Fault Section Estimation for Power Systems Based on Adaptive Fuzzy Petri Nets

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 th...

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Main Authors: Z.Y. He, J.W. Yang, Q.F. Zeng, T.L. Zang
Format: Article
Language:English
Published: Springer 2014-08-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Online Access:https://www.atlantis-press.com/article/25868518.pdf
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author Z.Y. He
J.W. Yang
Q.F. Zeng
T.L. Zang
author_facet Z.Y. He
J.W. Yang
Q.F. Zeng
T.L. Zang
author_sort Z.Y. He
collection DOAJ
description 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..
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spelling doaj.art-996a00b266d4495897e2dcfb8310325b2022-12-22T01:55:11ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832014-08-017410.1080/18756891.2014.960259Fault Section Estimation for Power Systems Based on Adaptive Fuzzy Petri NetsZ.Y. HeJ.W. YangQ.F. ZengT.L. ZangDue 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..https://www.atlantis-press.com/article/25868518.pdfFault-section estimationPower systemfault AFPN
spellingShingle Z.Y. He
J.W. Yang
Q.F. Zeng
T.L. Zang
Fault Section Estimation for Power Systems Based on Adaptive Fuzzy Petri Nets
International Journal of Computational Intelligence Systems
Fault-section estimation
Power system
fault AFPN
title Fault Section Estimation for Power Systems Based on Adaptive Fuzzy Petri Nets
title_full Fault Section Estimation for Power Systems Based on Adaptive Fuzzy Petri Nets
title_fullStr Fault Section Estimation for Power Systems Based on Adaptive Fuzzy Petri Nets
title_full_unstemmed Fault Section Estimation for Power Systems Based on Adaptive Fuzzy Petri Nets
title_short Fault Section Estimation for Power Systems Based on Adaptive Fuzzy Petri Nets
title_sort fault section estimation for power systems based on adaptive fuzzy petri nets
topic Fault-section estimation
Power system
fault AFPN
url https://www.atlantis-press.com/article/25868518.pdf
work_keys_str_mv AT zyhe faultsectionestimationforpowersystemsbasedonadaptivefuzzypetrinets
AT jwyang faultsectionestimationforpowersystemsbasedonadaptivefuzzypetrinets
AT qfzeng faultsectionestimationforpowersystemsbasedonadaptivefuzzypetrinets
AT tlzang faultsectionestimationforpowersystemsbasedonadaptivefuzzypetrinets