Name
Title | ||
|---|---|---|
Disturbances Classification Based on a Model Order Selection Method for Power Quality Monitoring. |
Abstract | ||
|---|---|---|
In this paper, a new technique for power quality disturbance classification is proposed. It focuses on voltage sags and swells that are first preclassified into four classes that depend on the number of nonzero symmetrical components and can contain different types of sag and swell. Using the estimated symmetrical component values, we can afterward classify the corresponding sag or swell signature... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TIE.2017.2711565 | IEEE Transactions on Industrial Electronics |
Keywords | Field | DocType |
Power quality,Power system stability,Smart grids,Transforms,Neural networks,Support vector machines | Monte Carlo method,Support vector machine,Electric power system,Control engineering,Engineering,Swell,Symmetrical components,Artificial neural network,Statistical classification,Voltage sag | Journal |
Volume | Issue | ISSN |
64 | 12 | 0278-0046 |
Citations | PageRank | References |
1 | 0.40 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zakarya Oubrahim | 1 | 3 | 0.76 |
| V. Choqueuse | 2 | 143 | 9.66 |
| Yassine Amirat | 3 | 32 | 6.64 |
| Mohamed El Hachemi Benbouzid | 4 | 174 | 34.64 |