摘要：This paper presents an intelligent protection mechanism for series compensated power network.
It principally focuses on identifying and locating the fault events in the network by applying
transient signal processing and intelligent computing technique. It involves realization of prime
characteristic features from the 3-phase post-fault current signal using discrete wavelet
transform decomposition. The realized feature sets (i.e. the entropy of DWT coefficients) are
utilized as the input data set to the designed classifier and distance appraisal model. The
designed classifier and distance estimator model predicts the type of events and its actuating
point in the network as their final output. The probabilistic neural network technique based
classifier model has been employed in present work for classifying the shunt abnormality events
in the compensated power network. For tracing the location of shunt fault in the network, a
cascaded-forward network model has been utilized. Various test cases with varying network
operating conditions have been performed on two different simulated test networks in MATLAB
for evaluating the competency and feasibility of the proposed intelligent protection scheme. The
results enlisted after different considered fault scenario, have vindicated the applicability and
strength of the proposed intelligent protection mechanism for ascertaining the class and location
of actuation of fault events in a compensated power network.
