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Vahid Rashtchi

Vahid Rashtchi; Ali. Chavoshi
Using Genetic Algorithm to Optimize the Weighting Parameters of Extension Theory for Islanding Detection in Photovoltaic Systems
Abstract


Identification of islanding situation is one of the most important protection concerns in both traditional and smart grids. In This paper,“extension theory” has been used for detection of islanding phenomenon in photovoltaic systems.Using extension theory would involve defining weighting parameters,in order to optimize the performance of mentionedtheory. Determination of weighting parameters with trial and error method would cause inaccuracy in outcome of extension theory. This paper proposes real coded genetic algorithm (RCGA) in order to optimize the weighting parameters which makes the extension theory more accurate for detection of islanding operation. The results show the effectiveness of RCGA algorithm in islanding detection with optimizing the weighting parameters.

 

 

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