|About this Abstract
||2016 TMS Annual Meeting & Exhibition
||Energy Technologies and Carbon Dioxide Management
||Long Term Prediction of Linz-Donawitz Converter Gas (LDG) in Steel Making Process
||Xiancong Zhao, Hao Bai, Qi Shi, Yang Wang, Zhancheng Guo
|On-Site Speaker (Planned)
Linz-Donawitz converter gas (LDG) or basic oxygen steelmaking gas (BOSG) is one of the most important secondary energy sources in iron and steel industry, whose effective use plays a vital role in energy saving and emission reduction. However, the generation of LDG suffers from great fluctuation with respect to the production status of steel making. Therefore, a long term prediction model of LDG generation would be essential in gas system balancing and optimization. In this paper, a long term prediction model for the generation volume of LDG was proposed based on the steelmaking production estimation from Gantt chart and k-means clustering algorithm. Compared with the previous model, this model considered the influence of different steel type on LDG generation. The experimental results of a steel plant demonstrate that the proposed model exhibits high accuracy and can provide an effective guidance for balancing and scheduling of byproduct gases.
||Planned: A print-only volume