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DTSTAMP:20230831T095746Z
LOCATION:Sanada I
DTSTART;TZID=Europe/Stockholm:20230628T110000
DTEND;TZID=Europe/Stockholm:20230628T113000
UID:submissions.pasc-conference.org_PASC23_sess156_msa265@linklings.com
SUMMARY:Advanced Computing for Hybrid Energy Systems
DESCRIPTION:Minisymposium\n\nJibonananda Sanyal (National Renewable Energy
  Laboratory)\n\nHybrid Energy Systems sit at the nexus of energy generatio
 n, storage, and end-use. With increasing penetration of renewables in the 
 generation infrastructure, single technology solutions are increasingly un
 able to meet the energy supply consistency and/or grid service needs. Comb
 inations of technologies involving various percentage contributions from s
 ay wind or solar with an appropriate energy storage component are needed t
 o meet the energy demand. There is a significant opportunity to use contro
 l to shape the load profiles, either in anticipation of the extreme, or du
 ring the event to meet the generation challenge to mitigate adverse outcom
 es. Key questions around how can end use devices in residential, commercia
 l, and industrial neighborhoods meet grid resiliency objectives is not wel
 l understood. Advanced computing is poised to play a significant role in e
 nabling the intelligence needed to accomplish the complex energy orchestra
 tion objectives. These computing systems will enact control for end-use de
 vices, particularly around sub-second device interactions and managing tra
 nsients. Computing will also enable optimization at longer time scales of 
 intra-day to seasonal fluctuations. The talk will focus on how hybrid ener
 gy systems that make use of advanced computing will play a major role in d
 elivering in these operating regimes.\n\nDomain: Computer Science, Machine
  Learning, and Applied Mathematics 
\n\nSession Chair: Jibonananda Sanyal 
 (National Renewable Energy Laboratory)
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