• DocumentCode
    2052906
  • Title

    High-performance computing for electric grid planning and operations

  • Author

    Epperly, T. ; Edmunds, T. ; Lamont, A. ; Meyers, C. ; Smith, S. ; Yiming Yao ; Drayton, G.

  • Author_Institution
    Lawrence Livermore Nat. Lab., Livermore, CA, USA
  • fYear
    2012
  • fDate
    22-26 July 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    High-performance computing (HPC) is having a profound impact on scientific discovery and engineering in a variety of areas, and researchers are beginning to demonstrate how HPC can impact problems in energy grid planning and operations. Contemporary supercomputers can perform over 1015 floating point operations per second and have more than 1.4 petabytes of memory - roughly 5 orders of magnitude greater than a commodity PC workstation. This level of computing power changes the very nature of problems that can be solved. Researchers at LLNL have used HPC systems to accelerate execution of a renewables planning study, by solving a thousand unit commitment and dispatch problems in parallel; this generated new insights and allowed for a more detailed study than would have been otherwise achievable. Ongoing work at LLNL includes the development and testing of new parallel algorithms for unit commitment problems, including multi-scenario stochastic unit commitment. These algorithms will enable greater grid and time resolution and provide more accurate solutions because of the increase in model fidelity.
  • Keywords
    parallel algorithms; parallel machines; power engineering computing; power generation dispatch; power generation planning; power generation scheduling; power grids; HPC systems; LLNL; commodity PC workstation; contemporary supercomputers; dispatch problem; electric grid operation; electric grid planning; energy grid planning; high-performance computing; multiscenario stochastic unit commitment; parallel algorithms; renewable planning; unit commitment problem; Computational modeling; Educational institutions; Laboratories; Optimization; Planning; Supercomputers; Supercomputers; parallel machines; photovoltaic systems; power generation planning; wind power generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting, 2012 IEEE
  • Conference_Location
    San Diego, CA
  • ISSN
    1944-9925
  • Print_ISBN
    978-1-4673-2727-5
  • Electronic_ISBN
    1944-9925
  • Type

    conf

  • DOI
    10.1109/PESGM.2012.6345086
  • Filename
    6345086