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Turbine Follower Control Strategy Design Based on Developed FFPP Model

Authors: Ali Ghaffari, Mansour Nikkhah Bahrami, Hesam Parsa

Abstract:

In this paper a comprehensive model of a fossil fueled power plant (FFPP) is developed in order to evaluate the performance of a newly designed turbine follower controller. Considering the drawbacks of previous works, an overall model is developed to minimize the error between each subsystem model output and the experimental data obtained at the actual power plant. The developed model is organized in two main subsystems namely; Boiler and Turbine. Considering each FFPP subsystem characteristics, different modeling approaches are developed. For economizer, evaporator, superheater and reheater, first order models are determined based on principles of mass and energy conservation. Simulations verify the accuracy of the developed models. Due to the nonlinear characteristics of attemperator, a new model, based on a genetic-fuzzy systems utilizing Pittsburgh approach is developed showing a promising performance vis-à-vis those derived with other methods like ANFIS. The optimization constraints are handled utilizing penalty functions. The effect of increasing the number of rules and membership functions on the performance of the proposed model is also studied and evaluated. The turbine model is developed based on the equation of adiabatic expansion. Parameters of all evaluated models are tuned by means of evolutionary algorithms. Based on the developed model a fuzzy PI controller is developed. It is then successfully implemented in the turbine follower control strategy of the plant. In this control strategy instead of keeping control parameters constant, they are adjusted on-line with regard to the error and the error rate. It is shown that the response of the system improves significantly. It is also shown that fuel consumption decreases considerably.

Keywords: Attemperator, Evolutionary algorithms, Fossil fuelled power plant (FFPP), Fuzzy set theory, Gain scheduling

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1083693

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References:


[1] R. D. Bell, and .K. J. Ã║ström, "Dynamic models for boiler-turbinealternator units: Data logs and parameter estimation for a 160 MW unit." Report TFRT-3192, Lund Institute of Technology, Sweden, 1987
[2] H. Habbi, M. Zelmat, and B. Ould Bouamama, , "A dynamic fuzzy model for a drum-boiler-turbine system" , Automatica 39 ,1213 - 1219 , 2003
[3] H.G. Kwatny, and C. Maffezzoni, "Control of Electrical Power", Control system applications, 281-311, CRC press, 2000
[4] R. Woo and G. R. Anderson, "Dynamic Response of a super critical Power plant", Instrumentation technology, 1969
[5] J.A. Rovnak, and R. Corlis, "Dynamic matrix based control of fossil power plants", IEEE Transaction on energy conversion, Vol. 6, No. 2, 1991
[6] F.P. De Mello, "Boiler Models For System Dynamic Performance Studies" IEEE Transaction on Power Systems, Vol.6, No. 1, February 1991
[7] C.K Weng,, A. Ray, and X. Dai, "Modeling of Power Plant Dynamics and Uncertainties for Robust Control Synthesis", Application of Mathematical Modeling, Vol. 20, Elsevier Science Inc, July 1996
[8] L. Changliang, L. Jizhen, and N. Yuguang, and Weiping, L."Nonlinear Boiler Model of 300MW Power Unit for System Dynamic Performance Studies", IEEE, 0-7803-7090-2/01, 2001
[9] Y.A. Cengel, and M.A. Boles, "Thermodynamics-an engineering approach", McGraw-Hill, 4th edition
[10] C.A. Pe├▒a-Reyes, and M. Sipper, "Fuzzy CoCo: A Cooperative- Coevolutionary Approach to Fuzzy Modeling", IEEE Transactions on fuzzy systems, Vol. 9, No. 5, 2001
[11] D. Živkovi├ª, "Nonlinear Model of the Condensing Steam Turbine", FACTA Universities Series, Mechanical Engineering, Vol.1, No.7, 2000, pp. 871 - 878
[12] Z. Michalewicz, "Genetic Algorithms + Data Structures = Evolution Programs", third ed. Heidelberg: Springer-Verlag, 1996
[13] J. Richardson, M. Palmer, G. Liepins, and M. Hilliard, 1989, "Some Guidelines for Genetic Algorithms with Penalty Functions", Proc. of the Third International Conference on Genetic Algorithms
[14] Z. Zhao, M. Tomizuka, and S. Isaka "Fuzzy gain scheduling of PID controllers", IEEE Transaction on system man and cybernetics. Vol. 23, No. 5, 1993
[15] JG. Zeigler, NB. Nichols, "Optimum settings for automatic controllers", Trans ASME, 1942, 64:11