Relevant bibliographies by topics / Phasor Data

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Phasor Data'

Author: Grafiati
Published: 4 June 2025
Last updated: 23 June 2025

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Journal articles on the topic "Phasor Data"

1

Krishnan, Kiruthika, and Srivani Iyengar. "Ensemble learning based fault detection using PMU data in imbalanced data condition." International Journal of Power Electronics and Drive Systems (IJPEDS) 16, no. 2 (2025): 851. https://doi.org/10.11591/ijpeds.v16.i2.pp851-863.

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Significant advancements in the electrical grid include enhanced regulation, communication, metering, and customer interaction, driven by information communication technologies (ICTs) and cyber-physical systems (CPS). The adaptation of synchro phasor devices like phasor measurement units (PMUs) enables real-time monitoring and control, aiding in power system security assessment. PMUs record voltage and current phasors with GPS time stamps, transmitting data to phasor data concentrators (PDCs) for decision-making. However, ensuring the stability and security of this method against cybersecurity threats is crucial due to its reliance on Internet Protocol (IP) networks. Dynamic security assessment utilizes PMU data, reported up to 30–60 times per second, to evaluate power system safety. To address security issues, a Python-based fault detection system employing a stack ensemble learning algorithm is developed. This approach consistently outperforms traditional methods, producing satisfactory results with superior AUC-ROC curves, validated through correctness checks and graphical analysis. The dataset includes both natural and man-made security threats, facilitating comprehensive assessment and mitigation strategies. The ensemble learning algorithm performed better than the individual algorithms by obtaining 95% in the AUC-ROC curve.
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Ravi Ponnala. "Modified PMU for Power System Monitoring in Dynamic State and Effective Data Handling." Journal of Information Systems Engineering and Management 10, no. 25s (2025): 242–48. https://doi.org/10.52783/jisem.v10i25s.3974.

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The world's modernization resulted to a sharp rise in the demand for power. Decentralized power generation and the inclusion of renewable energy sources are making power system operation more complex. As a result, power system monitoring and measurement also became more complicated. One of the main disadvantages of power system monitoring is the slower rate of the measurement and monitoring data obtained from the current power system monitoring techniques, such as Supervisory Control and Data Acquisition (SCADA) and Energy Management Systems (EMS), as they only provide a limited amount of information on the parameters of the power system. Therefore, it is necessary to improve the current power system monitoring techniques for gathering data from the power system. Phasor measurements using Intelligent Electronic Devices (IEDs) provide faster data gathering from the power system and more information about the parameters of the power system. In order to determine the phasor values of voltage, current, remaining power system operational parameters frequency, Change of Frequency (COF) and Rate of Change of Frequency (ROCOF), this IED gathers the voltage and current signal data from the power system more quickly and sends it to a software program. By using this software program, very quickly phsors, power system operational parameters are calculated.The calculated phasors gave the live representation of the power system feasible by appending a time tag to each phasor value. This is a crucial requirement for power system monitoring across a large area, leads to massive storage system of phasors and power system paprameters. To store only required and effective data and to avoid routine data storage, new storage method is proposed. This paper presents a phasor calculation technique, synchronized phasor measurements, effective data storage, and identifying of faults in the dynamic state.
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Zhao, Dongfang, Fuping Wang, Shisong Li, et al. "An Optimization of Least-Square Harmonic Phasor Estimators in Presence of Multi-Interference and Harmonic Frequency Variance." Energies 16, no. 8 (2023): 3397. http://dx.doi.org/10.3390/en16083397.

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The wide application of power electronic devices brings an increasing amount of undesired harmonic and interharmonic tones, and accurate harmonic phasor estimation under a complex signal input is an important task for smart grid applications. In this paper, an optimization of least-square dynamic harmonic phasor estimators, considering multi-interference and harmonic frequency variance, is proposed. A comprehensive error index (CEI) composed of the fundamental-leakage-led harmonic amplitude estimation error, harmonic mutual interference, out-of-band interference, and harmonic frequency deviation is employed. The largest CEI part of least-square algorithms using three different signal decomposition models is analyzed for the first time, and variables to reduce this error component are then introduced using singular value decomposition. With the CEI and defined variables, a minimum-error estimation of harmonic phasors under various interference and harmonic frequency change is discussed. Numerical tests are performed, and the test results show that after the proposed optimization is applied to least-square algorithms, the harmonic phasor estimation errors are considerably reduced, especially for low-order harmonics. We also show the possibility of choosing desired optimal phasor filter design by balancing the measurement accuracy and data latency. For example, when the window length is set to three nominal cycles, the proposed optimization can yield both good accuracy and fast measurement speed for estimating harmonic phasors under multi-interference and harmonic frequency variance.
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R.Alekya, Ponnala Ravi, Soumya Aleti, and Shiny Sucharitha B. "Synchronized Phasor Measurements with GPS Time Stamping using 64 Point DFT in PMU." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 4 (2020): 2435–40. https://doi.org/10.35940/ijeat.D8065.049420.

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This paper describes about the time synchronization of different locations voltage or current signals for accurate comparison of signals on single phasor graph, all the measured phasors are synchronized with Global Positioning System (GPS) time stamping. Day to day power demand increases very rapidly, to meet the growing demand of electrical energy new energy resources are required and manage them efficiently. For efficient allocation of sources there should be a good monitoring and fast control system. For better monitoring and control of the system accurately it requires “Wide Area Monitoring” of power system. In the wide area monitoring system collection of data from the power system should be at a faster level. The collection of data from the power system at faster level is possible by using “Phasor Measurement Units(PMUs)”. PMU collects the data at faster rate rates like 50-60 samples for cycle, this information is send to local Phasor Data Concentrator (PDC). Local phasor data concentrator collects the data from different PMUs which are located in different areas. This PDC helps to take the necessary action on power system. For synchronization, pulse per second(PPS) is taken from GPS module. From this 1PPS, 3200 pulses is generated for high accuracy of 64 point DFT of 50Hz signal using microcontroller. System frequency is calculated by using time period between the two consecutive raising edges or falling edges of square wave. This is in synchronous with the input sinusoidal signal.
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Ponnala, Ravi, Muktevi Chakravarthy, and Suraparaju Venkata Naga Lakshmi Lalitha. "Effective monitoring of power system with phasor measurement unit and effective data storage system." Bulletin of Electrical Engineering and Informatics 11, no. 5 (2022): 2471–78. http://dx.doi.org/10.11591/eei.v11i5.4085.

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In the recent years the monitoring and operation of the power system became complex, due to the more demand from the different linear and non-linear loads and generation from the different sources. For the effective monitoring and operation of the power system, existing power system monitoring methods need to improve or new technologies are required. For the effective monitoring and operation of the power system phasor measurement unit (PMU) based monitoring is suitable, because it provide the dynamic state monitoring system. In this paper PMU based monitoring is proposed with effective data storage system and protection. With this method phasor values of voltage and current signals are calculated at the location of PMU and with the help of software based program effective data storage also possible. With this proposed model the phasor values in the power system at different locations monitoring also possible and required phasor data only stored and total data is only monitored. The phasor values of signals are calculated with direct phasor measurement technique in LabVIEW and by adding time stamping to the each phasor value accurate measurement of power flow is possible.
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Parthasarathy, Hari Krishna Achuthan, Madhusudan Saranathan, Adhitya Ravi, M. C. Lavanya, and V. Rajini. "Comparative Analysis of Phasor Estimation Techniques for PMU Applications." Journal of Physics: Conference Series 2325, no. 1 (2022): 012010. http://dx.doi.org/10.1088/1742-6596/2325/1/012010.

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Abstract Phasor Measurement Units (PMU) are valuable sources of data which increase the visibility into several fields of application such as power production, transmission and distribution. With the initial goal of obtaining phasor values at fixed points in the network and syncing it to a standard time frame, the technology has morphed into an all-encompassing unit, which has its uses in the field of protection, control and automation. With the application of these units becoming a standard benchmark, the improvement in the current available units is a huge requirement. This study presents a comprehensive analysis of various techniques that is used for the estimation of phasors.
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Ponnala, Ravi, Muktevi Chakravarthy, and Suraparaju Venkata Naga Lakshmi Lalitha. "Novel PMU Model for Dynamic State Disturbance Analysis with Effective Data Handling System." International Journal of Electrical and Electronics Research 10, no. 4 (2022): 1306–14. http://dx.doi.org/10.37391/ijeer.100485.

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In this paper a hybrid DFT phasor calculation method is presented. This method is used to calculate the fundamental component phasor value of the harmonic signal without any physical filter. With this method the computational time for each phasor value calculation is reduced and the calculated phasor value has the constant magnitude and rotating phase angle. This calculated phasor values are used for the disturbance or fault identification in the power system based on Total Vector Error (TVE). The %TVE-based fault identification is more effective, because the TVE value is calculated with reference phasor value. If any fault/disturbance occurs or frequency changes then %TVE value changes. This change in TVE value is reflected in the calculation of the next sample (1/f.*N sec), giving the advantage to this method as compared to the other magnitude-based fault identification systems. Normally with the phasor calculation large data is produced, which requires large memory for the storage of this data and makes the analysis difficult. To avoid large data storage system conditional-based data storage system is proposed, where the data is stored during only the disturbance conditions or at every one second. With this technique, the data to be stored is reduced and the analysis of this data also becomes simpler for the post disturbance and for future load prediction. The performance of the proposed method is evaluated in terms of accuracy of calculation and its implementation ability. The simulation results are as per the IEEE C37.118.1a2014 for the power system monitoring and fault identification.
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Xiao, Xianyong, Runze Zhou, Xiaoyang Ma, and Rui Xu. "Harmonic Phasor Estimation Method Considering Dense Interharmonic Interference." Entropy 25, no. 2 (2023): 236. http://dx.doi.org/10.3390/e25020236.

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Due to the limitation of frequency resolution and the spectrum leakage caused by signal windowing, the spectrums of harmonic and interharmonic components with close frequencies overlap each other. When the dense interharmonic (DI) components are close to the harmonic spectrum peaks, the harmonic phasor estimation accuracy is seriously reduced. To address this problem, a harmonic phasor estimation method considering DI interference is proposed in this paper. Firstly, based on the spectral characteristics of the dense frequency signal, the phase and amplitude characteristics are used to determine whether DI interference exists in the signal. Secondly, an autoregressive model is established by using the autocorrelation of the signal. Data extrapolation is performed on the basis of the sampling sequence to improve the frequency resolution and eliminate the interharmonic interference. Finally, the estimated values of harmonic phasor, frequency and rate of change of frequency are obtained. The simulation and some experimental results demonstrate that the proposed method can accurately estimate the parameters of harmonic phasors when DIs exist in the signal, and has a certain anti-noise capability and dynamic performance.
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Tao, Weiqing, Mengyu Ma, Chen Fang, et al. "Design and Application of a Distribution Network Phasor Data Concentrator." Applied Sciences 10, no. 8 (2020): 2942. http://dx.doi.org/10.3390/app10082942.

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The wide area measurement system (WAMS) based on synchronous phasor measurement technology has been widely used in power transmission grids to achieve dynamic monitoring and control of the power grid. At present, to better realize real-time situational awareness and control of the distribution network, synchronous phasor measurement technology has been gradually applied to the distribution network, such as the application of micro multifunctional phasor measurement units (μMPMUs). The distribution network phasor data concentrator (DPDC), as a connection node between the μMPMUs and the main station, is also gaining more attraction. This paper first analyzes the communication network structure of DPDCs and μMPMUs and compares and analyzes the differences in the installation locations, functions, communication access methods and communication protocols of the phasor technology devices of the distribution network and the transmission network. It is pointed out that DPDCs not only need the functions of data collection, storage, and forwarding like transmission network PDCs, but also should be able to access more μMPMUs, and can aggregate the phasor data of the same time scale from μMPMUs by different communication methods. The communication protocol selected by DPDC should be expanded to support remote control, telemetry, fault diagnosis and other functions of distribution automation. The application requirements of DPDCs are clarified, and the key indicators of DPDCs are given as a method to evaluate the basic performance of DPDCs. Then, to address the problems of more μMPMU access, abnormal communication, and data collection with different delays that DPDC encountered, a DPDC that considers multiple communication methods is designed. Based on the Linux system and the libuv library, the DPDC is designed with event-driven mechanism and structured programming, runs multiple threads to implement multitasking, and invokes callbacks to perform asynchronous non-blocking operations. The DPDC test system and test methods are designed. The performance of the designed DPDC is evaluated through the test and the test results are analyzed. Lastly, its real-world application is disclosed, which further confirmed the value of our DPDC.
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Nuthalapati, Sarma, Jian Chen, Prakash Shrestha, et al. "Use of Synchronized Phasor Measurements for Model Validation in ERCOT." International Journal of Emerging Electric Power Systems 14, no. 1 (2013): 87–94. http://dx.doi.org/10.1515/ijeeps-2013-0029.

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Abstract This paper discusses experiences in the use of synchronized phasor measurement technology in Electric Reliability Council of Texas (ERCOT) interconnection, USA. Implementation of synchronized phasor measurement technology in the region is a collaborative effort involving ERCOT, ONCOR, AEP, SHARYLAND, EPG, CCET, and UT-Arlington. As several phasor measurement units (PMU) have been installed in ERCOT grid in recent years, phasor data with the resolution of 30 samples per second is being used to monitor power system status and record system events. Post-event analyses using recorded phasor data have successfully verified ERCOT dynamic stability simulation studies. Real time monitoring software “RTDMS”® enables ERCOT to analyze small signal stability conditions by monitoring the phase angles and oscillations. The recorded phasor data enables ERCOT to validate the existing dynamic models of conventional and/or wind generator.
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Dissertations / Theses on the topic "Phasor Data"

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Retty, Hema A. "Evaluation and Standardizing of Phasor Data Concentrators." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/32064.

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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.

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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
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Wehbe, Yasser. "Model Estimation of Electric Power Systems by Phasor Measurement Units Data." Scholar Commons, 2012. http://scholarcommons.usf.edu/etd/4419.

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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.

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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.

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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.

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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.

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The process of Synchronization between two buses in a power system plays a vital role, especially during blackstart or bulk power system restoration period. The synchronization process is primarily monitored in the presence of experienced personnel at the substation level, which might not control or even predict the after effects of synchronization as soon as the synchronizing breaker between the two buses respective to the two islands is closed. However, with the advent of phasor measurement units (PMUs) providing time synchronized synchrophasor data, synchroscope functionality can now be implemented at a centralized remote control platform, usually the control room of the specific utility. This thesis presents a technique along with the actual implementation of such a PMU Synchroscope analytic developed as a part of the Department of Energy sponsored open and Extensible Control and Analytics platform for synchrophasor data (openECA project). The challenges faced to realize this functionality at the centralized remote location along with methods to overcome these hurdles have been discussed in the document. Additional features in comparison to the conventional synchroscope device are also added to facilitate a smoother and successful synchronization, reducing error on behalf of the user /operator and thus, facilitating a faster power system restoration.<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.
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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.

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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.

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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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Books on the topic "Phasor Data"

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author, Santoso S., Muljadi E. author, National Renewable Energy Laboratory (U.S.), and Santoso Surya author, eds. Algorithm for screening phasor measurement unit data for power system events and categories and common characteristics for events seen in phasor measurement unit relative phase-angle differences and frequency signals. National Renewable Energy Laboratory, 2013.

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B, Bhasin K., Hendrickson Brian M, Society of Photo-optical Instrumentation Engineers., and American Academy of Otolaryngology--Head and Neck Surgery Foundation., eds. Optoelectronic signal processing for phased-array antennas. SPIE, 1988.

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1949-, Cunningham John R., Jones Dennis K, Design Institute for Physical Property Data (U.S.), and American Institute of Chemical Engineers., eds. Results from the Design Institute for Physical Property Data: Experimental results and data compilation procedures. American Institute of Chemical Engineers, 1990.

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M, Koepf Gerhard, Hendrickson Brian M, and Society of Photo-optical Instrumentation Engineers., eds. Optoelectronic signal processing for phased-array antennas II: 16-17 January 1990, Los Angeles, California. SPIE, 1990.

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United States. National Bureau of Standards, ed. Interelement interactions in phased arrays: Theory, methods of data analysis, and theoretical simulations. U.S. Dept. of Commerce, National Bureau of Standards, 1985.

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Villars, P. Pearson's handbook of crystallographic data for intermetallic phases. 2nd ed. ASM International, 1991.

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D, Calvert L., and Pearson W. B, eds. Pearson's handbook of crystallographic data for intermetallic phases. American Society for Metals, 1985.

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Zoller, Paul. Standard pressure-volume-temperature data for polymers. Technomic Pub. Co., 1995.

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R, Kunath Richard, Daryoush A. S, and United States. National Aeronautics and Space Administration., eds. Bit-error-rate testing of fiber optic data links for MMIC-based phased array antennas. NASA, 1990.

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Shalkhauser, Kurt A. Bit-error-rate testing of fiber optic data links for MMIC-based phased array antennas. NASA, 1990.

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Book chapters on the topic "Phasor Data"

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Phadke, A. G., and J. S. Thorp. "Phasor Measurement Units and Phasor Data Concentrators." In Power Electronics and Power Systems. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-76537-2_5.

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Phadke, Arun G., and James S. Thorp. "Phasor Measurement Units and Phasor Data Concentrators." In Power Electronics and Power Systems. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-50584-8_5.

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Morris, Thomas H., Shengyi Pan, Uttam Adhikari, Nicolas Younan, Roger King, and Vahid Madani. "Phasor Measurement Unit and Phasor Data Concentrator Cyber Security." In Energy Systems. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38134-8_7.

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Kundu, Pratim, Saumendra Sarangi, and Ashok Kumar Pradhan. "Secured relaying using synchronised data." In Synchronized Phasor Measurements for Smart Grids, 2nd ed. The Institution of Engineering and Technology, 2024. https://doi.org/10.1049/pbpo272e_ch3.

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Kumar, Rohit, Sourav Kumar Sahu, Debomita Ghosh, and Sarbani Chakraborty. "A Multi HIL-Based Approach for Real-Time Phasor Data Monitoring Using Phasor Measurement Unit." In Advances in Smart Grid Automation and Industry 4.0. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-7675-1_62.

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Martin, Kenneth, and Kevin Chen. "Impact of Phasor Measurement Data Quality in Grid Operations." In Power Electronics and Power Systems. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89378-5_2.

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Wu, Yan, Weiqing Tao, Yingjie Zhang, and Xueting Li. "Mixed Communication Design of Phasor Data Concentrator in Distribution Network." In Proceeding of 2021 International Conference on Wireless Communications, Networking and Applications. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2456-9_10.

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AbstractPhase Data Concentrator (PDC) is an important part of Wide Area Measurement System (WAMS) and is widely used in transmission systems. WAMS technology will also be applied in smart distribution network, which has many nodes, complex architecture and various types of data transmission services, and a single communication mode cannot meet its needs. In order to solve this problem, this paper first introduces the composition of WAMS system, communication network mode, and discusses the access layer communication network mode. According to the main station, sub-station interaction process design a synchronous phase data set device that can carry out up-down communication and mix network by various means of communication. Finally, the experimental environment of Power Line Carrier (PLC) and twisted pair network communication is set up to verify.
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Qu, Yanfeng, Xin Liu, Jiaqi Yan, and Dong Jin. "Dynamic Data-Driven Self-healing Application for Phasor Measurement Unit Networks." In Lecture Notes in Computer Science. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61725-7_12.

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Thomas, Polly, Emil Ninan Skariah, Sheena Thomas, Sandy J. Thomson, and Shanmugam Prabhakar Karthikeyan. "Identification of Bad Data from Phasor Measurement Units Using Evolutionary Algorithms." In Advances in Intelligent Systems and Computing. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1595-4_8.

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Mejia-Romero, Sergio, J. Eduardo Lugo, Delphine Bernardin, and Jocelyn Faubert. "The Dynamic Performance of Gaze Movement, Using Spectral Decomposition and Phasor Representation." In Proceedings of International Conference on Data Science and Applications. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7561-7_10.

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Conference papers on the topic "Phasor Data"

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Soni, Rajkumar, Manish Kumar Thukral, and Neeraj Kanwar. "Decentralized Phasor Measurement Unit Data Management on the Ethereum Blockchain." In 2024 IEEE Third International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES). IEEE, 2024. http://dx.doi.org/10.1109/icpeices62430.2024.10719177.

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Tiwari, Sukriti. "Hybrid Distribution System State Estimator Incorporating Micro Phasor Measurement Units Data." In 2024 IEEE 4th International Conference on Sustainable Energy and Future Electric Transportation (SEFET). IEEE, 2024. http://dx.doi.org/10.1109/sefet61574.2024.10718170.

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Top, Philip, and John Breneman. "Compressing Phasor Measurement data." In 2013 IEEE Power & Energy Society General Meeting. IEEE, 2013. http://dx.doi.org/10.1109/pesmg.2013.6672472.

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Top, Philip, and John Breneman. "Compressing Phasor Measurement data." In 2013 North American Power Symposium (NAPS). IEEE, 2013. http://dx.doi.org/10.1109/naps.2013.6666959.

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Buttayak, Suttinan, Apichai Wornpuen, Nattasit Promparn, Noppadol Charbkaew, and Teratam Bunyagul. "Design of Phasor Data Concentrator for phasor monitoring system." In 2012 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (STUDENT2012). IEEE, 2012. http://dx.doi.org/10.1109/student.2012.6408374.

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Davis, C. M., J. E. Tate, and T. J. Overbye. "Wide Area Phasor Data Visualization." In 2007 39th North American Power Symposium. IEEE, 2007. http://dx.doi.org/10.1109/naps.2007.4402318.

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Morris, Thomas, Shengyi Pan, Jeremy Lewis, et al. "Cybersecurity risk testing of substation phasor measurement units and phasor data concentrators." In the Seventh Annual Workshop. ACM Press, 2011. http://dx.doi.org/10.1145/2179298.2179324.

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Ramakrishna, Raksha, and Anna Scaglione. "On Modeling Voltage Phasor Measurements as Graph Signals." In 2019 IEEE Data Science Workshop (DSW). IEEE, 2019. http://dx.doi.org/10.1109/dsw.2019.8755588.

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Diakos, Konstantinos, Qiuwei Wu, and Arne Hejde Nielsen. "Phasor measurement unit and phasor data concentrator test with real time digital simulator." In 2014 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC). IEEE, 2014. http://dx.doi.org/10.1109/appeec.2014.7066096.

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Wache, Markus. "Wide area monitoring with Phasor Measurement Data." In 2011 IEEE Second International Conference on Smart Grid Communications (SmartGridComm). IEEE, 2011. http://dx.doi.org/10.1109/smartgridcomm.2011.6102389.

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Reports on the topic "Phasor Data"

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Hart, Philip, Weizhong Yan, Tianyi Wang, et al. Phasor-Measurement-Unit-Based Data Analytics Using Digital Twin and PhasorAnalytics Software. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1828164.

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Wan, Y. H. Synchronized Phasor Data for Analyzing Wind Power Plant Dynamic Behavior and Model Validation. Office of Scientific and Technical Information (OSTI), 2013. http://dx.doi.org/10.2172/1067916.

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Allen, A., S. Santoso, and E. Muljadi. Algorithm for Screening Phasor Measurement Unit Data for Power System Events and Categories and Common Characteristics for Events Seen in Phasor Measurement Unit Relative Phase-Angle Differences and Frequency Signals. Office of Scientific and Technical Information (OSTI), 2013. http://dx.doi.org/10.2172/1096101.

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Fanick, Dietzmann, and Urban. L51564 Emissions Data for Engines Used by the Gas Pipeline Transmission Industry. Pipeline Research Council International, Inc. (PRCI), 1988. http://dx.doi.org/10.55274/r0010937.

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Final Report; covers the annual phases of a two-phase effort to expand the data collected in the companion document (Compilation, L51565). Each annual section is approximately 100 pages and describes the test procedure and selection criteria for the 22 engines and 6 turbines added by the project.
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Tandon, Samarth, Ming Gao, and Ravi Krishnamurthy. PR-328-083501-R01 Evaluation of EMAT Tool Performance and Reliability by Monitoring Industry Experience. Pipeline Research Council International, Inc. (PRCI), 2017. http://dx.doi.org/10.55274/r0011442.

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PRCI project SCC 3-7 consists of two phases: Phase I: "Evaluation of EMAT Tool Performance by Monitoring Industry Experience" (2008-2011) and Phase II: "Evaluation of the Reliability of EMAT Tool by Monitoring Industry Experience" (2012-2015). In this report, performance of the EMAT tools based on analysis of the data from 15 pipeline segments from Phase I and 35 pipeline segments from Phase II is presented. The performance is updated with the newly analyzed data in terms of the probability of detection, identification, false calls, and sizing. Categorization of these 35 segments is presented at three different levels of using EMAT ILI as an integrity tool alternative to hydrotest for management of SCC in gas pipelines. Finally, the reliability of EMAT for SCC management is evaluated incorporating the performance measures and the assessment methodology. The reliability of the hydrotest is calculated based on the collected historical data from one Gas Pipeline Operator.
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Young, Matthew M. Proposed Methods For Estimating Costs Of Mental Health In Canada (2007-2020). Greo Evidence Insights, 2023. http://dx.doi.org/10.33684/2023.002.

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This report presents the results of an investigation by Greo Evidence Insights into how Canadian mental health (MH) costs could be estimated. It begins by conducting a review of studies estimating the costs of MH in Canada since 2010 and examines the various approaches employed. Based on this analysis the next section makes recommendations regarding cost types to include, the granularity of the estimates, and the approach to missing/ incomplete data. The report then recommends a phased approach to estimating the cost of mental health: Phase I describes in detail the data sources and methods to estimate public, direct health care costs associated with general and psychiatric MH-related hospitalizations and emergency room visits and non-hospital-based interventions (i.e., physician costs, pharmaceutical costs, community MH services). Phase II describes methods for estimating social and income support payments and indirect costs. Finally, Phase III describes data sources and methods for estimating private health and lost productivity costs.
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Rodriguez, Dirk, and Cameron Williams. Channel Islands National Park: Vegetation classification and mapping project report. National Park Service, 2025. https://doi.org/10.36967/2311434.

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In 2012, Channel Islands National Park (CHIS), with support and funding from the National Park Service’s (NPS) National Vegetation Mapping Inventory (VMI) Program, initiated new vegetation classifications and maps for four northern Channel Islands—Anacapa Island (ANI), Santa Rosa Island (SRI), Santa Cruz Island (SCI), and San Miguel Island (SMI). The project was conducted in two distinct phases. Phase 1 consisted of a mapping and classification effort for ANI, SRI, and SMI. Phase 2 mapped and classified the vegetation for SCI alone. Initial site visits and reconnaissance were conducted jointly by AIS and NPS, followed by NPS-led field data collection efforts. Data collection for the photo interpretation and for the basis of the vegetation classification continued for more than two years, resulting in the completion of over 1,600 field plots and rapid field assessments. For both Phases 1 and 2, map polygons were delineated from photo interpretation of 2012 and 2017 (respectively) aerial color imagery (six-inch resolution) using heads-up digitizing. In total, Phase 1 generated 13,767 polygons that were delineated across 84 different mapping units and Phase 2 generated 13,901 polygons that were delineated across 52 different mapping units. Once draft maps were completed, accuracy assessments were completed to ensure polygons were mapped accurately. The accuracy assessment analysis revealed some discrepancies; however, further review yielded no change to the original field identifications. For Phases 1 and 2 combined, analysis of the field data resulted in 58 plant alliances and 114 associations. SRI supported the highest number of vegetation types despite being the second largest Channel Island, whereas the largest island, SCI, ranked second. However, SCI had the most shrub-dominated vegetation types, whereas SRI had the most herb-dominated types. Six alliances/associations were shared among all four islands, 17 were shared by three islands, 39 were shared by two islands, and another 39 were unique to individual islands.
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Neuert, Mark, and Smitha Koduru. PR-244-173856-R01 In-line Inspection Crack Tool Reliability and Performance Evaluation. Pipeline Research Council International, Inc. (PRCI), 2019. http://dx.doi.org/10.55274/r0011599.

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The ability for operators to make operational and maintenance decisions based on in-line inspection (ILI) data depends on the performance of ILI tools with respect to sizing and detection of crack and stress corrosion cracking (SCC) features. A series of previous Pipeline Research Council International, Inc. (PRCI) projects created a database of ILI tool and pipe excavation data that can be used to evaluate the detection and sizing capabilities of ultrasonic (UT) (NDE-4-E Phase 1, PR-244-133731) and electromagnetic acoustic (EMAT) (NDE-4-E Phase 2, PR-244-153719) ILI technologies. This current project, NDE-4-7 (PR-244-173856), was carried out by C-FER Technologies (1999) Inc. (C-FER) for PRCI. It is Phase 3 of an ongoing industry-wide effort to understand and characterize ILI tool performance. In addition to adding a new data set to the database developed in Phases 1 and 2, estimates of ILI tool performance with respect to rate of detection (ROD), probability of identification (POI), false discovery rate (FDR), and sizing accuracy (SA) were calculated. Two further analyses were performed, namely an investigation of the effect of crack profile data on tool performance and burst pressure estimation, and an evaluation of the reduction in sizing uncertainty attained through multiple measurements of crack features. This document has a related webinar.
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Clausen, Jay, Christopher Felt, Michael Musty, et al. Modernizing environmental signature physics for target detection—Phase 3. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/43442.

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The present effort (Phase 3) builds on our previously published prior efforts (Phases 1 and 2), which examined methods of determining the probability of detection and false alarm rates using thermal infrared for buried object detection. Environmental phenomenological effects are often represented in weather forecasts in a relatively coarse, hourly resolution, which introduces concerns such as exclusion or misrepresentation of ephemera or lags in timing when using this data as an input for the Army’s Tactical Assault Kit software system. Additionally, the direct application of observed temperature data with weather model data may not be the best approach because metadata associated with the observations are not included. As a result, there is a need to explore mathematical methods such as Bayesian statistics to incorporate observations into models. To better address this concern, the initial analysis in Phase 2 data is expanded in this report to include (1) multivariate analyses for detecting objects in soil, (2) a moving box analysis of object visibility with alternative methods for converting FLIR radiance values to thermal temperature values, (3) a calibrated thermal model of soil temperature using thermal IR imagery, and (4) a simple classifier method for automating buried object detection.
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Nestleroth, Bruce, and Michael Rosenfeld. PR-218-173859-R01 ILI Crack Reliability Performance Evaluation and Integrity Management. Pipeline Research Council International, Inc. (PRCI), 2018. http://dx.doi.org/10.55274/r0011543.

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This work compiled and statistically analyzed results from two types of ultrasonic in-line inspection (ILI) tools designed to detect axial cracks. Phase 1 of NDE-4E provided a robust series of statistical results related to liquid coupled ultrasonic crack detect (UTCD) ILI performance. In a follow-on project, additional data collection in Phase 2 provided a similar overview of electromagnetic acoustic transducer (EMAT) tool performance. This complementary work communicates how the tech-nical results from NDE-4E Phases 1 and 2 can be used by pipeline operators as part of an opera-tor's robust integrity management program for cracks. This report demonstrates approaches to integrate the technical results from NDE-4E into integrity management frameworks to enhance the technology transfer of the results of several years of industry data collection. It also com-municates how these technical results can be used by PRCI member companies to improve program effectiveness, efficiency, and compliance with regulations and recommended practices.
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