State estimation on stand-alone DC microgrids through distributed intelligence

Wesley Doorsamy, Willem A. Cronje

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

4 Citations (Scopus)

Abstract

The development of stand-alone microgrids brings about different challenges in the efficient coordination of sources, storage and loads. State estimation is especially challenging as these types of applications require robust and low-cost methods that can produce fast and accurate estimates without the provision of topology information or data communications across the network. This research aims to address such challenges for stand-alone DC microgrids. The Recursive Least Squares (RLS) parameter estimation method is used together with local measurements to obtain the Thevenin equivalent parameters required for autonomous coordination of the microgrid's components. The presented on-line estimation method is simulated using Matlab/Simulink. The performance of the estimator is also tested using an experimental setup.

Original languageEnglish
Title of host publication2015 International Conference on Renewable Energy Research and Applications, ICRERA 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages227-231
Number of pages5
ISBN (Electronic)9781479999828
DOIs
Publication statusPublished - 2015
Externally publishedYes
Event4th International Conference on Renewable Energy Research and Applications, ICRERA 2015 - Palermo, Italy
Duration: 22 Nov 201525 Nov 2015

Publication series

Name2015 International Conference on Renewable Energy Research and Applications, ICRERA 2015

Conference

Conference4th International Conference on Renewable Energy Research and Applications, ICRERA 2015
Country/TerritoryItaly
CityPalermo
Period22/11/1525/11/15

Keywords

  • Thevenin equivalent
  • autonomous microgrids
  • on-line estimation
  • recursive least squares

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment

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