Online parameters estimation schemes to enhance control performance in DC microgrids

Juan E. Machado; Gianmario Rinaldi; Michele Cucuzzella; Prathyush P. Menon; Jacquelien M.A. Scherpen; Antonella Ferrara

doi:10.1016/j.ejcon.2023.100860

Online parameters estimation schemes to enhance control performance in DC microgrids

Juan E. Machado^*, Gianmario Rinaldi, Michele Cucuzzella, Prathyush P. Menon, Jacquelien M.A. Scherpen, Antonella Ferrara

^*Corresponding author for this work

Discrete Technology and Production Automation

Research output: Contribution to journal › Article › Academic › peer-review

3 Citations (Scopus)

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Abstract

This paper addresses the problem of achieving current sharing and voltage balancing in DC microgrids when the filter parasitic resistances of the Distributed Generation Units (DGUs) are unknown and potentially time-varying. Two schemes are proposed for current sharing and voltage balancing, which use only generated current and voltage measurements. The first scheme is a novel distributed adaptive control utilising the principles of back-stepping and passivity-based control design, intended for the case of constant parasitic resistances. The second scheme alters an existing stabilising controller for current sharing and voltage balancing by incorporating the estimation of the unknown, possibly time-varying, parasitic resistance. A Super-Twisting Sliding Mode Algorithm (STA) estimates the parasitic resistance and its bounded variations in finite-time. The simulation results using a DC microgrid composed of 4 DGUs demonstrate the performance of the proposed schemes.

Original language	English
Article number	100860
Number of pages	8
Journal	European Journal of Control
Volume	74
Early online date	16-Jun-2023
DOIs	https://doi.org/10.1016/j.ejcon.2023.100860
Publication status	Published - Nov-2023
Event	21st European Control Conference - University Politehnica of Bucharest, Bucharest, Romania Duration: 13-Jun-2023 → 16-Jun-2023 https://ecc23.euca-ecc.org/

Keywords

DC microgrids
Observers for nonlinear systems
Parameters estimation
Sliding mode control

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title = "Online parameters estimation schemes to enhance control performance in DC microgrids",

abstract = "This paper addresses the problem of achieving current sharing and voltage balancing in DC microgrids when the filter parasitic resistances of the Distributed Generation Units (DGUs) are unknown and potentially time-varying. Two schemes are proposed for current sharing and voltage balancing, which use only generated current and voltage measurements. The first scheme is a novel distributed adaptive control utilising the principles of back-stepping and passivity-based control design, intended for the case of constant parasitic resistances. The second scheme alters an existing stabilising controller for current sharing and voltage balancing by incorporating the estimation of the unknown, possibly time-varying, parasitic resistance. A Super-Twisting Sliding Mode Algorithm (STA) estimates the parasitic resistance and its bounded variations in finite-time. The simulation results using a DC microgrid composed of 4 DGUs demonstrate the performance of the proposed schemes.",

keywords = "DC microgrids, Observers for nonlinear systems, Parameters estimation, Sliding mode control",

author = "Machado, {Juan E.} and Gianmario Rinaldi and Michele Cucuzzella and Menon, {Prathyush P.} and Scherpen, {Jacquelien M.A.} and Antonella Ferrara",

note = "Publisher Copyright: {\textcopyright} 2023 The Author(s); 21st European Control Conference , ECC 2023 ; Conference date: 13-06-2023 Through 16-06-2023",

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AU - Machado, Juan E.

AU - Rinaldi, Gianmario

AU - Cucuzzella, Michele

AU - Menon, Prathyush P.

AU - Scherpen, Jacquelien M.A.

AU - Ferrara, Antonella

PY - 2023/11

Y1 - 2023/11

N2 - This paper addresses the problem of achieving current sharing and voltage balancing in DC microgrids when the filter parasitic resistances of the Distributed Generation Units (DGUs) are unknown and potentially time-varying. Two schemes are proposed for current sharing and voltage balancing, which use only generated current and voltage measurements. The first scheme is a novel distributed adaptive control utilising the principles of back-stepping and passivity-based control design, intended for the case of constant parasitic resistances. The second scheme alters an existing stabilising controller for current sharing and voltage balancing by incorporating the estimation of the unknown, possibly time-varying, parasitic resistance. A Super-Twisting Sliding Mode Algorithm (STA) estimates the parasitic resistance and its bounded variations in finite-time. The simulation results using a DC microgrid composed of 4 DGUs demonstrate the performance of the proposed schemes.

AB - This paper addresses the problem of achieving current sharing and voltage balancing in DC microgrids when the filter parasitic resistances of the Distributed Generation Units (DGUs) are unknown and potentially time-varying. Two schemes are proposed for current sharing and voltage balancing, which use only generated current and voltage measurements. The first scheme is a novel distributed adaptive control utilising the principles of back-stepping and passivity-based control design, intended for the case of constant parasitic resistances. The second scheme alters an existing stabilising controller for current sharing and voltage balancing by incorporating the estimation of the unknown, possibly time-varying, parasitic resistance. A Super-Twisting Sliding Mode Algorithm (STA) estimates the parasitic resistance and its bounded variations in finite-time. The simulation results using a DC microgrid composed of 4 DGUs demonstrate the performance of the proposed schemes.

KW - DC microgrids

KW - Observers for nonlinear systems

KW - Parameters estimation

KW - Sliding mode control

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SN - 0947-3580

VL - 74

JO - European Journal of Control

JF - European Journal of Control

M1 - 100860

T2 - 21st European Control Conference

Y2 - 13 June 2023 through 16 June 2023

ER -

Online parameters estimation schemes to enhance control performance in DC microgrids

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Keywords

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