Abstract
This paper illustrates an improved method of classification of electrical appliances, particularly for domestic loads, to construct load taxonomy on the basis of their signature analysis. Each electrical load is characterized by its own distinct signature and hence load signature analysis is useful in monitoring the health of the equipment, power quality, in determining individual energy usage etc. type of services. On the other hand, load taxonomy classifies these loads in several clusters on the basis of some features extracted from their signatures. In traditional methods of construction of load taxonomy, different signature patterns based on power metrics, V-I trajectories, Eigen vectors, etc. In this proposed method, with the adoption of sample shifting technique the required number of feature extraction is reduced to a lower value to find out various signature patterns than those are required in traditional load taxonomies. Moreover, a better taxonomy, having well separated groups of loads is achieved with lower number of extracted features.
Additional information
Notes on contributors
Rumpa Saha
Rumpa Saha is currently doing PhD from Applied Physics Department of University of Calcutta, West Bengal, India received the B.Tech degree in Electrical Engineering from JIS College of University, West Bengal University of Technology, India in the year 2005. She completed the M.Tech degree in Electrical Engineering from the Applied Physics department of University of Calcutta in the year of 2008. She was working as Assistant Professor at Narula Institute of Technology, Kolkata, West Bengal, India during 2005–2014. During 2014–2016, she worked as an Assistant Professor at Veer Surendra Sai University of Technology, Sambalpur, Odisha, India. Since 2016 to till date, she is working as an Assistant professor in Electrical Engineering department at Aliah University, Kolkata, West Bengal, India. She is a Chartered Engineer. Life Member of IEI. Her fields of interest are power quality analysis based on harmonic pollution, load classification for better distribution management of electrical power.
Jitendra N. Bera
Jitendra Nath Bera is associated with the Department of Applied Physics, University of Calcutta, Kolkata. He has obtained his B.Tech and M.Tech degrees from the University of Calcutta and PhD from Jadavpur University. He has more than 30 research publications in national and international journals. He is a member of IEEE and IET. His research areas include smart grid, power system, electrical machines, control system, wireless communication, and embedded system.
Gautam Sarkar
Gautam Sarkar is associated with the Department of Applied Physics, the University of Calcutta, Kolkata. He has obtained his B.Tech, M.Tech, and PhD degrees from the University of Calcutta. He has more than 70 research publications in national and international journals. He is a Fellow of IETE. His research areas include power system, electrical machines, and control system.