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Study on Fault Restoration Strategy of Distribution Systems with Colored Petri Net Model

With load growth of distribution systems, it becomes very complicated for dispatchers to obtain restoration plan for unfaulted but out-of-service areas. In this thesis, a rule-based expert system with a colored Petri net (CPN) inference model is developed. The CPN models of distribution components such as four-way line switches are proposed to derive the proper switching operation plan for service restoration by applying reasoning in the CPN.
After main transformer contingency has been identified and isolated, it is highly possible that the out of service customers can not be restored completely because of the shortage of capacity reserve. The feeders which serve more key customers with higher service priority will have better chance to be selected for restoration. With the system reconfiguration to cover the load change of service zones over a longer period, during the process of switching operation, the maximum load demand of out-of-service area over the restoration time is considered in the CPN. To prevent the over-unbalance tripping of distribution feeders during switching operation process, the maximum tolerable current unbalance between any two phases is also considered in the CPN model. To assure the restoration plan complying with the operation regulation, heuristic rules based on the standard operation procedures of Taipower distribution system are included in the best first search of the CPN.
A Taipower distribution system with 67 feeders is selected for computer simulation in this thesis to demonstrate the effectiveness of the proposed methodology. It is found that the service restoration of distribution systems can be obtained very efficiently by applying the proposed CPN model.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0612103-171222
Date12 June 2003
CreatorsTsai, Hung-Ying
ContributorsChia-Hung Lin, Jaw-Shyang Wu, Chao-Shun Chen
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageCholon
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0612103-171222
Rightsunrestricted, Copyright information available at source archive

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