摘要
石灰石-石膏湿法脱硫系统中,氧化风量的精准控制对提高脱硫效率、降低能耗及优化副产物质量至关重要。文章提出了一种基于神经网络预测与模糊PID控制相结合的氧化风量精准控制方法,通过实时监测烟气SO_(2)浓度、流量及浆液参数,动态调节氧化风量。试验结果表明,该方法在不同负荷工况下可将风量控制偏差控制在规定范围内,缩短响应时间,提升脱硫效率,降低年耗电量。通过对某600 MW和300 MW燃煤电厂的实测数据验证,控制系统在复杂工况下具有较高的稳定性和经济性,为脱硫系统的智能化运行提供了技术支持。
In the limestone-gypsum wet desulfurization system,the precise control of oxidation air volume is crucial for enhancing desulfurization efficiency,reducing energy consumption and optimizing the quality of by-products.The article proposes a precise control method for oxidation air volume based on the combination of neural network prediction and fuzzy PID control.By monitoring the SO_(2) concentration,flow rate and slurry parameters of flue gas in real time,the oxidation air volume is dynamically adjusted.The test results show that this method can control the air volume control deviation within the specified range under different load conditions,shorten the response time,improve the desulfurization efficiency and reduce the annual power consumption.The measured data of a certain 600 MW and 300 MW coal-fired power plant have verified that the control system has high stability and economy under complex working conditions,providing technical support for the intelligent operation of the desulfurization system.
作者
程宇
王哲
陶嘉伟
李志强
张鑫
CHENG Yu;WANG Zhe;TAO Jiawei;LI Zhiqiang;ZHANG Xin
出处
《电力系统装备》
2025年第12期38-40,共3页
Electric Power System Equipment
关键词
脱硫系统
氧化风量
精准控制
神经网络
模糊PID
能耗优化
desulfurization system
oxidation air volume
precise control
neural network
fuzzy PID
energy consumption optimization
