Volume 7, Issue 4, August 2014, Pages 605 - 614
Fault Section Estimation for Power Systems Based on Adaptive Fuzzy Petri Nets
- Z.Y. He, J.W. Yang, Q.F. Zeng, T.L. Zang
- Corresponding Author
- Z.Y. He
Available Online 9 January 2017.
- https://doi.org/10.1080/18756891.2014.960259How to use a DOI?
- Fault-section estimation, Power system, fault AFPN
- Due to the advantages of Fuzzy reasoning Petri-nets(FPN)on uncertain and incomplete information processing. It is a promising technique to solve the complex power system fault-section estimation problem. Therefore, we propose a novel estimation method based on Adaptive Fuzzy Petri Nets (AFPN), in this algorithm, the AFPN is used to build a dynamic fault diagnosis fuzzy reasoning model, where the weights in fuzzy reasoning are decided by the incomplete and uncertain alarm information of protective relays and circuit breakers. The validity and feasibility of this method is illustrated by simulation examples. Results show that the fault section can be diagnosed correctly through fuzzy reasoning models for ten cases, and the AFPN not only takes the descriptive advantages of fuzzy Petri net, but also has learning ability as neural network..
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - JOUR AU - Z.Y. He AU - J.W. Yang AU - Q.F. Zeng AU - T.L. Zang PY - 2017 DA - 2017/01 TI - Fault Section Estimation for Power Systems Based on Adaptive Fuzzy Petri Nets JO - International Journal of Computational Intelligence Systems SP - 605 EP - 614 VL - 7 IS - 4 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2014.960259 DO - https://doi.org/10.1080/18756891.2014.960259 ID - He2017 ER -