Title :
Analysis on nonlinearity of load-pressure-water level dynamic model for coordinated control system in thermal power plant
Author :
Liang Tian ; Xin-ping Liu ; Ji-Zhen Liu
Author_Institution :
Sch. of Control & Comput. Eng., North China Electr. Power Univ., Baoding, China
Abstract :
The coordinated control system of thermal power plant was a multivariable, strong-coupled, nonlinear, big inertia and big lag object. By mechanism analysis, based on the statistical analysis of real operation data, the multivariable simplified differential equation model of boiler fuel flow, turbine governor valve opening and feed water flow versus unit load, turbine pressure and drum water level was constructed. The nonlinearity degree on different load operating point of a 600 MW unit was analyzed by using the Gaussian statistics high-order spectrum. The conclusion is that the lower of the load is the more serious the nonlinearity is. It can provide support for the design of fuzzy control, neural network control, calculation, control structure, control parameters and optimization strategy in coordinated control system.
Keywords :
Gaussian processes; boilers; differential equations; fuzzy control; higher order statistics; multivariable control systems; neurocontrollers; nonlinear control systems; power generation control; thermal power stations; turbines; Gaussian statistics high-order spectrum; boiler fuel flow; control structure; coordinated control system; drum water level; feed water flow; fuzzy control design; load-pressure-water level dynamic model; multivariable control system; multivariable simplified differential equation model; neural network control; nonlinear control system; nonlinearity analysis; optimization strategy; power 600 MW; statistical analysis; thermal power plant; turbine governor valve opening; turbine pressure; Analytical models; Boilers; Fuels; Load modeling; Mathematical model; Spectral analysis; Turbines; drum boiler; dynamic model; high-order spectrum; mechanism analysis; nonlinearity analysis;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-180-9
DOI :
10.1109/FSKD.2011.6020047