【作者】 孔海宁；

【导师】 齐二石；

【作者基本信息】 天津大学 ， 管理科学与工程， 2011， 博士

【摘要】 钢铁行业是我国支柱型产业,近年来在国家政策的拉动下发生了飞速发展。同时,它也是能源密集型产业,消耗的能源占全国能源总消耗量的15%。因此,如何提高能源利用效率,降低能源浪费成为钢铁企业一个亟待解决的问题。其中副产煤气的综合利用是节能降耗的关键突破口。副产煤气是钢铁企业在生产过程中产生的重要二次能源,占钢铁企业总能源消耗的30%,其优化调度对于整个企业节能降耗发挥重大作用。但是,目前关于副产煤气优化调度的研究还处于起步阶段,因此对该课题的研究意义更加重大。在此背景下,本文以钢铁企业副产煤气系统为研究对象,对其优化调度建模进行了深入研究,并将建立的优化模型应用于我国K钢铁企业,达到了降低钢铁企业能源消耗、减少生产成本的目的。主要研究成果包括以下几方面内容:(1)在对钢铁企业副产煤气系统进行深入、详细描述分析的基础上,首次提出了适用于所有钢铁企业副产煤气系统的“三系统两层面”分析架构。“三系统”是指根据副产煤气的工艺流程,把整个副产煤气系统划分成三个相互关联的子系统,分别定义为存储系统、产消系统和转化系统。其中产消系统中的用户根据它们消耗煤气的不同特点分为两大类。第一类是只消耗某一种煤气的用户,这类用户的煤气消耗量无法人为进行优化调度;第二类是可以混烧两种以上煤气或者其它燃料的用户,这类用户和存储系统、转化系统的用户构成的集成系统是本研究优化调度的对象。“两层面”是指在对系统建立优化调度模型的目标函数中,要综合考虑显性成本和隐性成本两方面因素。(2)针对三种副产煤气的发生机理复杂、影响因素众多的特点,选取ARMA时间序列模型对三种煤气的产生量进行建模预测,通过算例分析验证,得到了较高的预测精度。用此模型的预测结果作为优化系统的输入值。(3)对产消系统中只消耗某一种煤气用户的消耗量进行建模预测。根据消耗用户的不同特点将其分为四类。分别采用时间序列方法、基于Levenberg -Marquardt (LM)算法的BP神经网络方法、平滑指数法和线性回归法对其消耗的煤气量进行建模预测,通过算例分析验证,得到了较高的预测精度。用此模型的预测结果作为优化系统的输出值。(4)建立了钢铁企业副产煤气系统动态优化调度模型。选取副产煤气系统生产成本最小化为目标函数,充分考虑影响副产煤气系统生产成本的所有因素,包括外购燃料成本、副产煤气的放散成本、副产煤气柜煤气量波动成本以及锅炉操作成本等;以物料守恒、能量守恒、设备操作要求等作为约束条件;采用混合整数线性规划模型建模,对副产煤气系统进行优化调度。实例分析中,将建立的优化模型应用我国K钢铁企业,节省30%的生产成本。(5)首次将环境成本引入到副产煤气系统优化调度模型中,建立了基于环境成本的钢铁企业副产煤气系统绿色优化调度模型。模型在考虑生产成本的基础上,综合考虑了副产煤气放散、燃烧排放和外购燃料燃烧排放所带来的环境成本。实例分析中,将基于环境成本的绿色优化调度模型与第六章优化模型对比,总成本节约了1.3%。最后,对本文的研究所取得的成果进行了总结,并对本领域未来的研究方向进行了展望。更多还原

【Abstract】 As one of the fundamental pillar industries in China, the iron and steel industry has developed rapidly in recent years. Meanwhile, it is an energy-intensive industry, whose energy cost accounts for 15% of the total energy cost of China. Therefore, efficient use of energy is crucial for reducing total operation cost. Byproduct gases, which are produced during the production of iron and steel without additional cost, are important energy sources to meet energy needs of the process of making iron and steel. Thus, optimization of byproduct gases will play a great role in energy saving. However,few research works have been reported on this field. As a result, it is extremely valuable to give a comprehensive research on this topic.Based on this background, this dissertation studies on byproduct gas system in the iron and steel industry, and makes a deeply research on optimization scheduling of byproduct gases. The optimal model is applied in an iron and steel plant in China, and an optimal result in terms of total cost reduction is obtained. The main contributions in this dissertation are as follows:(1) Based on a deeply and comprehensive analysis of byproduct gas system in the iron and steel industry, a“three systems, two aspects”theory is proposed. Three systems”means the whole byproduct gas system is delimited into three relative systems: produce-and-consume system, store system and transformation system. In produce-and-consume system, byproduct gas consuming users are divided into two kinds, the first kind of which is single-consuming users, and the second kind is mixed-consuming users. Byproduct gas consuming users belonging to the first kind of produce-and-consume system, store system and transformation system compose the objective, which is to be optimized.“Two aspects”means both explicit cost and inexplicit cost should be considered when an optimal model is established.(2) According to different affecting factors of three kinds of byproduct gases, different ARMA models are established separately to predict the supply of byproduct gases. The results obtaining from the forecasting models are used as the input of the system to be optimized. (3) The consumption forecasting models of byproduct gases are also established. Consuming users of byproduct gases are divided into four kinds according to their different consuming characters. Time series prediction model, Levenberg-Marquardt BP (LM-BP) neural network prediction model, linear regression prediction model, and exponential smoothing prediction model are used to predict the demands of four kinds of byproduct gas consuming users. The results obtained from the forecasting models are used as the output of the system to be optimized.(4) An Mixed Integer Linear Programming (MILP) model of byproduct gases in the iron and steel industry is established. The objective function is to reduce total operation cost in the entire energy system for multi-period operation through optimizing byproduct gas distribution. The total operation cost includes penalty cost for emission or shortage of byproduct gases, penalty cost for deviation from normal gasholder levels, penalty cost for burners switching and fuel load changing in the boilers, oil purchasing cost. Besides, certain relative constraints are given and an optimal model is presented. The model is applied in K iron and steel plant and 30% of the total operation cost is reduced.(5) The“environmental cost”is considered in the optimization of byproduct gas system in the iron and steel industry, and a green scheduling model including environmental cost of byproduct gas system is proposed for the first time. The penalty costs for the emission of byproduct gases, and waste gases produced from burned byproduct gases and purchased oil, are all calculated in the objective function to make the model more reasonable. Compared with the previous model proposed in Chapter 6, the green optimal model could save 1.3% total cost.Finally, a summary of the research referred above is concluded and some interesting and challenging topics, which deserve further investigation in the future, are discussed.更多还原