Generalized Predictive Control for superheated steam temperature regulation in a supercritical coal-fired power plant
Generalized Predictive Control for superheated steam temperature regulation in a supercritical coal-fired power plant
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DOI：
10.17775/cseejpes.2015.00009
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发表时间：
2015-05
影响因子：
7.1
通讯作者：
M. Draganescu;Shengkun Guo;Jacek Wojcik;Jihong Wang;Xiangjie Liu;G. Hou;Yali Xue;Qirui Gao
中科院分区：
文献类型：
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作者：
M. Draganescu;Shengkun Guo;Jacek Wojcik;Jihong Wang;Xiangjie Liu;G. Hou;Yali Xue;Qirui Gao
针对超临界燃煤电厂过热汽温调节问题，提出了一种广义预测控制（GPC）策略。利用实验数据对被控对象的未来行为进行近似预测，建立了被控对象的受控自回归滑动平均（CARMA）模型。GPC算法需要该模型来计算未来的控制输入。设计了一种新的GPC控制器，并通过大量的仿真研究对其性能进行了测试。与传统PID控制器相比，GPC控制器控制的汽温更稳定。稳定的蒸汽温度导致更有效的工厂操作和节能，如模拟结果所示。当电厂经历负荷需求变化和由煤米尔斯故障引起的扰动时，也测试了电厂性能的改善。
The design and implementation of a Generalized Predictive Control (GPC) strategy for the superheated steam temperature regulation in a supercritical (SC) coal-fired power plant is presented. A Controlled Auto-Regressive MovingAverage (CARMA) model of the plant is derived from using the experimental data to approximately predict the plant's future behavior. This model is required by the GPC algorithm to calculate the future control inputs. A new GPC controller is designed and its performance is tested through extensive simulation studies. Compared with the performance of the plant using a conventional PID controller, the steam temperature controlled by the GPC controller is found to be more stable. The stable steam temperature leads to more efficient plant operation and energy saving, as demonstrated by the simulation results. Plant performance improvement is also tested while the plant experiences the load demand changes and disturbances resulting from the malfunctioning of coal mills.