Title :
Collaborative optimization model of cost and energy consumption for sintering burden
Author :
Junkai Wang ; Fei Qiao ; Jun Zhu ; Jiacheng Ni
Author_Institution :
Coll. of Electron. & Inf. Eng., Tongji Univ., Shanghai, China
Abstract :
A collaborative optimization model is proposed to integrate the energy performance to the optimization of sintering burden. Firstly, the collaborative optimization problem in sintering burden is described, and then the association model between sinter raw material proportion, production parameter and energy consumption, drum index is provided using data-based methods. Furthermore, objective functions and constrains of the collaborative optimization model are generally formulated based on the association models. During the phase of model reduction and solving, linearization is conducted to the model, and production parameters are fixed to some typical value to investigate the model performance under these specific conditions. Case study derived from a large-scale iron and steel enterprise shows that the association models can demonstrate the relationship effectively. Meanwhile, Energy performance was optimized with the production performance satisfied.
Keywords :
energy consumption; optimisation; sintering; steel manufacture; association models; collaborative optimization model; cost consumption; drum index; energy consumption; large-scale iron enterprise; large-scale steel enterprise; model reduction; production parameter; sinter raw material proportion; sintering burden optimization; Aluminum oxide; Artificial neural networks; Collaboration; Educational institutions; Energy consumption; Optimization; Production; collaborative optimization; cost; data-based; energy consumption; sintering burden;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
DOI :
10.1109/WCICA.2014.7053083