Paper Info
Title
A Contactless Method for Unbalanced Loading Detection in Power Distribution Lines by Magnetic Measurements
Abstract
Reliability of power distribution network is highly desired by end customers. The power utility companies make best efforts to ensure balanced power transfer for single-phase customers. Phase unbalancing is common in congested power distribution systems where a large number of single-phase consumers are served by three-phase transformers. It deteriorates transformer efficiency and results in increased power system losses. As a standard practice, utility providers use portable CTs to periodically measure phase currents to reduce the unbalanced loading of transformers. The approach requires manual intervention and regular inspections. This article proposes a novel noncontact method for the measurement of unbalanced single-phase loading using a single magnetic sensor and processing with a trained neural network (NN). This article employs variation in phase and magnitude of the magnetic field produced by three-phase line conductors to detect and identify the unbalanced lines. The optimal sensing location is determined by using outcomes of coherence between the training and test data. Then, a trained NN uses a pattern recognition algorithm to estimate the unbalanced and the balanced loading. The method is comprehensively tested by numerical simulations and experimentation, which involves various potential configurations of distribution lines (flat, vertical, and delta). The method of estimation of unbalanced loading by magnetic field sensing and pattern recognition method has been experimentally implemented and verified in the laboratory setup. The results provide accurate unbalance phase detection with an error of less than 1%.
Year
DOI
Venue
2020
10.1109/TIM.2020.2983339
IEEE Transactions on Instrumentation and Measurement
Keywords
DocType
Volume
Artificial neural network (ANN),optimal sensor placement,pattern recognition scheme,power distribution lines
Journal
69
Issue
ISSN
Citations 
10
0018-9456
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Shah Zeb Malik100.34
Arsalan Habib Khawaja200.34
Abdul Kashif Janjua300.34
Muhammad Kazim462.11