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Wu, X., Kumar, V., Ross Quinlan, J., Ghosh, J., Yang, Q., Motoda, H., McLachlan, G.J., Ng, A., Liu, B., Yu, P.S., Zhou, Z.-H., Steinbach, M., Hand, D.J. and Steinberg, D. (2007) Top 10 Algorithms in Data Mining. Knowledge and Information Systems, 14, 1-37.
http://dx.doi.org/10.1007/s10115-007-0114-2
has been cited by the following article:
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TITLE:
Situational Awareness Using DBSCAN in Smart-Grid
AUTHORS:
Ranganath Vallakati, Anupam Mukherjee, Prakash Ranganathan
KEYWORDS:
Clustering, Density Based Clustering (DBSCAN), IEEE Test-Bed, Phasor Measurement Unit, Visualization
JOURNAL NAME:
Smart Grid and Renewable Energy,
Vol.6 No.5,
May
29,
2015
ABSTRACT: Synchrophasors are the state-of-the-art measuring devices that sense various parameters such as
voltage, current, frequency, and other grid parameters with a high sampling rate. This paper presents
an approach to visualize and analyze the smart-grid data generated by synchrophasors using
a visualization tool and density based clustering technique. A MATLAB based circle representation
tool is utilized to visualize the real-time phasor data generated by a smart-grid model that mimics
a synchrophasor. A density based clustering technique is also used to cluster the phasor data with
the aim to detect contingency situations such as bad-data classification, various fault types, deviation
on frequency, voltage or current values for better situational alertness. The paper uses data
from an IEEE fourteen bus system test-bed modeled in MATLAB/SIMULINK to aid system operators
in carrying various predictive analytics, and decisions.