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DTSTAMP:20191218T223158Z
UID:E63259FE-D4BE-447E-A3C3-EABE84F415EA
DTSTART;TZID=US/Pacific:20191113T180000
DTEND;TZID=US/Pacific:20191113T200000
DESCRIPTION:Synchrophasor measurements offer an unprecedented level of visi
 bility in power distribution infrastructure. These are time-synchronized s
 ingle-phase or three-phase voltage and current phasor measurements on medi
 um and low voltage distribution circuits. However\, data availability alon
 e is not enough to enhance operational intelligence. In this talk\, we mak
 e the case that the analysis of “events” is a key to translate the dat
 a from distribution synchrophasors into useful high-level information. An 
 event in this study is defined rather broadly to include any major change 
 in any component across the distribution feeder. The real data that is use
 d in this study is obtained from a pilot distribution feeder in Riverside\
 , CA. The goal is to enhance situational awareness in distribution grid by
  keeping track of the operation (or misoperation) of various grid equipmen
 t\, assets\, distribution energy resources\, loads\, etc. A combination of
  data-driven machine learning tools and hybrid model-based methodologies a
 re discussed to automatically (and often remotely) detect\, classify\, and
  identify the causes of events and their characteristics in power distribu
 tion systems. Use cases are diverse and may include asset monitoring\, non
 -intrusive load modeling\, analysis of system dynamics\, cybersecurity\, e
 tc.\n\nCo-sponsored by: PELS\n\nSpeaker(s): Dr. Hamed Mohsenian-Rad\, \n\n
 Agenda: \n6:00 - 6:30 pm: Food and Networking\n\n6:30 - 8 pm: Presentation
  and Q/A\n\nRoom: Auditorium\, Bldg: Century Park East\, 8680 Balboa Ave\,
  San Diego\, California\, United States\, 92101
LOCATION:Room: Auditorium\, Bldg: Century Park East\, 8680 Balboa Ave\, San
  Diego\, California\, United States\, 92101
ORGANIZER:fraddatz@sdge.com
SEQUENCE:2
SUMMARY:IEEE PES & PELS Chapter Meeting: Data-Driven Analysis of Events in 
 Distribution Synchrophasors
URL;VALUE=URI:https://events.vtools.ieee.org/m/208731
X-ALT-DESC:Description: <br /><p>Synchrophasor measurements offer an unprec
 edented level of visibility in power distribution infrastructure. These ar
 e time-synchronized single-phase or three-phase voltage and current phasor
  measurements on medium and low voltage distribution circuits. However\, d
 ata availability alone is not enough to enhance operational intelligence. 
 In this talk\, we make the case that the analysis of &ldquo\;events&rdquo\
 ; is a key to translate the data from distribution synchrophasors into use
 ful high-level information. An event in this study is defined rather broad
 ly to include any major change in any component across the distribution fe
 eder. The real data that is used in this study is obtained from a pilot di
 stribution feeder in Riverside\, CA. The goal is to enhance situational aw
 areness in distribution grid by keeping track of the operation (or misoper
 ation) of various grid equipment\, assets\, distribution energy resources\
 , loads\, etc. A combination of data-driven machine learning tools and hyb
 rid model-based methodologies are discussed to automatically (and often re
 motely) detect\, classify\, and identify the causes of events and their ch
 aracteristics in power distribution systems. Use cases are diverse and may
  include asset monitoring\, non-intrusive load modeling\, analysis of syst
 em dynamics\, cybersecurity\, etc.</p><br /><br />Agenda: <br /><p style="
 font-weight: 400\;">6:00 - 6:30 pm: Food and Networking</p>\n<p><span styl
 e="font-weight: 400\;">6:30 - 8 pm: Presentation and Q/A</span></p>
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