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DTSTART;TZID=America/Los_Angeles:20221110T140000
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DESCRIPTION:IEEE PES Foothill Section Seminar\n\nThursday\, November 10 | 1
 6:00 – 17:00 PM (CDT)\n\n14:00 – 15:00 PM (PST)\n\nZoom Meeting Link: 
 https://ucr.zoom.us/j/97226988824\n\nMeeting ID: 972 2698 8824\n\nInsight 
 to Action - Grid Analytics Journey\n\nAbstract:\n\nExelon&#39;s Infrastructure
  and Safety Analytics team is helping develop analytic insights to support
  Distribution\, Transmission\, Operation optimizations to drive reliabilit
 y\, resiliency\, cost benefits for grid investments and enhancing organiza
 tion safety by moving from lagging to leading indicators. This webinar wil
 l focus on a T&amp;S Advanced Analytics project\, to showcase the importance o
 f investment during project ideation on adoption strategy\, creating actio
 nable insights\, empowering business/ engineers to lead and take active ro
 le in analytic projects\, how to identify change management and external d
 ependencies upfront as part of analytics prioritization.\n\nUtilities have
  been heavily reliant on subject matter knowledge in the last century to d
 rive preventive maintenance (PM) program and schedule PM for a variety of 
 assets. Our engineers are experts in the industry and have leveraged their
  and industry knowledge of asset measurements and inspection results to ma
 nage these programs\, however\, as human beings\, we are limited in terms 
 of considering a variety of factors and assessing the distribution of each
  factor. This is where data driven approaches shine and enables subject ma
 tter experts with checking million to billion combinations to come up with
  the best model to predict future. These models can then be used to supple
 ment engineer knowledge\, and support industry-wide acceptance of a system
 atic approach to transition to condition-based maintenance programs. Lates
 t model was validated against business-as-usual to provide 85% accuracy us
 ing success criteria developed for this project. PECO team is quantifying 
 and confirming the benefits of model output to extract technical and data 
 science success\, including that model can be used in the real world “wh
 at would be do differently”.\n\nMr. Po-Chen Chen\n\nExelon\n\nPo-Chen Ch
 en received his B.Sc. and M.Sc. degrees in electrical engineering from Pol
 ytechnic Institute of New York University\, Brooklyn\, NY\, in 2010 and 20
 12\, respectively. His power system expertise includes distributed generat
 ion\, power system analysis\, power system protection and control\, voltag
 e quality and stability studies\, geographical information system\, and bi
 g data application for distribution system.\n\nPo-Chen Chen is currently a
  data science manager in Exelon&#39;s Infrastructure and Safety Analytics team
 . In his most recent role at Sentient Energy\, he focused on agile product
  development to develop predictive analytics using waveform classification
  for outage detection. At Duke Energy\, as a data scientist lead expert\, 
 his team developed advanced data analytics for load research and rate desi
 gn and developed models for behavioral demand response programs and winter
  peak analysis for energy modeling. At Oncor Electric Delivery\, he helped
  architect HDFS and data lake ecosystems on IBM cloud and developed AI sol
 utions on Spark-Hadoop and GPU platforms for their T&amp;D customers.\n\nMr. C
 hen&#39;s publications include 18 conference proceedings\, 6 journal articles 
 and 1 book chapter. He is also an elite reviewer for more than 16 journals
  and have been recognized by IEEE Transactions societies with 4 exceptiona
 l reviewer awards.\n\nCo-sponsored by: IEEE Power and Energy Society Worki
 ng Group: Data-Driven Modeling\, Monitoring\, and Control for Power Distri
 bution Systems\n\nSpeaker(s): Po-Chen Chen\, \n\nVirtual: https://events.v
 tools.ieee.org/m/329797
LOCATION:Virtual: https://events.vtools.ieee.org/m/329797
ORGANIZER:nyu@ece.ucr.edu
SEQUENCE:4
SUMMARY:IEEE PES Foothill Section Seminar: Insight to Action - Grid Analyti
 cs Journey
URL;VALUE=URI:https://events.vtools.ieee.org/m/329797
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;IEEE PES Foothill Section Semi
 nar&lt;/em&gt;&lt;/strong&gt;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;Thursday\, November 10 | 16:00 &amp;
 ndash\; 17:00 PM (CDT)&lt;/p&gt;\n&lt;p&gt;14:00 &amp;ndash\; 15:00 PM (PST)&lt;/p&gt;\n&lt;p&gt;Zoom 
 Meeting Link: &amp;nbsp\;&lt;a href=&quot;https://ucr.zoom.us/j/97226988824&quot;&gt;https://u
 cr.zoom.us/j/97226988824&lt;/a&gt;&lt;/p&gt;\n&lt;p&gt;Meeting ID: 972 2698 8824&lt;/p&gt;\n&lt;p&gt;&amp;nb
 sp\;&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;Insight to Action - Grid Analytics Journey&lt;/strong&gt;&lt;/
 p&gt;\n&lt;p&gt;&lt;strong&gt;&amp;nbsp\;&lt;/strong&gt;&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;Abstract:&lt;/strong&gt;&lt;/p&gt;\n&lt;p
 &gt;Exelon&#39;s Infrastructure and Safety Analytics team is helping develop anal
 ytic insights to support Distribution\, Transmission\, Operation optimizat
 ions to drive reliability\, resiliency\, cost benefits for grid investment
 s and enhancing organization safety by moving from lagging to leading indi
 cators. This webinar will focus on a T&amp;amp\;S Advanced Analytics project\,
  to showcase the importance of investment during project ideation on adopt
 ion strategy\, creating actionable insights\, empowering business/ enginee
 rs to lead and take active role in analytic projects\, how to identify cha
 nge management and external dependencies upfront as part of analytics prio
 ritization.&lt;/p&gt;\n&lt;p&gt;Utilities have been heavily reliant on subject matter 
 knowledge in the last century to drive preventive maintenance (PM) program
  and schedule PM for a variety of assets. Our engineers are experts in the
  industry and have leveraged their and industry knowledge of asset measure
 ments and inspection results to manage these programs\, however\, as human
  beings\, we are limited in terms of considering a variety of factors and 
 assessing the distribution of each factor. This is where data driven appro
 aches shine and enables subject matter experts with checking million to bi
 llion combinations to come up with the best model to predict future. These
  models can then be used to supplement engineer knowledge\, and support in
 dustry-wide acceptance of a systematic approach to transition to condition
 -based maintenance programs. Latest model was validated against business-a
 s-usual to provide 85% accuracy using success criteria developed for this 
 project. PECO team is quantifying and confirming the benefits of model out
 put to extract technical and data science success\, including that model c
 an be used in the real world &amp;ldquo\;what would be do differently&amp;rdquo\;.
 &lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;&amp;nbsp\;&lt;/strong&gt;&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;&amp;nbsp\;&lt;
 /strong&gt;&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;&amp;nbsp\;&lt;/strong&gt;&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;&amp;nbsp\;&lt;/strong&gt;
 &lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;&amp;nbsp\;&lt;/strong&gt;&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;&amp;nbsp\;&lt;/strong&gt;&lt;/p&gt;\n&lt;p
 &gt;&lt;strong&gt;&amp;nbsp\;&lt;/strong&gt;&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;Mr. Po-Chen Chen&lt;/strong&gt;&lt;/p&gt;\n&lt;
 p&gt;&lt;strong&gt;Exelon &lt;/strong&gt;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;Po-Chen Chen received his B.Sc. 
 and M.Sc. degrees in electrical engineering from Polytechnic Institute of 
 New York University\, Brooklyn\, NY\, in 2010 and 2012\, respectively. His
  power system expertise includes distributed generation\, power system ana
 lysis\, power system protection and control\, voltage quality and stabilit
 y studies\, geographical information system\, and big data application for
  distribution system.&lt;/p&gt;\n&lt;p&gt;Po-Chen Chen is currently a data science man
 ager in Exelon&#39;s Infrastructure and Safety Analytics team. In his most rec
 ent role at Sentient Energy\, he focused on agile product development to d
 evelop predictive analytics using waveform classification for outage detec
 tion. At Duke Energy\, as a data scientist lead expert\, his team develope
 d advanced data analytics for load research and rate design and developed 
 models for behavioral demand response programs and winter peak analysis fo
 r energy modeling. At Oncor Electric Delivery\, he helped architect HDFS a
 nd data lake ecosystems on IBM cloud and developed AI solutions on Spark-H
 adoop and GPU platforms for their T&amp;amp\;D customers.&lt;/p&gt;\n&lt;p&gt;Mr. Chen&#39;s p
 ublications include 18 conference proceedings\, 6 journal articles and 1 b
 ook chapter. He is also an elite reviewer for more than 16 journals and ha
 ve been recognized by IEEE Transactions societies with 4 exceptional revie
 wer awards.&lt;/p&gt;
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