• DocumentCode
    47755
  • Title

    Distributed Energy Trading: The Multiple-Microgrid Case

  • Author

    Gregoratti, David ; Matamoros, Javier

  • Author_Institution
    Centre Tecnol. de Telecomunicacions de Catalunya, Castelldefels, Spain
  • Volume
    62
  • Issue
    4
  • fYear
    2015
  • fDate
    Apr-15
  • Firstpage
    2551
  • Lastpage
    2559
  • Abstract
    In this paper, a distributed convex optimization framework is developed for energy trading between islanded microgrids. More specifically, the problem consists of several islanded microgrids that exchange energy flows by means of an arbitrary topology. Due to scalability issues and in order to safeguard local information on cost functions, a subgradient-based cost minimization algorithm that converges to the optimal solution in a practical number of iterations and with limited communication overhead is proposed. Furthermore, this approach allows for a very intuitive economics interpretation that explains the algorithm iterations in terms of a “supply-demand model” and “market clearing.” Numerical results are given in terms of the convergence rate of the algorithm and the attained costs for different network topologies.
  • Keywords
    distributed power generation; gradient methods; network topology; optimisation; power generation economics; power markets; algorithm iterations; arbitrary topology; communication overhead; convergence rate; cost functions; distributed convex optimization framework; distributed energy trading; energy flows; islanded microgrids; market clearing; multiple-microgrid case; network topologies; subgradient-based cost minimization algorithm; supply-demand model; Cost function; Generators; Microgrids; Minimization; Production; Transportation; Vectors; Distributed convex optimization; energy trading; smart grid;
  • fLanguage
    English
  • Journal_Title
    Industrial Electronics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0046
  • Type

    jour

  • DOI
    10.1109/TIE.2014.2352592
  • Filename
    6884821