giving importance to synchrophasor measurements, PMUs are being installed throughout the system. Hence, the three phase voltages can be obtained, making three phase analysis easier. To study the effect of unbalanced system on voltage stability a three phase L-Index based on traditional L-Index has been proposed. The proposed index takes into consideration the unbalance resulting due to untransposed transmission lines and unbalanced loads in the system. This index can handle any unbalance in the system and is much more realistic. To obtain bus voltages during unbalanced operation of the system a three phase decoupled Newton Raphson load ow was used. Reactive power distribution in a system can be altered using generators voltage set-ting, transformers OLTC settings and SVC settings. All these settings are usually in balanced mode i.e. all the phases have the same setting. Based on this reactive power optimization using LP technique on an equivalent single phase system is proposed. This method takes into account generator voltage settings, OLTC settings of transformers and SVC settings. The optimal settings so obtained are applied to corresponding three phase system. The effectiveness of the optimal settings during unbalanced scenario is studied. This method ensures better voltage pro les and decrease in power loss. Case studies of the proposed methods are carried on 12 bus and 24 bus EHV systems of southern Indian grid and a modified IEEE 30 bus system. Both balanced and unbalanced systems are studied and the results are compared.

abstract: In modern electric power systems, energy management systems (EMSs) are responsi-ble for monitoring and controlling the generation system and transmission networks. State estimation (SE) is a critical `must run successful' component within the EMS software. This is dictated by the high reliability requirements and need to represent the closest real time model for market operations and other critical analysis functions in the EMS. Tradi-tionally, SE is run with data obtained only from supervisory control and data acquisition (SCADA) devices and systems. However, more emphasis on improving the performance of SE drives the inclusion of phasor measurement units (PMUs) into SE input data. PMU measurements are claimed to be more accurate than conventional measurements and PMUs `time stamp' measurements accurately. These widely distributed devices meas-ure the voltage phasors directly. That is, phase information for measured voltages and currents are available. PMUs provide data time stamps to synchronize measurements. Con-sidering the relatively small number of PMUs installed in contemporary power systems in North America, performing SE with only phasor measurements is not feasible. Thus a hy-brid SE, including both SCADA and PMU measurements, is the reality for contemporary power system SE. The hybrid approach is the focus of a number of research papers. There are many practical challenges in incorporating PMUs into SE input data. The higher reporting rates of PMUs as compared with SCADA measurements is one of the salient problems. The disparity of reporting rates raises a question whether buffering the phasor measurements helps to give better estimates of the states. The research presented in this thesis addresses the design of data buffers for PMU data as used in SE applications in electric power systems. The system theoretic analysis is illustrated using an operating electric power system in the southwest part of the USA. Var-ious instances of state estimation data have been used for analysis purposes. The details of the research, results obtained and conclusions drawn are presented in this document.<br>Dissertation/Thesis<br>M.S. Electrical Engineering 2013