Advances and opportunities in the model predictive control of microgrids: Part II–Secondary and tertiary layers

Oluleke Babayomi; Zhenbing Zhang; Tomislav Dragicevic; Rasool Heydari; Yu Li; Cristian Garcia; José  Rodriguez; Ralph Kennel

doi:10.1016/j.ijepes.2021.107339

Advances and opportunities in the model predictive control of microgrids: Part II–Secondary and tertiary layers

Oluleke Babayomi, Zhenbing Zhang, Tomislav Dragicevic, Rasool Heydari, Yu Li, Cristian Garcia, José Rodriguez, Ralph Kennel

Research output: Contribution to journal › Journal article › Research › peer-review

Abstract

Model predictive control (MPC) facilitates the multi-variable control of power electronic systems while accommodating physical constraints without the necessity for a cascaded structure. These features result in fast control dynamic response and good performance when system involving non-linearities. In this second part of this paper, we present a review of the recent advances in the application of MPC to the secondary and tertiary control of microgrids (MGs). We also present comprehensive surveys of MPC techniques to the energy management and power flow control of autonomous and networked MGs. The application opportunities for MPC to both distributed secondary control and networked microgrids are also discussed.

Original language	English
Article number	107339
Journal	International Journal of Electrical Power & Energy Systems
Volume	134
Number of pages	13
ISSN	0142-0615
DOIs	https://doi.org/10.1016/j.ijepes.2021.107339
Publication status	Published - 2021

Keywords

Model predictive contro
Hybrid AC/DC microgri
Networked and autonomous microg
Three levels of microgrid contr
Multi-agent contr
Future trends of microgrid contr

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title = "Advances and opportunities in the model predictive control of microgrids: Part II–Secondary and tertiary layers",

abstract = "Model predictive control (MPC) facilitates the multi-variable control of power electronic systems while accommodating physical constraints without the necessity for a cascaded structure. These features result in fast control dynamic response and good performance when system involving non-linearities. In this second part of this paper, we present a review of the recent advances in the application of MPC to the secondary and tertiary control of microgrids (MGs). We also present comprehensive surveys of MPC techniques to the energy management and power flow control of autonomous and networked MGs. The application opportunities for MPC to both distributed secondary control and networked microgrids are also discussed.",

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AU - Babayomi, Oluleke

AU - Zhang, Zhenbing

AU - Dragicevic, Tomislav

AU - Heydari, Rasool

AU - Li, Yu

AU - Garcia, Cristian

AU - Rodriguez, José

AU - Kennel, Ralph

PY - 2021

Y1 - 2021

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AB - Model predictive control (MPC) facilitates the multi-variable control of power electronic systems while accommodating physical constraints without the necessity for a cascaded structure. These features result in fast control dynamic response and good performance when system involving non-linearities. In this second part of this paper, we present a review of the recent advances in the application of MPC to the secondary and tertiary control of microgrids (MGs). We also present comprehensive surveys of MPC techniques to the energy management and power flow control of autonomous and networked MGs. The application opportunities for MPC to both distributed secondary control and networked microgrids are also discussed.

KW - Model predictive contro

KW - Hybrid AC/DC microgri

KW - Networked and autonomous microg

KW - Three levels of microgrid contr

KW - Multi-agent contr

KW - Future trends of microgrid contr

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DO - 10.1016/j.ijepes.2021.107339

M3 - Journal article

SN - 0142-0615

VL - 134

JO - International Journal of Electrical Power & Energy Systems

JF - International Journal of Electrical Power & Energy Systems

M1 - 107339

ER -

Advances and opportunities in the model predictive control of microgrids: Part II–Secondary and tertiary layers

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