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Research Papers

Equalizing Aerodynamic Blade Loads Through Individual Pitch Control Via Multiblade Multilag Transformation

[+] Author and Article Information
Stefano Cacciola

Department of Aerospace Science
and Technology,
Politecnico di Milano,
Milano 20156, Italy
e-mail: stefano.cacciola@polimi.it

Carlo E.D. Riboldi

Department of Aerospace Science
and Technology,
Politecnico di Milano,
Milano 20156, Italy
e-mail: carlo.riboldi@polimi.it

Contributed by the Solar Energy Division of ASME for publication in the JOURNAL OF SOLAR ENERGY ENGINEERING: INCLUDING WIND ENERGY AND BUILDING ENERGY CONSERVATION. Manuscript received October 28, 2016; final manuscript received August 14, 2017; published online September 28, 2017. Assoc. Editor: Yves Gagnon.

J. Sol. Energy Eng 139(6), 061008 (Sep 28, 2017) (8 pages) Paper No: SOL-16-1461; doi: 10.1115/1.4037744 History: Received October 28, 2016; Revised August 14, 2017

Control algorithms for rotor load mitigation are today generally adopted by industry. Most of them are based on the Coleman transformation, which is easy to implement and bears satisfactory results when the rotor is balanced. A multitude of causes, e.g., blade erosion, dirt, and especially pitch misalignment, may create significant imbalances. This gives birth to undesirable vibrations and reduced control performance in terms of load mitigation. In this paper, an alternative transformation is introduced, able to detect and quantify the rotor load harmonics due to aerodynamic imbalance. Next, a control algorithm, capable of targeting rotor imbalance itself and simultaneously lowering rotor loads, is presented. The effectiveness of the proposed solution is confirmed through simulations in virtual environment.

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Copyright © 2017 by ASME
Topics: Stress , Blades , Rotors , Signals
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References

Bossanyi, E. , 2003, “ Wind Turbine Control for Load Reduction,” Wind Energy, 6(3), pp. 229–244. [CrossRef]
Bossanyi, E. , 2003, “ Individual Blade Pitch Control for Load Reduction,” Wind Energy, 6(2), pp. 119–128. [CrossRef]
Bossanyi, E. , 2004, “ Developments in Individual Blade Pitch Control,” The Science of Making Torque From Wind Conference, Delft, The Netherlands, Apr. 19–21, pp. 486–497.
Bossanyi, E. , 2005, “ Further Load Reductions With Individual Pitch Control,” Wind Energy, 8(4), pp. 481–485. [CrossRef]
Bottasso, C. L. , Croce, A. , Riboldi, C. E. D. , and Nam, Y. , 2013, “ Multi-Layer Control Architecture for the Reduction of Deterministic and Non-Deterministic Loads on Wind Turbines,” Renewable Energy, 51, pp. 159–169. [CrossRef]
Bottasso, C. L. , Croce, A. , Riboldi, C. E. D. , and Salvetti, M. , 2014, “ Cyclic Pitch Control for the Reduction of Ultimate Loads on Wind Turbines,” J. Phys. Conf. Ser., 524(1), p. 012063. [CrossRef]
Geyler, M. , and Caselitz, P. , 2007, “ Individual Blade Pitch Control Design for Load Reduction on Large Wind Turbines,” European Wind Energy Conference (EWEC), Milan, Italy, May 7–10, pp. 82–86.
Leithead, W. E. , Neilson, V. , and Dominguez, S. , 2009, “ Alleviation of Unbalanced Rotor Loads by Single Blade Controllers,” European Wind Energy Conference (EWEC), Marseille, France, Mar. 16–19, pp. 576–615.
Kanev, S. , and Van Engelen, T. G. , 2009, “ Exploring the Limits in Individual Pitch Control,” European Wind Energy Conference (EWEC), Marseille, France, Mar. 16–19, pp. 1–10.
Riboldi, C. E. D. , 2016, “ On the Optimal Tuning of Individual Pitch Control for Horizontal Axis Wind Turbines,” Wind Eng., 40(4), pp. 398–416.
Riboldi, C. E. D. , 2012, “ Advanced Control Laws for Variable Speed Wind Turbines and Supporting Enabling Technologies,” Ph.D. thesis, Politecnico di Milano, Milan, Italy.
Cacciola, S. , Munduate Agud, I. , and Bottasso, C. L. , 2016, “ Detection of Rotor Imbalance, Including Root Cause, Severity and Location,” J. Phys.: Conf. Ser., 753(7), p. 072003. [CrossRef]
Petrović, V. , Jelavić, M. , and Baotić, M. , 2014, “ Advanced Control Algorithms for Reduction of Wind Turbine Structural Loads,” Renewable Energy, 76, pp. 418–431. [CrossRef]
Bottasso, C. L. , Cacciola, S. , and Schreiber, J. , 2015, “ A Wake Detector for Wind Farm Control,” J. Phys.: Conf. Ser., 625(1), p. 012007. [CrossRef]
Jonkman, J. M. , and Buhl, M. , 2005, “ FAST User's Guide,” National Renewable Energy Laboratory, Boulder, CO.
IEC, 2005, “ Wind Turbines—Part 1: Design Requirements,” International Electrotechnical Commission, Geneva, Switzerland, Standard No. IEC61400-1.
Bottasso, C. L. , Croce, A. , Riboldi, C. E. D. , and Nam, Y. , 2012, “ Power Curve Tracking in the Presence of a Tip Speed Constraint,” Renewable Energy, 40(1), pp. 1–12. [CrossRef]
Bottasso, C. L. , and Cacciola, S. , 2014, “ Model-Independent Periodic Stability Analysis of Wind Turbines,” Wind Energy, 18(5), pp. 865–887. [CrossRef]
Riboldi, C. E. D. , and Cacciola, S. , 2017, “ Individual Pitch Control for Two-Bladed Wind Turbines Via Multi-Blade Multi-Lag Transformation,” Wind Energy, accepted.

Figures

Grahic Jump Location
Fig. 1

Rotor positions for a generic MBML transformation, left, for C1,π/33, center, and C2,2π/93, right

Grahic Jump Location
Fig. 2

Cyclic, equalizing, and collective misalignment compensating control scheme

Grahic Jump Location
Fig. 3

Comparison of nodding and yawing moments in NWP conditions. (a) 7 m/s and (b) 15 m/s. Green solid: no pitch imbalance. Yellow dashed: pitch imbalance, only trimmer. Purple dashed–dotted: pitch imbalance, trimmer, MBML-based equalizer.

Grahic Jump Location
Fig. 4

Comparison of blade pitch in NWP conditions. (a) 7 m/s and (b) 15 m/s. Green solid: no pitch imbalance. Yellow dashed: pitch imbalance, only trimmer. Purple dashed–dotted: pitch imbalance, trimmer, and MBML-based equalizer.

Grahic Jump Location
Fig. 5

Comparison of nodding and yawing moments in Cat. A turbulent conditions. Average wind: (a) 7 m/s and (b) 15 m/s. Green solid: no pitch imbalance. Yellow dashed: pitch imbalance, only trimmer. Purple dashed–dotted: pitch imbalance, trimmer, MBML-based equalizer.

Grahic Jump Location
Fig. 6

Comparison of nodding and yawing moments in NWP conditions with different controllers for load mitigation at 15 m/s. Green solid: no pitch misalignment, Coleman-based cyclic control. Yellow dashed: pitch misalignment, Coleman-based cyclic control. Purple dashed–dotted: pitch misalignment, MBML-based cyclic control and pitch equalizer.

Grahic Jump Location
Fig. 7

Comparison of nodding and yawing moments in Cat. A turbulent conditions with different controllers for load mitigation at 15 m/s average. Green solid: no pitch misalignment, Coleman-based cyclic control. Yellow dashed: pitch misalignment, Coleman-based cyclic control. Purple dashed–dotted: pitch misalignment, MBML-based cyclic control and pitch equalizer.

Grahic Jump Location
Fig. 8

Blade pitches in Cat. A turbulent conditions with different controllers for load mitigation at 15 m/s average. Green, yellow, and purple: blades 1, 2, and 3. Top plot, solid lines: no pitch misalignment, Coleman-based cyclic control. Middle plot, dashed: pitch misalignment, Coleman-based cyclic control. Bottom plot, dashed–dotted: pitch misalignment, MBML-based cyclic control and pitch equalizer.

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