• DocumentCode
    715099
  • Title

    Effect of different load models on the three-sample based quadratic prediction algorithm

  • Author

    Pal, Anamitra

  • Author_Institution
    Network Dynamics & Simulation Sci. Lab., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA
  • fYear
    2015
  • fDate
    18-20 Feb. 2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    A quadratic prediction algorithm has been proposed previously that estimates the future state from three preceding values of the same state. The original proof of that algorithm was developed based on loads changing at constant power factor. Since real power system loads are composite in nature, it is important to analyze that algorithm´s performance for different load models. This paper studies the effect of constant power load, constant current load, constant impedance load, and the WECC load model on the performance of the three-sample based quadratic prediction algorithm. The analysis is performed using the IEEE-118 bus system, a 4000-bus WECC model, as well as real-data obtained from a utility. The results indicate that the three-sample based quadratic prediction algorithm is able to estimate the states accurately for all the load models.
  • Keywords
    power factor; power system control; power system state estimation; 4000-bus WECC load model; IEEE-118 bus system; constant current load; constant impedance load; constant power load; power factor; power system; state estimation; three-sample based quadratic prediction algorithm; western electricity coordinating council; Heuristic algorithms; Impedance; Load modeling; Mathematical model; Power system dynamics; Prediction algorithms; Predictive models; Load models; Phasor measurement unit (PMU); Quadratic prediction; State estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Smart Grid Technologies Conference (ISGT), 2015 IEEE Power & Energy Society
  • Conference_Location
    Washington, DC
  • Type

    conf

  • DOI
    10.1109/ISGT.2015.7131811
  • Filename
    7131811