This paper presents a critical review of the research conducted for modeling and controlling supercritical power plants. Thermal power plants are classified according to the boiler pressure to supercritical and subcritical. The modeling concepts and control strategies of supercritical generation units are far more complex than those of subcritical. On the other hand, supercritical generation technologies are more efficient and much cleaner than subcritical generation units. From a deep technical analysis of the literature, there is no review that is dedicated to models-based control of supercritical power plants and most previous reviews are found to be too general to modeling-based control of fossil fuelled energy sources. This review reports the advancements on modeling and control of supercritical and ultra-supercritical plants as cleaner generation technologies. The various published achievements for modeling supercritical and ultra-supercritical units have been reviewed. The control strategies that fulfill the practical load demand requirements while keeping optimum efficiencies are also reviewed. Finally, expected future directions are reported as recommendations to overcome future challenges. The paper can be used as a brief educational directory to the postgraduate students or future researchers in the field.

This paper reviews the modeling techniques and control strategies applied to gas turbine power generation plants. Recent modeling philosophies are discussed and the state-of-the-art feasible strategies for control are shown. Research conducted in the field of modeling, simulation, and control of gas turbine power plants has led to notable advancements in gas turbines’ operation and energy efficiency. Tracking recent achievements and trends that have been made is essential for further development and future research. A comprehensive survey is presented here that covers the outdated attempts toward the up-to-date techniques with emphasis on different issues and turbines’ characteristics. Critical review of the various published methodologies is very useful in showing the importance of this research area in practical and technical terms. The different modeling approaches are classified and each category is individually investigated by reviewing a considerable number of research articles. Then, the main features of each category or approach is reported. The modern multi-variable control strategies that have been published for gas turbines are also reviewed. Moreover, future trends are proposed as recommendations for planned research.

This paper presents a novel strategy for implementing model predictive control (MPC) to a large gas turbine power plant as a part of our research progress in order to improve plant thermal efficiency and load–frequency control performance. A generalized state space model for a large gas turbine covering the whole steady operational range is designed according to subspace identification method with closed loop data as input to the identification algorithm. Then the model is used in developing a MPC and integrated into the plant existing control strategy. The strategy principle is based on feeding the reference signals of the pilot valve, natural gas valve, and the compressor pressure ratio controller with the optimized decisions given by the MPC instead of direct application of the control signals. If the set points for the compressor controller and turbine valves are sent in a timely manner, there will be more kinetic energy in the plant to release faster responses on the output and the overall system efficiency is improved. Simulation results have illustrated the feasibility of the proposed application that has achieved significant improvement in the frequency variations and load following capability which are also translated to be improvements in the overall combined cycle thermal efficiency of around 1.1 % compared to the existing one.