Based on the history operation data of flue gas desulfurization (FGD) system in thermal power plant, using data mining method, several important operation parameters were optimized. The optimal operation parameters values, which can meet the required desulphur-ization efficiency and the maximum economic efficiency, were confirmed. A fuzzy association rule mining algorithm was proposed to determine the optimization target of limestone-gypsum wet FGD in a 330 MW unit. Firstly, the fuzzy data set of history data was structured by the competitive agglomeration algorithm that can determine the cluster number and soften the demarcation of the boundaries. Secondly, for meeting the desulfurization efficiency, treating the economic benefit as optimization objective, using fuzzy Apriori association rules algorithm for data mining, the frequent item set was gained. Finally, the optimal objective value of the operation parameters was obtained. The experimental results and theoretical analysis show that the mining results can contribute to the economic operation of desulfurization system in power plant and can provide the important reference for the optimal operation of unit.%基于火电机组脱硫系统在实际运行过程中积累的历史数据,采用数据挖掘的方法对系统的重要运行参数进行优化,挖拙出在满足脱硫效率要求时经济效益最大的最佳运行参数值.提出了一种模糊关联规则挖掘算法,对某330 MW机组石灰石-石膏湿法烟气脱硫系统运行优化目标值进行确定.针对历史运行数据利用竞争凝聚算法决定分类数、软化划分边界并构造优化的模糊数据集,以满足脱硫效率为前提,以经济效益作为优化目标,利用模糊Apriori关联规则挖掘算法得到的频繁项集进行关联规则挖掘,最终得到运行参数最优目标值,实验结果和理论分析表明挖掘结果能为电厂脱硫系统的经济运行作出贡献,可以作为指导机组优化运行的重要依据.
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