Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
In this paper, an algorithm that monitors the power system to detect and classify power quality events in real time is presented. The algorithm is able to detect events caused by waveform distortions and variations of the RMS values of the voltage. Detection of the RMS events is done by comparing the RMS values with certain thresholds, while detection of waveform distortions is made using an algorithm based on multiharmonic leasts-squares fitting.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
543--554
Opis fizyczny
Bibliogr. 25 poz., rys., tab., wykr.
Twórcy
autor
autor
- Faculty of Electrical Engineering, Energetics and Applied Informatics, "Gheorghe Asachi" Technical University of Iaşi, 21-23 Professor Dimitrie Mangeron Blvd, 700050, Iaşi, România, a.ardeleanu@ee.tuiasi.ro
Bibliografia
- [1] Targosz, R., Manson, J. (2007). Pan European LPQI Power Quality Survey. In Proceedings of the 9th International Conference on Electric Power Quality and Utilisation 2007, Barcelona, Spain.
- [2] IEEE Std 1159-1995. (1995). IEEE Recommended Practice for Monitoring Electric Power Quality. The Institute of Electrical and Electronics Engineers, Inc., New York, USA.
- [3] IEC 61000-4-30:2003. (2003). Electromagnetic compatibility (EMC) - Part 4-30: Testing and measurement techniques - Power quality measurement methods. International Electrotechnical Commission, Geneva, Switzerland.
- [4] Bollen, M. H. J., Gu, I. Y. H. (2006). Signal Processing of Power Quality Disturbances, John Wiley & Sons.
- [5] Santoso, S., Powers, E. J., Grady, W. M., Hofmann, P. (1996). Power quality assessment via wavelet transform analysis. IEEE Transactions on Power Delivery, 11(2), 924-930.
- [6] Gaouda, A. M., Salama, M. M. A., Sultan, M. R., Chikhani, A. Y. (1999). Power quality detection and classification using wavelet-multiresolution signal decomposition. IEEE Transactions on Power Delivery, 14(4), 1469-1476.
- [7] Poisson, O., Rioual, P., Meunier, M. (2000). Detection and measurement of power quality disturbances using wavelet transform. IEEE Transactions on Power Delivery, 15(3), 1039-1044.
- [8] Karimi, M., Mokhtari, H., Iravani M. R. (2000). Wavelet based on-line disturbance detection for power quality application. IEEE Transactions on Power Delivery, 15(4), 1212-1220.
- [9] He, H., Starzyk, J. A. (2006). A self-organizing learning array system for power quality classification based on wavelet transform. IEEE Transactions on Power Delivery, 21(1), 286-295.
- [10] Kaewarsa, S., Attakitmongcol, K., Kulworawanichpong, T. (2008). Recognition of power quality events by using multiwavelet-based neural networks. International Journal of Electrical Power & Energy Systems, 30(4), 254-260.
- [11] Uyar, M., Yildirim, S., Gencoglu, M. T. (2008). An effective wavelet-based feature extraction method for classification of power quality disturbance signals. Electric Power Systems Research, 78(10), 1747-1755.
- [12] Artioli, M., Pasini, G., Peretto, L., Sasdelli, R., Filippetti, F. (2004). Low-cost DSP-based equipment for the real-time detection of transients in power systems. IEEE Transactions on Instrumentation and Measurement, 53(4), 933-939.
- [13] Radil, T., Ramos, P. M., Janeiro, F. M., Serra, A. C. (2007). DSP Based Power Quality Analyzer for Detection and Classification of Disturbances in a Single-phase Power System. Metrology and Measurement Systems, 14(4), 483-494.
- [14] Mindykowski, J., Tarasiuk, T. (2010). Development of DSP-based instrumentation for power quality monitoring on ships. Measurement, 43(8), 1012-1020.
- [15] Radil, T., Ramos, P. M., Janeiro, F. M., Serra, A. C. (2008). PQ Monitoring System for Real-Time Detection and Classification of Disturbances in a Single-Phase Power System. IEEE Transactions on Instrumentation and Measurement, 57(8), 1725-1733.
- [16] Radil, T., Janeiro, F. M., Ramos, P. M., Serra, A. C. (2008). An efficient approach to detect and classify power quality disturbances. COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 27(5), 1178-1191.
- [17] Perez, E., Barros, J. (2008). A proposal for on-line detection and classification of voltage events in power systems. IEEE Transactions on Power Delivery, 23(4), 2132-2138.
- [18] Zhu, F.-F., Hu, G.-S., Xie, J. (2005). Classification of power quality disturbances using wavelet and fuzzy support vector machines. Proceedings of the 4th International Conference on Machine Learning and Cybernetics, (7), 3981-3984.
- [19] Gaing, Z.-L. (2004). Wavelet-based neural network for power quality disturbance recognition and classification. IEEE Transactions on Power Delivery, 19(4), 1560-1568.
- [20] Gaouda, A. M., Kanoun, S. H., Salama, M. M. A., Chikhani, A. Y. (2002). Pattern Recognition Applications for Power System Disturbance Classification. IEEE Transactions on Power Delivery, 17(3), 677-683.
- [21] Wang, M., Rowe, G. I., Manishev, A. V. (2004). Classification of power quality events using optimal time-frequency representations, theory and application. IEEE Transactions on Power Delivery, 19(3), 1496-1503.
- [22] Chen, Z., Urwin, P. (2001). Power Quality Detection and Classification Using Digital Filters. 2001 IEEE Porto Power Tech Proceedings, (1), 6.
- [23] Ramos, P. M., Silva, M. F., Martins, R. C., Serra, A. M. C. (2006). Simulation and experimental results of multiharmonic least-squares fitting algorithms applied to periodic signals. IEEE Transactions on Instrumentation and Measurement, 55(2), 646-651.
- [24] IEEE Std 1057-2007 (2008). IEEE Standard for Digitizing Waveform Recorders, The Institute of Electrical and Electronics Engineers, Inc., New York, USA.
- [25] Serra, J. (1982). Image analysis and mathematical morphology. Academic Press, Inc.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSW1-0087-0003
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.