Hong Yue is a control systems researcher with expertise in advanced control theory, stochastic system modelling and optimisation, applied to complex and uncertainty-dominated energy systems. Her work combines a strong mathematical foundation with practical engineering applications, particularly in smart grids, renewable energy systems and energy storage integration.

A defining aspect of her research is the treatment of uncertainty beyond classical Gaussian assumptions. She has developed and applied control frameworks based on probability density functions and entropy measures, enabling control design for nonlinear stochastic systems subject to bounded and non-Gaussian disturbances. This work extends conventional minimum-variance approaches by allowing controllers to act directly on the shape of output distributions rather than only their mean behaviour.

These methods rely on rigorous stochastic modelling, functional approximation techniques and numerical optimisation, and are supported by stability analysis and simulation studies. Through this approach, Hong has contributed to the theoretical foundations of uncertainty-aware control for safety-critical and highly variable systems.

Building on this control-theoretic foundation, her more recent work focuses on energy system optimisation, particularly at the interface between renewable generation, energy storage and end-use behaviour. She has developed optimisation frameworks for residential and distributed energy systems that integrate photovoltaic generation, battery storage and electric vehicles under time-varying tariffs.

A distinctive feature of this work is the explicit probabilistic modelling of user behaviour, such as electric-vehicle driving and parking patterns. Rather than relying on deterministic assumptions, statistical usage models are embedded directly within optimisation routines, allowing cost, degradation and operational constraints to be evaluated in a realistic and data-informed manner.

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Key expertise

• Advanced control of stochastic and nonlinear dynamic systems
• Probability-density and entropy-based control methods
• Optimisation of energy systems with storage and electric vehicles
• Uncertainty modelling and data-informed decision making
• Control and optimisation for smart grids and renewable integration

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