• DocumentCode
    1985566
  • Title

    Geospatial visualization of Smart data for improved network management

  • Author

    Poursharif, Goudarz ; Brint, Andrew ; Holliday, John ; Black, Mary ; Marshall, Mark

  • Author_Institution
    Manage. Sch. & Inf. Sch., Univ. of Sheffield, Sheffield, UK
  • fYear
    2015
  • fDate
    June 29 2015-July 2 2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    As the penetration level of embedded generation in the electricity distribution network rises, network operators´ need for real time and geographically accurate information about the Low Voltage (LV) network increases. Smart meters and network monitors are the main providers of Smart data to the network operators. However, the Smart data need to be presented to the users in meaningful ways, that are helpful, relevant, and accurate. This paper proposes a model that identifies the granularity of data required by network operators and the best ways in which the Smart data need to be visualized in order to enhance network operation applications such as network planning, asset management, and fault management, leading to smarter grid operation.
  • Keywords
    distributed power generation; power distribution planning; power system faults; power system management; smart meters; asset management; data granularity; electricity distribution network; embedded generation; fault management; geospatial visualization; low voltage network; network management; network monitor; network planning; smart data; smart meters; Substations; Data Visualization; Embedded Generation; Smart Data; Smart Grid; Smart Meters;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    PowerTech, 2015 IEEE Eindhoven
  • Conference_Location
    Eindhoven
  • Type

    conf

  • DOI
    10.1109/PTC.2015.7232445
  • Filename
    7232445