Disturbance Rejection Based Model Predictive Control for DC-DC Converters in Photovoltaic and Battery Energy Systems of DC-Microgrid

Adel Merabet; Ahmed Al-Durra; Rupak K. Dhar

doi:10.1109/IAS54024.2023.10406765

Disturbance Rejection Based Model Predictive Control for DC-DC Converters in Photovoltaic and Battery Energy Systems of DC-Microgrid

Adel Merabet
, Ahmed Al-Durra
, Rupak K. Dhar

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

Abstract

This paper presents a disturbance rejection based model predictive control to regulate the currents of photovoltaic and battery energy systems in a DC-microgrid. The model predictive control is carried out through optimization of a cost function defined on a future horizon. Disturbance rejection is achieved using disturbance estimation to eliminate unknown uncertainties. The proposed disturbance rejection based model predictive control structure is experimentally evaluated using a laboratory setup for DC-microgrid. It is found that the proposed structure enhances the tracking performance compared to the conventional model predictive control.

Original language	British English
Title of host publication	2023 IEEE Industry Applications Society Annual Meeting, IAS 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350320169
DOIs	https://doi.org/10.1109/IAS54024.2023.10406765
State	Published - 2023
Event	2023 IEEE Industry Applications Society Annual Meeting, IAS 2023 - Nashville, United States Duration: 29 Oct 2023 → 2 Nov 2023

Publication series

Name	2023 IEEE Industry Applications Society Annual Meeting, IAS 2023

Conference

Conference	2023 IEEE Industry Applications Society Annual Meeting, IAS 2023
Country/Territory	United States
City	Nashville
Period	29/10/23 → 2/11/23

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

battery current
disturbance rejection
microgrid
model predictive control
PV current

Access to Document

10.1109/IAS54024.2023.10406765

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Cite this

Merabet, A., Al-Durra, A., & Dhar, R. K. (2023). Disturbance Rejection Based Model Predictive Control for DC-DC Converters in Photovoltaic and Battery Energy Systems of DC-Microgrid. In 2023 IEEE Industry Applications Society Annual Meeting, IAS 2023 (2023 IEEE Industry Applications Society Annual Meeting, IAS 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IAS54024.2023.10406765

Merabet, Adel ; Al-Durra, Ahmed ; Dhar, Rupak K. / Disturbance Rejection Based Model Predictive Control for DC-DC Converters in Photovoltaic and Battery Energy Systems of DC-Microgrid. 2023 IEEE Industry Applications Society Annual Meeting, IAS 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE Industry Applications Society Annual Meeting, IAS 2023).

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title = "Disturbance Rejection Based Model Predictive Control for DC-DC Converters in Photovoltaic and Battery Energy Systems of DC-Microgrid",

abstract = "This paper presents a disturbance rejection based model predictive control to regulate the currents of photovoltaic and battery energy systems in a DC-microgrid. The model predictive control is carried out through optimization of a cost function defined on a future horizon. Disturbance rejection is achieved using disturbance estimation to eliminate unknown uncertainties. The proposed disturbance rejection based model predictive control structure is experimentally evaluated using a laboratory setup for DC-microgrid. It is found that the proposed structure enhances the tracking performance compared to the conventional model predictive control.",

keywords = "battery current, disturbance rejection, microgrid, model predictive control, PV current",

author = "Adel Merabet and Ahmed Al-Durra and Dhar, \{Rupak K.\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Industry Applications Society Annual Meeting, IAS 2023 ; Conference date: 29-10-2023 Through 02-11-2023",

year = "2023",

doi = "10.1109/IAS54024.2023.10406765",

language = "British English",

series = "2023 IEEE Industry Applications Society Annual Meeting, IAS 2023",

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

booktitle = "2023 IEEE Industry Applications Society Annual Meeting, IAS 2023",

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Merabet, A , Al-Durra, A & Dhar, RK 2023, Disturbance Rejection Based Model Predictive Control for DC-DC Converters in Photovoltaic and Battery Energy Systems of DC-Microgrid. in 2023 IEEE Industry Applications Society Annual Meeting, IAS 2023. 2023 IEEE Industry Applications Society Annual Meeting, IAS 2023, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE Industry Applications Society Annual Meeting, IAS 2023, Nashville, United States, 29/10/23. https://doi.org/10.1109/IAS54024.2023.10406765

Disturbance Rejection Based Model Predictive Control for DC-DC Converters in Photovoltaic and Battery Energy Systems of DC-Microgrid. / Merabet, Adel ; Al-Durra, Ahmed; Dhar, Rupak K.
2023 IEEE Industry Applications Society Annual Meeting, IAS 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE Industry Applications Society Annual Meeting, IAS 2023).

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

TY - GEN

T1 - Disturbance Rejection Based Model Predictive Control for DC-DC Converters in Photovoltaic and Battery Energy Systems of DC-Microgrid

AU - Merabet, Adel

AU - Al-Durra, Ahmed

AU - Dhar, Rupak K.

PY - 2023

Y1 - 2023

N2 - This paper presents a disturbance rejection based model predictive control to regulate the currents of photovoltaic and battery energy systems in a DC-microgrid. The model predictive control is carried out through optimization of a cost function defined on a future horizon. Disturbance rejection is achieved using disturbance estimation to eliminate unknown uncertainties. The proposed disturbance rejection based model predictive control structure is experimentally evaluated using a laboratory setup for DC-microgrid. It is found that the proposed structure enhances the tracking performance compared to the conventional model predictive control.

AB - This paper presents a disturbance rejection based model predictive control to regulate the currents of photovoltaic and battery energy systems in a DC-microgrid. The model predictive control is carried out through optimization of a cost function defined on a future horizon. Disturbance rejection is achieved using disturbance estimation to eliminate unknown uncertainties. The proposed disturbance rejection based model predictive control structure is experimentally evaluated using a laboratory setup for DC-microgrid. It is found that the proposed structure enhances the tracking performance compared to the conventional model predictive control.

KW - battery current

KW - disturbance rejection

KW - microgrid

KW - model predictive control

KW - PV current

UR - https://www.scopus.com/pages/publications/85186120082

U2 - 10.1109/IAS54024.2023.10406765

DO - 10.1109/IAS54024.2023.10406765

M3 - Conference contribution

AN - SCOPUS:85186120082

T3 - 2023 IEEE Industry Applications Society Annual Meeting, IAS 2023

BT - 2023 IEEE Industry Applications Society Annual Meeting, IAS 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE Industry Applications Society Annual Meeting, IAS 2023

Y2 - 29 October 2023 through 2 November 2023

ER -

Merabet A , Al-Durra A, Dhar RK. Disturbance Rejection Based Model Predictive Control for DC-DC Converters in Photovoltaic and Battery Energy Systems of DC-Microgrid. In 2023 IEEE Industry Applications Society Annual Meeting, IAS 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 IEEE Industry Applications Society Annual Meeting, IAS 2023). doi: 10.1109/IAS54024.2023.10406765

Disturbance Rejection Based Model Predictive Control for DC-DC Converters in Photovoltaic and Battery Energy Systems of DC-Microgrid

Abstract

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UN SDGs

Keywords

Access to Document

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