Adaptive envelope protection control of wind turbines under varying operational conditions. (15th May 2022)
- Record Type:
- Journal Article
- Title:
- Adaptive envelope protection control of wind turbines under varying operational conditions. (15th May 2022)
- Main Title:
- Adaptive envelope protection control of wind turbines under varying operational conditions
- Authors:
- Sahin, Mustafa
Yavrucuk, Ilkay - Abstract:
- Abstract: This study introduces a new Envelope Protection System (EPS) algorithm for wind turbines. The algorithm is adaptive to turbine-changing operational conditions and can effectively reduce turbine excessive/ultimate loads. Through an adaptive neural network, the proposed algorithm continuously monitors instantaneous wind and turbine states. Simultaneously, it predicts the near future response of the turbine load and detects its future crossing with a predefined safe envelope limit by comparing the actual wind speed to a theoretically estimated wind speed. When required, a protection action is applied based on the comparison to keep the turbine load response within the safe limit. In this paper, the thrust force is used as the critical load and is chosen as the limit parameter. Simulations are carried out using the MS (Mustafa Sahin) Bladed Wind Turbine Simulation Model for the National Renewable Energy Laboratory (NREL) 5 MW turbine under normal turbulent winds with different mean values. Simulations show that the EPS algorithm adapts to varying operational conditions such as changes in turbine operating point in the below rated, transition, and above rated regions, as well as rotor blade icing and successfully reduces the excessive thrust forces. Performance analyses indicate that, for keeping the thrust force within the limit, the proposed EPS algorithm reduces the thrust force by 98.89%, 98.43%, 99.26% relative to standard baseline controls in the aforementionedAbstract: This study introduces a new Envelope Protection System (EPS) algorithm for wind turbines. The algorithm is adaptive to turbine-changing operational conditions and can effectively reduce turbine excessive/ultimate loads. Through an adaptive neural network, the proposed algorithm continuously monitors instantaneous wind and turbine states. Simultaneously, it predicts the near future response of the turbine load and detects its future crossing with a predefined safe envelope limit by comparing the actual wind speed to a theoretically estimated wind speed. When required, a protection action is applied based on the comparison to keep the turbine load response within the safe limit. In this paper, the thrust force is used as the critical load and is chosen as the limit parameter. Simulations are carried out using the MS (Mustafa Sahin) Bladed Wind Turbine Simulation Model for the National Renewable Energy Laboratory (NREL) 5 MW turbine under normal turbulent winds with different mean values. Simulations show that the EPS algorithm adapts to varying operational conditions such as changes in turbine operating point in the below rated, transition, and above rated regions, as well as rotor blade icing and successfully reduces the excessive thrust forces. Performance analyses indicate that, for keeping the thrust force within the limit, the proposed EPS algorithm reduces the thrust force by 98.89%, 98.43%, 99.26% relative to standard baseline controls in the aforementioned regions, respectively and by 99.61% under blade icing. Also, the mean value and the fluctuations of thrust force are reduced up to 5.52% and 68.7%, respectively. Depending on the operating region, the mean power decreases up to 2.07% or increases up to 1.21%, while power fluctuations decrease up to 30.97%. Highlights: The MS Bladed Model is briefly defined and example validations are presented. Baseline controllers are designed, validated and simulated for the NREL 5 MW turbine. Envelope Protection System (EPS) concept and adaptive EPS theory are defined. Adaptive EPS is designed and implemented for the controlled NREL 5 MW turbine. Adaptive EPS is simulated at various regions under varying operating point and icing. … (more)
- Is Part Of:
- Energy. Volume 247(2022)
- Journal:
- Energy
- Issue:
- Volume 247(2022)
- Issue Display:
- Volume 247, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 247
- Issue:
- 2022
- Issue Sort Value:
- 2022-0247-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-05-15
- Subjects:
- Envelope protection control -- Ultimate load reduction -- Excessive thrust force -- Adaptive neural network -- Blade icing -- MS Bladed wind turbine simulation model
Power resources -- Periodicals
Power (Mechanics) -- Periodicals
Energy consumption -- Periodicals
333.7905 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.energy.2022.123544 ↗
- Languages:
- English
- ISSNs:
- 0360-5442
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.445000
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