Czasopismo
2012
|
R. 88, nr 7a
|
99-102
Tytuł artykułu
Autorzy
Wybrane pełne teksty z tego czasopisma
Warianty tytułu
Diagnostyka sieci energetycznych przy użyciu rozmytych sieci Petriego
Języki publikacji
Abstrakty
A rapid and correct fault diagnosis is crucial for power system network. As the complexity of power system increases, fault diagnosis becomes very difficult task in the limited short time. This situation has made it necessary to develop intelligent systems to support operators in their decision making process. The paper mainly investigates fault diagnosis of power system by using Fuzzy Petri Nets (FPN) technology. FPN is used for accurately fault diagnosis in power system when some incomplete and uncertain alarm information of protective relays. It is shown from several cases that the faulted system elements can be diagnosed correctly by use of these models. By suggested method, it is possible to decline diagnosis time according to traditional methods. Finally, the suggested method can easily be adapted to different power system network. It is practicable an impressive for fault diagnosis in power system.
W artykule opisano metodę diagnostyki sieci energetycznej przy wykorzystaniu technologii rozmytych sieci Petriego FPN. Pokazano na kilku przykładach prawidłowe wykrycie błędów systemu przy czasie analizy krótszym niż to oferują systemy tradycyjne.
Czasopismo
Rocznik
Tom
Strony
99-102
Opis fizyczny
Bibliogr. 17 poz., schem.
Twórcy
autor
autor
- Turkish Electricity Transmission Company, Maltepe Mah., Orhangazi street, No: 74, PK: 54127, Sakarya / TURKEY, nihatpamuk@gmail.com.tr
Bibliografia
- [1] Yann-Chang Huang, Fault Section Estimation in Power Systems Using a Novel Decision Support System, IEEE Transactions Power Systems, Vol. 17, No. 2, (2002), 439-444
- [2] Jing S., Shi-Yin Q., Yong-Hua S., Modelling of Power System Based on Timed DPN, Proceedings of the IEEE Conference on Computers Communications Control and Power Engineering, 3 (2002), 28-31
- [3] Hong-Chan Chin, Fault Section Diagnosis of Power System Using Fuzzy Logic, IEEE Transactions Power System, Vol. 18, No. 1, (2003), 245-250
- [4] Pamuk N., Uyaroğlu Y., The Analysis of Electrical and Mechanical Faults in Power Transformers by Fuzzy Expert System, Scientific Research and Essays, 5 (2010), No. 24, 4018–4027
- [5] Sang-Won M., Jin-Man S., Jong-Keun P., Kwang-Ho K., Adaptive Fault Section Estimation Using Matrix Representation with Fuzzy Relations, IEEE Transactions Power Systems, Vol. 19, No. 2, (2004), 842-848
- [6] Pamuk N., Uyaroğlu Y., Comparison the 154 and 380 kV Transmission System Network of Northwest Anatolia by Making Power Flow Emulation with Constraint Analysis in Turkey, Scientific Research and Essays, 6 (2011), No. 2, 469–478
- [7] Chen-Fu C., Shi-Lin C., Yih-Shin L., Using Bayesian Network for Fault Location on Distribution Feeder, IEEE Transactions Power Delivery, 17 (2002), No. 3, 785-793
- [8] Calderaro V., Galdi V., Piccolo A., Siano P., DG and Protection Systems in Distribution Network: Failure Monitoring System Based on Petri Nets, Proc. of IREP Symposium, (2007)
- [9] Murata T., Petri Nets: Properties Analysis and Applications, Proceedings of the IEEE, 77 (1989), 540-581
- [10]Jiang C. J., Petri Net Theory and its Applications, Higher Education Press, (2003), 221-223
- [11] Haas P. J., Stochastic Petri Nets, Springer, (2002), 178-179
- [12] Jiroveanu G., Boel R. K., Petri Nets Model Based Fault Section Detection and Diagnosis in Electrical Power Networks, Proc. of 6th International Power Engineering Conference, Singapore (2003)
- [13] Peterson J. L., Petri Net Theory and the Modelling of Systems, N.J.: Prentice-Hall Inc., (1981), 171-175
- [14]Ahson S. I., Petri Nets Model of Fuzzy Neural Networks, IEEE Transaction on Systems Man and Cybernetic, Vol. 25, No. 6, (1995)
- [15] Jing S., Shi-Yin Q., Yong-Hua S., Fault Diagnosis of Electric Power Systems Based on Fuzzy Petri Nets, IEEE Transactions Power Systems, Vol. 19, No. 4, (2004), 2053-2059
- [16] Zidani F., Diallo D., El Hachemi Benbouzid M., Nait-Said R., A Fuzzy Based Approach for the Diagnosis of Fault Modes in a Voltage-Fed PWM Inverter Induction Motor Drive, IEEE Transactions Industrial Electronics, Vol. 55, No. 2, (2008), 586-593
- [17] Lee H. J., Park D. Y., Ahn B. S., Park Y. M., Park J. K., Venkata S. S., A Fuzzy Expert System for the Integrated Fault Diagnosis, IEEE Transactions Power Delivery, 15 (2000), No. 2, 833-838
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.baztech-article-BPOH-0065-0021