BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT DTSTART:20230312T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20231105T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20230918T013648Z UID:AEA3C5EA-BF30-4482-86B0-51614D9138D4 DTSTART;TZID=America/New_York:20230911T120000 DTEND;TZID=America/New_York:20230911T130000 DESCRIPTION:IEEE PES - Schenectady Chapter is excited to host a virtual web inar/Distinguished Lecture on the topic of "Advanced Prediction Techniques Applied to Smart Grids". This technical presentation will also offer one (1) continuing education credits (PDH). The PES chapter would like to invi te you to participate and learn from a well know power system modeling res earcher and expert.\n\nSpeaker: Prof. C.Y. Chung form The Hong Kong Polyte chnic University.\n\nCost:\n\n- $10 for IEEE Members (Includes 1 PDH credi t)\n- $15 for Non-IEEE Members (Includes 1 PDH credit)\n- Free for General Admission (No PDH credit)\n- Free for Student and Graduate Student Member s (No PDH credit)\n\n(All payments must be received by August 23\, 2023).\ n\nTime: Thursday\, August 24\, 2023 at 12 PM\, EDT\n\nReserve your seat b y clicking on the below Register Now Tab.\n\nAbstract:\nThe power system i ndustry is shifting towards a new digitalization era to better manage risk within volatile energy commodities\, increase customer engagement\, and e nhance efficiency via grid optimization. Data analytics play a vital role in this transformation and\, as such\, different measurement architectures have been used and implemented to facilitate data capturing process and s upervisory control at the generation\, transmission\, and distribution lev els. This seminar will briefly review the recent outcomes of some smart gr id challenges addressed by novel prediction techniques. At the generation level\, decomposition techniques have been applied to handle the inherent uncertainty in short-term wind power prediction. At the transmission level \, dynamic thermal line rating prediction has been studied as a viable sol ution to reduce congestion and utilize the actual capacity of the line. Co nsidering the high inclusion of phasor measurement units at the transmissi on level\, cutting-edge methods have been proposed to address stability st atus prediction of the grid following a contingency. Finally\, at the dist ribution level\, real-life data obtained from advanced metering infrastruc ture have been used for load prediction and customer segmentation.\n\nSpea ker(s): C.Y. Chung\, \n\nVirtual: https://events.vtools.ieee.org/m/368859 LOCATION:Virtual: https://events.vtools.ieee.org/m/368859 ORGANIZER:alkeshkumar.patel@siemens.com SEQUENCE:52 SUMMARY:Advanced Prediction Techniques Applied to Smart Grids URL;VALUE=URI:https://events.vtools.ieee.org/m/368859 X-ALT-DESC:Description: <br /><p>IEEE PES - Schenectady Chapter is excited to host a virtual webinar/Distinguished Lecture on the topic of "<strong>A dvanced Prediction Techniques Applied to Smart Grids</strong>". This techn ical presentation will also offer one (1) continuing education credits (PD H).&nbsp\; The PES chapter would like to invite you to participate and lea rn from a well know power system modeling researcher and expert.</p>\n<p>< u>Speaker:</u> Prof. C.Y. Chung form The Hong Kong Polytechnic University. </p>\n<p><u>Cost:&nbsp\; </u></p>\n<ul>\n<li>$10 for IEEE Members (Include s 1 PDH credit)</li>\n<li>$15 for Non-IEEE Members (Includes 1 PDH credit) </li>\n<li>Free for General Admission (No PDH credit)</li>\n<li>Free for S tudent and Graduate Student Members (No PDH credit)</li>\n</ul>\n<p>(All p ayments must be received by August 23\, 2023).</p>\n<p>Time:&nbsp\;<strong >Thursday\, August 24\, 2023 at 12 PM\, EDT</strong></p>\n<p>Reserve your seat by clicking on the below&nbsp\;<span style="background-color: #e67e23 \; color: #ecf0f1\;"><strong>Register Now</strong></span>&nbsp\;Tab.</p>\n <p><span style="text-decoration: underline\;"><strong>Abstract:</strong></ span><br />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.<br /><br /></p> END:VEVENT END:VCALENDAR