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AGC Coordination and Steam Temperature Optimization Control System

AGC Coordination and Steam Temperature Optimization Control System

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Based on online model identification, this predictive control technology can replace the traditional "feedforward + PID feedback" control mode, providing an advanced AGC control solution to the thermal power units. It can realize the functions of AGC control, primary frequency regulation control, boiler and turbine coordinated control and turbine governing valve characteristic curve optimization test, etc.. At the same time, factors influencing steam temperature like unit load, flue gas volume, coal feed rate, secondary air volume, feed water temperature, etc. will be comprehensively analyzed, and the disturbance model will be identified. This will help to overcome the difficulties that the traditional solution faces that it is hard to coordinate the regulating speed and stability in the long time lag and multivariable coupling process control.     Besides, it will also enhance the boiler load tracking performance, improve the control quality to those key parameters such as steam pressure and temperature.

Product Features
1. AGC operation speed and load control accuracy can reach 2.0% / min and 0.3% respectively 
2. Main steam pressure and temperature are more stable, under stable load condition:±0.1-0.2MPa /± 2 ℃, under varying load condition: ±0.4MPa /±6℃
3. The set value of main steam temperature is raised by 5-8℃, and the main steam pressure operates exactly in accordance with the sliding pressure curve.
4. The control strategy has true multivariable decoupling control capacity, it can clearly quantify the lagging level and inertia degree of the controlled object, making its dynamic characteristics conforming with the actual characteristics.
5. It provides a control algorithm that can cope with the long time lag of the main steam pressure, overcoming the shortcoming of the traditional PID control mode when facing this problem.
6. It overcomes the long time lag of the attemperating water to the final superheater by applying the foresight function of the predictive control model.