Journal of Iron and Steel Research International, 2023
The real-time energy flow data obtained in industrial production processes are usually of low qua... more The real-time energy flow data obtained in industrial production processes are usually of low quality. It is difficult to accurately predict the short-term energy flow profile by using these field data, which diminishes the effect of industrial big data and artificial intelligence in industrial energy system. The real-time data of blast furnace gas (BFG) generation collected in iron and steel sites are also of low quality. In order to tackle this problem, a three-stage data quality improvement strategy was proposed to predict the BFG generation. In the first stage, correlation principle was used to test the sample set. In the second stage, the original sample set was rectified and updated. In the third stage, Kalman filter was employed to eliminate the noise of the updated sample set. The method was verified by autoregressive integrated moving average model, back propagation neural network model and long short-term memory model. The results show that the prediction model based on the proposed three-stage data quality improvement method performs well. LSTM model has the best prediction performance, with a mean absolute error of 17.85 m3/min, a mean absolute percentage error of 0.21%, and an R squared of 95.17%.
Steelmaking-refining-continuous casting (SRCC), as a key electricity-intensive and flexible proce... more Steelmaking-refining-continuous casting (SRCC), as a key electricity-intensive and flexible process in the integrated iron and steel production route, has great potential in providing demand-side flexibility. Optimal scheduling of flexible resources is important for ensuring maximal flexibility. However, it is not considered in existing SRCC scheduling studies, leading to a low ability to provide operational flexibility at iron and steel production sites and an inability to support the sites to participate in flexibility transactions and reduce energy costs. To fill in the research gaps, a Basic resource-task network (RTN) model and a Flex RTN model for SRCC scheduling considering refining process flexibility are established. With minimizing the power cost of the process as the objective function, the Flex RTN model takes various load modes of refining ladle furnaces into account and provides an approach for the scheduling of flexible resources in the iron and steel sites. The energy cost of iron and steel sites under the Flex RTN model considering flexible resources is compared with that of the Basic RTN model without considering flexible resources. The results of a 2-min time step case study show that 12,000 yuan can be saved by implementing the flexibility-based scheduling, proving the technical and economic superiority of the proposed method.
The large-scale integration of renewable energy into power grids brings new problems and challeng... more The large-scale integration of renewable energy into power grids brings new problems and challenges to the flexible and stable operation of power systems. Providing flexibility from the industrial load side is an effective way to maintain the balance between power supply and demand in a power grid. Ladle furnaces (LFs) in the iron and steel industry consume copious power resources yet can provide flexible potential in changing power consumption rates. If the flexibility of LFs can be quantified, the iron and steel sites can response the demand signals from the power grid by adjusting their production plans. However, the real-time regulation capability of LFs in the refining process has not been clearly quantified. To fill in the research gaps, an evaluation model to quantify the provisions of flexibility of LFs, as cuttable loads, is proposed. The regulation capacity of LFs is evaluated, and the electricity costs before and after power adjustments are compared. The results of a case study shows that the maximum cuttable load can reach 23.3 MW, and the maximum load-cutting process duration can reach 34 min in the production cycle. The electricity cost may increase by 232 yuan under the background of the timeof-use electricity price and decrease by 797 yuan under the background of the peak electricity price.
Blast furnace gas (BFG) is an important energy-carrying byproduct of the iron and steel industry.... more Blast furnace gas (BFG) is an important energy-carrying byproduct of the iron and steel industry. High-accuracy prediction of BFG generation is the basis of the dynamic balance of gas supply-demand and energy scheduling. However, due to instrument faults, measurements of BFG are discontinuous or inaccurate, making it difficult to accurately predict future BFG generation by using historical data, which seriously restricts the development of intelligent management and coordination between various gas sources and users. To solve this problem, an attention mechanism-aided data-and knowledge-driven soft sensor is proposed to predict BFG generation. To reduce the complexity of the samples, the proposed method selects key features to simplify the model input by using attention mechanism. Genetic algorithm (GA) is used to optimize hyperparameters to improve the stability of the model. In addition, combined with the knowledge of the blast furnace process, the prediction results are reasonably constrained. The results show that the prediction accuracy of the A-DK-GA-XGBoost model is higher than that of the other prediction models, with a mean absolute error of 68.2 m 3 /min, a symmetric mean absolute percentage error of 0.83%, a root mean square error of 68.71 m 3 /min, and an R squared of 99.06%. It is proven that the A-DK-GA-XGBoost model has superior performance.
A carbon flow tracing and carbon accounting method for exploring CO2 emissions of the iron and st... more A carbon flow tracing and carbon accounting method for exploring CO2 emissions of the iron and steel industry: An integrated material-energy-carbon hub
The iron and steel industry is a notable particulate matter emitter. In source apportionment of p... more The iron and steel industry is a notable particulate matter emitter. In source apportionment of particulate matter, it is important to identify the characteristics of particulate matter originating from steel sites. However, previous studies mostly focus on stack emission sources, while few reports on fugitive emission sources are available. Aiming to fill this gap,
Integrated analysis and optimization of material and energy flows in the iron and steel industry ... more Integrated analysis and optimization of material and energy flows in the iron and steel industry have drawn considerable interest from steelmakers, energy engineers, policymakers, financial firms, and academic researchers. Numerous publications in this area have identified their great potential to bring significant benefits and innovation. Although much technical work has been done to analyze and optimize material and energy flows, there is a lack of overview of material and energy flows of the iron and steel industry. To fill this gap, this work first provides an overview of different steel production routes. Next, the modelling, scheduling and interrelation regarding material and energy flows in the iron and steel industry are presented by thoroughly reviewing the existing literature. This study selects eighty publications on the material and energy flows of steelworks, from which a map of the potential of integrating material and energy flows for iron and steel sites is constructed. The paper discusses the challenges to be overcome and the future directions of material and energy flows research in the iron and steel industry, including the fundamental understandings of flow mechanisms, the dynamic material and energy flow scheduling and optimization, the synergy between material and energy flows, flexible production processes and flexible energy systems, smart steel manufacturing and smart energy systems, and revolutionary steelmaking routes and technologies.
Massive material and energy are consumed in the integrated iron and steel industry, which results... more Massive material and energy are consumed in the integrated iron and steel industry, which results in substantial emissions. Many technologies and policies have been employed in the industry to achieve sustainable steelmaking. The potential of these technologies and policies is generally assessed at the facility/process level. The sitewide potential is usually overestimated or underestimated due to double-counting and missing items. To tackle this problem, a matrix model of the sitewide material-energy-emission nexus is developed in terms of the interconnection and interdependency of multiple flows. Based on the nexus model, the effects of operational actions on material, energy and emission intensities are investigated. In addition, the contribution of various operational parameters to the change in each flow is determined. Coke purchase, cast iron export, scrap steel utilization and metallic yield improvement are examined as a case study. The results showed that energy deficits or over-standard emissions may occur in certain cases influenced by the material-energy-emission nexus, and it is suggested to consider the whole-site energy balance and emission structure when making decisions. Finally, policy implications for reducing material consumption, energy consumption and emissions are provided.
Blast furnace gas (BFG) is a byproduct gas and a significant energy source in integrated steelwor... more Blast furnace gas (BFG) is a byproduct gas and a significant energy source in integrated steelworks. Precise BFG generation prediction plays a pivotal role in site energy scheduling and management. However, it is difficult to accurately predict fluctuations in BFG generation due to the variable operational statuses and complex chemical reactions that occur inside the blast furnace, hindering efficient energy utilization and accordingly causing BFG to flare and contribute to environmental pollution. To tackle this problem, a hybrid event-, mechanism-and data-driven prediction method is proposed in this work. In this novel approach, blast furnace operational events are considered when predicting BFG generation, thus making predictions more accurate by integrating a priori mechanism knowledge associated with the blast furnace ironmaking process; additionally, this approach ensures high accuracy by selecting the best available data-driven prediction model for different event-associated periods. To demonstrate the predictive performance of the proposed hybrid method, comparative experiments are conducted using practical data from integrated steelworks. The results highlight the excellent performance and accuracy of the proposed method when compared with the results of widely used moving average and artificial neural network models.
In order to investigate the particulate matters emission characteristics of various emitting sour... more In order to investigate the particulate matters emission characteristics of various emitting sources in the coking process of iron and steel plants, an automatic dust (smoke) tester and an eight-staged Anderson sampler were employed to conduct the on-site sampling of particulate matters emitting from coking process, including coal loading & coke pushing, coke dry quenching exhaust and coke screening & transferring in a steel plant, based on the measurement rule of particulate matter in the exhaust of fixed sources and the sampling method of gaseous pollutants. The morphology, particle size distribution and chemical composition of the particulate matters from different sources were investigated. The results show that the kinds of single particle can be divided into five categories: iron-rich, silicon-rich, calcium-rich, carbon and smoke polymer. In appearance, they are mainly in four forms: polygon block, irregular lamellae, lumps and floc. The size of particles is mainly 3.3-4.7 μm for coal loading & coke pushing unit, while 3.3-4.7 μm and 5.8-9.0 μm for dry quenching exhaust and 4.7-5.8 μm for coke screening & transferring unit. The main chemical components of the particulate matters in the coking process are C, SiO2, Al2O3, S, CaO and TFe, with the content of 76.30%-81.30%, 5.36%-5.91%, 3.96%-4.26%, 1.15%-1.34%, 0.52%-1.59% and 0.81%-1.34%, respectively. 0 Introduction The effect of air pollution on human health and environment visibility widely attracts the attentions of researchers. Some studies showed that particulate matter emitted from industry is one of the primary sources of urban air pollution. Among them, steel industry with large production scale has a large number of emission sources of particulate matters, and the emission amount reaches 3.572 million t, accounting for 28.9% of the total emission in industrial
Industry emits huge amount of CO2 and particulate matter (PM) in the form of flue gas. CO2 and PM... more Industry emits huge amount of CO2 and particulate matter (PM) in the form of flue gas. CO2 and PM are currently removed separately. In this work, a novel co-removal system is designed for simultaneously and synergistically removing CO2 and PM from industrial flue gas, by connecting an ammonia scrubber (AS) and a granular bed filter (GBF) in series. To validate the concept, an experimental apparatus was built, and the parameters influencing the CO2 and PM removal efficiencies in the AS, GBF and the whole system are investigated. Results show the CO2 and PM removal efficiencies of the co-removal system are 89.46% and 99.76%, respectively, and are higher than that of each single subsystem. In addition, the optimal operating conditions of the co-removal system are determined.
Industrial activities are generally energy and air emissions intensive, requiring bulky inputs of... more Industrial activities are generally energy and air emissions intensive, requiring bulky inputs of raw materials and fossil fuels and emitting huge waste gases including particulate matter (PM, or dust), sulphur dioxide (SO2), nitrogen oxides (NOx), carbon dioxide (CO2), and other substances, which are severely damaging the environment. Many studies have been carried out on the quantification of the concentrations of these air emissions. Although there are studies published on the co-effect of multi-air emissions, a more fair and comprehensive method for assessing the environmental impact of multi-air emissions is still lacking, which can simultaneously consider the flow rate of waste gases, the availability of emitting sources and the concentrations of all emission substances. In this work, a Total Environmental Impact Score (TEIS) approach is proposed to assess the environmental impact of the main industrial processes of an integrated iron and steel site located in the northeast of China. Besides the concentration of each air emission substance, this TEIS approach also combines the flow rate of waste gases and the availability of emitting sources. It is shown that the processes in descending order by the values of TEIS are sintering, ironmaking, steelmaking, thermal power, steel rolling, and coking, with the values of 17.57, 16.68, 10.86, 10.43, 9.60 and 9.27, respectively. In addition, a sensitivity analysis was conducted, indicating that the TEIS order is almost the same with the variation of 10% in the permissible CO2 concentration limit and the weight of each air emission substance. The effects of emitting source availability and waste gas flow rate on the TEIS cannot be neglected in the environmental impact assessment.
The iron and steel industry discharges large quantities of wastewater. The environmental impact o... more The iron and steel industry discharges large quantities of wastewater. The environmental impact of the wastewater is traditionally assessed from the quantitative aspect. However, the water quality of discharged wastewater plays a more significant role in damaging the natural environment. Moreover, comprehensive assessment of multi-pollutants in wastewater from both quality and quantity is still a gap. In this work, a total environmental impact score (TEIS) is defined to assess the environmental impact of wastewater discharge, by considering the volume of wastewater and the quality of main processes. To implement the comprehensively qualitative and quantitative assessment, a field monitoring and measurement of wastewater discharge volume and the quality is conducted to acquire pH, suspend solids (SS), chemical oxygen demand (COD), total nitrogen (TN), total iron (TFe), and hexavalent chromium (Cr(VI)). The sequence of TEIS values is obtained as steelmaking > ironmaking > sintering > hot rolling > coking > cold rolling and TN > COD > SS > pH > Cr(VI) > TFe. The TEIS of the investigated steel plant is 26.27. The leading process lies in steelmaking with a TEIS of 19.98. The dominant pollutant is TN with a TEIS of 15.00. Finally, a sensitivity analysis is performed to validate the feasibility and generalisability of the TEIS.
Journal of Mining and Metallurgy, Section B: Metallurgy, 2019
With the broad application of dry dedusting of blast furnace gas (BFG), the issue of BFG pipeline... more With the broad application of dry dedusting of blast furnace gas (BFG), the issue of BFG pipeline corrosion comes up because of chlorine in the BFG. Existing methods in preventing the corrosion, such as spraying alkali or installing corrosion-resistant materials, require a significant amount of investment. This paper conducted a novel thermal analysis of the corrosion mechanism to support the study on corrosion prevention without using additional materials. Firstly, thermal models were established to reflect the relationships among the amount of condensation water, the mass transfer rate, the concentration of chloride ion and the ambient temperature. Secondly, the relationship between BFG temperature and the corrosion rate was obtained via a cyclic exposure experiment. Key factors that affect the pipeline corrosion under various BFG temperatures were identified. Finally, a control scheme of the BFG temperature was proposed to avoid the chlorine corrosion.
There has always been a dispute about the energy efficiency and energy cost of electro-driven and... more There has always been a dispute about the energy efficiency and energy cost of electro-driven and turbo-driven blast furnace (BF) blast processes. In order to find where the problem lies, energy efficiency analysis models and energy cost analysis models of electro-driven and turbo-driven blast processes were established, and the differences between the two driving processes in terms of theoretical minimum steam consumption, energy efficiency and energy cost were studied. The results showed that the theoretical minimum steam consumption of a blast process depends on steam thermodynamic properties and is unrelated to drive mode and drive process. A certain overlapped interval between electro-driven and turbo-driven blast processes in terms of energy efficiency exists. The equation for calculating the standard coal coefficient of steam was proposed, and the relationship to judge strengths and weaknesses of the two driving modes in terms of energy efficiency and energy cost was established. Finally, two companies were selected for case study research. The results led to different conclusions because of the differences between energy media in terms of standard coal coefficient and unit price. To select the best driving mode, plant-running conditions and energy prices of the region of operation in addition to other relevant factors should all be taken into account.
Exhaust hot water (EHW) is widely used for various industrial processes. However, the excess heat... more Exhaust hot water (EHW) is widely used for various industrial processes. However, the excess heat carried by EHW is typically ignored and discharged into the environment, resulting in heat loss and heat pollution. An organic Rankine cycle (ORC) is an attractive technology to recycle heat from low-temperature energy carriers. Herein, ORC was used to recycle the heat carried by EHW. To investigate the energy and exergy recovery effects of EHW, a mathematical model was developed and a parametric study was conducted. The energy efficiency and exergy efficiency of the EHW-driven ORC system were modeled with R245fa, R113 and R123 as the working fluids. The results demonstrate that the EHW and evaporation temperatures have significant effects on the energy and exergy efficiencies of the EHW-driven ORC system. Under given EHW conditions, an optimum evaporation temperature exists corresponding to the highest exergy efficiency. To further use the low-temperature EHW, a configuration retrofitted to the ORC by combining with flash evaporation (FE) was conducted. For an EHW at 120 °C and 0.2 MPa, the maximum exergy efficiency of the FE-ORC system is 45.91% at a flash pressure of 0.088 MPa. The FE-ORC performs better in exergy efficiency than the basic FE and basic EHW-driven ORC.
Surplus by-product gas (SBPG) in a steel plant is the difference between gas production and consu... more Surplus by-product gas (SBPG) in a steel plant is the difference between gas production and consumption. Dynamic programming (DP) has been observed to be a useful method for SBPG dynamic allocation. However, in the SBPG allocation problem, standard dynamic programming (SDP) usually suffers from dimensionality. In this study, a novel dynamic programming method with a reduced state space algorithm (RSS-DP) is proposed. By decomposing the amount of SBPG into the reference and subsequent allocation, RSS-DP reduces the state space of the SDP model significantly such that the computation time is significantly reduced. An example of a five-boiler allocation of SBPG and a real-world online allocation of SBPG in these five boilers of a steel plant are implemented to exhibit the effectiveness of the proposed algorithm. In both cases, the solutions obtained using the proposed method are better than those obtained by traditional methods, in both computation time and energy benefit.
The study is to provide a detailed physical and chemical characterization of particles collected ... more The study is to provide a detailed physical and chemical characterization of particles collected in the ironmaking process, including a bunker system, a cast house and a pulverized coal feeding system. Using gravimetric, scanning electron microscope coupled with energy dispersive X-ray spectrometry (SEM-EDS), X-ray fluorescence spectrometry (XRF), inductively coupled plasma optical emission spectrometry (ICP-OES) analyses, the size distribution, morphology, elemental composition and emission factor of particles were investigated. The contribution rates of cast house for emission factors of total suspended particulates (TSP), PM10 and PM2.5 are the largest, 57.0%, 75.5% and 83.3%, respectively. SEM-EDS analysis indicated that cast house particle shapes are mainly formed by polymerization from spherical particles and ultrafine particles, whose main component is Fe. But, the particles of the bunker system or the pulverized coal feeding system are mainly the large ones of irregular block or powder particles and the main component is carbon. The highest content of the element in particles of the bunker system and cast house is Fe, followed by C, Si, Ca and Al. The main elements of particles in the pulverized coal feeding system are C, Si, Al and Ca, and their contents are 63.6%, 7.83%, 3.07% and 1.47%, respectively.
In this paper, five particulate emission points from a sinter plant in China, including anthracit... more In this paper, five particulate emission points from a sinter plant in China, including anthracite crusher, raw material blender, sinter strand, screener, and circular cooler, were selected for particle sampling. The particle size distribution, the toxic element content (As, Cd, Co, Cr, Cu, Ni, Pb, Ti, and Zn), and the morphology of the samples were determined by the gravimetric method, the ICP-OES, and the SEM-EDS, respectively. In addition, the gray relational analysis method was used to evaluate the rank of the particulate emission points in the sinter plant. The results show that the emission factor of PMTSP, PM10, and PM2.5 of the whole sintering process is 0.121, 0.075, and 0.039 kg/t-sinter, respectively. Furthermore, the total toxic element emission factor is 5282.49 mg/t-sinter. The sinter strand is the most important emitter and contributes 43.8% of PMTSP, 53.3% of PM10, 56.4% of PM2.5, and 81.1% of total toxic element in the sinter plant. Nevertheless, particles emitted from the post-sintering process are non-negligible and contribute 48.8% of PMTSP, 41.3% of PM10, 38.5% of PM2.5, and 15.5% of total toxic element in the sinter plant.
Mineral Processing and Extractive Metallurgy Review, 2018
As an energy-intensive industry, iron and steel production are suffering from the resource and en... more As an energy-intensive industry, iron and steel production are suffering from the resource and environmental issues. Blast furnace—basic oxygen furnace (BF-BOF) process and electric arc furnace (EAF) process are the two most common routes of steel production. Therefore, it is very important to quantify the industrial metabolism for the two routes. In this work, material flow analysis is used to comparatively investigate the energy efficiency, material efficiency, and emissions intensity at the enterprise level. The results show that the total energy consumption and material consumption per ton of steel of the BF-BOF route are 2.8 and 11 times larger than those of the EAF route, respectively. In addition, the emission intensities of dust, CO2, SO2, NO2 and CO of the BF-BOF route are 7.7, 2.6, 92.6, 33.5, and 12.0 times greater than those of the EAF route, respectively. To achieve a more sustainable steel industry, some policy recommendations are put forward finally.
Journal of Iron and Steel Research International, 2023
The real-time energy flow data obtained in industrial production processes are usually of low qua... more The real-time energy flow data obtained in industrial production processes are usually of low quality. It is difficult to accurately predict the short-term energy flow profile by using these field data, which diminishes the effect of industrial big data and artificial intelligence in industrial energy system. The real-time data of blast furnace gas (BFG) generation collected in iron and steel sites are also of low quality. In order to tackle this problem, a three-stage data quality improvement strategy was proposed to predict the BFG generation. In the first stage, correlation principle was used to test the sample set. In the second stage, the original sample set was rectified and updated. In the third stage, Kalman filter was employed to eliminate the noise of the updated sample set. The method was verified by autoregressive integrated moving average model, back propagation neural network model and long short-term memory model. The results show that the prediction model based on the proposed three-stage data quality improvement method performs well. LSTM model has the best prediction performance, with a mean absolute error of 17.85 m3/min, a mean absolute percentage error of 0.21%, and an R squared of 95.17%.
Steelmaking-refining-continuous casting (SRCC), as a key electricity-intensive and flexible proce... more Steelmaking-refining-continuous casting (SRCC), as a key electricity-intensive and flexible process in the integrated iron and steel production route, has great potential in providing demand-side flexibility. Optimal scheduling of flexible resources is important for ensuring maximal flexibility. However, it is not considered in existing SRCC scheduling studies, leading to a low ability to provide operational flexibility at iron and steel production sites and an inability to support the sites to participate in flexibility transactions and reduce energy costs. To fill in the research gaps, a Basic resource-task network (RTN) model and a Flex RTN model for SRCC scheduling considering refining process flexibility are established. With minimizing the power cost of the process as the objective function, the Flex RTN model takes various load modes of refining ladle furnaces into account and provides an approach for the scheduling of flexible resources in the iron and steel sites. The energy cost of iron and steel sites under the Flex RTN model considering flexible resources is compared with that of the Basic RTN model without considering flexible resources. The results of a 2-min time step case study show that 12,000 yuan can be saved by implementing the flexibility-based scheduling, proving the technical and economic superiority of the proposed method.
The large-scale integration of renewable energy into power grids brings new problems and challeng... more The large-scale integration of renewable energy into power grids brings new problems and challenges to the flexible and stable operation of power systems. Providing flexibility from the industrial load side is an effective way to maintain the balance between power supply and demand in a power grid. Ladle furnaces (LFs) in the iron and steel industry consume copious power resources yet can provide flexible potential in changing power consumption rates. If the flexibility of LFs can be quantified, the iron and steel sites can response the demand signals from the power grid by adjusting their production plans. However, the real-time regulation capability of LFs in the refining process has not been clearly quantified. To fill in the research gaps, an evaluation model to quantify the provisions of flexibility of LFs, as cuttable loads, is proposed. The regulation capacity of LFs is evaluated, and the electricity costs before and after power adjustments are compared. The results of a case study shows that the maximum cuttable load can reach 23.3 MW, and the maximum load-cutting process duration can reach 34 min in the production cycle. The electricity cost may increase by 232 yuan under the background of the timeof-use electricity price and decrease by 797 yuan under the background of the peak electricity price.
Blast furnace gas (BFG) is an important energy-carrying byproduct of the iron and steel industry.... more Blast furnace gas (BFG) is an important energy-carrying byproduct of the iron and steel industry. High-accuracy prediction of BFG generation is the basis of the dynamic balance of gas supply-demand and energy scheduling. However, due to instrument faults, measurements of BFG are discontinuous or inaccurate, making it difficult to accurately predict future BFG generation by using historical data, which seriously restricts the development of intelligent management and coordination between various gas sources and users. To solve this problem, an attention mechanism-aided data-and knowledge-driven soft sensor is proposed to predict BFG generation. To reduce the complexity of the samples, the proposed method selects key features to simplify the model input by using attention mechanism. Genetic algorithm (GA) is used to optimize hyperparameters to improve the stability of the model. In addition, combined with the knowledge of the blast furnace process, the prediction results are reasonably constrained. The results show that the prediction accuracy of the A-DK-GA-XGBoost model is higher than that of the other prediction models, with a mean absolute error of 68.2 m 3 /min, a symmetric mean absolute percentage error of 0.83%, a root mean square error of 68.71 m 3 /min, and an R squared of 99.06%. It is proven that the A-DK-GA-XGBoost model has superior performance.
A carbon flow tracing and carbon accounting method for exploring CO2 emissions of the iron and st... more A carbon flow tracing and carbon accounting method for exploring CO2 emissions of the iron and steel industry: An integrated material-energy-carbon hub
The iron and steel industry is a notable particulate matter emitter. In source apportionment of p... more The iron and steel industry is a notable particulate matter emitter. In source apportionment of particulate matter, it is important to identify the characteristics of particulate matter originating from steel sites. However, previous studies mostly focus on stack emission sources, while few reports on fugitive emission sources are available. Aiming to fill this gap,
Integrated analysis and optimization of material and energy flows in the iron and steel industry ... more Integrated analysis and optimization of material and energy flows in the iron and steel industry have drawn considerable interest from steelmakers, energy engineers, policymakers, financial firms, and academic researchers. Numerous publications in this area have identified their great potential to bring significant benefits and innovation. Although much technical work has been done to analyze and optimize material and energy flows, there is a lack of overview of material and energy flows of the iron and steel industry. To fill this gap, this work first provides an overview of different steel production routes. Next, the modelling, scheduling and interrelation regarding material and energy flows in the iron and steel industry are presented by thoroughly reviewing the existing literature. This study selects eighty publications on the material and energy flows of steelworks, from which a map of the potential of integrating material and energy flows for iron and steel sites is constructed. The paper discusses the challenges to be overcome and the future directions of material and energy flows research in the iron and steel industry, including the fundamental understandings of flow mechanisms, the dynamic material and energy flow scheduling and optimization, the synergy between material and energy flows, flexible production processes and flexible energy systems, smart steel manufacturing and smart energy systems, and revolutionary steelmaking routes and technologies.
Massive material and energy are consumed in the integrated iron and steel industry, which results... more Massive material and energy are consumed in the integrated iron and steel industry, which results in substantial emissions. Many technologies and policies have been employed in the industry to achieve sustainable steelmaking. The potential of these technologies and policies is generally assessed at the facility/process level. The sitewide potential is usually overestimated or underestimated due to double-counting and missing items. To tackle this problem, a matrix model of the sitewide material-energy-emission nexus is developed in terms of the interconnection and interdependency of multiple flows. Based on the nexus model, the effects of operational actions on material, energy and emission intensities are investigated. In addition, the contribution of various operational parameters to the change in each flow is determined. Coke purchase, cast iron export, scrap steel utilization and metallic yield improvement are examined as a case study. The results showed that energy deficits or over-standard emissions may occur in certain cases influenced by the material-energy-emission nexus, and it is suggested to consider the whole-site energy balance and emission structure when making decisions. Finally, policy implications for reducing material consumption, energy consumption and emissions are provided.
Blast furnace gas (BFG) is a byproduct gas and a significant energy source in integrated steelwor... more Blast furnace gas (BFG) is a byproduct gas and a significant energy source in integrated steelworks. Precise BFG generation prediction plays a pivotal role in site energy scheduling and management. However, it is difficult to accurately predict fluctuations in BFG generation due to the variable operational statuses and complex chemical reactions that occur inside the blast furnace, hindering efficient energy utilization and accordingly causing BFG to flare and contribute to environmental pollution. To tackle this problem, a hybrid event-, mechanism-and data-driven prediction method is proposed in this work. In this novel approach, blast furnace operational events are considered when predicting BFG generation, thus making predictions more accurate by integrating a priori mechanism knowledge associated with the blast furnace ironmaking process; additionally, this approach ensures high accuracy by selecting the best available data-driven prediction model for different event-associated periods. To demonstrate the predictive performance of the proposed hybrid method, comparative experiments are conducted using practical data from integrated steelworks. The results highlight the excellent performance and accuracy of the proposed method when compared with the results of widely used moving average and artificial neural network models.
In order to investigate the particulate matters emission characteristics of various emitting sour... more In order to investigate the particulate matters emission characteristics of various emitting sources in the coking process of iron and steel plants, an automatic dust (smoke) tester and an eight-staged Anderson sampler were employed to conduct the on-site sampling of particulate matters emitting from coking process, including coal loading & coke pushing, coke dry quenching exhaust and coke screening & transferring in a steel plant, based on the measurement rule of particulate matter in the exhaust of fixed sources and the sampling method of gaseous pollutants. The morphology, particle size distribution and chemical composition of the particulate matters from different sources were investigated. The results show that the kinds of single particle can be divided into five categories: iron-rich, silicon-rich, calcium-rich, carbon and smoke polymer. In appearance, they are mainly in four forms: polygon block, irregular lamellae, lumps and floc. The size of particles is mainly 3.3-4.7 μm for coal loading & coke pushing unit, while 3.3-4.7 μm and 5.8-9.0 μm for dry quenching exhaust and 4.7-5.8 μm for coke screening & transferring unit. The main chemical components of the particulate matters in the coking process are C, SiO2, Al2O3, S, CaO and TFe, with the content of 76.30%-81.30%, 5.36%-5.91%, 3.96%-4.26%, 1.15%-1.34%, 0.52%-1.59% and 0.81%-1.34%, respectively. 0 Introduction The effect of air pollution on human health and environment visibility widely attracts the attentions of researchers. Some studies showed that particulate matter emitted from industry is one of the primary sources of urban air pollution. Among them, steel industry with large production scale has a large number of emission sources of particulate matters, and the emission amount reaches 3.572 million t, accounting for 28.9% of the total emission in industrial
Industry emits huge amount of CO2 and particulate matter (PM) in the form of flue gas. CO2 and PM... more Industry emits huge amount of CO2 and particulate matter (PM) in the form of flue gas. CO2 and PM are currently removed separately. In this work, a novel co-removal system is designed for simultaneously and synergistically removing CO2 and PM from industrial flue gas, by connecting an ammonia scrubber (AS) and a granular bed filter (GBF) in series. To validate the concept, an experimental apparatus was built, and the parameters influencing the CO2 and PM removal efficiencies in the AS, GBF and the whole system are investigated. Results show the CO2 and PM removal efficiencies of the co-removal system are 89.46% and 99.76%, respectively, and are higher than that of each single subsystem. In addition, the optimal operating conditions of the co-removal system are determined.
Industrial activities are generally energy and air emissions intensive, requiring bulky inputs of... more Industrial activities are generally energy and air emissions intensive, requiring bulky inputs of raw materials and fossil fuels and emitting huge waste gases including particulate matter (PM, or dust), sulphur dioxide (SO2), nitrogen oxides (NOx), carbon dioxide (CO2), and other substances, which are severely damaging the environment. Many studies have been carried out on the quantification of the concentrations of these air emissions. Although there are studies published on the co-effect of multi-air emissions, a more fair and comprehensive method for assessing the environmental impact of multi-air emissions is still lacking, which can simultaneously consider the flow rate of waste gases, the availability of emitting sources and the concentrations of all emission substances. In this work, a Total Environmental Impact Score (TEIS) approach is proposed to assess the environmental impact of the main industrial processes of an integrated iron and steel site located in the northeast of China. Besides the concentration of each air emission substance, this TEIS approach also combines the flow rate of waste gases and the availability of emitting sources. It is shown that the processes in descending order by the values of TEIS are sintering, ironmaking, steelmaking, thermal power, steel rolling, and coking, with the values of 17.57, 16.68, 10.86, 10.43, 9.60 and 9.27, respectively. In addition, a sensitivity analysis was conducted, indicating that the TEIS order is almost the same with the variation of 10% in the permissible CO2 concentration limit and the weight of each air emission substance. The effects of emitting source availability and waste gas flow rate on the TEIS cannot be neglected in the environmental impact assessment.
The iron and steel industry discharges large quantities of wastewater. The environmental impact o... more The iron and steel industry discharges large quantities of wastewater. The environmental impact of the wastewater is traditionally assessed from the quantitative aspect. However, the water quality of discharged wastewater plays a more significant role in damaging the natural environment. Moreover, comprehensive assessment of multi-pollutants in wastewater from both quality and quantity is still a gap. In this work, a total environmental impact score (TEIS) is defined to assess the environmental impact of wastewater discharge, by considering the volume of wastewater and the quality of main processes. To implement the comprehensively qualitative and quantitative assessment, a field monitoring and measurement of wastewater discharge volume and the quality is conducted to acquire pH, suspend solids (SS), chemical oxygen demand (COD), total nitrogen (TN), total iron (TFe), and hexavalent chromium (Cr(VI)). The sequence of TEIS values is obtained as steelmaking > ironmaking > sintering > hot rolling > coking > cold rolling and TN > COD > SS > pH > Cr(VI) > TFe. The TEIS of the investigated steel plant is 26.27. The leading process lies in steelmaking with a TEIS of 19.98. The dominant pollutant is TN with a TEIS of 15.00. Finally, a sensitivity analysis is performed to validate the feasibility and generalisability of the TEIS.
Journal of Mining and Metallurgy, Section B: Metallurgy, 2019
With the broad application of dry dedusting of blast furnace gas (BFG), the issue of BFG pipeline... more With the broad application of dry dedusting of blast furnace gas (BFG), the issue of BFG pipeline corrosion comes up because of chlorine in the BFG. Existing methods in preventing the corrosion, such as spraying alkali or installing corrosion-resistant materials, require a significant amount of investment. This paper conducted a novel thermal analysis of the corrosion mechanism to support the study on corrosion prevention without using additional materials. Firstly, thermal models were established to reflect the relationships among the amount of condensation water, the mass transfer rate, the concentration of chloride ion and the ambient temperature. Secondly, the relationship between BFG temperature and the corrosion rate was obtained via a cyclic exposure experiment. Key factors that affect the pipeline corrosion under various BFG temperatures were identified. Finally, a control scheme of the BFG temperature was proposed to avoid the chlorine corrosion.
There has always been a dispute about the energy efficiency and energy cost of electro-driven and... more There has always been a dispute about the energy efficiency and energy cost of electro-driven and turbo-driven blast furnace (BF) blast processes. In order to find where the problem lies, energy efficiency analysis models and energy cost analysis models of electro-driven and turbo-driven blast processes were established, and the differences between the two driving processes in terms of theoretical minimum steam consumption, energy efficiency and energy cost were studied. The results showed that the theoretical minimum steam consumption of a blast process depends on steam thermodynamic properties and is unrelated to drive mode and drive process. A certain overlapped interval between electro-driven and turbo-driven blast processes in terms of energy efficiency exists. The equation for calculating the standard coal coefficient of steam was proposed, and the relationship to judge strengths and weaknesses of the two driving modes in terms of energy efficiency and energy cost was established. Finally, two companies were selected for case study research. The results led to different conclusions because of the differences between energy media in terms of standard coal coefficient and unit price. To select the best driving mode, plant-running conditions and energy prices of the region of operation in addition to other relevant factors should all be taken into account.
Exhaust hot water (EHW) is widely used for various industrial processes. However, the excess heat... more Exhaust hot water (EHW) is widely used for various industrial processes. However, the excess heat carried by EHW is typically ignored and discharged into the environment, resulting in heat loss and heat pollution. An organic Rankine cycle (ORC) is an attractive technology to recycle heat from low-temperature energy carriers. Herein, ORC was used to recycle the heat carried by EHW. To investigate the energy and exergy recovery effects of EHW, a mathematical model was developed and a parametric study was conducted. The energy efficiency and exergy efficiency of the EHW-driven ORC system were modeled with R245fa, R113 and R123 as the working fluids. The results demonstrate that the EHW and evaporation temperatures have significant effects on the energy and exergy efficiencies of the EHW-driven ORC system. Under given EHW conditions, an optimum evaporation temperature exists corresponding to the highest exergy efficiency. To further use the low-temperature EHW, a configuration retrofitted to the ORC by combining with flash evaporation (FE) was conducted. For an EHW at 120 °C and 0.2 MPa, the maximum exergy efficiency of the FE-ORC system is 45.91% at a flash pressure of 0.088 MPa. The FE-ORC performs better in exergy efficiency than the basic FE and basic EHW-driven ORC.
Surplus by-product gas (SBPG) in a steel plant is the difference between gas production and consu... more Surplus by-product gas (SBPG) in a steel plant is the difference between gas production and consumption. Dynamic programming (DP) has been observed to be a useful method for SBPG dynamic allocation. However, in the SBPG allocation problem, standard dynamic programming (SDP) usually suffers from dimensionality. In this study, a novel dynamic programming method with a reduced state space algorithm (RSS-DP) is proposed. By decomposing the amount of SBPG into the reference and subsequent allocation, RSS-DP reduces the state space of the SDP model significantly such that the computation time is significantly reduced. An example of a five-boiler allocation of SBPG and a real-world online allocation of SBPG in these five boilers of a steel plant are implemented to exhibit the effectiveness of the proposed algorithm. In both cases, the solutions obtained using the proposed method are better than those obtained by traditional methods, in both computation time and energy benefit.
The study is to provide a detailed physical and chemical characterization of particles collected ... more The study is to provide a detailed physical and chemical characterization of particles collected in the ironmaking process, including a bunker system, a cast house and a pulverized coal feeding system. Using gravimetric, scanning electron microscope coupled with energy dispersive X-ray spectrometry (SEM-EDS), X-ray fluorescence spectrometry (XRF), inductively coupled plasma optical emission spectrometry (ICP-OES) analyses, the size distribution, morphology, elemental composition and emission factor of particles were investigated. The contribution rates of cast house for emission factors of total suspended particulates (TSP), PM10 and PM2.5 are the largest, 57.0%, 75.5% and 83.3%, respectively. SEM-EDS analysis indicated that cast house particle shapes are mainly formed by polymerization from spherical particles and ultrafine particles, whose main component is Fe. But, the particles of the bunker system or the pulverized coal feeding system are mainly the large ones of irregular block or powder particles and the main component is carbon. The highest content of the element in particles of the bunker system and cast house is Fe, followed by C, Si, Ca and Al. The main elements of particles in the pulverized coal feeding system are C, Si, Al and Ca, and their contents are 63.6%, 7.83%, 3.07% and 1.47%, respectively.
In this paper, five particulate emission points from a sinter plant in China, including anthracit... more In this paper, five particulate emission points from a sinter plant in China, including anthracite crusher, raw material blender, sinter strand, screener, and circular cooler, were selected for particle sampling. The particle size distribution, the toxic element content (As, Cd, Co, Cr, Cu, Ni, Pb, Ti, and Zn), and the morphology of the samples were determined by the gravimetric method, the ICP-OES, and the SEM-EDS, respectively. In addition, the gray relational analysis method was used to evaluate the rank of the particulate emission points in the sinter plant. The results show that the emission factor of PMTSP, PM10, and PM2.5 of the whole sintering process is 0.121, 0.075, and 0.039 kg/t-sinter, respectively. Furthermore, the total toxic element emission factor is 5282.49 mg/t-sinter. The sinter strand is the most important emitter and contributes 43.8% of PMTSP, 53.3% of PM10, 56.4% of PM2.5, and 81.1% of total toxic element in the sinter plant. Nevertheless, particles emitted from the post-sintering process are non-negligible and contribute 48.8% of PMTSP, 41.3% of PM10, 38.5% of PM2.5, and 15.5% of total toxic element in the sinter plant.
Mineral Processing and Extractive Metallurgy Review, 2018
As an energy-intensive industry, iron and steel production are suffering from the resource and en... more As an energy-intensive industry, iron and steel production are suffering from the resource and environmental issues. Blast furnace—basic oxygen furnace (BF-BOF) process and electric arc furnace (EAF) process are the two most common routes of steel production. Therefore, it is very important to quantify the industrial metabolism for the two routes. In this work, material flow analysis is used to comparatively investigate the energy efficiency, material efficiency, and emissions intensity at the enterprise level. The results show that the total energy consumption and material consumption per ton of steel of the BF-BOF route are 2.8 and 11 times larger than those of the EAF route, respectively. In addition, the emission intensities of dust, CO2, SO2, NO2 and CO of the BF-BOF route are 7.7, 2.6, 92.6, 33.5, and 12.0 times greater than those of the EAF route, respectively. To achieve a more sustainable steel industry, some policy recommendations are put forward finally.
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