Fault Type Classification in Power Distribution Feeders Utilizing Statistical Functions and Neural Networks

Faculty Engineering Year: 2003
Type of Publication: ZU Hosted Pages:
Authors:
Amal Farouk Abdelgawad Badaawi
Journal: The 38th International Universities Power Engineering Conference, UPEC2003, Aristotle University, Thessaloniki, Greece. UPEC2003, Aristotle University, Thessaloniki, Greec Volume:
Keywords : Fault Type Classification , Power Distribution Feeders    
Abstract:
The present paper discusses a routine that utilizes statistical functions and neural networks to detect and classify different fault types by: Using statistical functions as a signal-processing tool for phase currents. Using many cases of
    
     
 
       

Author Related Publications

  • Amal Farouk Abdelgawad Badaawi, "Fault Location in Power Distribution Transmission Lines Utilizing either Curve Fitting or Neural Networks", Cigre'2005, Egypt, 2005 More
  • Amal Farouk Abdelgawad Badaawi, "Experimental Estimation of the Fault Location for the Transmission Line from One End", PSP 2006, Bled, Slovenia, 2006 More
  • Amal Farouk Abdelgawad Badaawi, "Studying the Impact of Different Lighting Loads on both Harmonics and Power Factor", UPEC2007, University of Brighton, UK, 2007 More
  • Amal Farouk Abdelgawad Badaawi, "Mitigation the Effect of TCSC on the Transmission Lines Protection Devices", UPEC2007, University of Brighton, UK, 2007 More
  • Amal Farouk Abdelgawad Badaawi, "Short-Term Load Forecasting Investigation in Egyptian Electrical Network Using ANNs", UPEC2007, University of Brighton, UK, 2007 More

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