基于负荷预测和负荷最优分配的工业锅炉房最优运行  

Optimal Operation of Industrial Boiler Plants Based on Load Forecast and Load Assignment

作　　者：曹家枞[1] 邱广[1] 朱冬林[1] 林星春[1] 

机构地区：[1]东华大学环境科学与工程学院,上海201620

出　　处：《东华大学学报（自然科学版）》2007年第1期25-31,共7页Journal of Donghua University(Natural Science)

摘　　要：应用BP神经网络预测锅炉房的日负荷曲线保证蓄热器运行的最优分段,采用最小差模型(MDM)法进行负荷的最优分配,据此编写相应的计算机程序.计算实例证明可有效减少锅炉房-蓄热器系统的日燃料耗量.The error back propagation （BP） neural networks are used to perform the forecast of daily load curves so that the optimal segmentation of the daily load curve can be accomplished. Then the plant load is optimally assigned to boilers by the minimum-departure model （MDM）. A computer program is completed and used in an example. The results show that the fuel costs of the boiler plant are reduced.

关 键 词：锅炉房 蓄热 最优运行 神经网络 负荷预测 负荷分配 

分 类 号：TK22[动力工程及工程热物理—动力机械及工程]