A neural net model-based multivariable long-range predictive control strategy applied in thermal power plant control

• Published in: IEEE transactions on energy conversion 1998-06, Vol.13 (2), p.176-182
• Main Authors: Prasad, G., Swidenbank, E., Hogg, B.W.
• Format: Article
• Language: English
• Subjects: Algorithm design and analysis; Algorithms; Applied sciences; Boilers; Computer simulation; Energy; Energy. Thermal use of fuels; Equipments for energy generation and conversion: thermal, electrical, mechanical energy, etc; Error correction; Exact sciences and technology; Installations for energy generation and conversion: thermal and electrical energy; Installations for industrial steam generation; Neural networks; Oil fired boilers; Power generation; Power system modeling; Prediction algorithms; Predictive control; Predictive control systems; Predictive models; Pressure control; Temperature control
• ISSN: 0885-8969; 1558-0059
• DOI: 10.1109/60.678982

A constrained multivariable control strategy along with its application in more efficient thermal power plant control is presented in this paper. A neural network model-based nonlinear long-range predictive control algorithm is derived, which provides offset-free closed-loop behavior with a proper and consistent treatment of modeling errors and other disturbances. A multivariable controller is designed and implemented using this algorithm. The system constraints are taken into account by including them in the control algorithm using real-time optimization. By running a simulation of a 200 MW oil-fired drum-boiler thermal power plant over a load-profile along with suitable PRBS signals superimposed on controls, the operating data is generated. Neural network (NN) modeling techniques have been used for identifying global dynamic models (NNARX models) of the plant variables off-line from the data. To demonstrate the superiority of the strategy in a MIMO case, the controller has been used in the simulation to control main steam pressure and temperature, and reheat steam temperature during load-cycling and other severe plant operating conditions.