基于数据驱动建模的气化炉配煤成本优化研究

为实现配煤煤质和配煤成本的最优化匹配,以配煤成本为优化目标,气化炉产气量为主要约束,采用数学建模的方式,研究了鄂尔多斯地区煤化工装置气化炉多煤种的用煤和配煤优化问题。根据现场数据,构建了基于数据驱动的气化炉煤质对产量影响的非线性过程模型,通过聚类分析,得到各煤质指标的约束条件;在满足约束条件的情况下,构建煤种与煤质之间的线性模型;通过帕累托遗传算法,在气化炉产气量满足约束条件的同时,给出了成本最低的多煤种配煤策略,并用MATLAB对气化炉配煤优化系统进行可视化组态界面设计。

Study on Optimization of Coal Blending Cost for Gasifier Based on Data-driven Modeling

To realize optimum matching between blended coal quality and coal blending cost,taking the coal blending cost as the optimization target and the gas production of gasifier as the main constraint,the mathematical modeling approach was adopted to study the optimization of coal use and coal blending in coal chemical gasifier in Ordos area.Based on the field data,a data driven nonlinear process model of the influence of coal quality on the output of gasifier was constructed,and the constraint range of each coal quality index was obtained by clustering analysis.Under the condition of satisfying the constraint condition,the linear model between coal type and coal quality was constructed.Through the Pareto genetic algorithm,while the gasifier gas production met the constraint conditions,multi-coal blending strategy with lowest cost was presented,using MATLAB for visual configuration interface design of gasifier coal blending optimization system.