This image showsDexing Liu

Dexing Liu

M.Sc.

Research Associate
Institut of Aircraft Design
Stuttgart Wind Energy

Contact

+49 711 685 68333

Business card (VCF)

Allmandring 5b
70569 Stuttgart
Deutschland
Room: 1.37

Office Hours

By appointment

Subject

Mr. Dexing Liu develops AI-powered digital twin technology for wind farms, with a focus on turning complex operational data into actionable control decisions that improve both asset performance and lifetime. His work combines machine learning, physics-based modeling, dimensionality reduction, compressed sensing, and wind LiDAR integration to predict loads, reconstruct inflow conditions, and optimize wind farm operation in real time.

Building on research projects such as OWEA Loads, VAMOS, and FlexiWind, he is developing a practical wind farm digital twin (AI-brain) that shifts optimization from the single-turbine level to the fleet level. The goal is to help operators increase energy production, reduce fatigue and maintenance risk, and unlock more flexible, lifetime-aware wind farm control. His research forms the foundation for scalable digital twin products that can support smarter derating, wake-aware control, and data-driven optimization across entire offshore wind farms.

  1. Liu, D., Ruck, N., & Cheng, P. W. (in press). A scalable surrogate framework for turbine and substructure fatigue assessment in flexible wind farm operation. Journal of Physics: Conference Series (TORQUE 2026).
  2. Liu, D., Ruck, N., & Cheng, P. W. (2025). Deep learning approaches for offshore wind turbine load prediction: A comparative study using simulation, measurement, and transfer learning. Journal of Physics: Conference Series, 3131(1), 012030. https://doi.org/10.1088/1742-6596/3131/1/012030
  3. Liu, D. Ruck, N. Cheng, P.W. (2025). Assessment of Deep Learning Models for Turbine Load Prediction Using Alpha Ventus Wind Farm Data. Presented at EERA DeepWind 2025 Conference, Trondheim, Norway. SINTEF. https://www.sintef.no/globalassets/project/eera-deepwind-2025/presentasjoner/3c-operation-and-maintenance_liu.pdf
  4. Costa, F.; Giyanani, A.; Liu, D.; Keane, A.; Ratti, C.A.; Clifton, A. An Ontology for Describing Wind Lidar Concepts. Remote Sens. 202416, 1982. https://doi.org/10.3390/rs16111982
  5. Özinan, U., Liu, D., Adam, R., Choisnet, T., & Cheng, P. W. (2022). Power curve measurement of a floating offshore wind turbine with a nacelle-based lidar. Journal of Physics: Conference Series2265(4), Article 4. https://doi.org/10.1088/1742-6596/2265/4/042016

Wind Turbine Design, OpenFAST seminar

Since 2020     Research Associate at Stuttgart Wind Energy (SWE)

2018 – 2019   Research Engineer at MaREI center, Ireland

2014 – 2018   Research Engineer at R&D center of Zhejiang Windey Co.,Ltd, China

2011 - 2014    Studies Harbor, Coastal and Offshore Engineering (M.Sc.) at Dalian Ocean University, China

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