Sensitivity analysis to model parameter errors of MPPT by model predictive control for photovoltaic applications

Morcos Metry, Mohammad B. Shadmand, Robert Balog, Haitham Abu-Rub

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

5 Citations (Scopus)

Abstract

Due to variability of solar energy resources, maximum power point tracking (MPPT) of photovoltaic (PV) is required to ensure continuous operation at the maximum power point (MPP) and maximize the energy harvest. This paper presents a digital model predictive control technique to employ the MPPT for flyback converter for photovoltaic applications. The MPP operating point is determined by using perturb and observe (P&O) technique. The proposed two-steps predictive model based MPPT presents significant advantages in dynamic response and power ripple at steady state. A characteristic of MPC is the use of system models for selecting optimal actuations, thus evaluating the effect of model parameter mismatch on control effectiveness is of interest. In this paper the load model is eliminated from the proposed MPC formulation by using an observer based technique. The sensitivity analysis results indicate a more robust controller to uncertainty and disturbances in the resistive load.

Original languageEnglish
Title of host publication2015 1st Workshop on Smart Grid and Renewable Energy, SGRE 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467367653
DOIs
Publication statusPublished - 17 Aug 2015
Event1st Workshop on Smart Grid and Renewable Energy, SGRE 2015 - Doha, Qatar
Duration: 22 Mar 201523 Mar 2015

Other

Other1st Workshop on Smart Grid and Renewable Energy, SGRE 2015
CountryQatar
CityDoha
Period22/3/1523/3/15

Fingerprint

Model predictive control
Sensitivity analysis
Energy resources
Solar energy
Dynamic response
Controllers

Keywords

  • Load modeling
  • Mathematical model
  • Maximum power point trackers
  • Power electronics
  • Predictive control
  • Predictive models
  • Switches

ASJC Scopus subject areas

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

Cite this

Metry, M., Shadmand, M. B., Balog, R., & Abu-Rub, H. (2015). Sensitivity analysis to model parameter errors of MPPT by model predictive control for photovoltaic applications. In 2015 1st Workshop on Smart Grid and Renewable Energy, SGRE 2015 [7208736] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SGRE.2015.7208736

Sensitivity analysis to model parameter errors of MPPT by model predictive control for photovoltaic applications. / Metry, Morcos; Shadmand, Mohammad B.; Balog, Robert; Abu-Rub, Haitham.

2015 1st Workshop on Smart Grid and Renewable Energy, SGRE 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7208736.

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

Metry, M, Shadmand, MB, Balog, R & Abu-Rub, H 2015, Sensitivity analysis to model parameter errors of MPPT by model predictive control for photovoltaic applications. in 2015 1st Workshop on Smart Grid and Renewable Energy, SGRE 2015., 7208736, Institute of Electrical and Electronics Engineers Inc., 1st Workshop on Smart Grid and Renewable Energy, SGRE 2015, Doha, Qatar, 22/3/15. https://doi.org/10.1109/SGRE.2015.7208736
Metry M, Shadmand MB, Balog R, Abu-Rub H. Sensitivity analysis to model parameter errors of MPPT by model predictive control for photovoltaic applications. In 2015 1st Workshop on Smart Grid and Renewable Energy, SGRE 2015. Institute of Electrical and Electronics Engineers Inc. 2015. 7208736 https://doi.org/10.1109/SGRE.2015.7208736
Metry, Morcos ; Shadmand, Mohammad B. ; Balog, Robert ; Abu-Rub, Haitham. / Sensitivity analysis to model parameter errors of MPPT by model predictive control for photovoltaic applications. 2015 1st Workshop on Smart Grid and Renewable Energy, SGRE 2015. Institute of Electrical and Electronics Engineers Inc., 2015.
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