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Power system reliability evaluation using fuzzy logic and neural networks

DSpace at IIT Bombay

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Title Power system reliability evaluation using fuzzy logic and neural networks
 
Creator KHAPARDE, SA
BHATTACHARYYA, K
 
Subject reliability evaluation
fuzzy logic
neural networks
 
Description Problems related to Power System Reliability calculations are very complex since it involves modeling the stochastic nature of the power system. Till now most of the reliability calculations were performed using a probalilistic model which aims at foreseeing only the average outage performance of a group of units during a long period of time [2]. Most models permit only the existance of two states i.e., whether an unit is available or not. Inclusion of additional states increases the complexity of the model. Using modern tools like fuzzy logic and neural networks, it is much more easier to incorporate the stochastic nature of the power system. It is also very convenient to model the power system closer to the actual operating indices rather than to use averaged indices. This paper presents the generator and load model which use fuzzy logic. Further the models are extended to the system with many units which is defined on aggregate basis. Finally, the system reliability is defined in the fuzzified jargon as Linguistic Reserve Capacity States. Artificial Neural Network is used to model the essential parameters of the generating units. The method presented can be easily incorporated into the existing frequency and duration approach for the evaluation of power system reliability. The proposed method has been applied to existing system data and the results are presented and discussed.
 
Publisher C R L PUBLISHING LTD
 
Date 2011-07-19T09:45:56Z
2011-12-26T12:51:08Z
2011-12-27T05:37:33Z
2011-07-19T09:45:56Z
2011-12-26T12:51:08Z
2011-12-27T05:37:33Z
1996
 
Type Article
 
Identifier ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS, 4(4), 197-206
1472-8915
http://dspace.library.iitb.ac.in/xmlui/handle/10054/5253
http://hdl.handle.net/10054/5253
 
Language en