• DocumentCode
    662422
  • Title

    Optimal distributed power generation for thermal and electrical scheduling in a microgrid

  • Author

    Mingming Liu ; Crisostomi, Emanuele ; Raugi, Marco ; Shorten, Robert

  • Author_Institution
    Hamilton Inst., Nat. Univ. of Ireland, Maynooth, Ireland
  • fYear
    2013
  • fDate
    6-9 Oct. 2013
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper illustrates stochastic distributed algorithms that optimally share the electrical and thermal power generation task among the several Distributed Energy Resources (DERs) within a microgrid. We borrow certain concepts from communication network theory, namely Additive-Increase-Multiplicative-Decrease (AIMD) algorithms, which are known to be convenient in terms of communication requirements and network efficiency. We adapt them to minimise a cost utility function of interest in the framework of smart grids. We then implement the AIMD utility optimisation strategies in a realistic power network simulation in Matlab-OpenDSS environment, and we show the performance of the proposed algorithms in achieving thermal and electrical power balancing1.
  • Keywords
    distributed power generation; smart power grids; thermal power stations; AIMD utility optimisation strategies; DER; Matlab-OpenDSS environment; additive-increase-multiplicative-decrease algorithms; communication network theory; communication requirements; distributed energy resources; electrical power balancing; electrical power generation task; electrical scheduling; microgrid; network efficiency; optimal distributed power generation; realistic power network simulation; smart grids; stochastic distributed algorithms; thermal power balancing; thermal power generation task; thermal scheduling; Cogeneration; Density estimation robust algorithm; Electricity; Microgrids; Optimization; Smart grids;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Smart Grid Technologies Europe (ISGT EUROPE), 2013 4th IEEE/PES
  • Conference_Location
    Lyngby
  • Type

    conf

  • DOI
    10.1109/ISGTEurope.2013.6695307
  • Filename
    6695307