摘要
目前绝大部分电厂的负荷率不高,但是电除尘设备大都维持在其对应设计煤种满负荷时的工况下运行,导致大量电能被浪费,因此电除尘自动控制技术应运而生。传统的电除尘自动控制技术是根据机组的负荷自动调整电除尘器出力的,不仅控制精度较低,而且对不同煤种的适应能力较弱。通过人工神经网络预测实现对入炉煤水分的预测,再通过机组稳定工况下能量平衡关系得到入炉煤的低位发热量,最后通过线性回归得出入炉煤的灰分,在此基础上,建立灰负荷率并作为电除尘节能系统的输入,通过对比节能系统投入前后不同负荷下的电除尘电耗情况,证明电除尘节能系统节能效果显著。
At present most of the plant load factor is not high,but most of electrostatic precipitator(ESP)equipment is maintained at run-time conditions of the corresponding design coal at full capacity,resulting in waste of a large amount of power and hastening the emergence of ESP automatic control technology.The traditional electric precipitator automatic control technology automatically adjusts the output of the electric precipitator according to the load of the unit,which not only has low control accuracy,but also has weak adaptability to different coal types.Therefore,the prediction of the coal moisture is realized through artificial neural network,and the low calorific value of the coal is obtained through the energy balance relationship under the stable working condition of the unit.Finally,the ash content of the coal is obtained through linear regression through coal moister and low calorific value.On this basis,the ash load rate is established and used as the input of the energy saving system of ESP.The comparison of power consumption of electrostatic precipitator under different loads before and after launching the energy saving system confirms the remarkable energy saving utility of ESP energy saving system.
作者
陈光宇
郑逸飞
周江
周高盛
郑日桂
孙文燕
廖丽霞
曾燕娥
CHEN Guangyu;ZHENG Yifei;ZHOU Jiang;ZHOU Gaosheng;ZHENG Rigui;SUN Wenyan;LIAO Lixia;ZENG Yane(Fujian Kemen Power Generation Co.,Ltd.,Fuzhou 350512,China;Electric Power Research Institute of State Grid Fujian Electric Power Co.,Ltd.,Fuzhou 350007,China)
出处
《电工技术》
2023年第22期15-18,共4页
Electric Engineering
关键词
煤
电除尘
灰分预测
节能
coal
electrostatic precipitator
ash prediction
energy saving
