• DocumentCode
    493187
  • Title

    Applying Load Factors to the Mean-Variance Analysis for Fuel Diversification

  • Author

    Ruangpattana, Suriya ; Gotham, Douglas J. ; Muthuraman, Kumar ; Preckel, Paul V. ; Rardin, Ronald L.

  • Author_Institution
    State Utility Forecasting Group, Purdue Univ., West Lafayette, IN
  • fYear
    2008
  • fDate
    25-29 May 2008
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Fuel diversification implies the selection of a mix of generation technologies for long-term electricity generation. The goal is to strike a good balance between reduced costs and reduced risk. The method of analysis that has been advocated and adopted for such studies is the mean-variance portfolio analysis pioneered by Markowitz (1952). However the standard mean-variance methodology, does not account for the ability of various fuels/technologies to adapt to varying loads. Such analysis often provides results that are easily dismissed by regulators and practitioners as unacceptable, since load cycles play critical roles in fuel selection. To account for such issues and still retain the convenience and elegance of the mean-variance approach, we propose a variant of the mean-variance analysis using the decomposition of the load into various types and utilizing the load factors of each load type. We also present examples using real data for the state of Indiana and demonstrate the ability of the model in providing useful insights.
  • Keywords
    electricity supply industry; fuel economy; power generation economics; risk management; Indiana; fuel diversification; fuel selection; long-term electricity generation; mean-variance portfolio analysis; Cost function; Cultural differences; Energy management; Fuels; Helium; Portfolios; Power generation; Regulators; Risk management; Scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Probabilistic Methods Applied to Power Systems, 2008. PMAPS '08. Proceedings of the 10th International Conference on
  • Conference_Location
    Rincon
  • Print_ISBN
    978-1-9343-2521-6
  • Electronic_ISBN
    978-1-9343-2540-7
  • Type

    conf

  • Filename
    4912625