Power System Transient Frequency Estimation Based on Random Forest




Gudodagi, Nikhita Kadesh

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The research is concentrated on "Power Systems Transient Frequency Estimation Based on Random Forest Classifier". Transient Frequency is a sudden change or abrupt change, within the small duration of the time. A well-known Great Blackout of 2011 in California incident where transient frequency analysis could have been an important study which would prevent the crisis and the blackout event. Transient frequency and Transient events serve as an important aspect for grid operators who can get warning of such events in the early stages from which they can inform their neighborhood utilities or facilities for the crisis prevention and to take the necessary steps.Grid Stability at 60Hz means the proper operation, proper distribution, prevention of blackout, prevention or managing of overload. If any Fluctuation occurs in the frequency from 60 Hz, it means the system is unsafe and one must disconnect the system in order to be safe which can mainly lead to the power crisis. This Research of study utilizes a machine learning algorithm Random Forest Classifier that boosts up the transient frequency estimation. The initial step involves Generating the signals, applying the threshold-detection method, detecting the transient events, and performing the transient frequency analysis. This will contribute to Signal Processing, Fault Diagnosis, identification of unexpected events, outlier detection, ease the future grid crises, modernization of grid.



Transient frequency, Random Forest Classifier



Electrical and Computer Engineering