Waste energy recovery and energy efficiency improvement in China’s iron and steel industry

• Published in: Applied energy 2017-04, Vol.191, p.502-520
• Main Authors: Zhang, Qi, Zhao, Xiaoyu, Lu, Hongyou, Ni, Tuanjie, Li, Yu
• Format: Article
• Language: English
• Subjects: Energy conservation supply curve; Energy saving technology; Iron and steel industry; Techno-economic model; Waste energy potential
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2017.01.072

•Three WERU potentials were thermodynamic, technical, and economic potentials.•A techno-economic model was proposed to quantify the available waste energy potential.•Various types of waste energy in the steel production process were examined.•Evaluated the energy benefit and cost effectiveness of energy saving technology.•Four scenarios were established to evaluate future energy consumption reduction. Waste energy recovery and utilization presents a crucial opportunity in primary energy reduction and energy efficiency improvement for the global iron and steel industry. However, lack of comprehensive and practical methodology, the exact quantity of waste energy is often poorly quantified. This paper develops an innovative techno-economic model to quantify this opportunity that links theoretical, technical, and economic potential with the characteristics of waste energy resources and waste recycling technologies. Various forms of waste energy, such as sensible heat, pressure energy, and chemical energy, were examined. In addition, four scenarios were established to evaluate future energy saving potential and energy consumption reduction under the synergistic effect of technology promotion and structure adjustment. Findings show that the proportion of practical potential is less than 20% when considering the technical implementation rate for the average industry value. The selected 35 energy-saving technologies contribute to 3.08GJ/t crude steel of cumulative energy savings, and technology implementation plays a significant role in energy consumption reduction. A sensitivity analysis indicates that energy price and discount rate are the most sensitive factors.