Exergy loss minimization for a blast furnace with comparative analyses for energy flows and exergy flows

Liu, Xiong; Chen, Lingen; Qin, Xiaoyong; Sun, Fengrui

doi:10.1016/j.energy.2015.09.008

Cited by 75 publications

(29 citation statements)

References 22 publications

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“…The results showed that 22.8% exergy output of waste heat can be effectively recovered by optimizing the sinter bed height. To reduce the exergy losses, Liu et al compared the energy flows and exergy flows of a blast furnace. Liu et al also analyzed the exergy flows in the coking process.…”

Section: Evaluation Methods Of Energy Efficiency In the Isimentioning

confidence: 99%

Review of evaluation methodologies and influencing factors for energy efficiency of the iron and steel industry

Sun

et al. 2019

Int J Energy Res

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Summary To promote the sustainable development of the iron and steel industry (ISI), evaluation methods and influencing factors of energy efficiency have been studied in the past decades. A systematic review of these methodologies and influencing factors is presented in this paper. Initially, this paper states the development, current situation, and energy consumption of the world's ISI. Then, the definition of energy efficiency is described. After that, the evaluation methods are categorized as single‐factor methods (including these indicators of thermodynamic, thermos‐physical, thermo‐economic, and economic) and multifactor methods (including parametric and nonparametric methods). Furthermore, typical evaluation methods are highlighted. Thermal analysis method and exergy analysis method are routinely combined to optimize the energy utilization. Data envelopment analysis (DEA) and stochastic frontier analysis (SFA) are widely concerned and well developed to gain a better economic benefit. Malmquist index method is often associated with DEA to analyze the technical process and return to scale. Some emerging methods are proposed, for example, the three‐stage DEA method together with DEA and SFA. Finally, the influencing factors of energy efficiency in the ISI are discussed, including industrial structure, technological level, energy consumption structure, price, and so on. It is suggested that optimizing energy structure and improving technology level are effective measures to improve the energy efficiency in the ISI.

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Section: Evaluation Methods Of Energy Efficiency In the Isimentioning

confidence: 99%

Review of evaluation methodologies and influencing factors for energy efficiency of the iron and steel industry

Sun

et al. 2019

Int J Energy Res

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show abstract

“…More systematic studies on exergy analysis have considered exergy loss as an assessment criterion. Liu et al established an optimization model of the blast furnace ironmaking process with the objective of minimizing exergy loss. Sequential quadratic programming was used to solve the minimization of the exergy loss and minimum coke ratio.…”

Section: Introductionmentioning

confidence: 99%

Exergy Analysis and Optimization of Sintering Process

Feng

et al. 2018

steel research int.

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Iron ore sintering is an important and large energy‐consumption segment in the iron and steel industry. It is thus essential to save energy in the sintering process considering both quality and quantity. This paper takes exergy loss minimization as an optimization objective, and a sintering optimization model is established based on material balance and exergy balance. Optimized results are obtained by solving constrained multidimensional nonlinear programming problems. Two types of sintering processes, in which solid fuels consist of coke and coke/coal powder, are calculated and analyzed. The effects of fuel ratio, fuel preheat temperature, and sinter basicity on exergy losses are also studied. The results show that the exergy losses obtained from optimizations for two types of solid fuels decrease by 5.0% and 8.1%, respectively. Exergy loss has a negative correlation with the coal ratio and fuel preheat temperature and a positive correlation with the coke ratio and sinter basicity. Exergy efficiencies increase from 29.7% to 35.0% and 35.5%, for each optimization. The research in this paper is highly significant to exploring of the sintering process, guiding steel production, and reducing energy consumption.

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“…The optimization results were obtained by using the SQP algorithm. The effects of major operating parameters on the optimization results are analyzed [54,55], and the energy flow and exergy flow before and after the optimizations for the coke ratio minimization objective and exergy loss minimization objective were analyzed comparatively [56]. Some guidelines for iron-making production were provided.…”

Section: Optimizations For Blast Furnace Iron-making Elemental Packagmentioning

confidence: 99%

“…As shown in Figure 14, based on the works in [54][55][56], an optimization model for a blast furnace iron-making procedure including blast furnace, TRT, blower and hot blast stove was established [57,58], and the energy consumption, cost, carbon emissions and exergy loss were taken as optimization objectives, respectively. Similar to the model of blast furnace iron-making elemental package, based on material balance and energy balance, 32 constraint conditions and 10 optimization variables were considered in the model.…”

Section: Optimizations For Blast Furnace Iron-making Procedures Basedmentioning

confidence: 99%

“…Many optimization models have been established to optimize various structures and operation parameters, aiming to achieve different targets, such as yield maximization [59], cost minimization [97] and exergy loss minimization [56], etc. Different methods of mixed integer linear programming (MILP), artificial neural network (ANN), constructal theory [59,60] and other methods have been introduced to solve the relevant problems.…”

Section: Performance Optimization Of Sintering and Iron-making Sectionmentioning

confidence: 99%

See 1 more Smart Citation

Generalized Thermodynamic Optimization for Iron and Steel Production Processes: Theoretical Exploration and Application Cases

Chen

Feng

Xie

2016

Entropy

Self Cite

110

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Abstract:Combining modern thermodynamics theory branches, including finite time thermodynamics or entropy generation minimization, constructal theory and entransy theory, with metallurgical process engineering, this paper provides a new exploration on generalized thermodynamic optimization theory for iron and steel production processes. The theoretical core is to thermodynamically optimize performances of elemental packages, working procedure modules, functional subsystems, and whole process of iron and steel production processes with real finite-resource and/or finite-size constraints with various irreversibilities toward saving energy, decreasing consumption, reducing emission and increasing yield, and to achieve the comprehensive coordination among the material flow, energy flow and environment of the hierarchical process systems. A series of application cases of the theory are reviewed. It can provide a new angle of view for the iron and steel production processes from thermodynamics, and can also provide some guidelines for other process industries.

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Exergy loss minimization for a blast furnace with comparative analyses for energy flows and exergy flows

Cited by 75 publications

References 22 publications

Review of evaluation methodologies and influencing factors for energy efficiency of the iron and steel industry

Review of evaluation methodologies and influencing factors for energy efficiency of the iron and steel industry

Exergy Analysis and Optimization of Sintering Process

Generalized Thermodynamic Optimization for Iron and Steel Production Processes: Theoretical Exploration and Application Cases

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