Skip to main content

Study of supercritical coal fired power plant dynamic responses for Grid Code compliance

 Project Brief

SCPP simulator

Supercritical coal fired power plant technology is one of the leading options with improved efficiency and hence reduced CO2 emissions per unit of electrical energy generated. Indeed, power plants using supercritical generation have energy efficiency up to 46%, around 10% above current coal fired power plants. Before any new cleaner coal technologies from supercritical boiler (SC) to carbon capture and storage (CCS) can be adopted, many important issues must be considered and pre-studied.


  • to set up a prestigious partnership of collaborative research between UK and China for cleaner coal technology;
  • to study the dynamic responses of the complete process of coal fired power generation with supercritical units;
  • to establish a fundamental body of knowledge that addresses the practical problems;
  • to develop a software platform and simulation study capacity to model the key physical processes, from fuel preparation to electricity generation;
  • to build a small scale supercritical water experimental facility to study the extreme cases of the process and to verify important aspects of the mathematical model;
  • to study feasible control strategies for improving dynamic responses and possible energy storage methods.

Project Tasks:

  • Mathematical modeling of complete power generation process;
  • Power plant simulation software platform;
  • Laboratory test system;
  • Dynamic simulation for the whole process and Grid Code compliance analysis;
  • Optimal control strategies and optimisation for power plant process.

Modelling and Simulation capability:

  • Supercritical Power plant modelling for pulverised-coal fired thermal power plants
  • Model parameters identification and verification based on Genetic Algorithms and data from operating power plants
  • Power plant dynamic response analysis for load change
  • Control system tuning
  • Advanced predictive control system algorithms


  1. Draganescu, Mihai; Wang, Jihong; Guo, Shen; Wojcik, Jacek; Al-Duri, Bushra ”Overview of Power System Frequency Control in Several European Countries, Australia and China” – submitted
  2. Draganescu, M.; Guo S.; Wojcik, J. ; Wang J.; Xue Y.; Gao Q.; Liu X.; Hou G.: “Dynamic matrix model predictive control of coal feeder speed of a supercritical power plant“ Automation and Computing (ICAC), 2013 19th International Conference, London, UK, Sept. 2013
  3. Omar Mohamed, Jihong Wang, Bushra Al-Duri “Study of a Multivariable Coordinate Control for a Supercritical Power Plant”. 17th International Conference on Automation and Computing. Huddersfield. UK. Sep. 2011
  4. Mohamed, O., Wang, J., Guo, S., Wei, J.L., Al-Duri, B., Lv, J.F. and Gao, Q.R., Mathematical modelling for coal fired supercritical power plants and model parameter identification using genetic algorithms, a book chapter in Electrical Engineering and Applied Computing, Lecture Notes in Electrical Engineering, Vol. 90, Ao, S-I; Gelman, L (Eds.) Springer, ISBN 978-94-007-1191-4, 2011.
  5. Omar Mohamed, Jihong Wang, Bushra Al-Duri, and Shen Guo “Modeling Study of Supercritical Power Plant and Parameter Identification Using Genetic Algorithm” Proceedings of the World Congress on Engineering 2010.London. Vol II, pp973-978.
  6. Omar Mohamed, Jihong Wang, Bushra Al-Duri, and Shen Guo “Modeling Study of a Nonlinear Power Plant Supercritical Boiler-Turbine-Generator System and Identification of Unknown Parameters” Proceedings of the 16th International Conference on Automation & Computing, Birmingham, 11 September 2010.