Sequential Model Predictive Control of Stand-Alone Voltage Source Inverters

Changming Zheng, Tomislav Dragicevic, Minrui Leng, Jose Rodriguez, Frede Blaabjerg

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

Abstract

To avoid the time-consuming weighting-factor tuning work in conventional finite control set model predictive control (FCS-MPC), a sequential model predictive control (SMPC) scheme for stand-alone voltage source inverters of an islanded ac microgrid is proposed in this paper. The main idea is that two cost functions for separately minimizing the capacitor voltage and the inductor current tracking errors of the LC filter are deployed in a sequential structure instead of being integrated into a single cost function. As a result, the weighting factor for balancing the two control objectives is eliminated. Moreover, the proposed SMPC does not degrade the output-voltage control performance too much. Simulation results are provided, verifying the effectiveness of the presented approach.

Original languageEnglish
Title of host publication2020 IEEE 11th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages409-412
Number of pages4
ISBN (Electronic)9781728169903
DOIs
Publication statusPublished - 28 Sep 2020
Event11th IEEE International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2020 - Dubrovnik, Croatia
Duration: 28 Sep 20201 Oct 2020

Publication series

Name2020 IEEE 11th International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2020

Conference

Conference11th IEEE International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2020
CountryCroatia
CityDubrovnik
Period28/09/201/10/20

Keywords

  • filter
  • inverters
  • microgrid
  • model predictive control
  • weighting factor

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Control and Optimization

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