• DocumentCode
    3225226
  • Title

    The micro-grid monitoring software design and development based on Python language

  • Author

    Hao Zhou ; Qiuxuan Wu ; Fengfeng Li ; Weijie Lin

  • Author_Institution
    Hangzhou Dianzi Univ., Hangzhou, China
  • fYear
    2015
  • fDate
    23-25 May 2015
  • Firstpage
    4792
  • Lastpage
    4797
  • Abstract
    The micro-grid monitoring software design and development which based on Python language proposed that application scripting Python language development micro-grid data acquisition system for management and distribution of each distributed power generation system. By using the Python language features, analysis of data structures of distributed generation, combined with the distributed power system designed a micro-grid monitoring software to give a detailed design of the PC software to monitor all electricity generation module. Finally, the experimental runs of the project showed that micro-grid monitoring software powerful, cross-platform suitable, reliable and solve the basic power monitoring requirements of distributed generation system.
  • Keywords
    authoring languages; data acquisition; data structures; distributed power generation; power engineering computing; power grids; power system measurement; PC software; Python language feature; data structure; distributed generation system; distributed power generation system; distributed power system design; electricity generation module; micro-grid monitoring software design; microgrid monitoring software; power monitoring requirement; scripting Python language development microgrid data acquisition system; Data acquisition; Data structures; Distributed power generation; Monitoring; Power systems; Software design; Data Acquisition System; Python; The Distributed Generation System;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2015 27th Chinese
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4799-7016-2
  • Type

    conf

  • DOI
    10.1109/CCDC.2015.7162773
  • Filename
    7162773