Supercritical CO2 power cycle control strategies: A review

Abstract

In recent years, the supercritical Carbon Dioxide (sCO<inf>2</inf>) cycle has been considered a future advanced technology for power conversion because of its distinctive characteristics, such as compactness, high efficiency and flexibility in handling different heat sources. So far, most studies on sCO<inf>2</inf> cycles have focused on thermodynamics and dynamic modelling, with much less attention given to control systems. Effective control strategies are crucial for optimising performance and ensuring safety. This paper aims to address the gap in the existing literature through providing a detailed review of the control strategies for sCO<inf>2</inf> power cycles, including basic control strategies for startup/shutdown and off-design performance, combined control strategies, and advanced control strategies. The review shows that the combined control strategies approach and control strategies with AI/data-driven techniques are promising approaches, but further research is needed to understand their long-term effectiveness and how well they adapt to different operating conditions. The sCO<inf>2</inf> cycle could also work better if it used advanced control strategies currently proven in other systems, such as fuzzy PID, model predictive control, and fuzzy neural network adaptive controllers. These methods, proven effective in managing complex systems like micro gas turbines, may offer significant improvements for sCO<inf>2</inf> cycle performance.