Fast-Model Predictive Control for a Grid-Tie Photovoltaic System

Jose Silva, Jose Espinoza, Luis Moran, Daniel Sbarbaro, Jaime Rohten, Miguel Torres, Rodrigo Mendez

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

Abstract

This paper proposes a hybrid control scheme based upon both a linear and a predictive control approach for a grid-tie inverter for photovoltaic applications. The proposed strategy uses the complex representation of the switching states and splits them choosing the best one without using an iterative loop. The resulting algorithm, in terms of the dynamic and static response, performs like the traditional Finite Set Model Predictive Control (FS-MPC). However, the proposed scheme is easy to implement, it does not need to tune parameters nor need a cost function and nor require iterating all the possible states to choose the best. Over the abovementioned advantages, it has the capability to operate the photovoltaic module at the maximum power point (MPP) and the ability to impose a sinusoidal current at the grid side with a unitary displacement power factor. Preliminary results are presented to validate the proposed control method.

Original languageEnglish
Title of host publicationProceedings - IECON 2020
Subtitle of host publication46th Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE Computer Society
Pages3212-3217
Number of pages6
ISBN (Electronic)9781728154145
DOIs
StatePublished - 18 Oct 2020
Externally publishedYes
Event46th Annual Conference of the IEEE Industrial Electronics Society, IECON 2020 - Virtual, Singapore, Singapore
Duration: 19 Oct 202021 Oct 2020

Publication series

NameIECON Proceedings (Industrial Electronics Conference)
Volume2020-October

Conference

Conference46th Annual Conference of the IEEE Industrial Electronics Society, IECON 2020
Country/TerritorySingapore
CityVirtual, Singapore
Period19/10/2021/10/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

  • grid tie inverter
  • model predictive control
  • photovoltaic systems

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