• DocumentCode
    54237
  • Title

    A Noniterative Method to Estimate Load Carrying Capability of Generating Units in a Renewable Energy Rich Power Grid

  • Author

    Abdullah, Mohd Ariff ; Muttaqi, Kashem M. ; Agalgaonkar, A.P. ; Sutanto, Danny

  • Author_Institution
    Australian Power Quality & Reliability Centre, Univ. of Wollongong, Wollongong, NSW, Australia
  • Volume
    5
  • Issue
    3
  • fYear
    2014
  • fDate
    Jul-14
  • Firstpage
    854
  • Lastpage
    865
  • Abstract
    It is important to estimate the contribution of renewable generation units in the evaluation of system generation adequacy for power generation planning taking into account the demand and renewable generation correlation and uncertainty. The effective load carrying capability (ELCC) is usually used for this purpose. In this paper, a noniterative analytical method is proposed for estimating the peak load carrying capability (PLCC) and ELCC of conventional and renewable generation units. The proposed method is verified using the IEEE RTS and an electricity network in New South Wales, Australia, and the results are compared with other estimation methods. The results show that the correlation between demand and renewable generation influences the ELCC of a renewable generation unit-the higher the correlation, the higher the ELCC, and vice versa. The main contribution of this paper is the development of an analytical noniterative and computationally efficient technique, which accounts for the correlation between demand and available renewable generation.
  • Keywords
    demand side management; power generation planning; power grids; renewable energy sources; transmission networks; Australia; ELCC; IEEE RTS; New South Wales; PLCC; effective load carrying capability; electricity network; noniterative analytical method; peak load carrying capability; power generation planning; renewable energy rich power grid; renewable generation units; Availability; Capacity planning; Correlation; Estimation; Iterative methods; Probability distribution; Wind; Approximation method; demand-generation correlation; joint probability distribution; power generation planning; renewable generation system;
  • fLanguage
    English
  • Journal_Title
    Sustainable Energy, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1949-3029
  • Type

    jour

  • DOI
    10.1109/TSTE.2014.2307855
  • Filename
    6779682