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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

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.

Original languageEnglish (US)
Title of host publication2015 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479917853
DOIs
StatePublished - Jun 23 2015
Externally publishedYes
Event2015 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2015 - Washington, United States
Duration: Feb 18 2015Feb 20 2015

Other

Other2015 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2015
CountryUnited States
CityWashington
Period2/18/152/20/15

Keywords

  • Load models
  • Phasor measurement unit (PMU)
  • Quadratic prediction
  • State estimation

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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    Pal, A. (2015). Effect of different load models on the three-sample based quadratic prediction algorithm. In 2015 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2015 [7131811] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISGT.2015.7131811