Predictive control strategy for a supercritical power plant and study of influences of coal mills control on its dynamic responses
- Resource Type
- Conference
- Authors
- Mohamed, Omar; Al-Duri, Bushra; Wang, Jihong
- Source
- Proceedings of 2012 UKACC International Conference on Control Control (CONTROL), 2012 UKACC International Conference on. :918-923 Sep, 2012
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Mathematical model
Computational modeling
Numerical models
Heating
Educational institutions
Object recognition
Turbines
Supercritical Boiler
Mathematical Modeling
Parameter identification
Genetic Algorithms
Model based predictive control
- Language
The paper is to investigate dynamic responses of supercritical power plants (SCPP) and study the potential strategies for improvement of their responses for Grid Code compliance. An approximate mathematical model that reflects the main features of SCPP is developed. The model unknown parameters are identified using Genetic Algorithms (GA) and the model is validated over a wide operating range. A model based predictive control (MPC) is then proposed to speed up the dynamic responses of the power plant by adjusting the reference of the plant local controls instead of direct control signal applications. Simulation results have shown encouraging improvement in performance of the plant with no interference with its associated local controllers.