The technology of power electronics is used increasingly during recent
years, and the electronic power facilities are used more and more in the power system. The non-linear electronic loads produce heavy harmonic currents and could significantly degrade the power quality. Nonlinear loads, including the un-interruptible power supply, motor control and converter, etc, are important equipment in a modern factory, however, these nonlinear loads could lead to power facility malfunction and capacitor damage. The harmonics would eventually cause severe unexpected capital loss.
Power quality has become an important study. This thesis proposes the probabilistic neural network (PNN) for power harmonics detection from distorted waves. Originally, Fourier transform is often used to analyze distorted waves in frequency spectrum, and low-pass filter is used to eliminate the fundamental component where characteristic harmonics can be detected. The complicated process is difficult to operate in real time. PNN based processing model with physical harmonic data is used to simplify the process. Computer simulation will show a simplified model and shorter processing time for harmonic detection in the active filter.
The Intranet based distributed characteristic harmonic monitoring system.LabVIEW language was used to develop the Human-Machine Interface(HMI) , and DataSocket tool was used to share the information on net.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0621105-193417 |
| Date | 21 June 2005 |
| Creators | Lin, Da-Cheng |
| Contributors | Shi-Jaw Chen, Fu-Sheng Cheng, Whei-Min Lin, Ta-Peng Tsao |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0621105-193417 |
| Rights | not_available, Copyright information available at source archive |
Page generated in 0.0015 seconds