Application of steam temperature optimization software in 500MW coal-fired unit

Abstract: The application information of steam temperature optimization software in 500MW coal-fired units is provided by excellent flowmeter and flowmeter manufacturers and quotation manufacturers. I. Introduction With the intensification of competition in the power industry, many power companies have adopted various means to adapt to the development of the new situation. Although no one can predict how the future will be, the most immediate measures are to reduce operation and maintenance costs, reduce coal consumption, and improve. For more flowmeter manufacturers to select models and prices, you are welcome to inquire. The following is the application article details of steam temperature optimization software in 500MW coal-fired units. 1. Introduction With the intensification of competition in the power industry, many power companies have adopted various means to adapt to the development of the new situation. Although no one can predict what the future will hold, the most immediate measures are to reduce operating and maintenance costs, reduce coal consumption, and increase unit availability. This article will take MidAmericanEnergy's GeorgeNeal Power Plant Unit 3 renovation project as an example to introduce the application of Smartprocess steam temperature optimizer in steam temperature control to improve the quality of steam temperature control, reduce furnace tube leakage, and ultimately reduce power generation costs. 2. User Background The GeorgeNeal Power Station is located by the Missouri River in IOWA. Its No. 3 unit, with a capacity of 515MW, adopts Foster-Wheeler hedging drum boiler and GE steam turbine, and 6 MPS-89 coal mills supply pulverized coal for 24 burners in the front and rear furnace walls respectively. The superheated steam temperature is controlled by the primary and secondary water sprays, and the reheated steam temperature is controlled by the water spray, superheated baffles and reheated baffles. The boiler control system adopts WDPF system. Before the transformation of the control system, the excessive oscillation of the steam temperature was too large, which limited the response speed of the unit. The response speed under low load was 1%/min, and the response speed under high load was 0.3%/min. Therefore, the user discussed with EPRI and the control system supplier Emerson, and decided to use the Smartproce steam temperature optimizer to improve the temperature response under dynamic load changes, thereby achieving an increase in the load response speed. Smartprocess steam temperature optimizer is a very important feedforward function in Emerson's power optimization software package to achieve the purpose of improving the quality of steam temperature control. 3. Engineering planning The entire control system renovation project needs to achieve two tasks; one is to improve the steam temperature control and improve the load response capability of the unit; the other is to compare the conventional PID control method and record the improvement effect of the optimized system. The main steps of the whole project include: ● Documenting the existing system design and performance ● Optimizing and testing the current system ● Designing and installing an advanced steam temperature control system ● Testing and recording the performance of the advanced control system ● Preparing a test report IV. Existing system The existing control system to be evaluated is a conventional PID control system. The secondary water spray of the superheater adopts cascade control, one outer loop controller and two inner loop controllers. The first-stage water spray of the superheater also adopts cascade control, and there are two internal and external loop controllers. The flue gas damper is controlled within a preconfigured range by a reheat temperature controller. The reheat water spray control loop is a single PID loop. The most peculiar thing in the existing control system is that there is no feedforward signal in the steam temperature control loop. Figure 1 is a functional block diagram of the secondary water spray control loop. The TTFuzz module is a feedforward module added after optimization. Before starting the optimization work, record the tuning settings of the PID controller and other adjustable modules in the existing loop. Then adjust the existing PID parameters in order to improve the control response quality. The superheated water spray adjustment parameters are greatly adjusted, and the load response speed is significantly improved. Further experimental analysis shows that the current parameter settings are very close to the settings given by the optimizer under certain operating conditions. Minor changes have been made to the flue gas damper adjustment settings and the reheat water spray settings. 5. Model identification and testing To design an advanced multivariable controller, a process model must be established first. There are many ways to build process models, the most practical is model identification. Model identification (or system identification) needs to collect the controller input and output and vibration variable data under the specific operating condition test of the unit. These experiments are used to stimulate all the process model features required for modeling. Typical experiments include: open-loop step experiments, pseudo-random binary sequence experiments, and frequency response experiments. If required, a closed-loop setpoint step test can also be performed. If the disturbance is known to have a significant effect on the process object, a disturbance test must be performed. For this project, all steam temperature control loops are subjected to open-loop step tests and closed-loop setpoint response tests.

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