Enhancing energy quality and grid stability with improved adaptive controller for renewable energy conversion systems under weak grid conditions
This work presents a systematic procedure for the parameterization of a robust adaptive proportional-integral controller applied to a grid-tied inverter with an LCL filter. The controller parameterization uses the Tasmanian devil optimizer, driven by performance indexes and controller stability cons...
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Published in | Electric power systems research Vol. 237; p. 111041 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier B.V
01.12.2024
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Subjects | |
Online Access | Get full text |
ISSN | 0378-7796 |
DOI | 10.1016/j.epsr.2024.111041 |
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Abstract | This work presents a systematic procedure for the parameterization of a robust adaptive proportional-integral controller applied to a grid-tied inverter with an LCL filter. The controller parameterization uses the Tasmanian devil optimizer, driven by performance indexes and controller stability constraints in the formulation of the optimization problem. Simulation results considering the renewable energy conversion system subject to periodic exogenous disturbances, grid impedance variations, and system uncertainties representing critical situations of real systems are presented. The optimized controller allows current tracking in less than one grid cycle (around 9 ms) during the initial transient regime, and when the grid inductance changes around 4.33 times the nominal value (from 0.3 mH to 1.3 mH), the transient regime ends in 11 ms without significant overshoot. Two extreme scenarios were also considered: when the grid inductance increases 17.66 times (from 0.3 mH to 5.3 mH) and 34.33 times (from 0.3 mH to 10.3 mH). The duration of transient regimes was again less than one grid cycle. Moreover, there are no significant tracking errors in the transient regimes associated with current reference changes, and the tracking error tends to a residual value in steady state in all scenarios, with values on the order of 10−6.
•A systematic procedure for parametrization of current controller of grid-tied power systems based on the Tasmanian devil optimization algorithm.•An optimized current controller that ensures energy quality and stability even in weak grid conditions.•An improved controller that is able to deal with harsh grid uncertainties with variation of more than 30 times its nominal inductance. |
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AbstractList | This work presents a systematic procedure for the parameterization of a robust adaptive proportional-integral controller applied to a grid-tied inverter with an LCL filter. The controller parameterization uses the Tasmanian devil optimizer, driven by performance indexes and controller stability constraints in the formulation of the optimization problem. Simulation results considering the renewable energy conversion system subject to periodic exogenous disturbances, grid impedance variations, and system uncertainties representing critical situations of real systems are presented. The optimized controller allows current tracking in less than one grid cycle (around 9 ms) during the initial transient regime, and when the grid inductance changes around 4.33 times the nominal value (from 0.3 mH to 1.3 mH), the transient regime ends in 11 ms without significant overshoot. Two extreme scenarios were also considered: when the grid inductance increases 17.66 times (from 0.3 mH to 5.3 mH) and 34.33 times (from 0.3 mH to 10.3 mH). The duration of transient regimes was again less than one grid cycle. Moreover, there are no significant tracking errors in the transient regimes associated with current reference changes, and the tracking error tends to a residual value in steady state in all scenarios, with values on the order of 10−6.
•A systematic procedure for parametrization of current controller of grid-tied power systems based on the Tasmanian devil optimization algorithm.•An optimized current controller that ensures energy quality and stability even in weak grid conditions.•An improved controller that is able to deal with harsh grid uncertainties with variation of more than 30 times its nominal inductance. |
ArticleNumber | 111041 |
Author | Leston, Luciano Anacker de Oliveira Evald, Paulo Jefferson Dias da Silva, Mateus Santos Hollweg, Guilherme Vieira |
Author_xml | – sequence: 1 givenname: Mateus Santos surname: da Silva fullname: da Silva, Mateus Santos organization: Intelligent Systems and Control Group, Federal University of Pelotas, Pelotas, Brazil – sequence: 2 givenname: Guilherme Vieira surname: Hollweg fullname: Hollweg, Guilherme Vieira organization: Department of Electrical and Computer Engineering, University of Michigan-Dearborn, Dearborn, USA – sequence: 3 givenname: Luciano Anacker surname: Leston fullname: Leston, Luciano Anacker organization: Intelligent Systems and Control Group, Federal University of Pelotas, Pelotas, Brazil – sequence: 4 givenname: Paulo Jefferson Dias orcidid: 0000-0002-5383-053X surname: de Oliveira Evald fullname: de Oliveira Evald, Paulo Jefferson Dias email: paulo.evald@ufpel.edu.br organization: Intelligent Systems and Control Group, Federal University of Pelotas, Pelotas, Brazil |
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Keywords | Renewable energy systems Tasmanian devil optimization algorithm PI-RMRAC LCL filter Robust adaptive control Meta-heuristic optimization |
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SubjectTerms | LCL filter Meta-heuristic optimization PI-RMRAC Renewable energy systems Robust adaptive control Tasmanian devil optimization algorithm |
Title | Enhancing energy quality and grid stability with improved adaptive controller for renewable energy conversion systems under weak grid conditions |
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