With the rapid development of power systems, more and more smart devices are installed in power industries, and each of them is gathering tons of information every day.Due to the data explosion and the difficulty of processing these data, data visualization, a big data technology, has become a trend. With the help of information technology, the visualization of real-time data has been achieved in power industries and there are multiple successful examples such as one-line diagram, load flow dashboard and equipment dashboard.In fault analysis group, digital fault recorders are essential to record and report an event.They are triggered when a fault occurs and corresponding report is generated instantly.However, people seldom utilize the historical data from DFRs to analyze the power quality issues.Therefore, this thesis presents the development of a power quality dashboard by using the collected data from DFRs.Three related power quality analyses have been accomplished in this paper: voltage and current variation, harmonics and unbalance components.Recursive algorithm is applied to compute the phasors and errors; Discrete Fourier Transform is utilized to extract harmonics from the samples; and the symmetric components are calculated by "A"-matrix transformation.The start page for the dashboard is a google map with all the DFR markers, and after double-clicking the marker, the report page will be opened.With the reports, engineers can not only monitor the event but also analyze out the possible causes and characteristics for a fault.For those renewable energy substation, the harmonic contents can be supervised so that the damages and losses can be significantly reduced by identifying the high harmonics.Ultimately, the goal of the dashboard is to achieve warning status and harmonic gradient mapping in the future. / Master of Science
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/81892 |
| Date | 22 January 2018 |
| Creators | Huang, Huiying |
| Contributors | Electrical Engineering, De La Ree, Jaime, Centeno, Virgilio A., Kekatos, Vasileios |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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