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作 者:徐樾 彭道刚 赵慧荣 孙宇贞 XU Yue;PENG Dao-gang;ZHAO Hui-rong;SUN Yu-zhen(School of Automation Engineering,Shanghai University of Electric Power,Shanghai,China,200090)
机构地区:[1]上海电力大学自动化工程学院,上海200090
出 处:《热能动力工程》2020年第4期210-219,250,共11页Journal of Engineering for Thermal Energy and Power
基 金:上海市“科技创新行动计划”高新技术领域项目(19511101600);上海市科学技术委员会工程技术研究中心项目(14DZ2251100)。
摘 要:对于目前电厂历史运行数据库高维度、大容量,挖掘效率低,算法占用较多的计算资源等问题,基于350 MW机组制粉系统历史稳态运行数据库,提出了基于目标制导的改进Apriori关联规则挖掘算法,利用目标制导方式对数据库进行降维和压缩,进一步通过改进Apriori算法将数据库矩阵转储为有效项坐标数组,挖掘制粉系统给煤机速率、排烟含氧量、排烟温度和一次风量等参数,以原煤单位净发电量为经济评价,获得了优化参数下全工况的制粉系统最优参数值。研究表明:对于中低负荷段,通过减少磨煤机运行台数和增加磨煤机出力,可以有效减少煤耗、一次风量和氮氧化物排放;单耗实验验证,参数优化后磨煤机单耗明显下降,能够有效降低厂用电率。For the current historical operation database of power plant with high dimension and large capacity,low mining efficiency and large computational resources,this paper proposes an improved Apriori association rule mining algorithm based on the historical stable operation database of 350 MW unit pulverizing system.This algorithm uses the target guidance mode to mine the database.Dimension reduction and compression are carried out.The database matrix is transferred to the effective term coordinate array by improving Apriori algorithm.The parameters of coal feeder speed,oxygen content in flue gas,temperature of flue gas and primary air volume are excavated.The economic evaluation is based on the net generating capacity per unit of raw coal,and the optimum operating conditions of the pulverized coal system are obtained.For the middle and low load conditions,by reducing the number of mills and increasing the output of mills,coal consumption,primary air flow and nitrogen oxide emissions can be effectively reduced,and the economy and environmental protection of operation can be improved.In addition,through the unit consumption experiment,the unit consumption of the optimized parameters of the coal mill is significantly reduced,which can effectively reduce the auxiliary power rate,and provide a reference for the field operation guidance.
关 键 词:制粉系统 关联规则 S_Kohonen网络 目标制导 最优参数值
分 类 号:TK229[动力工程及工程热物理—动力机械及工程]
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