Neuro-Fuzzy Approach for Fault Location and Diagnosis Using Online Learning System

In a power system, faults, dynamic operations, or nonlinear loads often cause various types of power quality disturbances such as voltage sags, voltage swells, switching transients, impulses, notches, flickers, harmonics, etc. On the other hand, the increased use of sensitive electronic circuitry by industrial and residential customers, as well as the progress of utility deregulation and competition has imposed greater demand on the quality of power. Consequently, the studies aimed at detecting and analyzing as well as eliminating or minimizing the effects of power quality disturbances on industrial and customer loads have assumed greater importance. One critical aspect of power quality studies is the ability to perform automatic power quality monitoring and data analysis.

Provided by: JATIT Topic: Big Data Date Added: May 2010 Format: PDF

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