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- W3106189087 abstract "The inclusion of distributed generation in usual distribution system has several advantages and technical harms. This inclusion has been done for fulfillment of several challenges such as fast growing population, world’s growing economy, improvement of life’s quality, and sustainability of resources. However, with this, several harms have also been seen which are yet to be solved and one such harm is fault detection in distributed generation (DG) system. The existing protecting equipment and fault detecting techniques cannot perform the same as in usual distribution system. This paper deals with a DG system consisting of two wind farms connected to a regular distribution network which is simulated using MATLAB for data collection and on the basis of the data of current and voltage samples various features are extracted. The features are trained and tested using the Neuro-Fuzzy classifier which identifies the type of fault during testing with a error very close to zero having RMSE of 0.031." @default.
- W3106189087 created "2020-11-23" @default.
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- W3106189087 date "2020-11-17" @default.
- W3106189087 modified "2023-09-28" @default.
- W3106189087 title "Detection and Classification of Fault in Distributed Generation System Using Neuro-Fuzzy Technique" @default.
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- W3106189087 doi "https://doi.org/10.1007/978-981-15-8700-9_7" @default.
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