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DESCRIPTION:The power system industry is shifting towards a new digitalizat
 ion era to better manage risk within volatile energy commodities\, increas
 e customer engagement\, and enhance efficiency via grid optimization. Data
  analytics play a vital role in this transformation and\, as such\, differ
 ent measurement architectures have been used and implemented to facilitate
  data capturing process and supervisory control at the generation\, transm
 ission\, and distribution levels. This seminar will briefly review the rec
 ent outcomes of some smart grid challenges addressed by novel prediction t
 echniques. At the generation level\, decomposition techniques have been ap
 plied to handle the inherent uncertainty in short-term wind power predicti
 on. At the transmission level\, dynamic thermal line rating prediction has
  been studied as a viable solution to reduce congestion and utilize the ac
 tual capacity of the line. Considering the high inclusion of phasor measur
 ement units at the transmission level\, cutting-edge methods have been pro
 posed to address stability status prediction of the grid following a conti
 ngency. Finally\, at the distribution level\, real-life data obtained from
  advanced metering infrastructure have been used for load prediction and c
 ustomer segmentation.\n\nSpeaker(s): \, Prof. CY Chung\n\nAgenda: \n11am |
  Begin event\, introductions\n11:10am | Presentation: Advanced Prediction 
 Techniques Applied to Smart Grids\n11:50am | Q&A\n12pm | Event ends\n\nVir
 tual: https://events.vtools.ieee.org/m/366046
LOCATION:Virtual: https://events.vtools.ieee.org/m/366046
ORGANIZER:philipmohn@pm.me
SEQUENCE:40
SUMMARY:Smart Grid Series Part 2: Advanced Prediction Techniques 
URL;VALUE=URI:https://events.vtools.ieee.org/m/366046
X-ALT-DESC:Description: <br /><p>The power system industry is shifting towa
 rds a new digitalization era to better manage risk within volatile energy 
 commodities\, increase customer engagement\, and enhance efficiency via gr
 id optimization. Data analytics play a vital role in this transformation a
 nd\, as such\, different measurement architectures have been used and impl
 emented to facilitate data capturing process and supervisory control at th
 e generation\, transmission\, and distribution levels. This seminar will b
 riefly review the recent outcomes of some smart grid challenges addressed 
 by novel prediction techniques. At the generation level\, decomposition te
 chniques have been applied to handle the inherent uncertainty in short-ter
 m wind power prediction. At the transmission level\, dynamic thermal line 
 rating prediction has been studied as a viable solution to reduce congesti
 on and utilize the actual capacity of the line. Considering the high inclu
 sion of phasor measurement units at the transmission level\, cutting-edge 
 methods have been proposed to address stability status prediction of the g
 rid following a contingency. Finally\, at the distribution level\, real-li
 fe data obtained from advanced metering infrastructure have been used for 
 load prediction and customer segmentation.</p><br /><br />Agenda: <br /><p
 ><strong>11am | </strong>Begin event\, introductions<br /><strong>11:10am 
 | </strong>Presentation:&nbsp\; Advanced Prediction Techniques Applied to 
 Smart Grids<br /><strong>11:50am | </strong>Q&amp\;A<br /><strong>12pm | <
 /strong>Event ends</p>
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