Book

 

Journal Papers

  • [J-22] L. Gao, T. Dasari, J. Hong, Wind farm icing loss forecast pertinent to winter extremes, Sustain. Energy Technol. Assessments. 50 (2022) 101872. https://doi:10.1016/j.seta.2021.101872.  

  • [J-21] L. Gao, J. Hong. Data-driven yaw misalignment correction for utility-scale wind turbines. Journal of Renewable and Sustainable  Energy. 13 (2021) 063302. (Editor's pick) https://doi.org/10.1063/5.0056671

  • [J-20] L. Gao, H. Hu, Wind turbine icing characteristics and icing-induced power losses to utility-scale wind turbines, Proc. Natl. Acad. Sci. 118 (2021) e2111461118. https://doi:10.1073/pnas.2111461118 

  • [J-19] L. Swenson, L. Gao, J. Hong, L. Shen, An efficacious model for predicting icing-induced energy loss for wind turbines. Applied Energy. 305 (2022) 117809. https://doi:10.1016/j.apenergy.2021.117809

  • [J-18] T. Tao, Y. Liu, Y. Qiao, L. Gao, J. Lu, C. Zhang, Y. Wang, Wind turbine blade icing diagnosis using hybrid features and Stacked-XGBoost algorithm. Renewable Energy 180 (2021) 1004–1013. https://doi:10.1016/j.renene.2021.09.008

  • [J-17] L. Gao, B. Li, J. Hong. Effect of wind veer on wind turbine power generation. Physics of Fluids (2020). 33 (2020) 015101. https://doi.org/10.1063/5.0033826

  • [J-16] L. Gao, T. Tao, Y. Liu, and H. Hu, A field study of ice accretion and its effects on the power production of utility-scale wind turbines. Renewable Energy. 167 (2021) 917-928. https://doi.org/10.1016/j.renene.2020.12.014

  • [J-15] L. Gao, J. Hong. Wind turbine performance in natural icing environments: A field characterization. Cold Regions Science and Technology. 181 (2020) 103193. https://doi.org/10.1016/j.coldregions.2020.103193

  • [J-14] R. He, L. Gao, M. Trifonov, J. Hong. Aerosol generation from different wind instruments. Journal of Aerosol Science. 151 (2020) 105669. https://doi.org/10.1016/j.jaerosci.2020.105669

  • [J-13] L. Ma, Z. Zhang, L. Gao, Y. Liu, H. Hu. Bio-inspired icephobic coatings for aircraft icing mitigation: A critical review. Reviews of Adhesion and Adhesives. 8 (2020) 168–199. https://doi.org/10.7569/RAA.2020.097307

  • [J-12] L. Ma, Z. Zhang, L. Gao, Y. Liu, H. Hu. An exploratory study on using Slippery-Liquid-Infused-Porous-Surface (SLIPS) for wind turbine icing mitigation. Renewable Energy. 162 (2020) 2344–2360. https://doi.org/10.1016/j.renene.2020.10.013 

  • [J-11] L. Gao, S. Yang, A, Abraham, J. Hong, Effects of inflow turbulence on the structural response of wind turbine blades. Journal of Wind Engineering & Industrial Aerodynamics. 2020.199: 104137. https://doi.org/10.1016/j.jweia.2020.104137 

  • [J-10] L. Gao, Y. Liu, H. Hu. An experimental investigation on the dynamic glaze ice accretion process over a wind turbine airfoil surface. International Journal of Heat and Mass Transfer. 2020.149: 119120. https://doi.org/10.1016/j.ijheatmasstransfer.2019.119120

  • [J-9] R.Veerakumar, L. Gao, Y. Liu, H. Hu. Dynamic ice accretion process and its effects on the aerodynamic drag characteristics of a power transmission cable model. Cold Regions Science and Technology. 2019. https://doi.org/10.1016/j.coldregions.2019.102908

  • [J-8] L. Gao, R. Veerakumar, Y. Liu, H. Hu.  Quantification of the 3D shapes of the ice structures accreted on a wind turbine airfoil model. Journal of Visualization. 2019. https://doi.org/10.1007/s12650-019-00567-4

  • [J-7] L. Gao, Y. Liu, L. Ma, H. Hu.  A hybrid strategy combining minimized leading-edge electric-heating and superhydro-/ice-phobic surface coating for wind turbine icing mitigation. Renewable Energy. 2019. 140: 943-956.  https://doi.org/10.1016/j.renene.2019.03.112

  • [J-6] L. Gao, Y. Liu, W. Zhou, and H. Hu. An experimental study on the aerodynamic performance degradation of a wind turbine blade model induced by ice accretion process. Renewable Energy. 2019. 133(4): 663-675.  https://doi.org/10.1016/j.renene.2018.10.032

  • [J-5] L. Gao, Y. Liu, H. Hu. An experimental investigation of dynamic ice accretion process on a wind turbine airfoil model considering various icing conditions. International Journal of Heat and Mass Transfer. 2019. 133: 930-939.   https://doi.org/10.1016/j.ijheatmasstransfer.2018.12.181

  • [J-4] L. Gao, H. Zhang, Y. Liu, S. Han. Effects of vortex generators on a blunt trailing-edge airfoil for wind turbines. Renewable Energy. 2015. 76:303-311.  https://doi.org/10.1016/j.renene.2014.11.043

  • [J-3] L. Li, L. Gao, Y. Cui, Y. Liu. Research on unsteady numerical simulation of large-scale wind turbine wake effect. Journal of Engineering Thermophysics. 2017. 38(3): 541-547. (大型风电机组尾流效应非定常数值模拟研究,工程热物理学报,In Chinese)

  • [J-2] Y. Liu, J. Yan, S. Han, I. David, D. Tian, L. Gao. An optimized short-term wind power interval prediction method considering NWP accuracy. Chinese Science Bulletin. 2014.59(11): 1167-1175.  https://doi.org/10.1007/s11434-014-0119-7

  • [J-1] S. Han, L. Gao, Y. Liu, W. Yang. Post evaluation of wind resource assessment and micro-siting. Journal of Power and Energy Engineering. 2014. 2(4): 288-296. http://dx.doi.org/10.4236/jpee.2014.24040

 

Conference Papers (Peer-reviewed) and Talks

  • [C-19] L.Gao, T. Dasari, A. Knoll, J. Hong. Can turbines benefit from wind veer? 74th Annual Meeting of the American Physical Society Division of Fluid Dynamics, Nov 21-23, 2021, Phoenix, AZ, USA. (abstract)

  • [C-18] L. Gao, J. Hong. Field characterization of the effect of wind veer on wind turbine power generation. 73rd Annual Meeting of the American Physical Society Division of Fluid Dynamics (Virtual), Nov 22-24, 2020, online. (Abstract)

  • [C-17] L. Gao, R. Veerakumar, Y. Liu, H. Hu. Quantification of the 3D ice structures accreted on a wind turbine airfoil model. SAE 2019 Icing Conference. Jun 17-21, 2019, Minneapolis, MN, USA.

  • [C-16] L. Gao, L. Ma, Y. Liu, H. Hu. A novel heating-coating hybrid strategy for wind turbine icing mitigation. SAE 2019 Icing Conference, Jun 17-21, 2019, Minneapolis, MN, USA.

  • [C-15] R. Veerakumar, L. Gao, Y. Liu, H. Hu. An experimental study of atmospheric icing process on power transmission line. SAE 2019 Icing Conference, Jun 17-21, 2019, Minneapolis, MN, USA.

  • [C-14] C. Kolbakir, L. Gao, Y. Liu, H. Hu. A parametric study on the thermodynamic characteristics of DBD plasma actuation and its potential for wind turbine icing mitigation. SAE 2019 Icing Conference, Jun 17-21, 2019, Minneapolis, MN, USA.

  • [C-13] L. Gao, Y. Liu, H. Hu. Quantification of dynamic glaze icing process over an airfoil surface by using a digital image projection (DIP) Technique. AIAA-2018-3829. AIAA Aviation Forum, Jun 25–29, 2018, Atlanta, Georgia, USA.

  • [C-12] L. Gao, Y. Liu, H. Hu. An experimental investigation on an electric-thermal strategy for wind turbines icing mitigation. AIAA-2018-3658, AIAA Aviation Forum, Jun 25–29, 2018, Atlanta, Georgia. USA.

  • [C-11] L. Ma, Z. Zhang, L. Gao, Y. Liu, H. Hu. An experimental study on the durability of icephobic slippery liquid-infused porous surfaces (slips) pertinent to aircraft anti-/de-icing. AIAA Aviation Forum, Jun 25–29, 2018, Atlanta, Georgia, USA.

  • [C-10] L. Gao, Y. Liu and H. Hu. An experimental investigation on the dynamic ice accretion process over the surface of a wind turbine blade model, AIAA-2017-3582, 2017 AIAA Aviation Forum, Jun 5–9, 2017, Denver, Colorado, USA.

  • [C-9] L. Gao, Y. Liu, H. Hu. An experimental study on icing physics for wind turbine icing mitigation, AIAA-2017-0918, 2017 AIAA Science and Technology Forum and Exposition, Jan 9–13, 2017, Grapevine, Texas, USA.

  • [C-8] L. Li, L. Gao, Y. Liu, Y. Cui, B. Wang. Field measurements of atmospheric boundary layer and the impact of its daily variation on wind turbine wakes. IET 5th Renewable Power Generation Conference Sep 21–23 2016. London, UK.

  • [C-7] L. Li, Y. Cui, Y. Liu, L. Gao, N. Wang, H. Lei. Comparison and validation of wake models based on field measurements with lidar. IET 5th Renewable Power Generation Conference Sep 21–23 2016. London, UK.

  • [C-6] L. Gao, Y. Liu, Y. Cui, L. Li. The impact of ambient turbulence on wind turbine wakes. IET 4th Renewable Power Generation Conference, Oct 17-18, 2015, Beijing, China.

  • [C-5] L. Li, L. Gao, Y. Liu, Y. Cui. Numerical simulation of wake interference effects on the downstream wind turbine performance. IET 4th Renewable Power Generation Conference, Oct 17-18, 2015, Beijing, China.

  • [C-4] Y. Cui, L. Li, Y. Liu, L. Gao. Wind turbine wake vertical distributions considering different inflow shear indices. IET 4th Renewable Power Generation Conference, Oct 17-18, 2015, Beijing, China.

  • [C-3] Y. Wang, Y. Liu, L. Li, S. Han, L. Gao. Impact of atmospheric stability on wind turbine wake velocity distribution. IET 4th Renewable Power Generation Conference, Oct 17-18, 2015, Beijing, China.

  • [C-2] P. Yan, S. Han, Y. Liu, L. Gao, L. Li. Effects of Gurney flap and trailing-edge wedge on a blunt trailing-edge aerofoil. IET 4th Renewable Power Generation Conference, Oct 17-18, 2015, Beijing, China.

  • [C-1] L. Gao, Y. Liu, S. Han, J. Yan. Aerodynamic performance of a blunt trailing-edge airfoil affected by vortex generators and a trailing-edge wedge. IET 3rd Renewable Power Generation Conference, Sep 24-25, 2014, Naples, Italy.

Patents

  • [P-2] Y. Liu, L. Li, Y. Cui, S. Han, J. Yan, W. Zhang, L. Gao, Y. Ma. A method of parabolic wake model for wind turbines considering turbulence intensity. CN 106897486A.

  • [P-1] H. Pan, G. Wei, S. Han, J. Yan, L. Gao. A short-term power prediction method for distributed wind power. CN 103745274A.

 

Invited Talks

  • [T-2] “Wind Turbines in Cold Climates: Icing Physics and Novel Strategies for Wind Turbine Icing Mitigation,” Invited Seminar, St. Anthony Falls Laboratory, University of Minnesota. (2019-05-10, Prof. Jiarong Hong as the host)

  • [T-1] “Experimental Investigations on Wind Turbine Icing Physics and Anti-/De-icing,” Invited Seminar, Institute of Engineering Thermo-physics, Chinese Academy of Sciences. (2018-12-28, Prof. Mingming Zhang as the host)