Parameter identification of a wind generator unit RMS model using sparse grid optimization algorithm

Qing Fang, Rastko Zivanovic

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

1 Citation (Scopus)

Abstract

This paper presents a global sparse grid optimization algorithm applied in parameter identification of a wind generation Root Mean Square (RMS) phasor model. The details of vendor specific RMS models used in dynamic simulation software (e.g. PSSE) are not provided by manufacturers. Therefore, there is a need to develop a procedure which can convert vendor specific models to standardized generic models (e.g. International Electrotechnical Commission model, IEC model). The procedure we propose, identifies the parameters of the IEC generic model using dynamic response of a given vendor specific model as input. The IEC model parameters can be found and dynamic response of the vendor model can be approximated with sufficient accuracy. In the simulation example we show that the parameter identification based on the global sparse grid optimization algorithm is effective in converting a vendor specific model to a standardized generic model.

Original languageEnglish
Title of host publicationProceedings of 2014 International Conference on Modelling, Identification and Control, ICMIC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages283-288
Number of pages6
ISBN (Electronic)9780956715746
DOIs
Publication statusPublished - 23 Jan 2015
Externally publishedYes
Event6th International Conference on Modelling, Identification and Control, ICMIC 2014 - Melbourne, Australia
Duration: 3 Dec 20145 Dec 2014

Publication series

NameProceedings of 2014 International Conference on Modelling, Identification and Control, ICMIC 2014

Conference

Conference6th International Conference on Modelling, Identification and Control, ICMIC 2014
CountryAustralia
CityMelbourne
Period03.12.201405.12.2014

Keywords

  • Doubly Fed Induction Generators (DFIGs)
  • global optimization
  • parameter identification
  • RMS phasor model
  • sparse grid
  • wind generation

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