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Title:Big data in power systems: a statistical approach on synchrophasor application
Author(s):Kirihara, Kenta
Advisor(s):Sauer, Peter W.
Department / Program:Electrical & Computer Engineering
Discipline:Electrical & Computer Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):Synchrophasor
Phasor Measurement Units (PMU)
big data
statistics
Abstract:Phasor Measurement Units (PMUs) are regarded as one of the most valuable device on the power system. PMUs, being devices that are found on buses of the power system, are capable of supplying both detailed and broad situational information. The data produced by PMUs, which are synchronized by GPS timing, are referred to as synchrophasor data, and have plethora of information about the power system that has traditionally not been observed. The general trend in the use of synchrophasor data is offline, such as model validation and post-event analysis. This thesis aims to provide a significantly different approach in the synchrophasor usage. Rather than considering synchrophasor data as extra sensor data that allows for enhancement of models, this thesis treats synchrophasor data as a type of big data, and utilizes statistical methods to find solutions and insight to synchrophasor data. The chapters of this thesis start with applying statistical methods to offline usage, and continue to consider statistical methods in real-time application.
Issue Date:2015-07-09
Type:Thesis
URI:http://hdl.handle.net/2142/87999
Rights Information:Copyright 2015 Kenta Kirihara
Date Available in IDEALS:2015-09-29
Date Deposited:August 201


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