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

Morcos Metry; Mohammad B. Shadmand; Yushan Liu; Robert S. Balog; Haitham Abu Rub

doi:10.1109/ECCE.2015.7310588

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

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

Texas A&M University
Hamad bin Khalifa University
Texas A&M University at Qatar

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Scopus citations

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 language	English
Title of host publication	2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	6635-6641
Number of pages	7
ISBN (Electronic)	9781467371506
DOIs	https://doi.org/10.1109/ECCE.2015.7310588
State	Published - 27 Oct 2015
Externally published	Yes
Event	7th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2015 - Montreal, Canada Duration: 20 Sep 2015 → 24 Sep 2015

Publication series

Name	2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015

Conference

Conference	7th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2015
Country/Territory	Canada
City	Montreal
Period	20/09/15 → 24/09/15

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Access to Document

10.1109/ECCE.2015.7310588

Cite this

Metry, M., Shadmand, M. B., Liu, Y., Balog, R. S., & Rub, H. A. (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). Article 7310588 (2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ECCE.2015.7310588

Metry, Morcos ; Shadmand, Mohammad B. ; Liu, Yushan et al. / 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 (2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015).

@inproceedings{e14e7009c3af45c5919a165a40f736a7,

title = "Maximum power point tracking of photovoltaic systems using sensorless current-based model predictive control",

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.",

author = "Morcos Metry and Shadmand, \{Mohammad B.\} and Yushan Liu and Balog, \{Robert S.\} and Rub, \{Haitham Abu\}",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 7th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2015 ; Conference date: 20-09-2015 Through 24-09-2015",

year = "2015",

month = oct,

day = "27",

doi = "10.1109/ECCE.2015.7310588",

language = "英语",

series = "2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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booktitle = "2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015",

address = "美国",

}

Metry, M, Shadmand, MB, Liu, Y, Balog, RS & Rub, HA 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, 2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015, Institute of Electrical and Electronics Engineers Inc., pp. 6635-6641, 7th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2015, Montreal, Canada, 20/09/15. 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 et al.
2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 6635-6641 7310588 (2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Maximum power point tracking of photovoltaic systems using sensorless current-based model predictive control

AU - Metry, Morcos

AU - Shadmand, Mohammad B.

AU - Liu, Yushan

AU - Balog, Robert S.

AU - Rub, Haitham Abu

PY - 2015/10/27

Y1 - 2015/10/27

N2 - 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.

AB - 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.

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T3 - 2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015

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BT - 2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 7th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2015

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ER -

Metry M, Shadmand MB, Liu Y, Balog RS, Rub HA. 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. (2015 IEEE Energy Conversion Congress and Exposition, ECCE 2015). doi: 10.1109/ECCE.2015.7310588

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

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