Voltage Variation Signals Source Identification And Diagnosis Method
Power Quality (PQ) problem has become an important issue for generating bad impact to the users nowadays.It is important to detect and identify the source of the PQ problem. This paper presents a voltage variation signals source identification and diagnosis method by determining the average time fr...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
International Journal of Advanced Computer Science and Applications(IJACSA)
2019
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| Online Access: | http://eprints.utem.edu.my/id/eprint/24177/2/VOLTAGE_VARIATION_SIGNALS_SOURCE_IDENTIF.PDF http://eprints.utem.edu.my/id/eprint/24177/ https://thesai.org/Downloads/Volume10No4/Paper_20-Voltage_Variation_Signals_Source_Identification.pdf |
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| Summary: | Power Quality (PQ) problem has become an important issue for generating bad impact to the users nowadays.It is important to detect and identify the source of the PQ
problem. This paper presents a voltage variation signals source identification and diagnosis method by determining the average time frequency representation (TFR) phase power of the impedance. The signals focused in this study are the voltage variation signals, which include voltage sag, swell and interruption. The voltage variation signals from different source location (upstream, downstream as well as up and downstream) according to the IEEE Standard 1159 by using the mathematical models. The signals are first analyzed by using the Spectrograms which act as the feature producing tool. Then, the average power TFR of phase domain of each signal is calculated and tabulated. Finally, the performance of the method is identified by using support vector machine (SVM) and k-nearest neighbor (kNN).The results show that this method is an effective and suitable
technique for identifying the source of voltage variation |
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