摘要
针对目前化工原料煤在配煤方案制定时采用经验预测方式,存在预测效率和准确率偏低且工作量大等问题,采用大数据、工业互联网及机器学习等技术,构建基于大数据的化工原料煤智慧配煤优化系统,并结合煤气化方面的专业技术和配煤预测模型,将大量的原煤数据纳入数据库,对原煤数据开展了数据使用价值的挖掘。打造的集煤质数据库、二元/三元配煤、智能配煤、气化性能预测、可视化数据分析、系统管理等功能于一体的化工原料煤智慧配煤优化系统,可为气化炉用户提供精准配煤方案,并指导化工原料煤新产品的开发。
In view of the low efficiency and accuracy,and heavy workload caused by the empirical prediction method in coal blending scheme preparation of feed coal for coal chemical industry,a big data-based intelligent coal blending optimization system of feed coal for coal chemical industry is built by the technologies of big data,industrial Internet and machine learning.Combined with the professional technology of coal gasification and prediction model,a large number of raw coal data are included into the database,and the usage value of data has been widely mined.The intelligent coal blending optimization system integrating the functions of coal quality database,binary/ternary coal blending,intelligent coal blending,gasification performance prediction,visual data analysis and system management can accurately recommend coal blending scheme for gasifier users and guide the development of new feed coal products for coal chemical industry.
作者
孙凯蒂
刘臻
谷红伟
王鹤
杨传沓
SUN Kaidi;LIU Zhen;GU Hongwei;WANG He;YANG Chuanda(National Institute of Clean-and-Low-Carbon Energy,Changping,Beijing 102211,China;China Energy Trading Group Co.,Ltd.,Dongcheng,Beijing 100011,China)
出处
《中国煤炭》
2023年第5期108-116,共9页
China Coal
关键词
大数据
化工原料煤
机器学习
智能配煤
big data
feed coal for coal chemical industry
machine learning
intelligent coal blending