Model predictive control for maximum power point tracking of quasi-Z-source inverter based grid-tied photovoltaic power system

Morcos Metry, Yushan Liu, Robert Balog, Haitham Abu-Rub

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

1 Citation (Scopus)

Abstract

Stochastic dynamic behavior of solar energy necessitates the use of robust controllers for photovoltaic (PV) power electronics interfaces. Such robust controller maximizes the energy harvest through continuous operation using a maximum power point tracker (MPPT). A model predictive control MPPT (MPC-MPPT) is proposed in this paper for a quasi-Z-source inverter (qZSI) based grid-connected PV power system. MPC is a robust suboptimal controller and is proposed in this paper as an elegant, embedded controller. Such controller has shown better dynamic performance than the conventional perturb and observe (P&O) technique, particularly under rapidly changing meteorological conditions. The qZSI is a single-stage topology that can guarantee MPPT and control the injected power to the grid simultaneously. The proposed method simulation results are presented in this paper.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE International Symposium on Industrial Electronics, ISIE 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1657-1662
Number of pages6
ISBN (Electronic)9781509014125
DOIs
Publication statusPublished - 3 Aug 2017
Event26th IEEE International Symposium on Industrial Electronics, ISIE 2017 - Edinburgh, Scotland, United Kingdom
Duration: 18 Jun 201721 Jun 2017

Other

Other26th IEEE International Symposium on Industrial Electronics, ISIE 2017
CountryUnited Kingdom
CityEdinburgh, Scotland
Period18/6/1721/6/17

Fingerprint

Model predictive control
Controllers
Power electronics
Solar energy
Topology
Maximum power point trackers

Keywords

  • Grid-tie photovoltaic system
  • Maximum power point tracking
  • Model predictive control
  • Quasi-Z-source inverter

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering

Cite this

Metry, M., Liu, Y., Balog, R., & Abu-Rub, H. (2017). Model predictive control for maximum power point tracking of quasi-Z-source inverter based grid-tied photovoltaic power system. In Proceedings - 2017 IEEE International Symposium on Industrial Electronics, ISIE 2017 (pp. 1657-1662). [8001496] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIE.2017.8001496

Model predictive control for maximum power point tracking of quasi-Z-source inverter based grid-tied photovoltaic power system. / Metry, Morcos; Liu, Yushan; Balog, Robert; Abu-Rub, Haitham.

Proceedings - 2017 IEEE International Symposium on Industrial Electronics, ISIE 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1657-1662 8001496.

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

Metry, M, Liu, Y, Balog, R & Abu-Rub, H 2017, Model predictive control for maximum power point tracking of quasi-Z-source inverter based grid-tied photovoltaic power system. in Proceedings - 2017 IEEE International Symposium on Industrial Electronics, ISIE 2017., 8001496, Institute of Electrical and Electronics Engineers Inc., pp. 1657-1662, 26th IEEE International Symposium on Industrial Electronics, ISIE 2017, Edinburgh, Scotland, United Kingdom, 18/6/17. https://doi.org/10.1109/ISIE.2017.8001496
Metry M, Liu Y, Balog R, Abu-Rub H. Model predictive control for maximum power point tracking of quasi-Z-source inverter based grid-tied photovoltaic power system. In Proceedings - 2017 IEEE International Symposium on Industrial Electronics, ISIE 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1657-1662. 8001496 https://doi.org/10.1109/ISIE.2017.8001496
Metry, Morcos ; Liu, Yushan ; Balog, Robert ; Abu-Rub, Haitham. / Model predictive control for maximum power point tracking of quasi-Z-source inverter based grid-tied photovoltaic power system. Proceedings - 2017 IEEE International Symposium on Industrial Electronics, ISIE 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1657-1662
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