电气参数的动态估计和能量优化方法  

Dynamic Estimation of Electric Parameters and Energy Optimization

作　　者：王瑞安[1] 王莹 高克伟 孙彦广[4] 

机构地区：[1]哈尔滨电站工程有限责任公司,哈尔滨150046 [2]辽宁省朝阳热电厂,朝阳122000 [3]江阴兴澄钢铁有限公司,江阴214433 [4]冶金自动化研究设计院,北京100071

出　　处：《仪器仪表学报》2002年第z2期497-498,500,共3页Chinese Journal of Scientific Instrument

摘　　要：炼钢电弧炉是耗能大户。由于用电设备的电气参数的时变性,为电能优化带来困难。本文基于智能技术和PC技术,开发了一种电气参数动态估计和能量优化方法。首先用特殊设计的高速电量采集系统获取外部信号,应用人工神经元网络进行电气参数的动态估计,然后进行能量优化。EAF for steel making consumes a lot of electric energy. It is difficult to optimize the energy because of the electric parameter time-varying property. Based on artificial neural network technology and PC technology, a dynamic estimation method of EAF electric parameters is presented. First, a special designed high speed electrical variable measurement system is adopted to collect the outer signals, an artificial neural network model is set to dynamically estimated the interested electric parameters, support the energy optimization.

关 键 词：动态估计 人工神经元网络 电气参数 

分 类 号：TP2[自动化与计算机技术—检测技术与自动化装置]