Multi-Agent Sliding Mode Control for State of Charge Balancing Between Battery Energy Storage Systems Distributed in a DC Microgrid

Thomas Morstyn, Andrey V. Savkin, Branislav Hredzak, Vassilios G. Agelidis

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

This paper proposes the novel use of multi-agent sliding mode control for state of charge balancing between distributed de microgrid battery energy storage systems. Unlike existing control strategies based on linear multi-agent consensus protocols, the proposed nonlinear state of charge balancing strategy: 1) ensures the battery energy storage systems are either all charging or all discharging, thus eliminating circulating currents, increasing efficiency, and reducing battery lifetime degradation; 2) achieves faster state of charge balancing; 3) avoids overloading the battery energy storage systems during periods of high load; and 4) provides plug and play capability. The proposed control strategy can be readily integrated with existing multi-agent controllers for secondary voltage regulation and accurate current sharing. The performance of the proposed control strategy was verified with an RTDS Technologies real-time digital simulator, using switching converter models and nonlinear lead-acid battery models.
Original languageEnglish
JournalI E E E Transactions on Smart Grid
Volume9
Issue number5
Pages (from-to)4735-4743
Number of pages9
ISSN1949-3053
DOIs
Publication statusPublished - 2018

Keywords

  • Battery energy storage systems
  • DC microgrid
  • Distributed energy storage
  • Distributed sliding mode control
  • Hybrid systems
  • Multi-agent control
  • Secondary control
  • State of charge balancing

Cite this

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title = "Multi-Agent Sliding Mode Control for State of Charge Balancing Between Battery Energy Storage Systems Distributed in a DC Microgrid",
abstract = "This paper proposes the novel use of multi-agent sliding mode control for state of charge balancing between distributed de microgrid battery energy storage systems. Unlike existing control strategies based on linear multi-agent consensus protocols, the proposed nonlinear state of charge balancing strategy: 1) ensures the battery energy storage systems are either all charging or all discharging, thus eliminating circulating currents, increasing efficiency, and reducing battery lifetime degradation; 2) achieves faster state of charge balancing; 3) avoids overloading the battery energy storage systems during periods of high load; and 4) provides plug and play capability. The proposed control strategy can be readily integrated with existing multi-agent controllers for secondary voltage regulation and accurate current sharing. The performance of the proposed control strategy was verified with an RTDS Technologies real-time digital simulator, using switching converter models and nonlinear lead-acid battery models.",
keywords = "Battery energy storage systems, DC microgrid, Distributed energy storage, Distributed sliding mode control, Hybrid systems, Multi-agent control, Secondary control, State of charge balancing",
author = "Thomas Morstyn and Savkin, {Andrey V.} and Branislav Hredzak and Agelidis, {Vassilios G.}",
year = "2018",
doi = "10.1109/TSG.2017.2668767",
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pages = "4735--4743",
journal = "I E E E Transactions on Smart Grid",
issn = "1949-3053",
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Multi-Agent Sliding Mode Control for State of Charge Balancing Between Battery Energy Storage Systems Distributed in a DC Microgrid. / Morstyn, Thomas; Savkin, Andrey V.; Hredzak, Branislav; Agelidis, Vassilios G.

In: I E E E Transactions on Smart Grid, Vol. 9, No. 5, 2018, p. 4735-4743.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Multi-Agent Sliding Mode Control for State of Charge Balancing Between Battery Energy Storage Systems Distributed in a DC Microgrid

AU - Morstyn, Thomas

AU - Savkin, Andrey V.

AU - Hredzak, Branislav

AU - Agelidis, Vassilios G.

PY - 2018

Y1 - 2018

N2 - This paper proposes the novel use of multi-agent sliding mode control for state of charge balancing between distributed de microgrid battery energy storage systems. Unlike existing control strategies based on linear multi-agent consensus protocols, the proposed nonlinear state of charge balancing strategy: 1) ensures the battery energy storage systems are either all charging or all discharging, thus eliminating circulating currents, increasing efficiency, and reducing battery lifetime degradation; 2) achieves faster state of charge balancing; 3) avoids overloading the battery energy storage systems during periods of high load; and 4) provides plug and play capability. The proposed control strategy can be readily integrated with existing multi-agent controllers for secondary voltage regulation and accurate current sharing. The performance of the proposed control strategy was verified with an RTDS Technologies real-time digital simulator, using switching converter models and nonlinear lead-acid battery models.

AB - This paper proposes the novel use of multi-agent sliding mode control for state of charge balancing between distributed de microgrid battery energy storage systems. Unlike existing control strategies based on linear multi-agent consensus protocols, the proposed nonlinear state of charge balancing strategy: 1) ensures the battery energy storage systems are either all charging or all discharging, thus eliminating circulating currents, increasing efficiency, and reducing battery lifetime degradation; 2) achieves faster state of charge balancing; 3) avoids overloading the battery energy storage systems during periods of high load; and 4) provides plug and play capability. The proposed control strategy can be readily integrated with existing multi-agent controllers for secondary voltage regulation and accurate current sharing. The performance of the proposed control strategy was verified with an RTDS Technologies real-time digital simulator, using switching converter models and nonlinear lead-acid battery models.

KW - Battery energy storage systems

KW - DC microgrid

KW - Distributed energy storage

KW - Distributed sliding mode control

KW - Hybrid systems

KW - Multi-agent control

KW - Secondary control

KW - State of charge balancing

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DO - 10.1109/TSG.2017.2668767

M3 - Journal article

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SP - 4735

EP - 4743

JO - I E E E Transactions on Smart Grid

JF - I E E E Transactions on Smart Grid

SN - 1949-3053

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ER -