Study of a multivariable coordinate control for a supercritical power plant process
Study of a multivariable coordinate control for a supercritical power plant process
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DOI：
10.5923/j.ijee.20120205.04
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发表时间：
2011-11
期刊：
影响因子：
--
通讯作者：
O. Mohamed;Jihong Wang;B. Al-Duri
中科院分区：
文献类型：
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作者：
O. Mohamed;Jihong Wang;B. Al-Duri
介绍了600 MW超临界（SC）电厂新型多变量协调控制的研究工作。本文第一部分介绍了该装置的数学模型。然后，基于模型预测控制（MPC）理论设计了一种控制策略。值得注意的是，线性MPC单独执行仅在有限的小的负载变化下的干扰和测量噪声从预测算法概括的一个恒定的水平。因此，提出了一种动态补偿器与MPC并行工作，以跟踪大的负载变化。因为模型已经用现场闭环响应数据识别，所以多变量最优控制信号被用作对工厂本地控制的参考的校正，而不是直接应用控制信号。仿真结果表明，该控制器对大负荷变化具有良好的响应性能。此外，已经证明，通过实施合适的磨煤机控制器，可以通过增加磨煤能力和煤粉排放来改善对象的动态响应。
The paper presents the recent research work in study of a novel multivariable coordinate control for a 600MW supercritical (SC) power plant. The mathematical model of the plant is described in the first part of the paper. Then, a control strategy is designed based on Model Predictive Control (MPC) theory. It is noticed that the linear MPC alone performs well only within limited small load changes under a constant level of disturbances and measurement noises generalized from the prediction algorithms. So, a dynamic compensator is proposed to work in parallel with the MPC to track large load changes. Because the model has been identified with on-site closed loop response data, the multivariable optimal control signals have been used as a correction to the reference of the plant local controls instead of direct control signal applications. The simulation results show the good performance of the controller in response to the large load changes. Furthermore, it has been proved that the plant dynamic response can be improved by increasing the coal grinding capability and pulverized coal discharging through implementation of suitable coal mill controllers.