KOHONEN NEURAL NETWORK CLUSTERING FOR VOLTAGE CONTROL IN POWER SYSTEMS.
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The elbow method to determine the optimal number of clusters and k-means as the clustering algorithm shows that courses with high average values are in cluster
To show the effectiveness of the proposed method on the optimal voltage sag monitor placement in power system, the proposed algorithm was implemented and tested on the IEEE 30-bus
Hence, the results obtained for the power loss prediction and minimum voltage prediction, proved that the models that have less input features such as Model III and Model VI will have a
The voltage injected essentially acts as a synchronous ac-voltage source, which is used to vary the parameters such as transmission angle and line impedance, thereby independently
The highlights of the proposed method are as follows: 1 A communication-less method; 2 Uses only the local voltage magnitude measurement for determining the relay operating time; 3
In the straightforward case where the VU at the POE arises only as a result of installation asymmetry, can be es- tablished using the well-known result employing the quanti- ties of
Hence, as a continuation of previous research in ultrasonic sensor characteristics, this paper carries out the application of artificial neural network algorithms that get input in the
