【作者】 汤振兴；

【导师】 王伟；

【作者基本信息】 大连理工大学 ， 检测技术与自动化装置， 2009， 硕士

【摘要】 钢铁焦炉煤气系统是企业副产煤气二次能源的主要组成部分。对焦炉煤气发生量和消耗量及煤气柜位的准确预测,可以改变目前调度人员仅凭经验实现焦炉煤气系统平衡的状态,为制定合理煤气调度方案提供科学指导,从而减少煤气放散损失,降低钢铁企业的能耗。本文通过分析焦炉煤气的发生机理和消耗特性,确定了影响煤气柜柜位变化的主要煤气用户,将焦炉煤气的产消预测归结为一类基于时间序列的预测问题,将煤气柜柜位预测归结为回归预测问题。建立了相应的基于最小二乘支持向量机的产消预测模型和柜位预测模型,并设计了在线学习算法和贝叶斯优化法循环构建和优化预测模型,加快了建模时间,同时提高了预测精度。现场实际数据预测结果表明所建模型在小样本和随机噪声数据环境下能保持很高的预测精度,与其它预测模型相比,适合于钢铁企业的焦炉煤气发生量实时在线预测。针对宝钢能源调度中心调度人员的实际需要,基于本文建立的产消预测模型和柜位预测模型,开发了宝钢焦炉煤气产消预测和调度系统,目前该系统已经投入到宝钢能源中心进行试运行,为调度人员的能源配置及调度过程提供定量的支持。更多还原

【Abstract】 Cove oven gas (COG) as a class of byproduct gas is a significant part of the secondary fuel in steel industry. Precisely forecasting the holder level and generation-consumption demand of the COG system can provide the scheduling workers with the scientific and reasonable guidance for balancing the whole gas system, reducing the waste of gas diffusion and decreasing the energy consumption of the steel enterprise.Based on an analysis of generation mechanism and the consumption characteristics of COG system, the main system units (COG users) that affect the COG gas holder level are determined. The generation and consumption of the COG are considered as a class of prediction problem based on the time series. The prediction of gas holder level is considered as a regression problem. A generation and consumption model and a gas holder level model are established based on the least square support vector machine (LSSVM) for COG system in this paper. An on-line learning algorithm and the circular Bayesian optimization are modeled in order to accelerate the model establishment and enhance the prediction precision. The practical production data from Shanghai BaoSteel is used to verify the proposed model and algorithm. The results demonstrate that the prediction precision can be greatly guaranteed under the circumstance of small training sample and high random noises. In addition, the comparison to some other prediction model also shows that the presented approach accommodates to the on-line prediction process of COG system in steel industry.Combined with the requirement of the Energy Center in Baosteel, the generation-consumption prediction and scheduling system for COG system is developed on the basis of the proposed generation-consumption model and holder level prediction model. At present, this system has been run for test in the Energy Center of Baosteel and provides with an effective guidance for the energy scheduling workers.更多还原