Adaptive Extremum Seeking Control of Urban Area Wind Turbines

Maximum-power point tracking of wind turbines is a challenging issue considering fast changing wind conditions of urban areas. For this purpose, an adaptive control approach that is fast and robust is required. Conventional approaches based on simple step perturbations and subsequent observation, ho...
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Autor*in:	Felix Dietrich [verfasserIn] Steffen Borchers-Tigasson [verfasserIn] Till Naumann [verfasserIn] Horst Schulte [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	adaptive control control of renewable energy resources extremum seeking control

Übergeordnetes Werk:	In: Energies - MDPI AG, 2008, 14(2021), 5, p 1356
Übergeordnetes Werk:	volume:14 ; year:2021 ; number:5, p 1356

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/en14051356

Katalog-ID:	DOAJ084694408

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spelling	10.3390/en14051356 doi (DE-627)DOAJ084694408 (DE-599)DOAJ9de03f33b7bc4bb9be4d07191675ef36 DE-627 ger DE-627 rakwb eng Felix Dietrich verfasserin aut Adaptive Extremum Seeking Control of Urban Area Wind Turbines 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Maximum-power point tracking of wind turbines is a challenging issue considering fast changing wind conditions of urban areas. For this purpose, an adaptive control approach that is fast and robust is required. Conventional approaches based on simple step perturbations and subsequent observation, however, are difficult to design and too slow for the demanding wind conditions of urban areas including gusts and turbulence. In this paper, an extremum seeking control scheme to the recently developed wind turbine MOWEA (Modulare Windenergieanlagen GmbH) is proposed and successfully applied. To this end, a comprehensive aero-electromechanical model of the wind turbine under study including basic control is formulated. Next, the extremum seeking control scheme is adapted to the system. Several aspects to increase adaptation speed are highlighted, including a novel phase compensation. Finally, a validation of the proposed approach is performed considering real wind data, thus demonstrating its fast and robust adaptability. The proposed control scheme is computationally efficient and can be easily implemented on the existing onboard electronics. adaptive control control of renewable energy resources extremum seeking control Technology T Steffen Borchers-Tigasson verfasserin aut Till Naumann verfasserin aut Horst Schulte verfasserin aut In Energies MDPI AG, 2008 14(2021), 5, p 1356 (DE-627)572083742 (DE-600)2437446-5 19961073 nnns volume:14 year:2021 number:5, p 1356 https://doi.org/10.3390/en14051356 kostenfrei https://doaj.org/article/9de03f33b7bc4bb9be4d07191675ef36 kostenfrei https://www.mdpi.com/1996-1073/14/5/1356 kostenfrei https://doaj.org/toc/1996-1073 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2021 5, p 1356
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allfieldsGer	10.3390/en14051356 doi (DE-627)DOAJ084694408 (DE-599)DOAJ9de03f33b7bc4bb9be4d07191675ef36 DE-627 ger DE-627 rakwb eng Felix Dietrich verfasserin aut Adaptive Extremum Seeking Control of Urban Area Wind Turbines 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Maximum-power point tracking of wind turbines is a challenging issue considering fast changing wind conditions of urban areas. For this purpose, an adaptive control approach that is fast and robust is required. Conventional approaches based on simple step perturbations and subsequent observation, however, are difficult to design and too slow for the demanding wind conditions of urban areas including gusts and turbulence. In this paper, an extremum seeking control scheme to the recently developed wind turbine MOWEA (Modulare Windenergieanlagen GmbH) is proposed and successfully applied. To this end, a comprehensive aero-electromechanical model of the wind turbine under study including basic control is formulated. Next, the extremum seeking control scheme is adapted to the system. Several aspects to increase adaptation speed are highlighted, including a novel phase compensation. Finally, a validation of the proposed approach is performed considering real wind data, thus demonstrating its fast and robust adaptability. The proposed control scheme is computationally efficient and can be easily implemented on the existing onboard electronics. adaptive control control of renewable energy resources extremum seeking control Technology T Steffen Borchers-Tigasson verfasserin aut Till Naumann verfasserin aut Horst Schulte verfasserin aut In Energies MDPI AG, 2008 14(2021), 5, p 1356 (DE-627)572083742 (DE-600)2437446-5 19961073 nnns volume:14 year:2021 number:5, p 1356 https://doi.org/10.3390/en14051356 kostenfrei https://doaj.org/article/9de03f33b7bc4bb9be4d07191675ef36 kostenfrei https://www.mdpi.com/1996-1073/14/5/1356 kostenfrei https://doaj.org/toc/1996-1073 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2021 5, p 1356
allfieldsSound	10.3390/en14051356 doi (DE-627)DOAJ084694408 (DE-599)DOAJ9de03f33b7bc4bb9be4d07191675ef36 DE-627 ger DE-627 rakwb eng Felix Dietrich verfasserin aut Adaptive Extremum Seeking Control of Urban Area Wind Turbines 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Maximum-power point tracking of wind turbines is a challenging issue considering fast changing wind conditions of urban areas. For this purpose, an adaptive control approach that is fast and robust is required. Conventional approaches based on simple step perturbations and subsequent observation, however, are difficult to design and too slow for the demanding wind conditions of urban areas including gusts and turbulence. In this paper, an extremum seeking control scheme to the recently developed wind turbine MOWEA (Modulare Windenergieanlagen GmbH) is proposed and successfully applied. To this end, a comprehensive aero-electromechanical model of the wind turbine under study including basic control is formulated. Next, the extremum seeking control scheme is adapted to the system. Several aspects to increase adaptation speed are highlighted, including a novel phase compensation. Finally, a validation of the proposed approach is performed considering real wind data, thus demonstrating its fast and robust adaptability. The proposed control scheme is computationally efficient and can be easily implemented on the existing onboard electronics. adaptive control control of renewable energy resources extremum seeking control Technology T Steffen Borchers-Tigasson verfasserin aut Till Naumann verfasserin aut Horst Schulte verfasserin aut In Energies MDPI AG, 2008 14(2021), 5, p 1356 (DE-627)572083742 (DE-600)2437446-5 19961073 nnns volume:14 year:2021 number:5, p 1356 https://doi.org/10.3390/en14051356 kostenfrei https://doaj.org/article/9de03f33b7bc4bb9be4d07191675ef36 kostenfrei https://www.mdpi.com/1996-1073/14/5/1356 kostenfrei https://doaj.org/toc/1996-1073 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2021 5, p 1356
language	English
source	In Energies 14(2021), 5, p 1356 volume:14 year:2021 number:5, p 1356
sourceStr	In Energies 14(2021), 5, p 1356 volume:14 year:2021 number:5, p 1356
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	adaptive control control of renewable energy resources extremum seeking control Technology T
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container_title	Energies
authorswithroles_txt_mv	Felix Dietrich @@aut@@ Steffen Borchers-Tigasson @@aut@@ Till Naumann @@aut@@ Horst Schulte @@aut@@
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author	Felix Dietrich
spellingShingle	Felix Dietrich misc adaptive control misc control of renewable energy resources misc extremum seeking control misc Technology misc T Adaptive Extremum Seeking Control of Urban Area Wind Turbines
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topic_title	Adaptive Extremum Seeking Control of Urban Area Wind Turbines adaptive control control of renewable energy resources extremum seeking control
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title	Adaptive Extremum Seeking Control of Urban Area Wind Turbines
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title_auth	Adaptive Extremum Seeking Control of Urban Area Wind Turbines
abstract	Maximum-power point tracking of wind turbines is a challenging issue considering fast changing wind conditions of urban areas. For this purpose, an adaptive control approach that is fast and robust is required. Conventional approaches based on simple step perturbations and subsequent observation, however, are difficult to design and too slow for the demanding wind conditions of urban areas including gusts and turbulence. In this paper, an extremum seeking control scheme to the recently developed wind turbine MOWEA (Modulare Windenergieanlagen GmbH) is proposed and successfully applied. To this end, a comprehensive aero-electromechanical model of the wind turbine under study including basic control is formulated. Next, the extremum seeking control scheme is adapted to the system. Several aspects to increase adaptation speed are highlighted, including a novel phase compensation. Finally, a validation of the proposed approach is performed considering real wind data, thus demonstrating its fast and robust adaptability. The proposed control scheme is computationally efficient and can be easily implemented on the existing onboard electronics.
abstractGer	Maximum-power point tracking of wind turbines is a challenging issue considering fast changing wind conditions of urban areas. For this purpose, an adaptive control approach that is fast and robust is required. Conventional approaches based on simple step perturbations and subsequent observation, however, are difficult to design and too slow for the demanding wind conditions of urban areas including gusts and turbulence. In this paper, an extremum seeking control scheme to the recently developed wind turbine MOWEA (Modulare Windenergieanlagen GmbH) is proposed and successfully applied. To this end, a comprehensive aero-electromechanical model of the wind turbine under study including basic control is formulated. Next, the extremum seeking control scheme is adapted to the system. Several aspects to increase adaptation speed are highlighted, including a novel phase compensation. Finally, a validation of the proposed approach is performed considering real wind data, thus demonstrating its fast and robust adaptability. The proposed control scheme is computationally efficient and can be easily implemented on the existing onboard electronics.
abstract_unstemmed	Maximum-power point tracking of wind turbines is a challenging issue considering fast changing wind conditions of urban areas. For this purpose, an adaptive control approach that is fast and robust is required. Conventional approaches based on simple step perturbations and subsequent observation, however, are difficult to design and too slow for the demanding wind conditions of urban areas including gusts and turbulence. In this paper, an extremum seeking control scheme to the recently developed wind turbine MOWEA (Modulare Windenergieanlagen GmbH) is proposed and successfully applied. To this end, a comprehensive aero-electromechanical model of the wind turbine under study including basic control is formulated. Next, the extremum seeking control scheme is adapted to the system. Several aspects to increase adaptation speed are highlighted, including a novel phase compensation. Finally, a validation of the proposed approach is performed considering real wind data, thus demonstrating its fast and robust adaptability. The proposed control scheme is computationally efficient and can be easily implemented on the existing onboard electronics.
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title_short	Adaptive Extremum Seeking Control of Urban Area Wind Turbines
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