• DocumentCode
    35956
  • Title

    Methodology for Estimation of Dynamic Response of Demand Using Limited Data

  • Author

    Milanovic, Jovica V. ; Yizheng Xu

  • Author_Institution
    Electr. Energy & Power Syst. Group, Univ. of Manchester, Manchester, UK
  • Volume
    30
  • Issue
    3
  • fYear
    2015
  • fDate
    May-15
  • Firstpage
    1288
  • Lastpage
    1297
  • Abstract
    The paper presents a methodology for estimation of dynamic response of aggregate load at distribution network buses by taking into account daily variation in demand composition and generic dynamic responses of different types of load. Dynamic load models for different load categories obtained from field or laboratory measurements or through appropriate mathematical modeling are used in combination with hourly load composition at the given bus. The load composition is derived based on past demand surveys, and daily loading curves for different classes of customers. Uncertainties in both dynamic load models/responses of individual loads and load compositions at different times of the day are modeled probabilistically. With established dynamic signatures of different load categories and load compositions at different times of the day, Monte Carlo simulations are used to estimate probabilistic real and reactive power responses, including ranges of variation of these responses, for every hour of the day for a given or anticipated mix of demand.
  • Keywords
    Monte Carlo methods; distribution networks; dynamic response; estimation theory; load forecasting; probability; reactive power; Monte Carlo simulations; daily loading curves; demand surveys; distribution network buses; dynamic load models; generic dynamic responses; reactive power responses; Aggregates; Estimation; Load modeling; Mathematical model; Power system dynamics; Probabilistic logic; Uncertainty; Aggregate load; Monte Carlo simulation; probabilistic; time-dependent dynamic response;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2014.2343691
  • Filename
    6880414