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Wake Interaction Modeling Using a Parallelized Free Vortex Wake Model

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Wake Interaction Modeling Using A Parallelized Free Vortex Wake Model Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Kelsey Shaler, M.S. Graduate Program in Mechanical Engineering The Ohio State University 2020 Dissertation Committee: Mei Zhuang, Co-advisor Krista M. Kecskemety, Co-advisor Datta V. Gaitonde Jen-Ping Chen Copyright by Kelsey Shaler 2020 Abstract Turbine-wake interactions pose significant challenges in the development of wind farms. These interactions can lead to an increase in wind energy cost through re- duction in wind farm power efficiency as well as a reduction of functional turbine lifetime. The overall objective of this work is to extend and assess a moderate- fidelity free vortex wake (FVW) model to capture turbine-wake interactions be- tween multiple turbines. Specific focus areas include: (1) analyzing the effects of turbine-wake interaction; (2) benchmarking of the model against experimental wind farm measurements; and (3) comparing wake interaction effects between the FVW model and a dynamic wake meandering (DWM) model. Results show that FVW produces an increased dynamic response in wake-influenced turbines than FAST.Farm, which is an important factor in fatigue life of turbine blades. Param- eter studies for various operating and layout conditions are performed. Analysis focuses on impact of wake interaction on wake structure, rotor power, and blade root bending moments. The parameter study shows expected power trends for all tested parameters. The effects of turbine-wake interactions are analyzed in terms ii of wake structure, rotor power, and structural response. The FVW model predicts increased unsteadiness in wake-influenced turbine rotor power and out-of-plane blade root bending moment. This could have implications for prediction of tur- bine life and suggests that the transient as well as average response of turbines should be considered to fully capture the effects of wake interaction. Comparisons between the FVW predictions and experimental measurements of relative rotor power are made over varying yaw angle and freestream velocity. Overall trends are predicted by the FVW approach, with less than 13% error on average when compared to wind farm measurements. These results indicate the FVW method is a useful tool for carrying out improved optimization of wind farms. iii Dedication To my parents, Steve and Robin, for their unconditional love, support, and encouragement. I could not have hoped for better parents or role models. iv Acknowledgments I would like to thank my advisor, Prof. Mei Zhuang, for her guidance and support on this project. I would also like to thank my co-advisor, Dr. Krista Kecskemety, for her time and assistance with this work. I would also like to thank Profs. Datta Gaitonde, Mo Samimy, and Jim Gregory for serving on my candidacy committee and Profs. Datta Gaitonde and Jen-Ping Chen for serving on my dissertation com- mittee. The results in Chapter 2 were produced with Dr. Krista Kecskemety and Dr. Jack McNamara as senior authors and is summarized in Shaler, Kecskemety, and McNamara, “Benchmarking of a Free Vortex Wake Model for Prediction of Wake Interactions,” Renewable Energy, V136, June 2019. I am deeply grateful for the financial support I have received for this work. The support from the National Science Foundation Graduate Research Fellowship Pro- gramming allowed me the freedom to conduct this research. This work was also supported in part by an allocation of computing time from the Ohio Supercomput- ing Center. I am grateful to all of my lab mates. Thank you to Emily Dreyer, Drs. Brent v Miller, Zach Riley, Rohit Deshmukh, Ben Grier, Steve Nogar, and everyone else. You were all always there to help and support me, and we had a few good times along the way. To everyone at NREL, thank you for the support and encouragement through- out this process. Without your kind words I’m not sure I would have had the resolve and confidence to push through. Thank you to my entire support system at Ohio State. To the WEGC ladies, thank you for helping me grow as a professional, as a person, and as a feminist. To the squad: Drs. Caroline, Elena, Rachel, and Sarahx2. I’m not sure I could have made it without you ladies. The workouts, wine nights, and laughter helped me through the hard times and I will always appreciate everything you’ve done for me. Andrew, thank you for the mid-day walks, singing emo songs with me, and bringing a bit of sparkle into my day. Kona and Olaf, thank you for the cuddles and unconditional love. Aaron, there are no words to describe how you have helped and supported me. Washing almost every pan I’ve used over the years; making me laugh; and always reminding me that I’m good enough, I’m smart enough, and gosh darn it people like me. For this and so much more, I am so thankful to have you in my life. Thank you to my family. To my mother, for encouraging me in everything I’ve ever wanted to do and being my best friend. To my father, for knowing me better than I know myself and insisting I would like physics and coding, as well as providing valuable insight throughout this whole journey. To Ross, nam ens vi optimum fuisse umquam fratrem me. And finally, I would like to thank every teacher who has ever influenced me. I have been truly blessed to have phenomenal educators through every step of my education. From preschool through graduate school, each of you has helped to shape me into the person I am. I know I would not be where I am today without you and I will forever be thankful for what you have given me. vii Vita 2011 . B.S. Mechanical Engineering, University of Maine 2016 . M.S. Mechanical Engineering, The Ohio State Univer- sity 2011 - 2016 . NSF GRFP Fellowship, The Ohio State University 2011 - 2012 . Graduate Research Assistant, The Ohio State Univer- sity 2014 - 2015 . Graduate Research Assistant, The Ohio State Univer- sity 2016 - 2017 . FAST Fellowship, The Ohio State University 2017 - 2018 . Graduate Research Assistant, The Ohio State Univer- sity 2018 - 2019 . Post-Doctoral Researcher, National Renewable Energy Laboratory 2019 - present . Research Engineer, National Renewable Energy Labo- ratory viii Publications Journal Publications Shaler, K., Jonkman, J., “FAST.Farm Development and Verification of Struc- tural Load Prediction Against Large Eddy Simulations”. Wind Energy, 2020. Sub- mitted. Doubrawa, P., Quon, E., Martinez-Tossas, L. A., Shaler, K., Debnath, M., Hamil- ton, N., et al., “Multi-model Validation of Single Wakes in Neutral and Stratified Atmospheric Conditions”. Wind Energy, 2020. Shaler, K., Kecskemety, K.M., and McNamara, J. J., “Benchmarking of a Free Vortex Wake Model for Prediction of Wake Interactions”. Renewable Energy, 2019. Robertson, A. N., Shaler, K., Sethuraman, L., Jonkman, J., “Sensitivity Analysis of Wind Characteristics and Turbine Properties on Wind Turbine Loads”. Wind Energy Science, 2019. ix Shaler, K., Debnath, M., Jonkman, J., Brugger, P., and Porte-Agel, F., “Vali- dation of FAST.Farm Against Full-Scale Turbine SCADA Data and LiDAR Wake Measurements for a Small Wind Farm”. Journal of Physics: Conference Series, 2020. Accepted. Martinez-Tossas, L. A., Branlard, E., Shaler, K., Vijayakumar, G., Ananthan, S., Sakievich, P., Jonkman. J., “Wind Turbine Wakes: High-Thrust Coefficient”. Journal of Physics: Conference Series, 2020. Accepted. Shaler, K., Jonkman, J., and Hamilton, N., “Spatial and Temporal Discretization Studies of Wake Meandering and Turbine Structural Response Using FAST.Farm”. Journal of Physics: Conference Series, 2019. Shaler, K., Branlard, E., Platt, A., and Jonkman, J., “Preliminary Introduction of a Free Vortex Wake Method Into OpenFAST”. Journal of Physics: Conference Series, 2019. Technical Reports Jonkman, J. and Shaler, K., “FAST.Farm User’s Guide and Theory Manual” NREL Technical Report, 2020. Submitted. x Shaler, K., Branlard, E., and Platt, A., “OLAF User’s Guide and Theory Man- ual”, NREL Technical Report, 2020. Submitted. Conference Publications and Presentations Shaler, K., Jonkman, J., Quon, E., and Hamilton, N., “Verification of FAST.Farm Structural Load Prediction Against Large Eddy Simulations”, Wind Energy Science Conference, June 17-20, Cork, Ireland, 2019. Shaler, K., Jonkman, J., Doubrawa, P., Hamilton, N., “FAST.Farm Response to Varying Inflow Conditions”, AIAA SciTech Wind Energy Conference, January 7-11, San Diego, CA, 2019. Shaler, K., Robertson, A. N., Sethuraman, L., Jonkman, J., “Assessment of Airfoil Property Sensitivity on Wind Turbine Extreme and Fatigue Loads”, AIAA SciTech Wind Energy Conference, January 7-11, San Diego, CA, 2019. Shaler, K., Kecskemety, K. M., Gogulapati, A., and McNamara, J. J., “Wind Farm Optimization Using a Free Vortex Wake Model”, AIAA SciTech 36th ASME Wind Energy Symposium, January 9-13, Kissimmee, FL, 2018. Shaler, K., Kecskemety, K. M., and McNamara, J. J., “Benchmarking of a Free xi Vortex Wake Model for Prediction of Wake Interactions”, AIAA SciTech 35th ASME Wind Energy Symposium, January 9-13, Grapevine, TX, 2017. Shaler, K., Kecskemety, K. M., and McNamara, J. J., “Wake Interaction Effects Using a Parallelized Free Vortex Wake Model”, AIAA SciTech 34rd ASME Wind Energy Symposium, January 4-8, San Diego, CA, AIAA2016-1520, 2016. Shaler, K., Kecskemety, K. M., and McNamara, J. J., “Preliminary Study of Wake Interaction Effects Using a Free Vortex Wake Model”, AIAA SciTech 33rd ASME Wind Energy Symposium, January 5-9, Kissimmee, FL, AIAA2015-0686, 2015. Shaler, K. and Gaitonde, D. V., “Flow Control of a Retreating Airfoil via NS- DBD Actuators Using Large Eddy Simulations”, 4th ASME Joint US-European Flu- ids Engineering Summer Meeting, August 3-7, Chicago, IL, 2014. Shaler, K., “Characterization of Sharp-Edged Airfoils Using Large Eddy Simu- lations”, 21st AIAA Computational Fluid Dynamics Conference, June 24-27, San Diego, CA, 2013.
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