• DocumentCode
    666052
  • Title

    Division of the energy market into zones in variable weather conditions using Locational Marginal Prices

  • Author

    Wawrzyniak, Karol ; Orynczak, Grzegorz ; Klos, Mariusz ; Goska, Aneta ; Jakubek, Marcin

  • Author_Institution
    Nat. Centre for Nucl. Res., Swierk Comput. Centre, Otwock-Świerk, Poland
  • fYear
    2013
  • fDate
    10-13 Nov. 2013
  • Firstpage
    2027
  • Lastpage
    2032
  • Abstract
    Adopting a zonal structure of electricity market requires specification of zones´ borders. One of the approaches to identify zones is based on clustering of Locational Marginal Prices (LMP). The purpose of the paper is twofold: (i) we extend the LMP methodology by taking into account variable weather conditions and (ii) we point out some weaknesses of the method and suggest their potential solutions. The offered extension comprises simulations based on the Optimal Power Flow (OPF) algorithm and twofold clustering method. First, LMP are calculated by OPF for each of scenario representing different weather conditions. Second, hierarchical clustering based on Ward´s criterion is used on each realization of the prices separately. Then, another clustering method, i.e. consensus clustering, is used to aggregate the results from all simulations and to find the global division into zones. The offered method of aggregation is not limited only to LMP methodology and is universal.
  • Keywords
    load flow; power markets; pricing; LMP methodology; Ward criterion; clustering method; consensus clustering; electricity market; energy market; hierarchical clustering; locational marginal prices; optimal power flow; two-fold clustering method; variable weather conditions; zonal structure; Clustering algorithms; Generators; Pricing; Wind farms; Wind speed; Power system economics; Wind energy generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE
  • Conference_Location
    Vienna
  • ISSN
    1553-572X
  • Type

    conf

  • DOI
    10.1109/IECON.2013.6699443
  • Filename
    6699443