On addressing wind turbine noise with after-market shape blade add-ons
When stricter noise limits are enforced to legacy wind turbines already deployed, actions need to be taken. In this paper, we present a solution of retrofitting wind turbine blades with additional outer layer skins that change their aeroacoustic footprint. An optimization design framework produces a...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Rodrigues, S.S. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019transfer abstract |
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| Schlagwörter: |
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| Umfang: |
13 |
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| Übergeordnetes Werk: |
Enthalten in: Technologies and practice of CO - HU, Yongle ELSEVIER, 2019, an international journal : the official journal of WREN, The World Renewable Energy Network, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:140 ; year:2019 ; pages:602-614 ; extent:13 |
| Links: |
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| DOI / URN: |
10.1016/j.renene.2019.03.056 |
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| Katalog-ID: |
ELV046408835 |
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| 520 | |a When stricter noise limits are enforced to legacy wind turbines already deployed, actions need to be taken. In this paper, we present a solution of retrofitting wind turbine blades with additional outer layer skins that change their aeroacoustic footprint. An optimization design framework produces add-ons shapes that, when attached to blades, reduce their noise without compromising aerodynamic performance. The Blade Element Momentum theory is used to predict the aerodynamic performance and generated noise is predicted using semi-empirical models. Two competing metrics are analyzed, Annual Energy Production and Overall Sound Pressure Level, using a multi-objective genetic algorithm. The add-on shapes are parameterized using NURBS totaling 54 design variables. The AOC 15/50 wind turbine is used as a test case and optimal solutions selected from the Pareto front are discussed. The after-market add-on approach produces solutions that range from an increase of 8.7% in energy production to a decrease of 3.5 dB(A) in noise levels, with an estimated blade weight increase of less than 4%. While the add-on approaches typically fall short in terms of performance when compared to a new blade design, this retrofiting is expected to be a competitive alternative when compared to the cost of replacing the whole blade. | ||
| 520 | |a When stricter noise limits are enforced to legacy wind turbines already deployed, actions need to be taken. In this paper, we present a solution of retrofitting wind turbine blades with additional outer layer skins that change their aeroacoustic footprint. An optimization design framework produces add-ons shapes that, when attached to blades, reduce their noise without compromising aerodynamic performance. The Blade Element Momentum theory is used to predict the aerodynamic performance and generated noise is predicted using semi-empirical models. Two competing metrics are analyzed, Annual Energy Production and Overall Sound Pressure Level, using a multi-objective genetic algorithm. The add-on shapes are parameterized using NURBS totaling 54 design variables. The AOC 15/50 wind turbine is used as a test case and optimal solutions selected from the Pareto front are discussed. The after-market add-on approach produces solutions that range from an increase of 8.7% in energy production to a decrease of 3.5 dB(A) in noise levels, with an estimated blade weight increase of less than 4%. While the add-on approaches typically fall short in terms of performance when compared to a new blade design, this retrofiting is expected to be a competitive alternative when compared to the cost of replacing the whole blade. | ||
| 650 | 7 | |a Noise reduction |2 Elsevier | |
| 650 | 7 | |a Retrofitting |2 Elsevier | |
| 650 | 7 | |a Multi-objective optimization |2 Elsevier | |
| 650 | 7 | |a Aeroacoustic analysis |2 Elsevier | |
| 650 | 7 | |a Airfoil self-noise |2 Elsevier | |
| 650 | 7 | |a Design optimization |2 Elsevier | |
| 700 | 1 | |a Marta, A.C. |4 oth | |
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10.1016/j.renene.2019.03.056 doi GBV00000000000711.pica (DE-627)ELV046408835 (ELSEVIER)S0960-1481(19)30361-1 DE-627 ger DE-627 rakwb eng Rodrigues, S.S. verfasserin aut On addressing wind turbine noise with after-market shape blade add-ons 2019transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier When stricter noise limits are enforced to legacy wind turbines already deployed, actions need to be taken. In this paper, we present a solution of retrofitting wind turbine blades with additional outer layer skins that change their aeroacoustic footprint. An optimization design framework produces add-ons shapes that, when attached to blades, reduce their noise without compromising aerodynamic performance. The Blade Element Momentum theory is used to predict the aerodynamic performance and generated noise is predicted using semi-empirical models. Two competing metrics are analyzed, Annual Energy Production and Overall Sound Pressure Level, using a multi-objective genetic algorithm. The add-on shapes are parameterized using NURBS totaling 54 design variables. The AOC 15/50 wind turbine is used as a test case and optimal solutions selected from the Pareto front are discussed. The after-market add-on approach produces solutions that range from an increase of 8.7% in energy production to a decrease of 3.5 dB(A) in noise levels, with an estimated blade weight increase of less than 4%. While the add-on approaches typically fall short in terms of performance when compared to a new blade design, this retrofiting is expected to be a competitive alternative when compared to the cost of replacing the whole blade. When stricter noise limits are enforced to legacy wind turbines already deployed, actions need to be taken. In this paper, we present a solution of retrofitting wind turbine blades with additional outer layer skins that change their aeroacoustic footprint. An optimization design framework produces add-ons shapes that, when attached to blades, reduce their noise without compromising aerodynamic performance. The Blade Element Momentum theory is used to predict the aerodynamic performance and generated noise is predicted using semi-empirical models. Two competing metrics are analyzed, Annual Energy Production and Overall Sound Pressure Level, using a multi-objective genetic algorithm. The add-on shapes are parameterized using NURBS totaling 54 design variables. The AOC 15/50 wind turbine is used as a test case and optimal solutions selected from the Pareto front are discussed. The after-market add-on approach produces solutions that range from an increase of 8.7% in energy production to a decrease of 3.5 dB(A) in noise levels, with an estimated blade weight increase of less than 4%. While the add-on approaches typically fall short in terms of performance when compared to a new blade design, this retrofiting is expected to be a competitive alternative when compared to the cost of replacing the whole blade. Noise reduction Elsevier Retrofitting Elsevier Multi-objective optimization Elsevier Aeroacoustic analysis Elsevier Airfoil self-noise Elsevier Design optimization Elsevier Marta, A.C. oth Enthalten in Elsevier Science HU, Yongle ELSEVIER Technologies and practice of CO 2019 an international journal : the official journal of WREN, The World Renewable Energy Network Amsterdam [u.a.] (DE-627)ELV002723662 volume:140 year:2019 pages:602-614 extent:13 https://doi.org/10.1016/j.renene.2019.03.056 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 140 2019 602-614 13 |
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10.1016/j.renene.2019.03.056 doi GBV00000000000711.pica (DE-627)ELV046408835 (ELSEVIER)S0960-1481(19)30361-1 DE-627 ger DE-627 rakwb eng Rodrigues, S.S. verfasserin aut On addressing wind turbine noise with after-market shape blade add-ons 2019transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier When stricter noise limits are enforced to legacy wind turbines already deployed, actions need to be taken. In this paper, we present a solution of retrofitting wind turbine blades with additional outer layer skins that change their aeroacoustic footprint. An optimization design framework produces add-ons shapes that, when attached to blades, reduce their noise without compromising aerodynamic performance. The Blade Element Momentum theory is used to predict the aerodynamic performance and generated noise is predicted using semi-empirical models. Two competing metrics are analyzed, Annual Energy Production and Overall Sound Pressure Level, using a multi-objective genetic algorithm. The add-on shapes are parameterized using NURBS totaling 54 design variables. The AOC 15/50 wind turbine is used as a test case and optimal solutions selected from the Pareto front are discussed. The after-market add-on approach produces solutions that range from an increase of 8.7% in energy production to a decrease of 3.5 dB(A) in noise levels, with an estimated blade weight increase of less than 4%. While the add-on approaches typically fall short in terms of performance when compared to a new blade design, this retrofiting is expected to be a competitive alternative when compared to the cost of replacing the whole blade. When stricter noise limits are enforced to legacy wind turbines already deployed, actions need to be taken. In this paper, we present a solution of retrofitting wind turbine blades with additional outer layer skins that change their aeroacoustic footprint. An optimization design framework produces add-ons shapes that, when attached to blades, reduce their noise without compromising aerodynamic performance. The Blade Element Momentum theory is used to predict the aerodynamic performance and generated noise is predicted using semi-empirical models. Two competing metrics are analyzed, Annual Energy Production and Overall Sound Pressure Level, using a multi-objective genetic algorithm. The add-on shapes are parameterized using NURBS totaling 54 design variables. The AOC 15/50 wind turbine is used as a test case and optimal solutions selected from the Pareto front are discussed. The after-market add-on approach produces solutions that range from an increase of 8.7% in energy production to a decrease of 3.5 dB(A) in noise levels, with an estimated blade weight increase of less than 4%. While the add-on approaches typically fall short in terms of performance when compared to a new blade design, this retrofiting is expected to be a competitive alternative when compared to the cost of replacing the whole blade. Noise reduction Elsevier Retrofitting Elsevier Multi-objective optimization Elsevier Aeroacoustic analysis Elsevier Airfoil self-noise Elsevier Design optimization Elsevier Marta, A.C. oth Enthalten in Elsevier Science HU, Yongle ELSEVIER Technologies and practice of CO 2019 an international journal : the official journal of WREN, The World Renewable Energy Network Amsterdam [u.a.] (DE-627)ELV002723662 volume:140 year:2019 pages:602-614 extent:13 https://doi.org/10.1016/j.renene.2019.03.056 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 140 2019 602-614 13 |
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10.1016/j.renene.2019.03.056 doi GBV00000000000711.pica (DE-627)ELV046408835 (ELSEVIER)S0960-1481(19)30361-1 DE-627 ger DE-627 rakwb eng Rodrigues, S.S. verfasserin aut On addressing wind turbine noise with after-market shape blade add-ons 2019transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier When stricter noise limits are enforced to legacy wind turbines already deployed, actions need to be taken. In this paper, we present a solution of retrofitting wind turbine blades with additional outer layer skins that change their aeroacoustic footprint. An optimization design framework produces add-ons shapes that, when attached to blades, reduce their noise without compromising aerodynamic performance. The Blade Element Momentum theory is used to predict the aerodynamic performance and generated noise is predicted using semi-empirical models. Two competing metrics are analyzed, Annual Energy Production and Overall Sound Pressure Level, using a multi-objective genetic algorithm. The add-on shapes are parameterized using NURBS totaling 54 design variables. The AOC 15/50 wind turbine is used as a test case and optimal solutions selected from the Pareto front are discussed. The after-market add-on approach produces solutions that range from an increase of 8.7% in energy production to a decrease of 3.5 dB(A) in noise levels, with an estimated blade weight increase of less than 4%. While the add-on approaches typically fall short in terms of performance when compared to a new blade design, this retrofiting is expected to be a competitive alternative when compared to the cost of replacing the whole blade. When stricter noise limits are enforced to legacy wind turbines already deployed, actions need to be taken. In this paper, we present a solution of retrofitting wind turbine blades with additional outer layer skins that change their aeroacoustic footprint. An optimization design framework produces add-ons shapes that, when attached to blades, reduce their noise without compromising aerodynamic performance. The Blade Element Momentum theory is used to predict the aerodynamic performance and generated noise is predicted using semi-empirical models. Two competing metrics are analyzed, Annual Energy Production and Overall Sound Pressure Level, using a multi-objective genetic algorithm. The add-on shapes are parameterized using NURBS totaling 54 design variables. The AOC 15/50 wind turbine is used as a test case and optimal solutions selected from the Pareto front are discussed. The after-market add-on approach produces solutions that range from an increase of 8.7% in energy production to a decrease of 3.5 dB(A) in noise levels, with an estimated blade weight increase of less than 4%. While the add-on approaches typically fall short in terms of performance when compared to a new blade design, this retrofiting is expected to be a competitive alternative when compared to the cost of replacing the whole blade. Noise reduction Elsevier Retrofitting Elsevier Multi-objective optimization Elsevier Aeroacoustic analysis Elsevier Airfoil self-noise Elsevier Design optimization Elsevier Marta, A.C. oth Enthalten in Elsevier Science HU, Yongle ELSEVIER Technologies and practice of CO 2019 an international journal : the official journal of WREN, The World Renewable Energy Network Amsterdam [u.a.] (DE-627)ELV002723662 volume:140 year:2019 pages:602-614 extent:13 https://doi.org/10.1016/j.renene.2019.03.056 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 140 2019 602-614 13 |
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10.1016/j.renene.2019.03.056 doi GBV00000000000711.pica (DE-627)ELV046408835 (ELSEVIER)S0960-1481(19)30361-1 DE-627 ger DE-627 rakwb eng Rodrigues, S.S. verfasserin aut On addressing wind turbine noise with after-market shape blade add-ons 2019transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier When stricter noise limits are enforced to legacy wind turbines already deployed, actions need to be taken. In this paper, we present a solution of retrofitting wind turbine blades with additional outer layer skins that change their aeroacoustic footprint. An optimization design framework produces add-ons shapes that, when attached to blades, reduce their noise without compromising aerodynamic performance. The Blade Element Momentum theory is used to predict the aerodynamic performance and generated noise is predicted using semi-empirical models. Two competing metrics are analyzed, Annual Energy Production and Overall Sound Pressure Level, using a multi-objective genetic algorithm. The add-on shapes are parameterized using NURBS totaling 54 design variables. The AOC 15/50 wind turbine is used as a test case and optimal solutions selected from the Pareto front are discussed. The after-market add-on approach produces solutions that range from an increase of 8.7% in energy production to a decrease of 3.5 dB(A) in noise levels, with an estimated blade weight increase of less than 4%. While the add-on approaches typically fall short in terms of performance when compared to a new blade design, this retrofiting is expected to be a competitive alternative when compared to the cost of replacing the whole blade. When stricter noise limits are enforced to legacy wind turbines already deployed, actions need to be taken. In this paper, we present a solution of retrofitting wind turbine blades with additional outer layer skins that change their aeroacoustic footprint. An optimization design framework produces add-ons shapes that, when attached to blades, reduce their noise without compromising aerodynamic performance. The Blade Element Momentum theory is used to predict the aerodynamic performance and generated noise is predicted using semi-empirical models. Two competing metrics are analyzed, Annual Energy Production and Overall Sound Pressure Level, using a multi-objective genetic algorithm. The add-on shapes are parameterized using NURBS totaling 54 design variables. The AOC 15/50 wind turbine is used as a test case and optimal solutions selected from the Pareto front are discussed. The after-market add-on approach produces solutions that range from an increase of 8.7% in energy production to a decrease of 3.5 dB(A) in noise levels, with an estimated blade weight increase of less than 4%. While the add-on approaches typically fall short in terms of performance when compared to a new blade design, this retrofiting is expected to be a competitive alternative when compared to the cost of replacing the whole blade. Noise reduction Elsevier Retrofitting Elsevier Multi-objective optimization Elsevier Aeroacoustic analysis Elsevier Airfoil self-noise Elsevier Design optimization Elsevier Marta, A.C. oth Enthalten in Elsevier Science HU, Yongle ELSEVIER Technologies and practice of CO 2019 an international journal : the official journal of WREN, The World Renewable Energy Network Amsterdam [u.a.] (DE-627)ELV002723662 volume:140 year:2019 pages:602-614 extent:13 https://doi.org/10.1016/j.renene.2019.03.056 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 140 2019 602-614 13 |
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10.1016/j.renene.2019.03.056 doi GBV00000000000711.pica (DE-627)ELV046408835 (ELSEVIER)S0960-1481(19)30361-1 DE-627 ger DE-627 rakwb eng Rodrigues, S.S. verfasserin aut On addressing wind turbine noise with after-market shape blade add-ons 2019transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier When stricter noise limits are enforced to legacy wind turbines already deployed, actions need to be taken. In this paper, we present a solution of retrofitting wind turbine blades with additional outer layer skins that change their aeroacoustic footprint. An optimization design framework produces add-ons shapes that, when attached to blades, reduce their noise without compromising aerodynamic performance. The Blade Element Momentum theory is used to predict the aerodynamic performance and generated noise is predicted using semi-empirical models. Two competing metrics are analyzed, Annual Energy Production and Overall Sound Pressure Level, using a multi-objective genetic algorithm. The add-on shapes are parameterized using NURBS totaling 54 design variables. The AOC 15/50 wind turbine is used as a test case and optimal solutions selected from the Pareto front are discussed. The after-market add-on approach produces solutions that range from an increase of 8.7% in energy production to a decrease of 3.5 dB(A) in noise levels, with an estimated blade weight increase of less than 4%. While the add-on approaches typically fall short in terms of performance when compared to a new blade design, this retrofiting is expected to be a competitive alternative when compared to the cost of replacing the whole blade. When stricter noise limits are enforced to legacy wind turbines already deployed, actions need to be taken. In this paper, we present a solution of retrofitting wind turbine blades with additional outer layer skins that change their aeroacoustic footprint. An optimization design framework produces add-ons shapes that, when attached to blades, reduce their noise without compromising aerodynamic performance. The Blade Element Momentum theory is used to predict the aerodynamic performance and generated noise is predicted using semi-empirical models. Two competing metrics are analyzed, Annual Energy Production and Overall Sound Pressure Level, using a multi-objective genetic algorithm. The add-on shapes are parameterized using NURBS totaling 54 design variables. The AOC 15/50 wind turbine is used as a test case and optimal solutions selected from the Pareto front are discussed. The after-market add-on approach produces solutions that range from an increase of 8.7% in energy production to a decrease of 3.5 dB(A) in noise levels, with an estimated blade weight increase of less than 4%. While the add-on approaches typically fall short in terms of performance when compared to a new blade design, this retrofiting is expected to be a competitive alternative when compared to the cost of replacing the whole blade. Noise reduction Elsevier Retrofitting Elsevier Multi-objective optimization Elsevier Aeroacoustic analysis Elsevier Airfoil self-noise Elsevier Design optimization Elsevier Marta, A.C. oth Enthalten in Elsevier Science HU, Yongle ELSEVIER Technologies and practice of CO 2019 an international journal : the official journal of WREN, The World Renewable Energy Network Amsterdam [u.a.] (DE-627)ELV002723662 volume:140 year:2019 pages:602-614 extent:13 https://doi.org/10.1016/j.renene.2019.03.056 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U AR 140 2019 602-614 13 |
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on addressing wind turbine noise with after-market shape blade add-ons |
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When stricter noise limits are enforced to legacy wind turbines already deployed, actions need to be taken. In this paper, we present a solution of retrofitting wind turbine blades with additional outer layer skins that change their aeroacoustic footprint. An optimization design framework produces add-ons shapes that, when attached to blades, reduce their noise without compromising aerodynamic performance. The Blade Element Momentum theory is used to predict the aerodynamic performance and generated noise is predicted using semi-empirical models. Two competing metrics are analyzed, Annual Energy Production and Overall Sound Pressure Level, using a multi-objective genetic algorithm. The add-on shapes are parameterized using NURBS totaling 54 design variables. The AOC 15/50 wind turbine is used as a test case and optimal solutions selected from the Pareto front are discussed. The after-market add-on approach produces solutions that range from an increase of 8.7% in energy production to a decrease of 3.5 dB(A) in noise levels, with an estimated blade weight increase of less than 4%. While the add-on approaches typically fall short in terms of performance when compared to a new blade design, this retrofiting is expected to be a competitive alternative when compared to the cost of replacing the whole blade. |
| abstractGer |
When stricter noise limits are enforced to legacy wind turbines already deployed, actions need to be taken. In this paper, we present a solution of retrofitting wind turbine blades with additional outer layer skins that change their aeroacoustic footprint. An optimization design framework produces add-ons shapes that, when attached to blades, reduce their noise without compromising aerodynamic performance. The Blade Element Momentum theory is used to predict the aerodynamic performance and generated noise is predicted using semi-empirical models. Two competing metrics are analyzed, Annual Energy Production and Overall Sound Pressure Level, using a multi-objective genetic algorithm. The add-on shapes are parameterized using NURBS totaling 54 design variables. The AOC 15/50 wind turbine is used as a test case and optimal solutions selected from the Pareto front are discussed. The after-market add-on approach produces solutions that range from an increase of 8.7% in energy production to a decrease of 3.5 dB(A) in noise levels, with an estimated blade weight increase of less than 4%. While the add-on approaches typically fall short in terms of performance when compared to a new blade design, this retrofiting is expected to be a competitive alternative when compared to the cost of replacing the whole blade. |
| abstract_unstemmed |
When stricter noise limits are enforced to legacy wind turbines already deployed, actions need to be taken. In this paper, we present a solution of retrofitting wind turbine blades with additional outer layer skins that change their aeroacoustic footprint. An optimization design framework produces add-ons shapes that, when attached to blades, reduce their noise without compromising aerodynamic performance. The Blade Element Momentum theory is used to predict the aerodynamic performance and generated noise is predicted using semi-empirical models. Two competing metrics are analyzed, Annual Energy Production and Overall Sound Pressure Level, using a multi-objective genetic algorithm. The add-on shapes are parameterized using NURBS totaling 54 design variables. The AOC 15/50 wind turbine is used as a test case and optimal solutions selected from the Pareto front are discussed. The after-market add-on approach produces solutions that range from an increase of 8.7% in energy production to a decrease of 3.5 dB(A) in noise levels, with an estimated blade weight increase of less than 4%. While the add-on approaches typically fall short in terms of performance when compared to a new blade design, this retrofiting is expected to be a competitive alternative when compared to the cost of replacing the whole blade. |
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