Fuzzy classification based identification of voltage sag via wavelets
Increasing awareness of power quality issues, deregulation, use of consumer devices sensitive to power system disturbance and possibility of making up some of the inherent design limitations through monitoring based operational strategies have created a need for extensive monitoring of the power sys...
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2023
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my.uniten.dspace-298792023-12-28T16:58:02Z Fuzzy classification based identification of voltage sag via wavelets Mukerjee R.N. Tanggawelu B. Rogers G.J. Soyat S. 7003827066 6504260720 58715114800 57189523130 Computer aided analysis Computer applications Expert systems Fuzzy systems Knowledge based systems Power distribution Power system monitoring Power systems Signal analysis Wavelet transforms Artificial intelligence Computer aided analysis Computer applications Electric power distribution Electric power system measurement Expert systems Fuzzy systems Information science Knowledge based systems Signal analysis Standby power systems Wavelet transforms Characteristic voltages Electric power distribution systems Fuzzy classification Operational strategies Power distributions Power system disturbances Power system operations Zero sequence voltage Monitoring Increasing awareness of power quality issues, deregulation, use of consumer devices sensitive to power system disturbance and possibility of making up some of the inherent design limitations through monitoring based operational strategies have created a need for extensive monitoring of the power system operation. Voltage disturbance is a common phenomenon in electric power distribution system operation. A fuzzy diagnostic procedure is proposed for detecting cause of voltage disturbance, so that appropriate remedial procedures could be initiated during system operation. The method uses indices like PN factor, characteristic voltage, and zero sequence voltage and also proposes an index termed frequency jump index, extracted from zero sequence voltage using wavelets. � 2002 Nanyang Technological University. Final 2023-12-28T08:58:02Z 2023-12-28T08:58:02Z 2002 Conference paper 10.1109/ICONIP.2002.1201920 2-s2.0-67650502928 https://www.scopus.com/inward/record.uri?eid=2-s2.0-67650502928&doi=10.1109%2fICONIP.2002.1201920&partnerID=40&md5=177bd3afde0dab875762787cff03a875 https://irepository.uniten.edu.my/handle/123456789/29879 5 1201920 2381 2385 Institute of Electrical and Electronics Engineers Inc. Scopus |
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Computer aided analysis Computer applications Expert systems Fuzzy systems Knowledge based systems Power distribution Power system monitoring Power systems Signal analysis Wavelet transforms Artificial intelligence Computer aided analysis Computer applications Electric power distribution Electric power system measurement Expert systems Fuzzy systems Information science Knowledge based systems Signal analysis Standby power systems Wavelet transforms Characteristic voltages Electric power distribution systems Fuzzy classification Operational strategies Power distributions Power system disturbances Power system operations Zero sequence voltage Monitoring |
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Computer aided analysis Computer applications Expert systems Fuzzy systems Knowledge based systems Power distribution Power system monitoring Power systems Signal analysis Wavelet transforms Artificial intelligence Computer aided analysis Computer applications Electric power distribution Electric power system measurement Expert systems Fuzzy systems Information science Knowledge based systems Signal analysis Standby power systems Wavelet transforms Characteristic voltages Electric power distribution systems Fuzzy classification Operational strategies Power distributions Power system disturbances Power system operations Zero sequence voltage Monitoring Mukerjee R.N. Tanggawelu B. Rogers G.J. Soyat S. Fuzzy classification based identification of voltage sag via wavelets |
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Increasing awareness of power quality issues, deregulation, use of consumer devices sensitive to power system disturbance and possibility of making up some of the inherent design limitations through monitoring based operational strategies have created a need for extensive monitoring of the power system operation. Voltage disturbance is a common phenomenon in electric power distribution system operation. A fuzzy diagnostic procedure is proposed for detecting cause of voltage disturbance, so that appropriate remedial procedures could be initiated during system operation. The method uses indices like PN factor, characteristic voltage, and zero sequence voltage and also proposes an index termed frequency jump index, extracted from zero sequence voltage using wavelets. � 2002 Nanyang Technological University. |
| author2 |
7003827066 |
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7003827066 Mukerjee R.N. Tanggawelu B. Rogers G.J. Soyat S. |
| format |
Conference paper |
| author |
Mukerjee R.N. Tanggawelu B. Rogers G.J. Soyat S. |
| author_sort |
Mukerjee R.N. |
| title |
Fuzzy classification based identification of voltage sag via wavelets |
| title_short |
Fuzzy classification based identification of voltage sag via wavelets |
| title_full |
Fuzzy classification based identification of voltage sag via wavelets |
| title_fullStr |
Fuzzy classification based identification of voltage sag via wavelets |
| title_full_unstemmed |
Fuzzy classification based identification of voltage sag via wavelets |
| title_sort |
fuzzy classification based identification of voltage sag via wavelets |
| publisher |
Institute of Electrical and Electronics Engineers Inc. |
| publishDate |
2023 |
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1806423966260133888 |
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13.226497 |