A bottom-up model to estimate the energy efficiency improvement and CO2 emission reduction potentials in the Chinese iron and steel industry

Hasanbeigi, Ali; Morrow, William R.; Sathaye, Jayant; Masanet, Eric; Xu, Tengfang

doi:10.1016/j.energy.2012.10.062

Cited by 232 publications

(49 citation statements)

References 16 publications

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“…Hasanbeigi et al (2013) investigated cost-effective fuel and electricity saving technologies and they concluded that by implementing these in the Chinese iron and steel industry, in total 3.3 PWh fuel and 251 TWh electricity could be saved during the time period -2030. Morrow Iii et al (2013 estimated the total cost-effective energy saving potential for the Indian iron and steel industry at 213 TWh for the same time period.…”

Section: Energy Efficiency Potential In Existing Steel Plantsmentioning

confidence: 99%

Improved Energy Efficiency and Fuel Substitution in the Iron and Steel Industry

Johansson¹

2014

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IPCC reported in its climate change report 2013 that the atmospheric concentrations of the greenhouse gases (GHG) carbon dioxide (CO2), methane, and nitrous oxide now have reached the highest levels in the past 800,000 years. CO2 concentration has increased by 40% since pre-industrial times and the primary source is fossil fuel combustion. It is vital to reduce anthropogenic emissions of GHGs in order to combat climate change. Industry accounts for 20% of global anthropogenic CO2 emissions and the iron and steel industry accounts for 30% of industrial emissions. The iron and steel industry is at date highly dependent on fossil fuels and electricity. Energy efficiency measures and substitution of fossil fuels with renewable energy would make an important contribution to the efforts to reduce emissions of GHGs. This thesis studies energy efficiency measures and fuel substitution in the iron and steel industry and focuses on recovery and utilisation of excess energy and substitution of fossil fuels with biomass. Energy systems analysis has been used to investigate how changes in the iron and steel industry’s energy system would affect the steel plant’s economy and global CO2 emissions. The thesis also studies energy management practices in the Swedish iron and steel industry with the focus on how energy managers think about why energy efficiency measures are implemented or why they are not implemented. In-depth interviews with energy managers at eleven Swedish steel plants were conducted to analyse energy management practices. In order to show some of the large untapped heat flows in industry, excess heat recovery potential in the industrial sector in Gävleborg County in Sweden was analysed. Under the assumptions made in this thesis, the recovery output would be more than three times higher if the excess heat is used in a district heating system than if electricity is generated. An economic evaluation was performed for three electricity generation technologies for the conversion of low-temperature industrial excess heat. The results show that electricity generation with organic Rankine cycles and phase change material engines could be profitable, but that thermoelectric generation of electricity from low-temperature industrial excess heat would not be profitable at the present stage of technology development. With regard to fossil fuels substituted with biomass, there are opportunities to substitute fossil coal with charcoal in the blast furnace and to substitute liquefied petroleum gas (LPG) with bio-syngas or bio synthetic natural gas (bio-SNG) as fuel in the steel industry’s reheating furnaces. However, in the energy market scenarios studied, substituting LPG with bio-SNG as fuel in reheating furnaces at the studied scrap-based steel plant would not be profitable without economic policy support. The development of the energy market is shown to play a vital role for the outcome of how different measures would affect global CO2 emissions. Results from the interviews show that Swedish steel companies regard improved...

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Section: Energy Efficiency Potential In Existing Steel Plantsmentioning

confidence: 99%

Improved Energy Efficiency and Fuel Substitution in the Iron and Steel Industry

Johansson¹

2014

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“…The most common research on energy conservation potential is the conservation supply curve (CSC) model, which expresses energy conservation potential as a function of the marginal cost of conserved energy [22]. This analytical tool captures both the engineering and economic perspectives of energy conservation [23], which has been used in various studies to access the industrial energy-saving potentials [24,25]. From the perspective of the sectoral shifts within manufacturing, Huntington [26] improved the economic projections of industrial energy demand.…”

Section: Literature Reviewmentioning

confidence: 99%

Determinants of Electricity Demand in Nonmetallic Mineral Products Industry: Evidence from a Comparative Study of Japan and China

Sun

2015

Sustainability

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Electricity intensity is an important indicator for measuring production efficiency. A comparative study could offer a new perspective on investigating determinants of electricity demand. The Japanese non-metallic mineral products industry is chosen as the object for comparison considering its representative position in production efficiency. By adopting the cointegration model, this paper examines influencing factors of electricity demand in Japanese and Chinese non-metallic mineral products industries under the same framework. Results indicate that although economic growth and industrial development stages are different between the two countries, major factors that affect the sectoral energy consumption are the same. Specifically, economic growth and industrial activity contribute to the growth of sectoral electricity consumption, while R&D intensity, per capita productivity and electricity price are contributors to the decline of sectoral electricity consumption. Finally, in order to further investigate the development trend of sectoral electricity demand, future electricity consumption and conservation potential are predicted under different scenarios. Electricity demand of the Chinese non-metallic mineral products industry is predicted to be 680.53 TWh (terawatt-hours) in 2020 and the sectoral electricity conservation potentials are estimated to be 118.26 TWh and 216.25 TWh under the moderate and advanced electricity-saving scenarios, respectively. OPEN ACCESSSustainability 2015, 7 7113

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“…Research and innovation are key drivers to realize this transition [1][2][3][4][5][6]. Studies on power technologies and technological innovation as a means to achieve a more efficient energy-intensive industry, with reduced CO 2 emissions are reported in the literature [7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Model Predictive Control of the Exit Part Temperature for an Austenitization Furnace

2016

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Quench hardening is the process of strengthening and hardening ferrous metals and alloys by heating the material to a specific temperature to form austenite (austenitization), followed by rapid cooling (quenching) in water, brine or oil to introduce a hardened phase called martensite. The material is then often tempered to increase toughness, as it may decrease from the quench hardening process. The austenitization process is highly energy-intensive and many of the industrial austenitization furnaces were built and equipped prior to the advent of advanced control strategies and thus use large, sub-optimal amounts of energy. The model computes the energy usage of the furnace and the part temperature profile as a function of time and position within the furnace under temperature feedback control. In this paper, the aforementioned model is used to simulate the furnace for a batch of forty parts under heuristic temperature set points suggested by the operators of the plant. A model predictive control (MPC) system is then developed and deployed to control the the part temperature at the furnace exit thereby preventing the parts from overheating. An energy efficiency gain of 5.3% was obtained under model predictive control compared to operation under heuristic temperature set points tracked by a regulatory control layer.

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A bottom-up model to estimate the energy efficiency improvement and CO2 emission reduction potentials in the Chinese iron and steel industry

Cited by 232 publications

References 16 publications

Improved Energy Efficiency and Fuel Substitution in the Iron and Steel Industry

Improved Energy Efficiency and Fuel Substitution in the Iron and Steel Industry

Determinants of Electricity Demand in Nonmetallic Mineral Products Industry: Evidence from a Comparative Study of Japan and China

Model Predictive Control of the Exit Part Temperature for an Austenitization Furnace

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