Maximum power point tracking of photovoltaic systems using sensorless current-based model predictive control

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

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

8 Citations (Scopus)

Abstract

Variability of the solar resource necessitates that Maximum Power Point Tracking (MPPT) techniques be used in photovoltaic (PV) systems to ensure maximum electrical energy is harvested. This paper presents a MPPT algorithm using Model Predictive Control (MPC) that does not require the use of current sensors. The main contribution is the use of the model based predictive control (MPC-MPPT) to eliminate the current sensor that is usually required in the perturb and observe (P&O) MPPT technique. By predicting and controlling the future PV system operation in the time horizon, the proposed method is an elegant, embedded controller that has faster response than the conventional P&O technique under rapidly changing atmospheric conditions and without requiring expensive sensing and communications equipment and networks to directly measure solar insolation changes. Real time simulations run on a dSpace DS1007 platform compare of the proposed sensorless current MPC-MPPT (SC MPC-MPPT) technique to the full sensor version.

Original languageEnglish
Title of host publication2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6635-6641
Number of pages7
ISBN (Electronic)9781467371506
DOIs
Publication statusPublished - 27 Oct 2015
Event7th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2015 - Montreal, Canada
Duration: 20 Sep 201524 Sep 2015

Other

Other7th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2015
CountryCanada
CityMontreal
Period20/9/1524/9/15

Fingerprint

Model predictive control
Sensors
Incident solar radiation
Controllers
Communication

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

Cite this

Metry, M., Shadmand, M. B., Liu, Y., Balog, R., & Abu-Rub, H. (2015). Maximum power point tracking of photovoltaic systems using sensorless current-based model predictive control. In 2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015 (pp. 6635-6641). [7310588] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ECCE.2015.7310588

Maximum power point tracking of photovoltaic systems using sensorless current-based model predictive control. / Metry, Morcos; Shadmand, Mohammad B.; Liu, Yushan; Balog, Robert; Abu-Rub, Haitham.

2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 6635-6641 7310588.

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

Metry, M, Shadmand, MB, Liu, Y, Balog, R & Abu-Rub, H 2015, Maximum power point tracking of photovoltaic systems using sensorless current-based model predictive control. in 2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015., 7310588, Institute of Electrical and Electronics Engineers Inc., pp. 6635-6641, 7th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2015, Montreal, Canada, 20/9/15. https://doi.org/10.1109/ECCE.2015.7310588
Metry M, Shadmand MB, Liu Y, Balog R, Abu-Rub H. Maximum power point tracking of photovoltaic systems using sensorless current-based model predictive control. In 2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 6635-6641. 7310588 https://doi.org/10.1109/ECCE.2015.7310588
Metry, Morcos ; Shadmand, Mohammad B. ; Liu, Yushan ; Balog, Robert ; Abu-Rub, Haitham. / Maximum power point tracking of photovoltaic systems using sensorless current-based model predictive control. 2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 6635-6641
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