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2019 IEEE 5th International Conference for Convergence in Technology (I2CT) - Decision Rules Based Supervised Machine Learning for Power Quality Application by Shinde, Pravin; Ahmad, Akbar; Munje, Ravindra is a scholarly article available to read on EtoBox.

What is 2019 IEEE 5th International Conference for Convergence in Technology (I2CT) - Decision Rules Based Supervised Machine Learning for Power Quality Application about?

The power grid has to suffer from several power quality issues with the increased penetration of renewable energy resources. These power quality related problems impact both distributor and consumer applications. Actually, there are limited prediction models to identify power quality issues in advance. Furthermore, the traditional methods are practically costly, which makes it challenging to use for prediction and classification of power quality events. The supervised machine learning technique, the subfield of artificial intelligence, explores binary classification and prediction approach, superior learning capabilities and high-speed response. This is an efficient alternative solution in the field of power quality. This paper introduces the linear mathematical decision-based rule to predict/ classify the sag, swell and interruption related power quality problems more precisely. Data collected from Maharashtra State Electricity Distribution Company Ltd. is used as training samples to train the classifier by means of supervisory approach. Applicability of the supervisory learning method to the classification of power quality problems is demonstrated in this paper and it can be cons

Author

Shinde, Pravin; Ahmad, Akbar; Munje, Ravindra

Publisher

IEEE

Published

2019

Language

EN