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DTSTART:20240310T030000
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DTSTART:20231105T010000
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DTSTAMP:20240225T220443Z
UID:9CA3335B-5EF3-4579-BEA9-31C0FE90D557
DTSTART;TZID=America/Los_Angeles:20240222T160000
DTEND;TZID=America/Los_Angeles:20240222T173500
DESCRIPTION:Join us for a session on AI and Microgrids.\n\nVybe Energy&#39;s AI
 -Driven Whole Building Optimization and Control. The flagship product turn
 s your facility into a “smart” building by synergistically managing al
 l of its energy usage\, generation\, and storage under a single master con
 troller. The patented AI-driven software uses machine learning algorithms 
 that allow for dynamic predictive modeling of building load\, on-site ener
 gy production\, and battery charge and discharge to maximize demand reduct
 ion and utility savings while reducing greenhouse gas emissions. It can al
 so generate additional revenue streams from participation in utility progr
 ams and wholesale energy markets\, thereby delivering comprehensive load m
 anagement into the hands of the customer.\n\nCo-sponsored by: IEEE Power a
 nd Energy Society\n\nSpeaker(s): Nisha Thirumurthy\, \n\nAgenda: \n4:00 pm
  PDT IEEE Announcements\n4:02 pm PDT Introduction of Speakers\n4:04 pm PDT
  Presentation\n4:45 pm PDT Q&amp;A\n4:50 pm PDT Speaker Presentations\n\nVirtu
 al: https://events.vtools.ieee.org/m/408144
LOCATION:Virtual: https://events.vtools.ieee.org/m/408144
ORGANIZER:mike.brisbois@ieee.org
SEQUENCE:40
SUMMARY:IEEE Tech Talk AI and Microgrids
URL;VALUE=URI:https://events.vtools.ieee.org/m/408144
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;Join us for a session on AI and Microgrids
 .&lt;/p&gt;\n&lt;p&gt;Vybe Energy&#39;s AI-Driven Whole Building Optimization and Control.
 &amp;nbsp\; The flagship product turns your facility into a &amp;ldquo\;smart&amp;rdqu
 o\; building by synergistically managing all of its energy usage\, generat
 ion\, and storage under a single master controller. The patented AI-driven
  software uses machine learning algorithms that allow for dynamic predicti
 ve modeling of building load\, on-site energy production\, and battery cha
 rge and discharge to maximize demand reduction and utility savings while r
 educing greenhouse gas emissions. It can also generate additional revenue 
 streams from participation in utility programs and wholesale energy market
 s\, thereby delivering comprehensive load management into the hands of the
  customer.&lt;/p&gt;&lt;br /&gt;&lt;br /&gt;Agenda: &lt;br /&gt;&lt;p&gt;4:00 pm PDT IEEE Announcements&lt;
 br /&gt;4:02 pm PDT Introduction of Speakers&lt;br /&gt;4:04 pm PDT Presentation &lt;b
 r /&gt;4:45 pm PDT Q&amp;amp\;A&lt;br /&gt;4:50 pm PDT Speaker Presentations&lt;/p&gt;
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