Big data in power systems: a statistical approach on synchrophasor application

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.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Kirihara, Kenta

Contributors dc:contributor

• Sauer, Peter W.

• Synchrophasor
• Phasor Measurement Units (PMU)
• big data
• statistics

Statement dc:rights

• Copyright 2015 Kenta Kirihara

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/87999

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/87999