作　　者： ; ; ;

机构地区： 华南理工大学电力学院

出　　处： 《华南理工大学学报（自然科学版）》 2007年第6期34-37,42,共5页

摘　　要： 利用最小二乘支持向量机分别建立了中间储仓式制粉系统的制粉单耗和煤粉细度模型,采用混合遗传算法对制粉单耗模型进行寻优,以获得不同工况下制粉单耗最小的运行参数,然后利用煤粉细度模型对优化后的运行参数进行煤粉细度预测,根据预测出的煤粉细度是否在给定范围内来反馈控制制粉单耗的优化.对某电厂的50MW机组进行现场热态试验,结果表明这种基于煤粉细度反馈控制的制粉优化控制系统具有较高的可靠性和实用性,可以指导运行人员进行制粉系统的优化调整,从而提高机组运行的安全性和经济性. Two models respectively describing the pulverizing unit cost and the coal fineness of the middle-storage pulverizing system are established by means of the least-square support vector machine, and the combinational genetic algorithm is adopted to seek the optimal operation parameters for the minimum unit consumption in different operating modes. The proposed model of coal fineness is then adopted to predict the coal fineness based on the optimized operation parameters, and the predicted results are fed back to control the optimization of the pulverizing unit cost. The hot test at a 50 MW unit in a power plant indicates that the proposed optimization control system based on the feedback control of coal fineness is of high dependability and practicability, which provides guidance for the optimization of the pulverizing system, improves the operation security and saves the cost.

关 键 词： 制粉单耗 煤粉细度 最小二乘支持向量机 制粉系统 优化

领　　域： [动力工程及工程热物理]