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7 results for “PMU”
PMU measurements altered by wireless communication such as 3G, 4G, 5G
<p><span>Dataset which shows the effect of three types of wireless communication (e.g., 3G, 4G, and 5G, respectively) on data integrity of two real Phasor Measurement Unit (PMU) measurements which are sent to a virtual Phasor Data Concentrator (vPDC) for timestamp synchronization function. Each file contains the values of the two real PMUs installed at each end of a high voltage (HV) transmission line located in a transmission power grid in South Europe. The datasets were collected using an advanced Power-Hardware In the Loop (P-HIL) setup, including in the communication loop between the PMUs and the vPDC a hardware network emulator. The later had the role to realistically emulate the macroscopic behavior of the communication delays and packet data loss of the three wireless communication networks. The delays and data packet loss were imposed only at one of the two PMUs (PMU Lab1) considering a power grid system running in balanced operation conditions. Therefore, only phase A was recorded in the data, and the reason why the current values from phase B and phase C are almost zero. </span></p>
Data Set for Publication "Traceable Characterization of Low Power Voltage Instrument Transformers for PQ and PMU Applications"
<p>This is dataset for paper published in CPEM2020 Conference Proceedings:</p> <p>Crotti G., Delle Femine A., Gallo D., Giordano D., Landi C., Letizia P.,S., Luiso M., "Traceable Characterization of Low Power Voltage Instrument Transformers for PQ and PMU Applications".</p> <p>https://doi.org/10.5281/zenodo.4153819</p> <p>Excel file provides data for Figure 2 and following evaluation</p> <p> </p>
Dataset of PMU calibrator calibration.
<p>Calibration data for calibration of Phasor Measurement Unit calibrator. Data includes GNU Octave script to process and display results.</p> <p>The calibration method relies on the properties of a two channel digitizer with a time base common to<br>both ADCs. Because of the common time base, time errors of samples acquired by first channel are almost the same as the time errors of the samples acquired by second channel. The first channel is used to calibrate the time base and the second channel is used to sample the synchrophasor waveform.<br> </p> <p>Data are part of paper published in 25th IMEKO TC4 International Symposium, 23rd International Workshop on ADC and DAC Modelling and Testing, IMEKO TC-4 2020, Brescia, Italy / September 12-14, 2022.</p> <p>Title: Simple method for calibration of PMU calibrators<br>Authors: Martin Šíra and Stanislav Mašláň<br>Contact: Czech Metrology Institute, Okružní 31, 638 00 Brno, msira@cmi.cz<br> </p> <p>Part of project Quantum traceability for AC power standards, QuantumPower, Project Number: 19RPT01. This project (19RPT01) has received funding from the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme.</p> <p>https://www.euramet.org/research-innovation/search-research-projects/details/project/quantum-traceability-for-ac-power-standards/?L=0&tx_eurametctcp_project%5Baction%5D=show&tx_eurametctcp_project%5Bcontroller%5D=Project&cHash=05c245c325fe8dcb6a358fe6e192e199</p>
Data set from 'Sequential Feature Selection for Power System Event Classification Utilizing Wide-Area PMU Data'
<p>The increasing penetration of intermittent, nonsynchronous<br> generation has led to a reduction in total power<br> system inertia. Low inertia systems are more sensitive to sudden<br> changes, and more susceptible to secondary issues that can result<br> in large scale events. Due to the short time frames involved,<br> automatic methods for power system event detection and diagnosis<br> are required. Wide-area monitoring systems can provide<br> the data required to detect and diagnose events; however due to<br> the increasing quantity of data it is next to impossible for power<br> system operators to manually process raw data. The important<br> information is required to be extracted and presented to system<br> operators for real/near-time decision making and control. This<br> paper demonstrates an approach for the wide-area classification<br> of a number of power system events. A mixture of sequential<br> feature selection and linear discriminant analysis is adopted<br> to reduce the dimensionality of PMU data. Successful event<br> classification is obtained by employing quadratic discriminant<br> analysis on wide-area synchronized frequency, phase angle and<br> voltage measurements. The reliability of the proposed method is<br> evaluated using simulated case studies and benchmarked against<br> other classification methods.</p>
Data from: Transmission line data of different fault instances retrieved through Phasor Measurement Unit (PMU)
<p>This study presents a dataset comprising time series data pertaining to different electrical grid scenarios, encompassing both fault-free instances and occurrences of short circuits. The dataset was meticulously created by simulating various fault scenarios using the ePMU DSA tools and Matlab Simulink. To capture these scenarios, a Phasor Measurement Unit (PMU) was deployed on a transmission line simulation model. Given the impracticality and potential risks associated with generating actual faults in a real power grid, this approach of simulating faulty scenarios through advanced tools has proven to be a reliable and effective methodology in the field of electrical grid studies. The resulting dataset offers valuable insights into power grid behavior during both normal and faulted conditions, thereby serving as a valuable resource for researchers and practitioners in the domain of power systems and fault analysis.</p>
Data from: Transmission line data of different fault instances retrieved through Phasor Measurement Unit (PMU)
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Comparing the Reliability of Expressed Prostatic Secretion (EPS) and Post Massage Urine (PMU) for the Prediction of Prostate Cancer Biopsy Outcome
ClinicalTrials.gov study NCT01441687. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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