摘要
目前新一代信息技术与火力发电技术正在深度融合,燃烧智能优化在火电站节能减排、少人值守等方面具有重要意义,是智慧电厂建设的关键一环。对大数据驱动下的燃烧智能优化以及开环/闭环控制策略分析后得到:在保证安全的前提下,燃烧智能优化将从历史经验向机器学习,开环控制向闭环控制逐渐过渡,最终实现锅炉燃烧参数自动调整,经济与环保性能提升的闭环优化控制。
At present,the new generation of information technology and thermal power generation technology are being deeply integrated.Intelligent combustion optimization is of great significance in terms of energy saving and emission reduction,and unattended control in thermal power plants.It is a key link in the construction of smart power plants.After analyzing the intelligent combustion optimization and open-loop/closed-loop control strategies driven by big data,it is obtained:under the premise of ensuring safety,the intelligent combustion optimization will gradually transition from historical experience to machine learning,open-loop control to closed-loop control,and finally realize the closed-loop optimization control for automatic adjustment of boiler combustion parameters and improvement of economic and environmental performance.
作者
廖彭伟
Liao Pengwei(Datang Central South Electric Power Test Research Institute,HenanZhengzhou 450000)
出处
《科技风》
2023年第24期7-9,共3页
关键词
燃烧优化
历史经验
机器学习
开环
闭环
combustion optimization
historical experience
machine learning
open-loop
closed-loop
