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Exploring theoretical energy consumption introduces a fresh perspective for energy-saving research within the iron and steel industry, with a primary focus on the energy expended during material transformation. Building upon the theory of theoretical energy consumption, this study meticulously investigates the theoretical energy consumption associated with each stage of the iron and steel making process, including coking, sintering, pelletizing, ironmaking, steelmaking, and hot rolling. The findings reveal that, under specific conditions, the theoretical energy consumption for each process is as follows: coking (2.59 GJ), sintering (1.36 GJ), pelletizing (1.02 GJ), ironmaking (8.81 GJ), steelmaking (−0.16 GJ), and hot rolling (0.76 GJ). Additionally, this study delves into the analysis of influencing factors on theoretical energy consumption. Using the coking process as an illustrative example, it is observed that the theoretical energy consumption in coking decreases with a reduction in both moisture and volatile content in coal. Under the specified conditions, the minimum theoretical energy consumption for each process is as follows: coking (2.51 GJ), sintering (0.98 GJ), pelletizing (0.67 GJ), ironmaking (8.38 GJ), steelmaking (−0.58 GJ), and hot rolling (0.07 GJ), respectively. This comprehensive analysis serves as a valuable resource for advancing sustainable practices in the iron and steel industry. [ABSTRACT FROM AUTHOR]

Improving energy efficiency has been widely recognized as a direct, efficient, and cost-effective approach to advancing energy conservation, reducing emissions, and achieving sustainable development. While there are numerous and effective methods to enhance energy efficiency in a typical steel manufacturing system, they are relatively scattered and independent, lacking a systematic review for multi-level, comprehensive and scientific evaluation and improvement of energy efficiency within the steel industry. To fill this gap, this work initially presents an overview of the component units and energy networks within steel production system. Subsequently, a comprehensive review and analysis are conducted from multiple perspectives, such as energy evaluation, diagnosis, benchmarking analysis, optimization, and energy-saving measures. Each part meticulously selects the literature through content evaluation analysis to discuss methods, technologies, and models for improving energy efficiency, along with potential challenges that need to be overcome for future advancements. Furthermore, the paper examines the diverse challenges encountered by steel manufacturing in realizing energy efficiency improvements and exploring energy-saving potential. It also underscores the corresponding future developmental direction, including the construction of multi-level evaluation systems, implementation of intelligent energy efficiency improvement methods and technologies, and adoption of intelligent energy systems crucial for intelligent analysis and manufacturing in steel sector. • Energy efficiency improvement methods within the steel production sector are comprehensively reviewed. • Multi-level energy efficiency evaluation methods for the steel production are summarized. • Advances in energy efficiency diagnosis, benchmarking analysis, optimization and energy-saving technologies are summarized. • Challenges and prospects for energy efficiency improvement in steel sector are discussed. [ABSTRACT FROM AUTHOR]

Evaluating the energy efficiency of the iron and steel smelting route is of vital significance to achieve energy saving and consumption reduction. By establishing an input‐use‐end model, a new index is put forward herein to evaluate the energy utilization of the iron and steel smelting route—energy utilization efficiency. Furthermore, energy utilization efficiency of a typical iron and steel smelting route is analyzed based on the established network diagram. The results show that 1) the cleaned coal is the largest energy input in the whole route, which is 14 460.4 MJ, followed by injected coal. 2) About 57.6% of primary energy is converted into byproduct gases and 31.7% of that is converted into various waste heats. 3) The energy loss of the whole route is 9583.8 MJ, of which the direct loss, indirect loss, and internal loss are 2630.8, 5366.9, and 1586.1 MJ, respectively, accounting for 14.5%, 29.5%, and 8.7% of the total purchased energy. 4) The energy utilization efficiency of the whole process is 47.6%. 5) Improving energy recovery is the most effective measure to improve energy utilization efficiency instead of degrading energy input and changing product structure. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The integrated optimization and analysis of material and energy flows are effective ways to reduce energy consumption and costs in the iron and steel sector. There is still a lack of research on the multi-objective optimization of the integrated steel production process and the auxiliary energy process. To fill this gap, this paper presented a single- and multi-objective optimization model for material and energy scheduling and utilization of the steelworks. This model considered physical and chemical conversion mechanisms in the production process, as well as operating characteristics and production-consumption relations of equipment in the gas-steam-electricity network. The objective function was constructed using comprehensive energy consumption (CEC) and economic cost (EC), and fuzzy sets were used to find a compromise solution and the trade-off operation strategies between the two goals. The CEC and EC effectively dropped by 5.09% and 7.29%, respectively, in comparison to the actual enterprise value, through the optimization of the material ratio, product structure, energy utilization, and other parameters of the steelworks. Additionally, a quantitative analysis of the effects of variables such as the ratio of pellets, the ratio of scrap, the hot charging temperature of the slab, and the utilization of surplus gases was conducted. • A single- and multi-objective optimization model for material and energy scheduling and utilization is proposed. • The compromise solution of energy consumption and economic multi-objective optimization is found. • Influence of material and energy flows on variation in multi-objective is discussed. • Highly efficient and cost-effective modes of using surplus gases are explored. [ABSTRACT FROM AUTHOR]

Improving energy efficiency of the iron and steel manufacturing process (ISMP) plays a vital role in saving energy and reducing CO 2 emissions. However, there is currently a lack of research on assessment method and improvement rules of energy efficiency of the ISMP. In addition, the impact of energy efficiency on CO 2 emissions and energy consumption is rarely mentioned in previous studies. To fill this gap, this study establishes an assessment and optimization model of energy efficiency, energy consumption and CO 2 emissions in the ISMP. Taking material parameters, process parameters and reaction conditions as constraints, this study optimizes a practical ISMP with maximizing energy efficiency as the optimization goal, and further analyze energy consumption and CO 2 emissions of typical ISMP. After optimizing, energy efficiency of the ISMP is increased from 64.00% to 68.20%, energy consumption of the ISMP is reduced from 15.76 GJ/t-steel to 12.31 GJ/t-s, and the CO 2 emission of the ISMP is reduced from 1215.2 kg/t-steel to 815.3 kg/t-s. It is found that injected coal ratio of blast furnace, charge structure of blast furnace, iron-steel interface and casting-rolling interface have a greater impact on energy efficiency, energy consumption and CO 2 emission of the ISMP. • The optimization model of energy efficiency of the iron and steel making process is established. • The optimal energy efficiency of a typical steel plant is given. • Energy efficiency, energy consumption and CO 2 emissions are jointly analyzed. • The influencing factors of energy efficiency, energy consumption and CO 2 emission are discussed. • The iron-steel interface and casting-rolling interface are considered. [ABSTRACT FROM AUTHOR]

Energy efficiency is an extremely important indicator for exploring energy conservation and consumption reduction. The traditional energy efficiency assessment methods for process industry lack an in-depth thinking on energy utilization of the whole system. Based on the proposed required energy, this paper established an energy efficiency assessment method for process industry. By establishing material and energy flow networks, energy efficiency of typical iron and steel manufacturing process (ISMP) is analyzed and its influencing factors are discussed. The results found that the required energy of coking, sintering, pelletizing, blast furnace iron-making, basic oxygen furnace steel-making and steel rolling are 2626.2 MJ/t-coke, 1122.9 MJ/t-sinter, 992.3 MJ/t-pellet, 9781.5 MJ/t-hot metal, 393.95 MJ/t-molten steel and 445.3 MJ/t-steel products, respectively. The energy efficiency of typical ISMP is 66.9%. The energy efficiency of the ISMP can be effectively improved by adjusting the steel ratio, recovering waste heat and residual energy, and developing interface technologies. • Energy efficiency assessment method of process industry is proposed and established. • The material and energy flow networks of iron and steel manufacturing process are established. • The required energy of iron and steel manufacturing process is analyzed and given. • Energy efficiency of typical iron and steel manufacturing process is evaluated and given. • The influencing factor of energy efficiency is discussed. [ABSTRACT FROM AUTHOR]

In the context of carbon neutrality, energy conservation and carbon reduction in the heating industry have become the focus of attention. However, severe heat loss is currently occurring in the secondary heating system due to hydraulic imbalance, which is unable to supply heat according to users' needs. In view of this, a thermodynamic-hydraulic model of users' demand for heat and flow rate for the heating system is established. Then, a novel method to regulate hydraulic imbalance is proposed, with the dynamic heat demand satisfied by regulating the valve opening based on NSGA-II. The optimization results show that the comprehensive hydraulic imbalance coefficient has been reduced from 23.08 to less than 0.019, which means that almost 100% of users can get heat supplies corresponding to their needs, while the energy consumption is reduced by about 30%. Additionally, when there are 1000 population and iteration steps, good convergence and high speed are presented using this method. In summary, an on-demand optimized model of hydraulic balance for the secondary heating network is put forward, which provides powerful engineering support and guidance for intelligent heating construction. • This paper presents a method to regulate the hydraulic balance of network using NSGA-II according to the heat demand. • This paper combines the demand flow regulation of users with the resistance analysis of the heating network. • The hydraulic balance can be implemented greatly by using the hydraulic imbalance coefficient as the optimization goal. • The number of iteration steps in the algorithm has an effect on the optimization results. [ABSTRACT FROM AUTHOR]

Due to high material density, high energy consumption density and CO 2 emission density, it is not only difficult but significant to clarify the relationship between energy consumption, the CO 2 emission and the production cost in different conditions. However, the previous researches rarely refer how to balance the energy consumption, the CO 2 emission and the production cost after the fluctuation of material, energy and carbon price as well as what will happen to them if production structure changes. Therefore, based on the conservation law of mass and energy, to study iron and steel manufacturing process (ISMP), this paper, taking carbon price into consideration, establishes a muti-optimization model of energy consumption, CO 2 emission and cost. After optimization with different objectives, the production cost per tonne of crude steel is reduced by 192.03 CNY (7.71%), the CO 2 emission per tonne of crude steel is reduced by 224.22 kg (13.37%), and the energy consumption per tonne of steel is reduced by 51.20 kgce (9.10%). Moreover, based on the optimization results under different objectives, it is ironmaking process (coal ratio and ore ratio) and steelmaking process (amount of scrap steel) that has more impact on three above as well as ore blending and coal blending have a great influence on production cost but little effect on energy consumption and CO 2 emission. • The muti-objective optimization model of iron and steel industry is established. • The carbon price is considered during model establishment and analyzing. • The objective with energy consumption, CO 2 emissions and cost are optimized. • The factors affecting cost, energy consumption and CO 2 emission are discussed. [ABSTRACT FROM AUTHOR]