Biography

Professor Xiaowei Zhao is the director of the EPSRC Supergen Network Plus in Artificial Intelligence for Renewable Energy, a co-director of the EPSRC Supergen Offshore Renewable Energy Hub, and a member of the Science Expert Group of the UK Government Department for Energy Security and Net Zero. He is an inaugural Manchester Prize finalist in 2024, a prestigious challenge prize by UK government rewarding breakthroughs in artificial intelligence for public good.

He obtained his PhD in Control Theory from Imperial College London in 2010 and then worked as a postdoctoral researcher in the Control Engineering Group of the University of Oxford until 2013. After that he joined the University of Warwick where he was promoted to Professor of Control Engineering in 2018.

His main research areas are control theory and machine learning with applications in offshore renewable energy systems, energy storage, smart grids, and autonomous systems. Since 2017, he has held 16 grants from these areas funded by EPSRC, Horizon Europe/UKRI/ Innovate UK, H2020 and industry with a total project value of over £40 million. At Warwick he established the Intelligent Control & Smart Energy (ICSE) research group (consisting of around 20 PhD students and postdoctoral researchers) and four state-of-the-art laboratories: the Offshore Renewable Energy Lab, the Renewable Energy Integration and Smart Grid Lab, the Hydrogen Technology Lab, and the Autonomous Systems Lab.

Research Interests

Control theory and machine learning with application on

1. offshore renewable energy;
2. energy storage;
3. smart grids;
4. autonomous systems.

Teaching Interests

Projects and Grants

Current Grants

(His share: £4.02 million; total project value: £23.35 million)

1. 2024 - 2026, EPSRC: EPSRC Supergen Network Plus in Artificial Intelligence for Renewable Energy, PI
2. 2024 - 2026, UK Government Department for Science, Innovation and Technology, Manchester Prize (for Artificial Intelligence) finalist, PI
3. 2023 - 2027, EPSRC, EP/Y016297/1: EPSRC Supergen ORE (Offshore Renewable Energy) Impact Hub, co-director
4. 2023 - 2027, UKRI/Innovate UK: Smart, Aware, Integrated Wind Farm Control Interacting with Digital Twins (ICONIC), PI
5. 2023 - 2027, UKRI: Modelling and Control of Flexible Structures Interacting with Fluids (ModConFlex), PI
6. 2023 - 2025, Horizon Europe, Economic & Reliable DC Microgrids, Coordinator (PI)
7. 2023 - 2024, National Grid ESO, Transient Stability Assessment of GB Power System based on Real-Time Phasor-EMT Simulations, PI
8. 2022 - 2025, EPSRC, EP/W003694/1: High efficiency reversible solid oxide cells for the integration of offshore renewable energy using hydrogen, PI
9. 2020 - 2024, EPSRC, EP/T021713/1: Resilient Operation of Sustainable Energy Systems (ROSES), CoI (PI to Warwick).
10. 2024 - 2026, An industry grant has been secured to start in summer 2024.

Past Grants

(His share: £3.34 million; total project value: £18.23 million)

1. 2019 - 2024, H2020, WinGrid: Wind farm - Grid interactions: exploration and development, Coordinator (PI)
2. 2018 - 2023, EPSRC, EP/S000747/1: EPSRC Supergen ORE (Offshore Renewable Energy) Hub, co-director
3. 2020 - 2023, EPSRC Supergen ORE Hub Strategic Fund, PI
4. 2021 - 2023, Supergen Cross Hub Seedcorn Fund, PI
5. 2018 - 2022, EPSRC: Data-driven Intelligent Energy Management System for a Micro Grid -- PI.
6. 2017-2022, H2020: Control of flexible structures and fluid structure interactions -- Co-coordinator.
7. 2017 - 2020, EPSRC: Farming the ENvironment into the Grid: Big data in Offshore Wind -- CoI (PI to Warwick).
8. 2018 - 2020, EPSRC: Passive vibration control of a floating hydrostatic transmission wind turbine and theoretical extensions -- PI
9. 2017 - 2019, National Grid ESO: Assessment of power oscillation damping control on offshore wind turbine control performance -- PI
10. 2016 - 2017, Royal Society Research Grant -- PI

Internal Grants

1. 2018-2020, Warwick International Partnership Fund: Aeroelastic control of wind turbine blades, PI
2. 2013 - 2018, IAS Global Research Fellowship -- PI
3. 2014 - 2016, IAS Visiting Fellowship -- PI
4. 2015, 2016, Warwick Summer Research Fund -- PI
5. 2014 - 2015, Energy GRP Research Fund -- PI
6. 2014, Energy GRP Workshop Fund
7. 2013 - 2018, Global Research Fellowship

Journal Publications (since 2020)

95. Q. Liu, Y. Liang, Z. Zhang, M. Wang, and X. Zhao*, Small-Signal Stability of Sequence-Decomposed Grid-Forming IBRs with DC-Link Voltage Dynamics, IEEE Transactions on Power Electronics DOI: 10.1109/TPEL.2024.3488532, 2024.

94. Q. Liu, Y. Liang, Z. Zhang, M. Wang, and X. Zhao*, Small-Signal Synchronization Stability of Sequence-Decomposed Grid-Forming IBRs, IEEE Transactions on Industrial Electronics, 2024, in press.

93. Z. Zhang and X. Zhao*, Startup control of grid-forming offshore wind turbines connected to the diode-rectifier-based HVDC Link, IEEE Transactions on Sustainable Energy DOI: 10.1109/TSTE.2024.3454797, 2024.

92. H. Yang, H. Dong, and X. Zhao*, Integration of prescribed performance with control barrier functions for attitude control and allocation with reaction wheels, IEEE Transactions on Aerospace and Electronic Systems DOI: 10.1109/TAES.2024.3460765, 2024.

91. R. Li, and X. Zhao*, LSwinSR: UAV Imagery Super-Resolution based on Linear Swin Transformer, IEEE Transactions on Geoscience and Remote Sensing DOI: 10.1109/TGRS.2024.3463204, 2024.

90. Z. Wu and X. Zhao*, An algorithm design framework for linearly constrained convex optimization: proximal and contractive perspectives, IEEE Transactions on Automatic Control DOI: 10.1109/TAC.2024.3428071, 2024.

89. M. Heidari, L. Ding, M. Kheshti, X. Zhao, and V. Terzija, Adaptive inertial control for wind turbine generators in fast frequency response based on the power reduction period assessment, IEEE Transactions on Sustainable Energy DOI: 10.1109/TSTE.2024.3459729, 2024.

88. Y. Feng, Y. Zhou, H.W. Ho, H. Dong, and X Zhao, Online adaptive critic designs with tensor product B-splines and incremental model techniques, Journal of the Franklin Institute 361, 2024

87. H. Yang, H. Dong, and X. Zhao*, Safety-critical control allocation for obstacle avoidance of quadrotor aerial photography, IEEE Control Systems Letters DOI: 10.1109/LCSYS.2024.3427269, 2024.

86. Y. Fan, H. Dong, X. Zhao*, and P. Denissenko, Path-following control of unmanned underwater vehicle based on an improved TD3 deep reinforcement learning, IEEE Transactions on Control Systems Technology 32, 2024.

85. J. Xie, H. Dong, S. Lin, and X. Zhao*, Wind turbine fault-tolerant control via incremental model-based reinforcement learning, IEEE Transactions on Automation Science and Engineering DOI: 10.1109/TASE.2024.3372713, 2024.

84. Y. Huang and X. Zhao*, Reinforcement learning-based multi-objective control of grid-connected wind farms, IEEE Transactions on Industrial Informatics DOI: 10.1109/TII.2024.3359420, 2024.

83. Q. He, J. Shen, Z. Dong, C. Liu, X. Guo, and X. Zhao*, Online systemic energy management strategy of fuel cell system with efficiency enhancement, IEEE Transactions on Transportation Electrification DOI: 10.1109/TTE.2024.3361649, 2024.

82. J. Ye, H. Dong, Y. Bian, H. Qin, and X. Zhao*, ADP-based optimal control for discrete-time systems with safe constraints and disturbances, IEEE Transactions on Automation Science and Engineering DOI: 10.1109/TASE.2023.3346876, 2024.

81. G. Liu, Y. Yang, X. Zhao, and C.K. Ahn, Adaptive fuzzy practical bipartite synchronization for multi-agent systems with intermittent feedback under multiple unknown control directions, IEEE Transactions on Fuzzy Systems 32, 2024.

80. Y. Lv, X. Zhao*, and P. Shah, Robust optimal framework for doubly fed induction generator with uncertain dynamics, Protection and Control of Modern Power Systems 9, 2024.

79. M. Heidari, L. Ding, , M. Kheshti, W. Bao, X. Zhao, M. Popov, and V. Terzij, A Review on Application of Machine Learning-Based Methods for Power System Inertia Monitoring, International Journal of Electrical Power & Energy Systems 162, 2024.

78. C. Liu, J. Shen, Z. Dong, Q. He, and X. Zhao*, Accuracy improvement of fuel cell prognostics based on voltage prediction, International Journal of Hydrogen Energy 58, 2024.

77. G. Liu, Y. Yang, X. Zhao, and C.K. Ahn, Novel Nussbaum design for nonlinear systems with unknown switching control directions, IEEE Transactions on Circuits and Systems II: Express Briefs 71, 2024.

76. Y Lv, W Zhang, J Zhao, and X Zhao, Finite-horizon optimal control for nonlinear multi-input systems with online adaptive integral reinforcement learning, IEEE Transactions on Automation Science and Engineering DOI: 10.1109/TASE.2024.3354830, 2024.

75. Z. Zhang. Y. Liang, and X. Zhao*, Adaptive Inter-area power oscillation damping from offshore wind farm and MMC-HVDC using deep reinforcement learning, Renewable Energy 224, 2024.

74. C. Liu, P. Shah, Z. Dong, and X. Zhao*, Distribution system identification using FISTA algorithm, International Journal of Electrical Power & Energy Systems 155, 2024.

73. Z Wu and X Zhao*, Parameter-separable prox-Lagrangian method for convex-concave saddle point problem, IEEE Control Systems Letters 8, 2024.

72. J. Xie, H. Dong and X. Zhao*, Power regulation and load mitigation of floating wind turbines via reinforcement learning, IEEE Transactions on Automation Science and Engineering 21, 2024.

71. J. Zhang and X. Zhao*, Digital twin of wind farms via physics-informed deep learning, Energy Conversion and Management 293, 2023.

70. R. Li, J. Zhang, X. Zhao*, D. Wang, M. Hann, and D. Greaves, Phase-resolved real-time forecasting of three-dimensional ocean waves via machine learning and wave tank experiments, Applied Energy 348, 2023.

69. J. Zhang, X. Zhao*, D. Greaves, and S. Jin, Modeling of a hinged-raft wave energy converter via deep operator learning and wave tank experiment, Applied Energy 341, 2023.

68. H. Dong and X. Zhao*, Reinforcement learning-based wind farm control: towards large farm applications via automatic grouping and transfer learning, IEEE Transactions on Industrial Informatics 19, 2023

67. Y. Liang, X. Zhao*, and L. Sun, A multiagent reinforcement learning approach for wind farm frequency control, IEEE Transactions on Industry Informatics 19, 2023.

66. Z. Zhang and X. Zhao*, Coordinated power oscillation damping from a VSC-HVDC grid integrated offshore wind farms: using capacitors energy, IEEE Transactions on Sustainable Energy 14, 2023.

65. Y. Huang, S. Lin and X. Zhao*, Multi-agent reinforcement learning control of a hydrostatic wind turbine-based farm, IEEE Transactions on Sustainable Energy 14, 2023.

64. P. Shah and X. Zhao*, Leakage current mitigation technique in solar PV array system using passive filter, IEEE Transactions on Energy Conversion 38, 2023.

63. H. Dong and X. Zhao*, Data-driven wind farm control via multiplayer deep reinforcement learning, IEEE Transactions on Control Systems Technology 31, 2023.

62. Y. Lv, J. Na, X. Zhao*, Y. Huang, and X. Ren, Multi-H∞ controls for unknown inputs-interference nonlinear system with reinforcement learning, IEEE Transactions on Neural Networks and Learning Systems 34, 2023.

61. H. Yang, Q. Hu, H. Dong, X. Zhao, and D. Li, Optimized data-driven prescribed performance attitude control for actuator saturated spacecraft, IEEE/ASME Transactions on Mechatronics 28, 2023.

60. X. Guo, Z. Dong, J. Shen, Y. Xu, Q. He, X. Zhao and Z. Ding, Towards intelligent and integrated architecture for hydrogen fuel cell system: challenges and approaches, National Science Open 2, 2023.

59. J. Xie, H. Dong and X. Zhao*, Data-driven torque and pitch control of wind turbines via reinforcement learning, Renewable Energy 215, 2023.

58. P. Shah and X. Zhao*, Unified power quality conditioner, in book Power Quality: Infrastructures and Control, Springer Nature DOI:10.1007/978-981-19-7956-9_5, 2023.

57. Q. He, P. Shah and X. Zhao*, Resilient operation of dc microgrid against FDI attack: a GRU based framework, International Journal of Electrical Power & Energy Systems 145, 2023.

56. Y. Lv, Z. Wu, and X. Zhao*, Data-based optimal microgrid management for energy trading with integral Q-learning scheme, IEEE Internet of Things Journal 10, 2023.

55. Y. Lv, X. Ren, J. Tian, and X. Zhao*, Inverse-model-based iterative learning control for unknown MIMO nonlinear system with neural network, Neurocomputing 519, 2023.

54. P. Shah and X. Zhao*, Network identification using micro-PMU and smart meter measurements: an ADMM based approach, IEEE Transactions on Industry Informatics 18, 2022.

53. M. Kheshti, S. Lin, X. Zhao*, L. Ding, M. Yin, and V. Terzija, Gaussian distribution-based inertial control of wind turbine generators for fast frequency response in low inertia systems, IEEE Transactions on Sustainable Energy 13, 2022.

52. Y. Zhao, T. Zhang, L. Sun, X. Zhao, L. Tong, L. Wang, J. Ding, and Y. Ding, Energy storage for black start services: a review, International Journal of Minerals, Metallurgy and Materials 29, 2022.

51. H. Dong, J. Xie, and X. Zhao*, Wind farm control technologies: from classical control to reinforcement learning, Progress in Energy 4, 2022.

50. L. Sun and X. Zhao*, Stability analysis and enhancement of power sharing control in islanded microgrids, IEEE Transactions on Smart Grid 13, 2022.

49. J. Zhang, X. Zhao*, S. Jin, and D. Greaves, Phase-resolved real-time ocean wave prediction with quantified uncertainty based on variational Bayesian machine learning, Applied Energy 324, 2022.

48. R. Li, J. Zhang, and X. Zhao*, Dynamic wind farm wake modeling based on a bilateral convolutional neural network and high-fidelity LES data, Energy 258, 2022.

47. Z. Zhang, X. Zhao*, L. Fu, and M. Edrah, Stability and dynamic analysis of the PMSG-based WECS with torsional oscillation and power oscillation damping capabilities, IEEE Transactions on Sustainable Energy 13, 2022.

46. X. Zhang, D. Lu, H. Dong, X. Zhao*, F. Brennan, and Y. Liang, Vibration suppression of multi-component floating structures via passive TMDs and Bayesian ascent, Ocean Engineering 259, 2022.

45. R. Li, J. Zhang, and X. Zhao*, Multi-fidelity modeling of wind farm wakes based on a novel super-fidelity network, Energy Conversion and Management 270, 2022.

44. M. Kheshti, X. Zhao*, T. Liang, B. Nie, Y. Ding, and D. Greaves, Liquid air energy storage for ancillary services in an integrated hybrid renewable system, Renewable Energy 199, 2022.

43. Y. Wang, X. Zhao, J.M.R Graham, and J. Li, Vortex force map for multi-body flows with application to wing-flap configurations, Journal of Fluid Mechanics 953, 2022.

42. L. Sun and X. Zhao*, Impacts of phase-locked loop and reactive power control on inertia provision by DFIG wind turbine, IEEE Transactions on Energy Conversion 37, 2022.

41. J. Li, Y. Wang, S. Lin, and X. Zhao*, Nonlinear modelling and adaptive control of smart rotor wind turbines, Renewable Energy 186, 2022.

40. H. Dong, X. Zhao*, Q. Hu, H. Yang, and P. Qi, Learning-based attitude tracking control with high-performance parameter estimation, IEEE Transactions on Aerospace and Electronic Systems 58, 2022.

39. H. Dong and X. Zhao*, Wind-farm power tracking via preview-based robust reinforcement learning, IEEE Transactions on Industrial Informatics 18, 2022.

38. J. Xie, H. Dong, X. Zhao*, and A. Karcanias, Wind farm power generation control via double-network-based deep reinforcement learning, IEEE Transactions on Industrial Informatics 18, 2022.

37. H. Dong and X. Zhao*, Composite experience replay-based deep reinforcement learning with application in wind farm control, IEEE Transactions on Control Systems Technology 30, 2022.

36. J. Zhang and X. Zhao*, Wind farm wake modeling based on deep convolutional conditional generative adversarial network, Energy 238, 2022.

35. Y. Wang, X. Zhao, R. Palacios and K. Otsuka, Aeroelastic simulation of high-aspect ratio wings with intermittent leading-edge separation, AIAA Journal 60, 2022.

34. M. Edrah, X. Zhao*, W. Hung, P. Qi, B. Marshall, S. Baloch, and A. Karcanias, Electromechanical interactions of full scale converter wind turbine with power oscillation damping and inertia control, International Journal of Electrical Power & Energy Systems 135, 2022.

33. L. Sun and X. Zhao*, Modelling and analysis of frequency-responsive wind turbine involved in power system ultra-low frequency oscillation, IEEE Transactions on Sustainable Energy 13, 2022.

32. J. Zhang, X. Zhao* and X. Wei, Reinforcement learning-based structural control of floating wind turbines, IEEE Transactions on Systems, Man, and Cybernetics: Systems 52, 2022.

31. H. Dong, X. Zhao* and B. Luo, Optimal tracking control for uncertain nonlinear systems with prescribed performance via critic-only ADP, IEEE Transactions on Systems, Man, and Cybernetics: Systems 52, 2022.

30. J. Zhang and X. Zhao*, Three-dimensional spatiotemporal wind field reconstruction based on physics-informed deep learning, Applied Energy 300, 2021.

29. H. Dong, J. Zhang, and X. Zhao*, Intelligent wind farm control via deep reinforcement learning and high-fidelity simulations, Applied Energy 292, 2021.

28. X. Yin and X. Zhao*, Optimal power extraction of a two-stage tidal turbine system based on backstepping disturbance rejection Control, International Journal of Electrical Power & Energy Systems 132, 2021.

27. J. Xie, X. Zhao and H. Dong, Learning-based nonlinear model predictive control with accurate uncertainty compensation, Nonlinear Dynamics 104, 2021.

26. J. Li, Y. Wang, X. Zhao* and P. Qi, Model free adaptive control of large and flexible wind turbine rotors with controllable flaps, Renewable Energy 180, 2021.

25. Q. Hu, H. Yang, H. Dong, and X. Zhao, Learning-based 6-DOF control for autonomous proximity operations under motion constraints, IEEE Transactions on Aerospace and Electronic Systems 57, 2021.

24. H. Yang, Q. Hu, H. Dong, and X. Zhao, ADP-based spacecraft attitude control under actuator misalignment and pointing constraints, IEEE Transactions on Industrial Electronics 69, 2021.

23. X. Yin and X. Zhao*, Data driven learning model predictive control of offshore wind farms, International Journal of Electrical Power & Energy Systems 127, 2021.

22. X. Tong and X. Zhao*, Vibration and power regulation control of a floating wind turbine with hydrostatic transmission, Renewable Energy 167, 2021.

21. J. Zhang and X. Zhao*, Spatiotemporal wind field prediction based on physics-informed deep learning and LIDAR measurements, Applied Energy 288, 2021.

20. J. Zhang and X. Zhao*, Machine-learning-based surrogate modeling of aerodynamic flow around distributed structures, AIAA Journal 59, 2021.

19. K. Chen, Y. Qiu, J. Lin, F. Liu, X. Zhao, and Y. Song, Wake-effect aware optimal online control of wind farms: an explicit solution, IET Renewable Power Generation 15, 2021.

18. H. Dong, X. Zhao* and H. Yang, Reinforcement learning-based approximate optimal control for attitude reorientation under state constraints, IEEE Transactions on Control Systems Technology 29, 2021.

17. J. Li, Y. Wang, J.M.R. Graham and X. Zhao*, Evaluating unsteady fluid dynamic forces in viscous flows from the vorticity field, AIAA Journal 59, 2021.

16. J. Zhang and X. Zhao*, A novel dynamic wind farm wake model based on deep learning, Applied Energy 277, 2020.

15. X. Yin and X. Zhao*, Deep neural learning based distributed predictive control for offshore wind farm using high fidelity LES data, IEEE Transactions on Industrial Electronics 68, 2020.

14. X. Yin, X. Zhao*, J. Lin and A. Karcanias, Reliability aware multi-objective predictive control for wind farm based on machine learning and heuristic optimizations, Energy 202, 2020.

13. X. Wei and X. Zhao*, Vibration suppression of a floating hydrostatic wind turbine model using bidirectional tuned liquid column mass damper, Wind Energy 23, 2020.

12. Y. Zhang, X. Zhao* and X. Wei, Robust structural control of an underactuated floating wind turbine, Wind Energy 23, 2020.

11. M. Edrah, X. Zhao*, W. Hung, P. Qi, B. Marshall, A. Karcanias and S. Baloch, Effects of POD control on a DFIG wind turbine structural system, IEEE Transactions on Energy Conversion 35, 2020.

10. S. Lin, X. Zhao* and X. Tong, Feasibility studies of a converter-free grid-connected offshore hydrostatic wind turbine, IEEE Transactions on Sustainable Energy 11, 2020.

9. S. Lin, P. Qi and X. Zhao*, Power generation control of a hydrostatic wind turbine implemented by model-free adaptive control scheme, Wind Energy 23, 2020.

8. P. Qi and X. Zhao*, Flight control for very flexible aircraft using model-free adaptive control, Journal of Guidance, Control, and Dynamics 43, 2020.

7. A. Khosravi, M. Malekan, J.J.G. Pabon, X. Zhao, and M.E.H. Assad, Design parameter modeling of solar power tower system using adaptive neuro-fuzzy inference system optimized with a combination of genetic algorithm and teaching learning-based optimization algorithm, Journal of Cleaner Production 244, 2020.

6. J. Zhang and X. Zhao*, Quantification of parameter uncertainty in wind farm wake modeling, Energy 196, 2020.

5. J. Li, Y. Wang, J.M.R. Graham and X. Zhao*, Vortex moment map for unsteady incompressible viscous flows, Journal of Fluid Mechanics 891, 2020.

4. J. Li, X. Zhao* and J.M.R. Graham, Vortex force maps for three-dimensional viscous unsteady flows with application to a delta wing, Journal of Fluid Mechanics 900, 2020.

3. X. Yin and X. Zhao*, Sensor-less maximum power extraction control of a hydrostatic tidal turbine based on adaptive extreme learning machine, IEEE Transactions on Sustainable Energy 11, 2020

2. X. Yin, X. Tong, X. Zhao* and A. Karcanias, Maximum power generation control of a hybrid wind turbine transmission system based on H∞ loop shaping approach, IEEE Transactions on Sustainable Energy 11, 2020.

1. X. Yin and X. Zhao*, Composite hierarchical pitch angle control for a tidal turbine based on the uncertainty and disturbance estimator, IEEE Transactions on Industrial Electronics 67, 2020.

* denotes corresponding author