Condition Monitoring of Limestone and Soft Sensing Model of SO2 Emissions in a Circulating Fluidized Bed Boiler

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• 作者：Wenguang Zhang ; Yue Zhang ; Yazhou Sun ; Jizhen Liu ; Mingming Gao ; Deliang Zeng
• 刊名：Energy & Fuels
• 出版年：2016
• 出版时间：April 21, 2016
• 年：2016
• 卷：30
• 期：4
• 页码：3519-3528
• 全文大小：485K
• 年卷期：0
• ISSN：1520-5029

文摘

Soft sensing models of the desulfurization process are developed in a circulating fluidized bed (CFB) boiler that can capture sulfur dioxide (SO<sub>2sub>) with the limestone sorbent in the furnace. First, calcining utilization of CaCO<sub>3sub> and sulfating utilization of CaO are proposed by mechanism analysis of the theoretical air and flue gas, and the online prediction method is achieved by using an adaptive-tree-structure-based fuzzy inference system (ATSFIS). Second, condition monitoring models of active CaCO<sub>3sub>, active CaO, and soft sensing model of SO<sub>2sub> emissions are studied by using the experimental data of a CFB boiler in China, which can monitor the storage and condition of the limestone in the furnace and predict SO<sub>2sub> emissions. Finally, a nonlinear proportional–integral–derivative (PID) control system based on the above models is designed to control the feed rate of limestone for the reduction of SO<sub>2sub> emissions. The simulation results show that the soft sensing models are consistent with the mechanism test results and can accurately predict SO<sub>2sub> emissions. The control system of limestone is also proven to be effective.