Liu Dong

Essential information

Liu Dong, male, Han nationality,

born in Luoyang, Henan Province in January 1992

PhD, Lecturer

Major: Power engineering and engineering thermophysics; Hydraulic engineering

Research interests: refined modeling and intelligent control of hydropower cluster, condition monitoring and fault diagnosis of hydropower units, and joint optimal operation of hydropower and new energy

Personal learning experience：

2022-08 to present, North China University of Water Resources and Electric Power, College of Energy and Power Engineering, Lecturer

2020-07 to 2022-08, Huazhong University of Science and Technology, School of Civil and Hydraulic Engineering, Postdoctoral Fellow

2015-09 to 2020-06, Wuhan University, Fluid Mechanics and Engineering, Doctoral Degree

2011-09 to 2015-06, North China University of Water Resources and Electric Power, Thermal and Power Engineering (Hydrodynamic Direction), Bachelor's Degree

Teaching task：

"Hydraulic turbine", "Hydraulic turbine regulation", "Professional English", "Principles of automatic control"

Research projects：

1. National Natural Science Foundation of China (52309111), Host

2. China Postdoctoral Foundation (2020M682416), Host

3. Enterprise Technology Project (HCDK-CGHT39-20231006Y), Host

4. National Natural Science Foundation of China (52379088), Participant

5. National Natural Science Foundation of China (52279085), Participant

6. National Natural Science Foundation of China (51979204), Participant

   Published academic papers：

7. Liu D*, Wei X, Zhang J, Hu X, Zhang L. A Parameter Sensitivity Analysis of Hydropower Units under Full Operating Conditions Considering Turbine Nonlinearity [J]. Sustainability, 2023, 15(15): 11691.

8. Liu D, Li C*, Malik OP. Nonlinear modeling and multi-scale damping characteristics of hydro-turbine regulation systems under complex variable hydraulic and electrical network structures [J]. Applied Energy, 2021, 293: 116949.

9. Liu D, Li C*, Tan X, Lu X, Malik OP. Damping characteristics analysis of hydropower units under full operating conditions and control parameters: accurate quantitative evaluation based on refined models [J]. Applied Energy, 2021, 292: 116881.

10. Liu D, Li C*, Malik OP. Operational characteristics and parameter sensitivity analysis of hydropower unit damping under ultra-low frequency oscillations [J]. International Journal of Electrical Power and Energy systems, 2022, 136: 107689.

11. Liu D, Wang X, Peng Y, Zhang H, Xiao Z*, Han X, Malik OP. Stability analysis of hydropower units under full operating conditions considering turbine nonlinearity [J]. Renewable Energy, 2020, 154:723-742.

12. Liu D, Xiao Z*, Hu X, Zhang C*, Malik OP. Feature extraction of rotor fault based on EEMD and curve code [J]. Measurement, 2019, 135(3):712-724.

13. Liu D, Xiao Z*, Li H, Liu D, Hu X, Malik OP. Accurate Parameter Estimation of a Hydro-Turbine Regulation System Using Adaptive Fuzzy Particle Swarm Optimization [J]. Energies, 2019, 12:3903.

14. Liu D, Zeng H*, Xiao Z*, Peng L, Malik OP. Fault diagnosis of rotor using EMD thresholding-based de-noising combined with probabilistic neural network [J]. Journal of Vibroengineering, 2017, 19(8):5920-5931.

15. Chen J, Zheng Y, Liu D, Du Y, Xiao Z*. Quantitative stability analysis of complex nonlinear hydraulic turbine regulation system based on accurate calculation [J]. Applied Energy, 2023, 351:121853.

16. Lu X, Li C*, Liu D, Zhu Z, Tan X, Xu R. Comprehensive stability analysis of complex hydropower system under flexible operating conditions based on a fast stability domain solving method [J]. Energy, 2023, 274:127368.

17. Lu X, Li C*, Liu D*, Zhu Z, Tan X. Influence of water diversion system topologies and operation scenarios on the damping characteristics of hydropower units under ultra-low frequency oscillations [J]. Energy, 2022, 239:122679.

18. Tan X, Li C*, Liu D, Wang H, Xu R, Lu X, Zhu Z. Multi-time scale model reduction strategy of variable-speed pumped storage unit grid-connected system for small-signal oscillation stability analysis [J]. Renewable Energy, 2023, 211:985-1009.

19. Ren Y*, Jin K, Gong C, Hu J, Liu D, Jing X, Zhang K. Modelling and capacity allocation optimization of a combined pumped storage/wind/photovoltaic/ hydrogen production system based on the consumption of surplus wind and photovoltaics and reduction of hydrogen production cost [J]. Energy Conversion and Management, 2023, 296:117662.

    Contact information：

    E-mail：liudongwhu@126.com

    Address: College of Energy and Power Engineering, North China University of Water Resources and Electric Power, No. 36 Beihuan Road, Zhengzhou, Henan, China