摘要
背压变化直接影响汽轮机运行效率,因此空冷机组背压是滑压运行优化中需要考虑的重要因素。本文为获取考虑背压变化的机组最优滑压运行曲线,利用聚类算法对多个背压工况下的机组的历史数据进行深度挖掘与分析,主要包括不同背压条件下6个月近100个测点(负荷、主汽压力、主蒸汽温度等)的数据,以给出机组最优滑压运行曲线及背压变化对其影响规律。在实际超临界600 MW机组应用效果显示:该方法可在不进行大量专有试验的前提下,准确获取考虑背压变化的机组最优滑压运行曲线,有效提升了机组在变负荷过程中的经济性,也为同类型机组的运行优化提供参考。
The change of back pressure directly affects the operating efficiency of steam turbines,so the back pressure of air-cooled units is an important factor to be considered in the optimization of slip pressure operation.In order to obtain the optimal slip pressure operation curve of the unit considering the change of back pressure,this paper uses clustering algorithm to deeply mine and analyze the historical data of the unit under multiple back pressure conditions,mainly including 6 months under different back pressure conditions.Data from 100 measurement points(load,main steam pressure,main steam temperature,etc.)to give the unit's optimal slip pressure operating curve and the influence of back pressure changes on it.The application effect of the actual supercritical 600 MW unit shows that this method can accurately obtain the optimal slip pressure operating curve of the unit considering the change of back pressure without conducting a large number of proprietary tests,which effectively improves the economy of the unit in the process of variable load It also provides a reference for the operation optimization of the same type of unit.
作者
李健
石家魁
LI Jian;SHI Jia-kui(Inner Mongolia Guohua Hulunbeier Power Generation Co., Ltd., Hulunbuir 021000, China;School of Automation Engineering, Northeast Dianli University, Jilin 132000, China)
出处
《节能技术》
CAS
2020年第2期127-130,共4页
Energy Conservation Technology
基金
中国神华能源股份有限公司国华电力分公司科技项目
吉林省科技发展计划项目(No.20182021009SF)。
关键词
汽轮机
空冷机组
数据挖掘
背压
滑压优化
steam turbine
air cooling unit
data mining
back pressure
sliding pressure optimization