Optimal modelling and artificial intelligent control of ultra-supercritical power unit: a survey

Ultra-supercritical (USC) units, which represent the forefront of clean coal technology, offer superior efficiency and significantly lower emissions compared to conventional units. However, their operation under extreme conditions introduces complex technical challenges that necessitate sophisticated solutions. The existing literature review indicates a notable lack of dedicated reviews on modelling and control strategies for USC units. To address this gap, the study begins by contextualizing the operational challenges, technological significance, and fundamental principles of USC units within contemporary energy systems. Subsequently, a comprehensive examination of modelling methodologies is provided, covering both first-principles and experimental approaches, along with a critical discussion of their applicability and limitations. The review further analyzes advanced control strategies, ranging from classical linear and nonlinear methods to cutting edge artificial intelligence based techniques, assessing their performance in enhancing operational efficiency and flexibility. Finally, promising future research directions are outlined, offering insights into next generation modelling and control paradigms that may further optimize USC unit performance. Unlike earlier surveys focussed on conventional coal-fired units, this work specifically addresses the unique requirements and emerging intelligent solutions tailored to ultra-supercritical technology.