CV

Employment

Postdoctoral Associate, Massachusetts Institute of Technology, 2023 - present Postdoctoral Researcher, DTU Wind Energy, 2023

Education

• Ph.D. in Wind Energy, Technical University of Denmark, 2020-2023
• M.Sc. in Engineering (European Wind), Technical University of Denmark, 2016-2018
• M.Sc. in Aerospace Engineering, Delft University of Technology, 2016-2018
• Bachelor in Engineering (Mechanical), University of Adelaide, 2011-2015
• Bachelor in Finance, University of Adelaide, 2011-2015

Publications

Analytical model for the power-yaw sensitivity of wind turbines operating in full wake

Liew, J., Urbán, A. M., and Andersen, S. J.: Analytical model for the power–yaw sensitivity of wind turbines operating in full wake, Wind Energ. Sci., 5, 427–437, https://doi.org/10.5194/wes-5-427-2020, 2020.

The effect of wake position and yaw misalignment on power loss in wind turbines

Urbán, A. M., Liew, J., Dellwik, E., and Larsen, G. C (2019). "The effect of wake position and yaw misalignment on power loss in wind turbines." Journal of Physics: Conference Series. 1222 012002.

Active tip deflection control for wind turbines

Liew, J., Lio, W. H., Urbán, A. M., Holierhoek, J., & Kim, T. (2020). Active tip deflection control for wind turbines. Renewable Energy, 149, 445-454.

Effect of varying fidelity turbine models on wake loss prediction

Liew, J., Pirrung, G. R., and Urbán, A. M. (2020). "Effect of varying fidelity turbine models on wake loss prediction." Journal of Physics: Conference Series. 1618 062002.

Wind farm layout optimization with load constraints using surrogate modelling

Riva, R., Liew, J., Friis-Møller, M., Dimitrov, N., Barlas, E., Réthoré, P.-E., & Beržonskis, A. (2020). Wind farm layout optimization with load constraints using surrogate modelling. Journal of Physics. Conference Series, 1618(4), 042035 (11pp), 042035 (11pp). https://doi.org/10.1088/1742-6596/1618/4/042035

Yaw induced wake deflection - a full-scale validation study

Larsen, G. C., Ott, S., Liew, J., van der Laan, M. P., Simon, E., R.Thorsen, G., & Jacobs, P. (2020). Yaw induced wake deflection - a full-scale validation study. Journal of Physics - Conference Series, 1618(6), 062047 (11pp), 062047 (11pp). https://doi.org/10.1088/1742-6596/1618/6/062047

Model-free estimation of available power using deep learning

Göçmen, T., Meseguer Urbán, A., Liew, J., and Lio, A. W. H.: Model-free estimation of available power using deep learning, Wind Energ. Sci., 6, 111–129, https://doi.org/10.5194/wes-6-111-2021, 2021.

Streaming dynamic mode decomposition for short-term forecasting in wind farms

Liew J, Göçmen T, Hou Lio W, Larsen GC. Streaming dynamic mode decomposition for short-term forecasting inwind farms. Wind Energy. 2021;1-16. doi:10.1002/we.269416

How does the quantity, resolution, and scaling of turbulence boxes affect aeroelastic simulation convergence?

Liew J & Larsen, G. C. (2022, May). How does the quantity, resolution, and scaling of turbulence boxes affect aeroelastic simulation convergence?. In Journal of Physics: Conference Series (Vol. 2265, No. 3, p. 032049). IOP Publishing.

LES verification of HAWC2Farm aeroelastic wind farm simulations with wake steering and load analysis

Liew J, Andersen, S. J., Troldborg, N., & Göçmen, T. (2022, May). LES verification of HAWC2Farm aeroelastic wind farm simulations with wake steering and load analysis. In Journal of Physics: Conference Series (Vol. 2265, No. 2, p. 022069). IOP Publishing.

Model-free closed-loop wind farm control using reinforcement learning with recursive least squares

Liew, J., Göçmen, T., Lio, A. W. H., & Larsen, G. C. (2023, July). Model-free closed-loop wind farm control using reinforcement learning with recursive least squares. In Wind Energy.

Extending the dynamic wake meandering model in HAWC2Farm: a comparison with field measurements at the Lillgrund wind farm

Liew, J., Göçmen, T., Lio, A. W. H., & Larsen, G. C. (2023). Extending the dynamic wake meandering model in HAWC2Farm: a comparison with field measurements at the Lillgrund wind farm. In Wind Energy Science.

Efficient Mann turbulence generation for offshore wind farms with applications in fatigue load surrogate modelling

Liew, J., Riva, R., & Göçmen, T. (2023). Efficient Mann turbulence generation for offshore wind farms with applications in fatigue load surrogate modelling. In Journal of Physics - Conference Series. (Vol. 2626). IOP Publishing.