Hybrid Methods for Fast Detection and Characterization of Power Quality Disturbances

2015 ◽  
Vol 26 (5) ◽  
pp. 556-566 ◽  
Author(s):  
S. Upadhyaya ◽  
S. Mohanty ◽  
C. N. Bhende
Keyword(s):  
Power Quality ◽  
Hybrid Methods ◽  
Fast Detection ◽  
Power Quality Disturbances

scholarly journals Proposed Scheme for Characterization of Power Quality Disturbances (Dept.E)

2020 ◽  
Vol 32 (3) ◽  
pp. 17-25
Author(s):  
Akram Ibrahim El-Mitwally ◽  
A. Abdelmageid ◽  
S. Fathy
Keyword(s):  
Power Quality ◽  
Power Quality Disturbances

Development of a platform for analysis and characterization of power quality disturbances

2017 ◽  
Author(s):  
B. Jose A. Tumialan ◽  
S. Luis H. Correa ◽  
Diana Lancheros Cuestas ◽  
F. Carlos A. Correa
Keyword(s):  
Power Quality ◽  
Power Quality Disturbances

scholarly journals Homogeneity-PMU-Based Method for Detection and Classification of Power Quality Disturbances

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 433 ◽  
Author(s):  
Jose Razo-Hernandez ◽  
Martin Valtierra-Rodriguez ◽  
Juan Amezquita-Sanchez ◽  
David Granados-Lieberman ◽  
Jose Gomez-Aguilar ◽  
...  
Keyword(s):  
Power Quality ◽  
Phasor Measurement Unit ◽  
Measurement Unit ◽  
Negative Consequences ◽  
Processing Scheme ◽  
Fast Detection ◽  
The Past ◽  
Power Quality Disturbances ◽  
Computational Resources

Over the past few years, power quality (PQ) monitoring has become of paramount importance for utilities and users since poor PQ generates negative consequences. In monitoring, fast detection and accurate classification of PQ disturbances (PQDs) are desirable features. In this work, a new method to detect and classify PQDs is proposed. The proposal takes advantage of the low computational resources of both a phasor measurement unit (PMU)-based signal processing scheme and the homogeneity approach. To classify the PQDs, if–then–else rules are used. To validate and test the proposal, synthetic and real signals of sags, swells, interruptions, notching, spikes, harmonics, and oscillatory transients are considered. For the generation of real signals, a PQD generator based on a power inverter is used. In the proposed method, the PMU information is directly used to classify sags, swells, and interruptions, whereas the homogeneity index is used to distinguish among the remaining PQDs. Results show that the proposal is an effective and suitable tool for PQ monitoring.

Sign in / Sign up

Export Citation Format

Share Document