Classification of EMI Signatures for Smart Grid

India's Electricity sector faces many problems but chief among them is the consumer level losses which amount to 30% of the total power loss in India. The most modern way to compensate for the energy loss is identified as the deployment of smart grids. Our aim of the project is to provide the s...

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Bibliographic Details
Published in:	2018 International Conference on Communication and Signal Processing (ICCSP) pp. 1106 - 1110
Main Authors:	Prathija, R, Alex, S Sajin, Shanmathi, C, Subramanian, A Ganesh, Gandhiraj, R
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01-04-2018
Subjects:	classifier covariance Electromagnetic interference Fans Feature extraction Hardware K-nearest neighbors Principal component analysis Smart grids support vector machine Support vector machines
Online Access:	Get full text
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Summary:	India's Electricity sector faces many problems but chief among them is the consumer level losses which amount to 30% of the total power loss in India. The most modern way to compensate for the energy loss is identified as the deployment of smart grids. Our aim of the project is to provide the smart grid with a new methodology for appliance identification and also to identify its state of operation. This project is going to upgrade the smart grid with new algorithm that will cross leaps and bounds in non-intrusive load monitoring technique. This technique is used to separate the electric load composition of appliances using single point sensing. This includes capturing interference patterns generated by ON state or OFF state of electrical appliances like fan, light etc. and then extracting features from the captured EMI's dataset and then classifying it as which appliance the particular EMI signature belongs to. This paper shows the process of classification of EMI signatures for Smart Grid.
DOI:	10.1109/ICCSP.2018.8524295