Title :
Rule-expert knowledge-based Petri net approach for distribution system temperature adaptive feeder reconfiguration
Author :
Chuang, Ying-Chun ; Ke, Yu-Lung ; Chen, Chao-Shun ; Chen, Yuan-Lin
Author_Institution :
Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan
Abstract :
This paper presents a novel inference mechanism to determine appropriate switching operations by the rule-expert knowledge-based Petri net (RKPN) approach. A practical distribution system with 26 feeders is specified to reveal the effectiveness of the developed methodology with computer simulations. The proposed inference mechanism can successfully solve feeder overload/fault contingency based on the load variations resulting from temperature rises
Keywords :
Petri nets; expert systems; fault diagnosis; inference mechanisms; power distribution faults; power engineering computing; adaptive feeder reconfiguration; computer simulations; distribution system temperature; inference mechanism; load variations; overload-fault contingency; rule-expert knowledge-based Petri net approach; Adaptive systems; Energy consumption; Inference mechanisms; Management information systems; Power system modeling; Power system restoration; Spinning; Temperature distribution; Temperature sensors; Transformers; Feeder reconfiguration; load balance; load transfer; rule-expert knowledge-based Petri net (RKPN); service restoration; switching operation; temperature sensitivity;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2006.876681
