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1
Retty, Hema A. "Evaluation and Standardizing of Phasor Data Concentrators." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/32064.
Full textAbstract:
The power grid is interconnected in many ways; so that when disturbances occur in a small region, their effects can be seen across large areas causing major blackouts. In order to isolate the fault, measurements taken at different times throughout the blackout need to be collected and analyzed. With each measurement device having its own time source, time alignment can be a quite tedious and lengthy process. The need for a new time synchronized measurement device has arrived. The Phasor Measurement Units (PMU) is not only GPS time synchronized, but it also takes measurements as voltage and current phasors.
PMUs are becoming an integral part in many power system applications from load flow analysis and state estimation to analyzing blackout causes. Phasor Data Concentrators (PDC) collect and process PMU data. As such, it is important that PMU and PDC communication is seamless. PDCs are set up at multiple utilities and power authorities and also need to be able to communicate and send data to one another seamlessly to encompass analysis of large measurement systems. If these devices are not working similarly when processing and sending/receiving data, unnecessary problems may arise. Therefore it is important that there is an expectation as to how they should work. However, what is expected from these devices is not entirely clear. For this reason, standards such as IEEE C37.118.2-2011 [5] have been proposed to help make operation as uniform as possible. Unfortunately, the standards for PDCs are lacking and tend to only set up communication protocols. To help normalize PDCs, these standards need to be expanded to include all PDC operations and give little room for discrepancy as to what a PDC should do in any given situation. Tests have been performed on PDCs not only to see how they match up to current standards but on how they act outside of the standards.<br>Master of Science
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Kersey, Philip Michael. "Applications of PMUSimulator in PDC Testing." Thesis, Virginia Tech, 2012. http://hdl.handle.net/10919/32090.
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With the development of the power grid into an automated system, phasor measurement units and phasor data concentrators are essential for real time control of the system. PMUs are time synchronized throughout the power system and take sample measurements in very small windows of time. Phasor Data Concentrators accept PMU data and time align the data so that a snapshot of the power system can be viewed in real time. It is unfeasible to possess enough real PMUs to thoroughly test PDCs, thus a Real Time PMU Simulator is desired.
It is possible to implement a UNIX based PMU simulator that can emulate the behavior of real PMUs, while also allowing the user to alter the Synchrophasor data to test the response of a PDC. GPS is used to synchronize a UNIX machine to UTC time to match that of a real PMU. In this way, the PMU simulator will accurately behave as a PMU. This PMU data can be sent to PDCs to test the response of the device. To test extremes of the PDC, alterations were made to the PMU software to send irregular data to a PDC. The results conclude that the open source iPDC software is capable of being used for latency testing, sending late data frames, as well as sending corrupted data. The PMU simulator proved to be successful in the area of PDC testing. The purpose of this thesis is to demonstrate how the iPDC software can be implemented to test PDCâ s.<br>Master of Science
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Dekhane, Kunal Shashikant. "The Virginia Tech Phasor Data Concentrator Analysis & Testing System." Thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/46332.
Full textAbstract:
The development of Smart Grid and an increased emphasis on Wide Area Measurement,
Automation, Protection and Control (WAMPAC) has lead to the substantial increase in the
development and use of Synchrophasor Systems. The Department of Energy having realized its
importance in the Power System has encouraged its deployment through the Smart Grid
Investment Grant. With many utilities beginning to implement a large number of PMUs over
their respective power systems, Phasor Data Concentrators (PDCs) play a crucial part in
accurately relaying data from the point of measurement to the operators at the control center. The
current Synchrophasor standard, IEEE C37.118-2005 covers adequately the steady state
characterization of PMUs but does not specify requirements for PDCs. Having recognized the
need for such a standard for PDCs, the North American Synchrophasor Initiative (NASPI) has
developed a guide outlining some of its objectives, functions and tests requirements. Virginia
Tech has developed a PDC Test System under these guidelines and as per the requirements of the
PJM Synchrophasor Systems Deployment Project. This thesis focuses on the testing tools
developed and the procedures implemented in the Virginia Tech PDC Test System.<br>Master of Science
4
Wehbe, Yasser. "Model Estimation of Electric Power Systems by Phasor Measurement Units Data." Scholar Commons, 2012. http://scholarcommons.usf.edu/etd/4419.
Full textAbstract:
This dissertation tackles the online estimation of synchronous machines' power subsystems electromechanical models using the output based Phasor Measurements Units (PMUs) data while disregarding any inside data. The research develops state space models
and estimates their parameters and states. The research tests the developed algorithms against models of a higher and of the same complexity as the estimated models.
The dissertation explores two estimations approaches using the PMUs data: i)non-linear Kalman filters namely the Extended Kalman Filter (EKF) and then the Unscented
Kalman Filter (UKF) and ii) Least Squares Estimation (LSE) with Finite Differences (FN) and then with System Identification. The EKF based research i) establishes a decoupling
technique for the subsystem the rest of the power system ii) finds the maximum number of parameters to estimate for classical machine model and iii) estimates such parameters
. The UKF based research i) estimates a set of electromechanical parameters and states for the flux decay model and ii) shows the advantage of using a dual estimation filter with
colored noise to solve the difficulty of some simultaneous state and parameter estimation.
The LSE with FN estimation i) evaluates numerically the state space differential equations and transform the problem to an overestimated linear system whose parameters
can be estimated, ii) carries out sensitivity studies evaluating the impact of operating conditions and iii) addresses the requirements for implementation on real data taken from
the electric grid of the United States. The System Identification method i) develops a linearized electromechanical model, ii) completes a parameters sub-set selection study using
si8ngular values decomposition, iii) estimates the parameters of the proposed model and iv) validates its output versus the measured output.
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Ghassempour, Aghamolki Hossein. "Phasor Measurement Unit Data-based States and Parameters Estimation in Power System." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6505.
Full textAbstract:
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.
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Li, Meiyan. "Transient Stability Prediction based on Synchronized Phasor Measurements and Controlled Islanding." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/52623.
Full textAbstract:
Traditional methods for predicting transient stability of power systems such as the direct method, the time domain approach, and the energy function methods do not work well for online transient stability predictions problems. With the advent of Phasor Measurement Units (PMUs) in power systems, it is now possible to monitor the behavior of the system in real time and provide important information for transient stability assessment and enhancement. Techniques such as the rotor oscillation prediction method based on time series have made the prediction of system stability possible for real-time applications. However, methods of this type require more than 300 milliseconds after the start of a transient event to make reliable predictions. The dissertation provides an alternate prediction method for transient stability by taking advantage of the available PMUs data. It predicts transient stability using apparent impedance trajectories obtained from PMUs, decision trees, and FLDSD method. This method enables to find out the strategic locations for PMUs installation in the power system to rapidly predict transient stability. From the simulations performed, it is realized that system stability can be predicted in approximately 200 milliseconds (12 cycles). The main advantage of this method is its simplicity as the PMUs can record the apparent impedance trajectories in real-time without any previous calculations. Moreover, using decision trees built in CART, transient stability prediction becomes straightforward and computationally very fast. The optimum locations for PMUs placement can also be determined using this technique.
After the transient instability prediction by the apparent impedance trajectories, a slow- coherency based intelligent controlled islanding scheme is also developed to restore the stability of system. It enables the generators in the same island to stay in synchronism and the imbalance between the generators and load demand is minimized.<br>Ph. D.
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Quint, Ryan David. "Practical Implementation of a Security-Dependability Adaptive Voting Scheme Using Decision Trees." Thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/35667.
Full textAbstract:
Todayâ s electric power system is operated under increasingly stressed conditions. As electrical demand increases, the existing grid is operated closer to its stable operating limits while maintaining high reliability of electric power delivery to its customers. Protective schemes are designed to account for pressures towards unstable operation, but there is always a tradeoff between security and dependability of this protection.
Adaptive relaying schemes that can change or modify their operation based on prevailing system conditions are an example of a protective scheme increasing reliability of the power system. The purpose of this thesis is to validate and analyze implementation of the Security-Dependability Adaptive Voting Scheme. It is demonstrated that this scheme can be implemented with a select few Phasor Measurement Units (PMUs) reporting positive sequence currents to a Phasor Data Concentrator (PDC). At the PDC, the state of the power system is defined as Stressed or Safe and a set of relays either vote or perform normal operation, respectively.
The Adaptive Voting Scheme was implemented using two configurations: hardware- and software-based PDC solutions. Each was shown to be functional, effective, and practical for implementation. Practicality was based on the latency of Wide Area Measurement (WAM) devices and the added latency of relay voting operation during Stressed conditions. Phasor Measurement Units (PMUs), Phasor Data Concentrators (PDCs), and relay operation delays were quantified to determine the benefits and limitations of WAMS protection and implementation of the voting scheme. It is proposed that the delays injected into the existing protection schemes would have minimal effect on the voting scheme but must be accounted for when implementing power system controls due to the real-time requirements of the data.<br>Master of Science
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Barik, Tapas Kumar. "Synchrophasor Based Centralized Remote Synchroscope for Power System Restoration." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/82849.
Full textAbstract:
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.<br>Master of Science<br>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.
9
Kamireddy, Srinath. "Comparison of state estimation algorithms considering phasor measurement units and major and minor data loss." Master's thesis, Mississippi State : Mississippi State University, 2008. http://library.msstate.edu/etd/show.asp?etd=etd-11072008-121521.
Full text
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Retty, Hema. "Load Modeling using Synchrophasor Data for Improved Contingency Analysis." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/78328.
Full textAbstract:
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.
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Zhu, Kun. "Data Quality in Wide-Area Monitoring and Control Systems : PMU Data Latency, Completness, and Design of Wide-Area Damping Systems." Doctoral thesis, KTH, Industriella informations- och styrsystem, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-129078.
Full textAbstract:
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>
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Khan, Mukhtaj. "Hadoop performance modeling and job optimization for big data analytics." Thesis, Brunel University, 2015. http://bura.brunel.ac.uk/handle/2438/11078.
Full textAbstract:
Big data has received a momentum from both academia and industry. The MapReduce model has emerged into a major computing model in support of big data analytics. Hadoop, which is an open source implementation of the MapReduce model, has been widely taken up by the community. Cloud service providers such as Amazon EC2 cloud have now supported Hadoop user applications. However, a key challenge is that the cloud service providers do not a have resource provisioning mechanism to satisfy user jobs with deadline requirements. Currently, it is solely the user responsibility to estimate the require amount of resources for their job running in a public cloud. This thesis presents a Hadoop performance model that accurately estimates the execution duration of a job and further provisions the required amount of resources for a job to be completed within a deadline. The proposed model employs Locally Weighted Linear Regression (LWLR) model to estimate execution time of a job and Lagrange Multiplier technique for resource provisioning to satisfy user job with a given deadline. The performance of the propose model is extensively evaluated in both in-house Hadoop cluster and Amazon EC2 Cloud. Experimental results show that the proposed model is highly accurate in job execution estimation and jobs are completed within the required deadlines following on the resource provisioning scheme of the proposed model. In addition, the Hadoop framework has over 190 configuration parameters and some of them have significant effects on the performance of a Hadoop job. Manually setting the optimum values for these parameters is a challenging task and also a time consuming process. This thesis presents optimization works that enhances the performance of Hadoop by automatically tuning its parameter values. It employs Gene Expression Programming (GEP) technique to build an objective function that represents the performance of a job and the correlation among the configuration parameters. For the purpose of optimization, Particle Swarm Optimization (PSO) is employed to find automatically an optimal or a near optimal configuration settings. The performance of the proposed work is intensively evaluated on a Hadoop cluster and the experimental results show that the proposed work enhances the performance of Hadoop significantly compared with the default settings.
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Gyawali, Sanij. "Dynamic Load Modeling from PSSE-Simulated Disturbance Data using Machine Learning." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/100591.
Full textAbstract:
Load models have evolved from simple ZIP model to composite model that incorporates
the transient dynamics of motor loads. This research utilizes the latest trend on Machine
Learning and builds reliable and accurate composite load model. A composite load model
is a combination of static (ZIP) model paralleled with a dynamic model. The dynamic
model, recommended by Western Electricity Coordinating Council (WECC), is an induction
motor representation. In this research, a dual cage induction motor with 20 parameters
pertaining to its dynamic behavior, starting behavior, and per unit calculations is used as
a dynamic model. For machine learning algorithms, a large amount of data is required.
The required PMU field data and the corresponding system models are considered Critical
Energy Infrastructure Information (CEII) and its access is limited. The next best option for
the required amount of data is from a simulating environment like PSSE. The IEEE 118 bus
system is used as a test setup in PSSE and dynamic simulations generate the required data
samples. Each of the samples contains data on Bus Voltage, Bus Current, and Bus Frequency
with corresponding induction motor parameters as target variables. It was determined that
the Artificial Neural Network (ANN) with multivariate input to single parameter output
approach worked best. Recurrent Neural Network (RNN) is also experimented side by side
to see if an additional set of information of timestamps would help the model prediction.
Moreover, a different definition of a dynamic model with a transfer function-based load
is also studied. Here, the dynamic model is defined as a mathematical representation of
the relation between bus voltage, bus frequency, and active/reactive power flowing in the
bus. With this form of load representation, Long-Short Term Memory (LSTM), a variation
of RNN, performed better than the concurrent algorithms like Support Vector Regression
(SVR). The result of this study is a load model consisting of parameters defining the load
at load bus whose predictions are compared against simulated parameters to examine their
validity for use in contingency analysis.<br>Master of Science<br>Independent system Operators (ISO) and Distribution system operators (DSO) have a responsibility to provide uninterrupted power supply to consumers. That along with the
longing to keep operating cost minimum, engineers and planners study the system beforehand and seek to find the optimum capacity for each of the power system elements like
generators, transformers, transmission lines, etc. Then they test the overall system using
power system models, which are mathematical representation of the real components, to
verify the stability and strength of the system. However, the verification is only as good as
the system models that are used. As most of the power systems components are controlled
by the operators themselves, it is easy to develop a model from their perspective. The load
is the only component controlled by consumers. Hence, the necessity of better load models.
Several studies have been made on static load modeling and the performance is on par with
real behavior. But dynamic loading, which is a load behavior dependent on time, is rather
difficult to model. Some attempts on dynamic load modeling can be found already. Physical
component-based and mathematical transfer function based dynamic models are quite widely
used for the study. These load structures are largely accepted as a good representation of
the systems dynamic behavior. With a load structure in hand, the next task is estimating
their parameters. In this research, we tested out some new machine learning methods to
accurately estimate the parameters. Thousands of simulated data are used to train machine
learning models. After training, we validated the models on some other unseen data. This
study finally goes on to recommend better methods to load modeling.
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Guo, Tingyan. "On-line identification of power system dynamic signature using PMU measurements and data mining." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/online-identification-of-power-system-dynamic-signature-using-pmu-measurements-and-data-mining(989938d4-c236-48a7-a653-17326937f5b4).html.
Full textAbstract:
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.
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Thomas, Michael Kyle. "Implementation of the Security-Dependability Adaptive Voting Scheme." Thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/32542.
Full textAbstract:
As the world moves further into the 21st century, the electricity demand worldwide continues to rapidly grow. The power systems that supply this growing demand continue to be pushed closer to their limits. When those limits are exceeded, system blackouts occur that have massive societal and economical impact. Power system protection relays make up a piece of these limits and can be important factors in preventing or causing a system blackout. The purpose of this thesis is to present a working implementation of an adaptive protection scheme known as the adaptive voting scheme, used to alter the security/dependability balance of protection schemes. It is argued that as power system conditions change, the ability of protection relays to adjust the security/dependability balance based on those conditions can allow relays to play a part in preventing power system catastrophes.
It is shown that the adaptive voting scheme can be implemented on existing protection technology given Wide Area Measurements (WAMs) provided by Phasor Measurement Units (PMUs). The proposed implementation characteristics allow numerous existing protection practices to be used without changing the basic operation of the practices.<br>Master of Science
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Ghanavati, Goodarz. "Statistical Analysis of High Sample Rate Time-series Data for Power System Stability Assessment." ScholarWorks @ UVM, 2015. http://scholarworks.uvm.edu/graddis/333.
Full textAbstract:
The motivation for this research is to leverage the increasing deployment of the phasor measurement unit (PMU) technology by electric utilities in order to improve situational awareness in power systems. PMUs provide unprecedentedly fast and synchronized voltage and current measurements across the system. Analyzing the big data provided by PMUs may prove helpful in reducing the risk of blackouts, such as the Northeast blackout in August 2003, which have resulted in huge costs in past decades.
In order to provide deeper insight into early warning signs (EWS) of catastrophic events in power systems, this dissertation studies changes in statistical properties of high-resolution measurements as a power system approaches a critical transition. The EWS under study are increases in variance and autocorrelation of state variables, which are generic signs of a phenomenon known as critical slowing down (CSD).
Critical slowing down is the result of slower recovery of a dynamical system from perturbations when the system approaches a critical transition. CSD has been observed in many stochastic nonlinear dynamical systems such as ecosystem, human body and power system. Although CSD signs can be useful as indicators of proximity to critical transitions, their characteristics vary for different systems and different variables within a system.
The dissertation provides evidence for the occurrence of CSD in power systems using a comprehensive analytical and numerical study of this phenomenon in several power system test cases. Together, the results show that it is possible extract information regarding not only the proximity of a power system to critical transitions but also the location of the stress in the system from autocorrelation and variance of measurements. Also, a semi-analytical method for fast computation of expected variance and autocorrelation of state variables in large power systems is presented, which allows one to quickly identify locations and variables that are reliable indicators of proximity to instability.
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Badayos, Noah Garcia. "Machine Learning-Based Parameter Validation." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/47675.
Full textAbstract:
As power system grids continue to grow in order to support an increasing energy demand, the system's behavior accordingly evolves, continuing to challenge designs for maintaining security. It has become apparent in the past few years that, as much as discovering vulnerabilities in the power network, accurate simulations are very critical. This study explores a classification method for validating simulation models, using disturbance measurements from phasor measurement units (PMU). The technique used employs the Random Forest learning algorithm to find a correlation between specific model parameter changes, and the variations in the dynamic response. Also, the measurements used for building and evaluating the classifiers were characterized using Prony decomposition. The generator model, consisting of an exciter, governor, and its standard parameters have been validated using short circuit faults. Single-error classifiers were first tested, where the accuracies of the classifiers built using positive, negative, and zero sequence measurements were compared. The negative sequence measurements have consistently produced the best classifiers, with majority of the parameter classes attaining F-measure accuracies greater than 90%. A multiple-parameter error technique for validation has also been developed and tested on standard generator parameters. Only a few target parameter classes had good accuracies in the presence of multiple parameter errors, but the results were enough to permit a sequential process of validation, where elimination of a highly detectable error can improve the accuracy of suspect errors dependent on the former's removal, and continuing the procedure until all corrections are covered.<br>Ph. D.
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Pal, Anamitra. "PMU-Based Applications for Improved Monitoring and Protection of Power Systems." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/51093.
Full textAbstract:
Monitoring and protection of power systems is a task that has manifold objectives. Amongst others, it involves performing data mining, optimizing available resources, assessing system stresses, and doing data conditioning. The role of PMUs in fulfilling these four objectives forms the basis of this dissertation. Classification and regression tree (CART) built using phasor data has been extensively used in power systems. The splits in CART are based on a single attribute or a combination of variables chosen by CART itself rather than the user. But as PMU data consists of complex numbers, both the attributes, should be considered simultaneously for making critical decisions. An algorithm is proposed here that expresses high dimensional, multivariate data as a single attribute in order to successfully perform splits in CART.
In order to reap maximum benefits from placement of PMUs in the power grid, their locations must be selected judiciously. A gradual PMU placement scheme is developed here that ensures observability as well as protects critical parts of the system. In order to circumvent the computational burden of the optimization, this scheme is combined with a topology-based system partitioning technique to make it applicable to virtually any sized system.
A power system is a dynamic being, and its health needs to be monitored at all times. Two metrics are proposed here to monitor stress of a power system in real-time. Angle difference between buses located across the network and voltage sensitivity of buses lying in the middle are found to accurately reflect the static and dynamic stress of the system. The results indicate that by setting appropriate alerts/alarm limits based on these two metrics, a more secure power system operation can be realized.
A PMU-only linear state estimator is intrinsically superior to its predecessors with respect to performance and reliability. However, ensuring quality of the data stream that leaves this estimator is crucial. A methodology for performing synchrophasor data conditioning and validation that fits neatly into the existing linear state estimation formulation is developed here. The results indicate that the proposed methodology provides a computationally simple, elegant solution to the synchrophasor data quality problem.<br>Ph. D.
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Brown, K. D., and Chris Allen. "DYNAMIC TRACKING PHASED ARRAY DATA LINKS." International Foundation for Telemetering, 2004. http://hdl.handle.net/10150/605303.
Full textAbstract:
International Telemetering Conference Proceedings / October 18-21, 2004 / Town & Country Resort, San Diego, California<br>This paper describes a flexible telemetry data link developed by National Nuclear Safety
Administration’s Kansas City Plant (NNSA-KCP) and the University of Kansas (KU) in support
of NNSA’s Remote Sensing Laboratory (NNSA-RSL) located at the Nevada Test Site. This data
link is based on a beam steerable phased array antenna (PAA). The paper describes the PAA and
the Airborne Measurement System (AMS) application requiring signal source tracking. It
highlights flight test data collected during recent flight testing on the Nevada Test Site for the
AMS.
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Barros, Sara Pena. "OFDM for data distribution in phased array antennas." Master's thesis, Universidade de Aveiro, 2013. http://hdl.handle.net/10773/12879.
Full textAbstract:
Mestrado em Engenharia Eletrónica e Telecomunicações<br>Currently, all the control data behind the RF front-end modules in phased array
radars is transmitted digitally and simultaneously by means of optical ber, resulting
in a massive distribution network. The design of cheaper radars requires
alternative ways of transmission to be explored. An intuitive and rather straight
approach is to take advantage of the already existent RF layer used for the distribution
of the radar pulse.
The aim of this thesis work is to investigate OFDM as a modulation option for
that approach and to determine whether or not it is a viable one. As proof of
concept, experimental results are presented and discussed.<br>Actualmente, toda a informa cão de controlo por detráas dos móodulos T/R (Transmit/
Receive) em radares com phased arrays e transmitida digital e simultaneamente
atrav és de fi bra optica, resultando numa rede de distribuiçaõ massiva.
Para que se possa reduzir o custo de produção e limitações no design, e fundamental
a exploração de alternativas para a transmissão destes dados. Uma ideia
intuitiva e que não implica grandes modi ca ções estruturais, e tirar vantagem da
j a existente layer de RF (R adio Frequência) usada para distribuição do pulso de
radar pelos m ódulos.
O objectivo desta tese é investigar OFDM (Orthogonal Frequency Division Multiplexing)
como uma das opções para modulação do novo sinal de RF responsável
pela informa ção de controlo e determinar se esta é ou não uma escolha vi ável.
Como prova de conceito, resultados experimentais serão apresentados e discutidos.
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Lee, Dong-Wook. "Extracting multiple frequencies from phase-only data." Diss., Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/15031.
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Depoy, Randy S. Jr. "Mitigating atmospheric phase errors in SAL data." Wright State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1610632181418557.
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Berger, Gernot. "Volume holographic data storage utilizing phase modulations." Aachen Shaker, 2008. http://d-nb.info/993156657/04.
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Cheng, Hui. "Data integration and visualization for systems biology data." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/77250.
Full textAbstract:
Systems biology aims to understand cellular behavior in terms of the spatiotemporal interactions among cellular components, such as genes, proteins and metabolites. Comprehensive visualization tools for exploring multivariate data are needed to gain insight into the physiological processes reflected in these molecular profiles. Data fusion methods are required to integratively study high-throughput transcriptomics, metabolomics and proteomics data combined before systems biology can live up to its potential. In this work I explored mathematical and statistical methods and visualization tools to resolve the prominent issues in the nature of systems biology data fusion and to gain insight into these comprehensive data.
In order to choose and apply multivariate methods, it is important to know the distribution of the experimental data. Chi square Q-Q plot and violin plot were applied to all M. truncatula data and V. vinifera data, and found most distributions are right-skewed (Chapter 2). The biplot display provides an effective tool for reducing the dimensionality of the systems biological data and displaying the molecules and time points jointly on the same plot. Biplot of M. truncatula data revealed the overall system behavior, including unidentified compounds of interest and the dynamics of the highly responsive molecules (Chapter 3). The phase spectrum computed from the Fast Fourier transform of the time course data has been found to play more important roles than amplitude in the signal reconstruction. Phase spectrum analyses on in silico data created with two artificial biochemical networks, the Claytor model and the AB2 model proved that phase spectrum is indeed an effective tool in system biological data fusion despite the data heterogeneity (Chapter 4). The difference between data integration and data fusion are further discussed. Biplot analysis of scaled data were applied to integrate transcriptome, metabolome and proteome data from the V. vinifera project. Phase spectrum combined with k-means clustering was used in integrative analyses of transcriptome and metabolome of the M. truncatula yeast elicitation data and of transcriptome, metabolome and proteome of V. vinifera salinity stress data. The phase spectrum analysis was compared with the biplot display as effective tools in data fusion (Chapter 5). The results suggest that phase spectrum may perform better than the biplot.
This work was funded by the National Science Foundation Plant Genome Program, grant DBI-0109732, and by the Virginia Bioinformatics Institute.<br>Ph. D.
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Namachivayam, Abishek. "High speed Clock and Data Recovery Analysis." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1587583678200267.
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Madore, Bruno. "Reduced data requirements for phase-contrast MR angiography." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape16/PQDD_0014/NQ28005.pdf.
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McCaffrey, Philip D. "Equilibrium structures from gas-phase electron-diffraction data." Thesis, University of Edinburgh, 2007. http://hdl.handle.net/1842/2601.
Full textAbstract:
For the past 75 years gas-phase electron diffraction (GED) has remained the most valuable technique for determining structures of small molecules, free from intermolecular interactions. Throughout this period many improvements have been made to both the experimental and theoretical aspects of this technique, leading to the determination of more accurate structures. As the uncertainties associated with many stages of the process have been greatly reduced, errors introduced by assumptions, which were previously neglected, now play an important role in the overall accuracy of the determined structure. This work is focused on two such areas, namely the treatment of vibrational corrections and the vibrational effects on the scattering of individual electrons by multiple atoms. A novel method has been developed which allows the extraction of equilibrium structures (re) from distances obtained directly from GED experiments (ra). In unfavourable cases (such as small molecules with large-amplitude and / or highly anharmonic modes of vibration) traditional methods can introduce errors of comparable size to those obtained from the experiment. The newly developed method, EXPRESS (EXPeriments Resulting in Equilibrium StructureS), overcomes the problems which have plagued previous attempts through exploring a more extensive region of the potential-energy surface (PES), specifically regions relating to the normal modes of vibration. The method has been applied, initially, to sodium chloride in the gas phase as this contains dimer molecules with very low-frequency large-amplitude modes of vibration. The experimentally determined re structure gives good agreement with high-level ab initio calculations. Following this success, the EXPRESS method was then applied to sodium fluoride, sodium bromide and sodium iodide, giving similarly good agreement with theoretical calculations. The regular mixed alkali halide dimers (D2h symmetry) cannot be studied by microwave spectroscopy as they do not have a permanent dipole moment. However, vi mixed dimers (C2v) and asymmetric dimers (Cs) do not suffer from this constraint. Using insights learned from the ab initio studies of the sodium halides, geometries and dipole moments have been calculated for a range of mixed and asymmetric alkali halide dimers to enable their study by microwave spectroscopy. A multi-dimensional version of the EXPRESS method has been applied to the lowfrequency modes of chlorofluoroacetylene and chlorodifluoronitrosomethane to assess the effects of coupling between these modes of vibration in these structurally challenging systems. To obtain re structures of larger molecules a second method, using molecular dynamics (MD), has been developed and has been implemented on two test cases: the sodium chloride dimer and octasilsesquioxane. Traditional scattering theory used in GED employs the first-order Born approximation (FBO). However, this ignores any multiple scattering events, which are important for heavier atoms. Using a method similar in nature to EXPRESS a full vibrational analysis of three-atom scattering has been conducted on tellurium dibromide and tellurium tetrabromide.
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Owens, James Webster 1966. "Compression of synthetic aperture radar phase history data." Diss., The University of Arizona, 1997. http://hdl.handle.net/10150/282500.
Full textAbstract:
Synthetic aperture radars (SARs) are modern airborne or spaceborne high-resolution imaging systems used in target imaging and terrain mapping applications. SAR systems collect large volumes of complex phase history data that, in some systems, is downlinked to predetermined ground receiving stations for storage and/or subsequent processing. Considering the volume of data generated, SAR phase history data compression techniques are naturally of interest. In this dissertation, three complete SAR phase history data compression systems are presented. Two compression systems are based on trellis coded quantization and can be used to compress phase history data collected by a SAR system, independent of the SAR's mode of operation. The third compression system employs an optimal rate allocation strategy. It is designed specifically for spotlight mode SAR systems and utilizes the fundamental result that a complex image can be formed from spotlight mode SAR phase history data using a (windowed) two-dimensional FFT. Performance evaluations are presented for these compression systems relative to other existing SAR phase history data compression systems.
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Rajeswaran, Jeevanantham. "JOINT MODELING OF MULTIVARIATE LONGITUDINAL DATA AND COMPETING RISKS DATA." Case Western Reserve University School of Graduate Studies / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=case1354508776.
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Berger, Gernot [Verfasser]. "Volume Holographic Data Storage Utilizing Phase Modulations / Gernot Berger." Aachen : Shaker, 2009. http://d-nb.info/1126378488/34.
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Ahmad, N. "GPS : Preprocessing and data validation for the phase observable." Thesis, University of Newcastle Upon Tyne, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.234480.
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Leibly, Frank J. (Frank Joseph). "Measurement and digitization of phase angle modulated sensor data." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/37753.
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Gharabaghi, Sara. "Quantitative Susceptibility Mapping (QSM) Reconstruction from MRI Phase Data." Wright State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1610018553822445.
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Venkataraman, Suzanne Marie. "CAD graphics utilization in the design and marketing phases of textile/apparel product development." Thesis, Virginia Tech, 1992. http://hdl.handle.net/10919/41538.
Full textAbstract:
The purpose of this research was to identify the expertise of CAD graphics operators/managers in the design and marketing phases of textile/apparel product development. Additionally, the purposes were to determine the effect of CAD graphics on product development in the textile/apparel industry, and to identify future needs and uses of CAD graphics in the industry.
A questionnaire was sent to 117 CAD graphics operators/managers. The results from the questionnaire were obtained through frequency and percentage distributions.
The major findings of this study concluded that textile design and/or colorations and coloration of sketches were the major uses for CAD graphics systems. The shortening of response time of development of idea in design cycle was the major benefit of using a CAD graphics system. Future needs and wants were found to be mainly in the areas of better color control, matching and selection, better resolution in printing, and faster, larger printout capabilities.<br>Master of Science
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Laiho, Petra Marjut Johanna. "Modelling survey participation in surveys involving multiple phases of data collection." Thesis, University of Southampton, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.442783.
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Petersson, Sven. "Simulation of Phase Contrast MRI Measurements from Numerical Flow Data." Thesis, Linköping University, Department of Biomedical Engineering, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-14871.
Full textAbstract:
<p>Phase-contrast magnetic resonance imaging (PC-MRI) is a powerful tool for measuring blood flow and has a wide range of cardiovascular applications. Simulation of PC-MRI from numerical flow data would be useful for addressing the data quality of PC-MRI measurements and to study and understand different artifacts. It would also make it possible to optimize imaging parameters prior to the PC-MRI measurements and to evaluate different methods for measuring wall shear stress.</p><p>Based on previous studies a PC-MRI simulation tool was developed. An Eulerian-Lagrangian approach was used to solve the problem. Computational fluid dynamics (CFD) data calculated on a fix structured mesh (Eulerian point of view) were used as input. From the CFD data spin particle trajectories were computed. The magnetization of the spin particle is then evaluated as the particle travels along its trajectory (Lagrangian point of view).</p><p>The simulated PC-MRI data were evaluated by comparison with PC-MRI measurements on an in vitro phantom. Results indicate that the PC-MRI simulation tool functions well. However, further development is required to include some of the artifacts. Decreasing the computation time will make more accurate and powerful simulations possible. Several suggestions for improvements are presented in this report.</p>
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Stevenson, Brady Roos. "Analysis of Near-Infrared Phase Effects on Biometric Iris Data." BYU ScholarsArchive, 2006. https://scholarsarchive.byu.edu/etd/1299.
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The purpose of this research is to ascertain potential iris scan data variations from near infrared waves derived from fluorescent illumination. Prior studies of iris data variances from infrared wave interference of halogen, incandescent, and sunlight with iris cameras suggest that similar changes may exist under near infrared wavelengths from fluorescent light. The concern is that the fluorescent energy emission may interfere with the near infrared detection of an iris camera. An iris camera is used to measure human eye characteristics known as biometrics. If such infrared emission is statistically significant, then it can alter the validity of the iris scan data. The experiment utilized nine hundred forty-five (945) scans from sixty-three (63) subjects. Measured results showed increased heat from ambient fluorescent illumination does not statistically alter the biometric readings of human eyes. The test results fail to reject that data loss will not occur as heat is increased in the ambient fluorescent light source.
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GABARDI, SILVIA. "First principles simulations of phase change materials for data storage." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2015. http://hdl.handle.net/10281/76292.
Full textAbstract:
I materiali a cambiamento di fase sono calcogenuri a base di tellurio di notevole interesse tecnologico per la realizzazione di memorie ottiche (DVD) e di memorie elettroniche non volatili di nuova concezione, le memorie a cambiamento di fase o PCM. Questi dispositivi si basano su una veloce (50 ns) e reversibile transizione di fase amorfo-cristallo indotta per riscaldamento. Le due fasi corrispondono ai due stati di memoria che possono essere distinti grazie alla grande differenza tra le proprietà ottiche ed elettroniche dell'amorfo e quelle del cristallo. Nonostante il Ge2Sb2Te5 (GST) sia il materiale attualmente usato nelle PCM, si stanno studiando nuovi materiali con una temperatura di cristallizzazione più alta per aumentare la stabilità termica delle PCM. A questo proposito in questa tesi sono state studiate, attraverso simulazioni di dinamica molecolare ab-initio, diverse leghe ad alta temperatura di cristallizzazione con composizione In3Sb1Te2, In13Sb11Te3 e Ga4Sb6Te3. Queste leghe sono state studiate sperimentalmente e proposte come sostituti del GST, ma le proprietà strutturali e l'origine microscopica dell'elevata temperatura di cristallizzazione della fase amorfa di questi composti non è ancora del tutto chiara. Sono stati, quindi, generati modelli di qualche centinaio di atomi della fase amorfa raffreddando dal liquido in centinaia di ps allo scopo di trovare una relazione tra la struttura dell'amorfo e l'alta temperatura di cristallizzazione di queste leghe. La topologia di legame dei modelli amorfi risulta principalmente tetraedrica, molto diversa dalla geometria della fase cristallina che presenta invece intorni ottaedrici. La presenza di strutture tetraedriche nell'amorfo, assenti invece nella fase cristallina, può quindi costituire un ostacolo alla cristallizzazione con l'effetto di innalzare la temperatura di cristallizzazione rispetto al GST che presenta una geometria di legame prevalentemente ottaedrica sia nell'amorfo che nel cristallo.
Nella seconda parte di questo lavoro è stato affrontato il problema del drift, che consiste in un aumento della resistenza elettrica
della fase amorfa con il tempo. Questo fenomeno rappresenta un problema nelle celle PCM in quanto modifica le caratteristiche elettriche del dispositivo; tuttavia, manca ancora una spiegazione completa del meccanismo microscopico alla base di questo processo. Il drift sembra però legato al fenomeno del rilassamento strutturale che si verifica nei semiconduttori amorfi e che modifica nel tempo gli stati di difetto in prossimità degli edge delle bande di valenza e di conduzione, da cui dipende la conduzione nella fase amorfa. Per studiare il fenomeno del drift sono stati generati modelli di grandi dimensioni (circa duemila atomi) di GeTe amorfo raffreddando dal liquido in 100 ps attraverso simulazioni di dinamica molecolare classica con un potenziale Neural-Network. Una volta rilassati ab-initio, i modelli presentano diversi stati nel gap localizzati su catene di atomi di Ge. Dopo aver riscaldato i modelli a 500 K in modo da accelerare il processo di drift, si osserva una riduzione del numero di catene di Ge e di legami omopolari Ge-Ge con un conseguente allargamento del gap e riduzione dell'ampiezza delle code di Urbach che possono giustificare un aumento della resistenza. Si propone quindi che il drift sia dovuto al rilassamento strutturale della fase amorfa che porta alla riduzione delle catene di legami omopolari di Ge.<br>Phase change materials based on chalcogenide alloys are of great technological importance because of their use in optical data storage
devices (DVDs) and electronic non-volatile memories of new concept, the Phase Change Memory cell (PCM). These applications rely on a
fast (50 ns) and reversible change between the crystalline and the amorphous phases upon heating. The two phases correspond to the two
states of the memory that can be discriminated thanks to a large difference in their optical and electronic properties. Although Ge2Sb2Te5
(GST) is the compound presently used as active layer in PCMs, alternative materials with a higher crystallization temperature are under scrutiny in order to increase the thermal stability of the PCM devices. In this respect, we analysed, by means of ab-initio molecular dynamics simulations, different high crystallization temperature alloys with composition In3Sb1Te2, In13Sb11Te3 and Ga4Sb6Te3, which have been experimentally proposed as substitute of GST. However, the structural properties and the microscopical reason of the high thermal stability of the amorphous phases of these compounds is still unclear. We, thus, generated models of the amorphous phase of few hundreds of atoms by quenching from the melt in few hundreds of ps aiming at finding out a relation between the structural properties of the amorphous phase and the high crystallization temperature of these alloys. The topology of our amorphous models turned out to be mostly tetrahedral which differs from the octahedral-like geometry of the crystalline phases. The presence of tetrahedral structures in the amorphous which are absent in the crystalline phase, probably hinders the crystallization process resulting in a higher crystallization temperature with respect to GST which display a mostly octahedral-like structures in both amorphous and the crystalline phase.
In the second part of this work we addressed the issue of the resistance drift phenomenon, which consists of an increase of the electrical
resistance of the amorphous phase with time. This effect is detrimental in PCMs since it changes the electrical characteristics of the devices.
This process is believed to be due to an aging of the amorphous phase which modifies during time the defect states in the proximity
of the valence and conduction band edges which control the electrical conductivity. The microscopic origin of the structural relaxations leading to the drift is still unknown. To address this problem, we generated large models (about two thousand atoms) of amorphous GeTe by quenching from the melt in 100 ps with classical molecular dynamics simulations by using a neural-network potential. Once relaxed by first principles, the models showed the presence of several in-gap states localized on chains of Ge atoms. After an annealing at 500 K, performed to accelerate the drift process, Ge chains and homopolar Ge-Ge bonds reduce in number resulting in a band gap widening and a reduction of the Urbach tails at the band edges which can account for the increase of the resistance. We thus propose that the resistance drift originates from structural relaxations leading to the removal of Ge chains.
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Keche, Mokhtar. "Data association and adaptive filtering in multiple target tracking using phased arrays." Thesis, University of Nottingham, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263467.
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Karczmarek, Michal 1977. "Constrained and phased scheduling of synchronous data flow graphs for StreamIt language." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/87333.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2003.<br>Includes bibliographical references (p. 107-109).<br>by Michal Karczmarek.<br>S.M.
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Palani, Ananta. "Development of an optical system for dynamic evaluation of phase recovery algorithms." Thesis, University of Cambridge, 2015. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.708850.
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Zeydan, Engin. "Channel Phase And Data Estimation In Slowly Fading Frequency Nonselective Channels." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12607419/index.pdf.
Full textAbstract:
In coherent receivers, the effect of the multipath fading channel on the transmitted signal must be estimated to recover the transmitted data. In this thesis, the channel
phase and data estimation problems are investigated in a transmitted data sequence when the channel is modeled as slowly fading, frequency non-selective channel.
Channel phase estimation in a transmitted data sequence is investigated and data estimation is obtained in a symbol-by-symbol MAP receiver that is designed for minimum symbol error probability criterion.
The channel phase is quantized in an interval of interest, the trellis diagram is constructed and Viterbi decoding algorithm is applied that uses the phase transition and observation models for channel phase estimation. The optimum coherent and noncoherent detectors for binary orthogonal and PSK signals are derived and the modulated signals in a sequence are detected in symbol-by-symbol MAP receivers.Simulation results have shown that the performance of the receiver with phase estimation is between the performance of the optimum coherent and noncoherent
receiver.
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Jalali, Mohammad Sadegh. "A hybrid phase-locked loop for clock and data recovery applications." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/27486.
Full textAbstract:
Clock and data recovery (CDR) circuits are among critical building blocks of wireline receivers. In these receivers, typically after compensating for the adverse effects of the
channel by an equalizer, the received signal is processed to the CDR block. The timing of the signal is first extracted (clock recovery), and then the actual data is recovered (data recovery). To recover the clock, phase-locked loops (PLLs) are usually used. The PLL output can track the phase and the frequency of its input.
In this thesis, a hybrid PLL architecture is proposed. The PLL starts its operation using a binary phase/frequency detector (PFD) to achieve a fast lock and a wide tuning range. The operation is then automatically switched to a linear phase detector (PD) to achieve a low jitter clock signal upon lock, and finally the bandwidth is decreased to decrease the output jitter even more. Automatic switching of the operation from the binary to the linear PD is achieved by detecting the point at which the clock frequency crosses the data frequency. This PLL structure is particularly suitable for CDR applications, as its output is insensitive to continuous data streams.
Also, a feedback-based technique is used in the charge pump (CP) to increase its swing. This is done by detecting the change in the drain-source voltages of the current source transistors of the CP and changing their gate-source voltages in a closed-loop feedback system to keep their currents constant.
The PLL is designed and simulated in a 0.13 μm CMOS technology. Post-layout simulations show that the tuning range of the PLL is from ∼8.3 GHz to 9.6 GHz, and it consumes about 35 mW from a 1.2 V supply and has a deterministic jitter of about 35 fs. The total random jitter of the designed PLL is about 0.1 unit interval (UI) (11.7 ps with a clock frequency of 8.5 GHz). The worst-case lock time of the PLL is slightly less than 30 ns.
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Mahdavi, Ali Reza. "Data-aided phase control in differential GMSK receivers for narrowband communications." Thesis, University of Hull, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.301633.
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Davidson, H. D. "A reliable data channel for underwater communications using phase shift keying." Thesis, University of Newcastle Upon Tyne, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.233423.
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Loveless, Ian. "Binary Classification With First Phase Feature Selection forGene Expression Survival Data." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1555444873531262.
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Rhodes, Hannah Rasmussen. "Multivariate and geostatistical analyses of Phase I Eastern Lake Survey data." Diss., The University of Arizona, 1993. http://hdl.handle.net/10150/186139.
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Many difficulties are encountered when analyzing large spatial data sets. The following research focuses on how various univariate, multivariate, geostatistical, and geographic information systems techniques can aid in the examination of spatial data sets containing large numbers of samples, as well as variables. The analyses are applied to data from Phase I of the Eastern Lake Survey which deals with the effects of acidic deposition on aquatic ecosystems. Relationships among chemical analytes are explored, and outlying or atypical lake samples and chemical analytes are identified using statistical techniques including univariate statistics, correlation analysis, normality testing, multivariate outlier testing, correspondence analysis, and ordinary kriging. The primary objective of the correspondence analysis was to obtain a reduction in the number of chemical analytes in order to make subsequent data analyses and interpretations easier. The main reason for performing a geostatistical analysis of the ELS-I data was to obtain maps of interpolated values for unsampled lake locations. Geographic information systems technology was used to examine the influence of lake size on the kriging analysis. This research should provide useful for future efforts to detect and ameliorate the effects of acidic deposition on aquatic ecosystems.
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Humali, I. Gokhan. "Sensor fusion for boost phase interception of ballistic missiles." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Sep%5FHumali.pdf.
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Thesis (M.S. in Systems Engineering)--Naval Postgraduate School, Sept. 2004.<br>Thesis advisor(s): Phillip E. Pace, Murali Tummala. Includes bibliographical references (p. 73-74). Also available online.
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Navarra, Alessandro. "Data structures and n-dimensional mechanics in materials science." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=112546.
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By extending the diagrams of materials science, the field is broadened in a natural way. For example, binary phase diagrams are like black boxes, used in the design and simulation of microstructures. They explore a balance of two chemical species, but real alloys have several chemical species, and merit a higher dimensional space. The n-dimensional extension is simplified by dividing the problem into discrete and continuous components.<br>"Discrete" is the identification of behavioural regimes, and their interactions, in a network graph. "Continuous" includes the curvature of boundaries, and the motion through the space. In thermochemical phase spaces, a homogenous alloy is mapped to a particle, whose motion represents the evolution of the alloy. Likewise, non-homogeneous alloys evolve as multidimensional continua.<br>The classical diagrams may also be hybridized. For example, TTT-curves may be treated as extra dimensions of a thermochemical phase space; the resulting hybrid synthesizes microstructural thermodynamics and kinetics.
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O'Cull, Douglas C. "The Effects of Phase Noise on Trellis FM & SOQPSK Data Links." International Foundation for Telemetering, 2011. http://hdl.handle.net/10150/595625.
Full textAbstract:
ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada<br>Current IRIG standards provide guidelines for system phase noise and several manufactures provide receivers and transmitters that perform within this standard. However, legacy receivers and transmitters that do not meet the current IRIG standards are sometimes still used during a mission. This paper will address how phase noise outside of the current IRIG standard affects the performance of an FM data link when using a trellis demodulator, as well as the performance of an SOQPSK data link in a high phase noise environment. Bit error rate performance and test results at several different rates with various phase noise masks are presented in this paper.