Hong Yue is a systems and control researcher with expertise in modelling, control, optimisation and uncertainty quantification. Her methodological contributions have been developed across multiple engineering domains and are now applied primarily to wind energy, offshore renewables and sustainable energy systems.

In recent years, Hong’s work has focused on control, optimisation and decision-support methods for renewable and integrated energy systems, including wind energy, battery energy storage, integrated energy systems and floating offshore wind farms. Her research has contributed to model predictive control for wind turbines and wind energy conversion systems, airborne wind energy technologies, battery health estimation, and AI-enabled forecasting and decision-making for future energy networks.

In parallel, Hong has pursued a long-standing programme of research in optimal experimental design and uncertainty quantification, developing novel methodologies that have been applied to biochemical systems, process systems and energy systems. These methods support more efficient data acquisition, model development and decision-making under uncertainty.

Across these research strands, Hong combines model-based and data-driven approaches to develop advanced control, optimisation and analysis methods for complex systems operating under uncertainty. Her work spans model predictive control, stochastic distribution control, optimal experimental design and uncertainty-aware optimisation, with applications across diverse domains including process systems, biological and biochemical systems, renewable energy, and autonomous systems.

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Key expertise

• Advanced control, optimisation and digitalisation methods for sustainable energy systems
• Wind energy systems, including wind turbine control, floating offshore wind and airborne wind energy
• Optimal experimental design, uncertainty quantification and system identification
• Data-driven modelling, analysis and decision-support for complex engineering systems

Hong Yue’s work strengthens WEC’s capability in uncertainty-aware control, systems analysis and optimisation, supporting the reliable, efficient and sustainable design and operation of future energy systems where variability, stochastic behaviour and complex interactions play a central role.