Evaluation and Optimization of Energy Efficiency for Iron and Steel Production Xu Hailun 1,2 *, Shao Yuanjing 1,2, Ye Lide 1,2, Li Juyan 1,2 (1. R&D Institute, WISDRI Engineering& Research Incorporation Limited, Wuhan 430223, Hubei, China; 2. National Research Center of Energy Efficiency Optimization of Steel Production, Wuhan 430223, Hubei, China) Abstract: The iron and steel industry is typical high energy consumption and high pollution industry. The energy efficiency improvement in the iron and steel industry is very important and urgent. Aiming at finding energy-saving potential for steel plants, the evaluation methods and indexes of energy efficiency are discussed. Hierarchical and modular energy efficiency evaluation system for iron and steel production process is established. The whole process of iron and steel production is divided into three levels, and multistage energy efficiency index is proposed. In conjunction with energy consumption calculation model and process characteristics of iron and steel production, energy efficiency evaluation and optimization software is developed, which can be used for analyzing energy consumption in detail. With the help of software, reasons for low energy efficiency can be identified and system solutions for energy efficiency optimization are provided, which can promote energy conservation and emission reduction, reducing cost and increasing benefit for steel plants. Key words: modularization, energy-saving potential, energy efficiency evaluation, energy efficiency optimization 1. Introduction After experiencing long term extensive expansion, China iron and steel industry is characterized by large resource consumption, much pollutant emission and low energy efficiency. It is estimated that energy consumption of iron and steel industry accounts for about 15% of total energy consumption nationwide, and CO 2 emission of iron and steel industry accounts for about 14% of total CO 2 emission nationwide. With more and more strict restrictions for energy source and environmental protection, etc., energy saving and consumption reduction have become imperative for cost reduction, benefit increasing, transformation and upgrading, and sustainable development of iron and steel enterprise. However, a comprehensive, scientific and specific energy efficiency evaluation & diagnosis system is required for bringing energy saving potential into full play as iron and steel production flow is more and more complicated, energy saving space is increasingly compressed and energy saving of iron and steel enterprise becomes more difficult. The iron and steel industry is a typical high energy consumption industry. Mainly there are two kinds of energy consumption indexes, i.e. comprehensive energy consumption per ton of steel and process energy consumption; many investigators home and abroad have made studies on its energy consumption evaluation. GJM Phylipsen et al. [1] point out that direct energy consumption comparison is not accurate as there is difference in respect of raw material proportion, product mix, process flow and system boundary, and such difference should be changed into structural index or * Corresponding author. Tel.:+86 027-81996529. E-mail address: 03100@wisdri.com (H. Xu). 1
explanatory index for correction of energy consumption index. Mikael Larsson et al. [2] argue that it is not easy to analyze the energy saving potential of steel mills due to the interrelations and effects of different subsystems; they also put forth with the effect of analyzing energy saving measures by mixed integer linear programming model on subsystems and overall systems and its further application for guiding the process of operating parameters and equipment selection. The most common one in China is the e-p analysis method [3] presented by Academician Lu Zhongwu and the process energy consumption diagnostic analysis based on the former, both of which are employed to find out the process with large potential for energy saving by decomposing the comprehensive energy consumption into quantitative relation of iron/steel ratio, process energy consumption and amount of qualified casting semis. Another c-g analysis [4], decomposing energy consumption per ton of steel into product of energy media quantity and its energy value, mainly focuses on the conversion efficiency of each energy medium, consumption of end user, and energy media buffer capacity and emission amount and other factors. Energy efficiency benchmarking is one of the most popular energy consumption evaluation methods at present; enterprises could compare energy consumption with national standard [5] and advanced trade level home and abroad to find out the gap. As the comprehensive energy consumption involves many non-comparable factors, energy efficiency benchmarking mainly applies to main processes. At present, for most energy consumption evaluation studies with respect to steel production, no relatively perfect evaluation system has been established and the evaluation index is also relatively extensive, difficult to meet the requirements of delicacy management. Part of the energy consumption index has insufficient theory for value setting, and interference of non-comparable factors has not been taken into account, therefore its guidance being poor. In order to make up for the deficiency of the existing energy consumption evaluation method, this paper establishes a hierarchical, modular energy efficiency evaluation system, puts forward the multi-level energy efficiency evaluation index from entirety to part, and develops professional energy efficiency calculation and evaluation software by combining advanced information technology with the steel production, which could carry out energy efficiency calculation and analysis for energy consumption at all levels of enterprise, identify low-energy-efficiency production processes and diagnose key factors affecting energy efficiency, and establish energy efficiency improvement system solution to provide guidance for energy saving and consumption reduction of enterprise in an efficient and economical way. 2 Conventional energy consumption indexes analysis Main energy consumption statistics indexes employed for iron and steel industry include comprehensive energy consumption per ton of steel and process energy consumption, the former being comprehensive index of enterprise and the latter being process-based energy consumption index. 2.1 Comprehensive energy consumption per ton of steel The comprehensive energy consumption per ton of steel is the total energy consumed by the enterprise during the statistical period divided by steel output. The formula is: self - consumed energy amount Comprehens ive energy consumption per ton of steel = (1) steel output 2
Where, the amount of self-consumed energy is calculated as per the following formula with various energy media converted into standard coal according to specified conversion coefficient: Amount of self-consumed energy = amount of energy purchased + increasing/decreasing amount of stock amount of energy sold out (2) The comprehensive energy consumption per ton of steel is one of the most commonly used energy consumption indexes, but it has non-comparable factors and obvious disadvantages due to complexity and diversity of the steel industry. It is briefly illustrated as follows: (1) Energy consumption statistical range not unified The steel production uses natural ore as main raw material to produce the final product after multiple processes with carbon material, ferroalloy, slagging agent and refractory as auxiliary material and various energy media as impetus. Therefore, the actual energy consumption demand for producing one ton of steel should include the direct energy consumption from the ore mining to product rolling process and indirect energy consumption in preparation of metallurgical auxiliary materials [3]. However, the energy statistical range is not completely unified as shown in Table 1 due to different process ranges covered by different steel producers coupled with different understandings of steel industry range by different organizations and entities. In the actual energy consumption index analysis process, the data of different ranges is often mixed and confused by people in case of missing clear data source, thus resulting in unauthentic indexes. Taking Japan s steel industry as an example, Kanavos Tanaka finds out that energy consumption per ton of steel ranges from 16GJ to 21GJ for different statistical ranges, quite a wide gap [6]. Table 1 Data statistical range for comprehensive energy consumption per ton of steel Statistical range of energy consumption data 1 Including energy consumption for steel production, auxiliary material production (like ferroalloy, refractory and machine repairing), byproduct production (like coking refining and blast furnace slag processing), energy loss (incl. loss and metering error), collective and individual production under the steel producer, office and public facilities in the plant and outsourcing processing with supplied materials, etc. 2 Including energy consumption of such processes in the statistical period as mining, sintering, pelletizing, iron making, steel making, rolling, refractory, ferroalloy, carbon product, machine repairing and transportation, etc. 3 For statistics of ferrous material smelting and rolling processing industry by National Bureau of Statistics, the energy consumption statistical range includes steel producer and ferroalloy, but not include mining & dressing and carbon product/metal product/refractory making. 4 Including total energy consumption of major production processes of enterprise (raw material storage, coking, sintering, pelletizing, iron making, steel making, continuous casting, rolling, captive power plant and oxygen making plant, etc.), plant transportation, fuel processing & conveying and enterprise loss; not including energy consumption of mining & dressing as well as that of non-steel production processes like carbon product, refractory, machine repairing and ferroalloy production process. References [7] [3] [8] [9] (2) Process flow difference not taken into account 3
The current prevailing steelmaking approach includes long process represented by blast furnace-converter and short process represented by EAF, and the proportion of the two in different enterprises and countries are quite different. At the same time, the two processes vary widely in energy consumption. According to theoretical calculation [10], comprehensive energy consumption per ton of steel for 8 million t long process is 670 ~ 730 kgce/t, while that for short process is 340 ~ 400 kgce/t, so it is obviously unreasonable to directly mix the two for comparison. On the other hand, as continuous casting is difficult for producing special steel grade and flat products, there are still two casting methods for liquid steel, i.e. continuous casting and mold casting, and energy consumption for the two also differ greatly. According to calculation [11], comprehensive energy consumption per ton of steel is reduced by 1.575 kgce/t for every 1% increase of continuous casting ratio of long process, while that is reduced by 1.495 kgce/t for every 1% increase of continuous casting ratio of the short process. Such difference should be taken into account for comparison in terms of comprehensive energy consumption per ton of steel. (3) Energy consumption difference caused by different raw material structure In steel smelting process, the difference of raw material will also lead to difference in energy consumption. For instance, when variety and iron content of iron ore are different, the consumption of reducing agent and fuel during the iron making process will also be different; the higher iron/steel ratio for converter smelting, the higher specific energy consumption per ton of steel, and according to China s steel industry [10], comprehensive energy consumption will be raised by approx. 20 kgce/t for every 0.1 increase of iron/steel ratio; Less effective composition of metallurgical auxiliary material will result in higher energy consumption as more such auxiliary material is required and therefore more heat needs taking away. Normally, the raw material structure is objective condition, difficult to change. Although beneficiated material has a lot of benefits, poor quality of ore resource has become irreversible trend for many enterprises. Hence, the influence of different raw material structure should be properly considered during analysis of energy consumption. (4) Energy consumption difference resulted from different product mix Energy consumption for different product processing is different due to different market demands and variable steel grades. Such difference could attribute to the following two reasons: on one hand, different final composition of product requires different amounts of metallurgical auxiliary material and smelting time; on the other hand, different processing depth and size of product will result in different processing strength and work. Enterprise producing long products has low energy consumption, while that producing flat products has high energy consumption and more energy consumption is required when the production line of flat products is longer with more processing passes; furthermore, refining, finishing and heat treatment will be added for products with high added value, which will also increase energy consumption. The energy consumption difference resulted from different product mix exists objectively, so it should be properly considered during analysis of comprehensive energy consumption. (5) Limitation of using steel (casting semis) as calculation unit It can be seen from the calculation formula of comprehensive energy consumption per ton of steel that the self-consumed energy consumption in the numerator includes the energy consumption of all the processes from the process upstream iron making up to rolling, but the steel output in the 4
denominator only refers to casting semis (i.e. the qualified casting blank and the ingot). This will make it impossible to properly evaluate the energy saving measures taken for the process downstream the said casting semis. For instance, increasing yield could significantly reduce energy waste, but it could not be reflected in the comprehensive energy consumption index per ton of steel. The increase of scrap during the rolling process will reduce the energy consumption of the rolling process, thereby reducing the self-consumed energy, but the qualified steel output will keep the same, so the comprehensive energy consumption per ton of steel will be reduced, which is obviously unreasonable. Hence, it is the inevitable disadvantage for using semis (steel) as the calculation unit. In summary, the comprehensive energy consumption per ton of steel, due to its many shortcomings, should not be used as index for energy consumption comparison between enterprises or countries, and it could only be used for rough measuring of historical change of energy consumption level in steel industry of a country or for comparison of energy consumption level over the years in an enterprise with its production structure basically kept unchanged. 2.2 Process energy consumption The process energy consumption is used to measure the energy consumption level of a specific production process of the steel production flow. It is defined as: Process energy consumption = (energy consumption of process and auxiliary procedure recovered energy for external supply)/qualified product amount (3) Process is the composition of the steel production flow, and the product of the upstream process is the raw material of the downstream process. Each process is a relatively independent link. It is the specific energy consumption for products of each process and it is comparable within definite boundary; it could accurately reflect the energy consumption level of the production process and is one of the most-widely-used indexes which could reflect the actual energy saving conditions of the enterprise to a maximal extent. However, the conventional process energy consumption still has its disadvantages: (1) The boundary of the process energy consumption is not clearly defined, particularly that auxiliary production links and utility system in the main process shop are not specifically defined, which allows some enterprises to arbitrarily change the statistical range of energy data during energy index test and energy auditing, thus bringing obstacles for reasonable evaluation of energy consumption level; (2) The process energy consumption index only includes the major processes like coking, sintering, iron making, steel making and rolling process, not including energy media making, conveying, storage and conversion links. No evaluation is made for the utility system. (3) The process is roughly divided. For instance, the steel making system is divided into three relatively independent processes, i.e. steel making, refining and continuous casting, and the rolling system is divided into two different processes of hot rolling and cold rolling. Such processes vary in different enterprises, and the combination will not be good for energy consumption evaluation or tapping of energy saving potential. (4) The present process energy consumption index only focuses on the energy consumed in the 5
processing course, and the effective energy carried by the raw material and product itself of the process are not taken into account. For example, hot metal is used as the raw material for steel making, but the sensible heat and chemical energy contained in it is not considered in the steel making process. However, analysis shows that the effective energy carried by hot metal is an important factor affecting the steel making process and is one of the main factors for realizing negative energy steel making. 3 Hierarchical and modular energy efficiency evaluation system The iron and steel production process is a very complicated process industry involving multiple processes as well as a large number of energy-consuming units and equipment. To realize fine evaluation of full process energy efficiency, the full steel production process should be decomposed in a hierarchical and modular way based on characteristic of the production process. Reasonable modular division is the important basis for realizing scientific and careful evaluation. With reference to the current trade practice and literature study, the steel production process is divided into three levels, including system level, process level and sub-process level in a hierarchical order. (1) System level As shown in Fig. 1, the full iron & steel production process is divided into the system upstream iron making, iron making system, steel making system, hot rolling system, cold rolling system and utility system. The system division is beneficial for enterprise to understand energy consumption level of various production areas and convenient for internal management of enterprise, particularly for the system with multiple production modes and variable products. For instance, the iron making system consists of blast furnace iron making process and non-blast-furnace iron making process, and steel making system consists of several processes like steel making, refining and continuous casting. Fig.1 System division of iron & steel production flow (2) Process level In the modular deconstruction of the steel production flow, process is the most important connecting module and is also the most common module for energy consumption statistics. When 6
the system is divided into processes, it is required that seamless connection should be realized among the processes, without any missing or repeated content. The process could be used as independent energy efficiency evaluation module. Fig. 2 shows the blast furnace iron making process module. Fig. 2 Blast furnace iron making process module (3) Sub-process level As each process of steel production includes a wide range, the process could be further divided into sub-processes for highlighting of the energy consumption issue. Separate energy consumption statistics and analysis are carried out for the sub-process, and special attention is paid to such sub-process as with high energy consumption or with high energy saving potential so as to make the energy consumption analysis more specific and elaborate. It should be noted that the above three-level modules shall meet the following requirements: (a) Specific boundary: distinct boundary is defined for all the modules and data interface is available for adjacent modules; (b) Independent and complete information: each module contains complete input/output energy flow, material flow and information flow; (c) Possible for combination: each module could be used as an independent evaluation unit, and several modules should be combined into a big unit for evaluation. 4 Multi-stage energy efficiency evaluation index EEI (energy efficiency index) [12-13] is introduced here for more accurate representation of the energy efficiency of the steel production process. EEI mainly reflects the energy efficiency level of the object to be evaluated relative to the benchmark energy-saving object. The calculation formula is: 7
EEI i = E i (4) EEI i Energy efficiency index of a process or unit, zero dimension; E i Actual energy consumption of a process or unit, kgce/t; E bi Benchmark energy cosnumption of a process or unit, kgce/t; It could be seen from formula (4) that for a specific EEI calculation process, the actual energy consumption E i could be obtained from local measurement or statistics analysis, and the key point is to determine the benchmark energy consumption E bi which could be fixed in many ways. It is pointed out in Literature 13] that the benchmark energy consumption could be determined in the same range with reference to the best historical level of the enterprise as well as advanced level and theoretical value in the same industry home and abroad. It is suggested here that it could be determined by means of mechanism model, regression statistical analysis and local measuring with advanced, well-proven and economical production conditions as calculation parameters. In this way, the benchmark energy consumption could be guaranteed with sufficient theoretical basis. Based on the above 3-level modules plus comprehensive energy efficiency index of full steel production process, there are 4 levels of energy efficiency indexes in total as shown in table 2. E bi Table 2 Energy efficiency index of modules at various levels of steel production flow Production flow Actual energy Benchmark energy division consumption consumption Energy efficiency index Full process flow E 0 E b0 EEI 0 System E 1 E b1 EEI 1 Process E 2 E b2 EEI 2 Sub-process E 3 E b3 EEI 3 It could be seen from the calculation process of the specific energy consumption that all the system, process and sub-process could be used as independent unit for energy consumption calculation. The formula is as follows: E i = (e in e out ) Qi...(5) E i specific energy cosnumption of module in the statistical period, kgce/unit product; e in Input energy of module in the statistical period, kgce; e out recovered energy for external supply of module in the statistical period, kgce; Q i Qualified product quantity of this module in the statistical period, and the unit depending on the product; In addition, the full process flow, system and process could be calculated by the lower-level module and product proportion with the calculating method similar to the E-P calculating method of comprehensive energy consumption per ton of steel. The calculation formula is as follows: nn E i 1 = jj =1 EE jj ii qq jj... (6) E i 1 specific energy consumption of upper-level module in the statistical period, kgce/t; 8
qq ii quantity of level i product required for producing unit level i-1 product, kgce/unit product; nn quantity of modules decomposed; In order to make the energy efficiency more specific and concrete, energy efficiency impact factor analysis could be added, singling the production condition having big influence on energy efficiency out as separate test index. In case of energy consumption abnormity of sub-process, the energy efficiency impact factor analysis could be employed to diagnose the specific problem for realizing real fine energy efficiency evaluation. 5 Energy efficiency evaluation software for iron and steel production The elaborate energy efficiency evaluation for steel production involves a large amount of energy calculation models and data processing. An energy efficiency evaluation & diagnostics system software is developed adapting to varying and complex field conditions based on the above hierarchical modules and multi-stage energy efficiency index and with reference to actual working conditions, metallurgical empiric parameter and metallurgical chemical reaction and physical principle, etc. This software could be used to calculate theoretical benchmark energy consumption value and energy efficiency index of different energy consumption units under varying and complex conditions; meanwhile, actual energy consumption of several enterprises have been listed as reference database, which could make the energy efficiency evaluation more accurate and reliable by avoiding such non-comparable factors as resulted from variable objective conditions in conventional energy efficiency benchmarking. See Fig. 3 and 4 for calculation of the software. Main functions of the software are briefly described as follows: It could set corresponding system, process and sub-process module based on actual conditions of the plant to be evaluated and establish benchmark system with the same configuration as the main processes of the enterprise. It could calculate comprehensive energy consumption of the system, process and sub-process module under various benchmark conditions as well as specific energy consumption of energy media like water, electric power, air and gas, etc; and evaluate its energy efficiency level. It could calculate the energy efficiency level for different production process configurations and that before and after optimization of production conditions; and perform quantitative analysis. It could diagnose the specific production link and critical factor affecting energy consumption by comparing actual production condition of enterprise with benchmark working condition in the software. 9
Fig. 3 Energy consumption calculation of each module in software Fig. 4 Input and output calculation of material and energy of each module in software 6 Energy-saving technologies analysis software system Energy saving and consumption reduction prescription should be given after the root cause for low energy efficiency is found out for enterprise through energy efficiency calculation. The energy efficiency optimization model & software system based on analysis of multiple factors like energy saving effect and technical economy is developed to enable enterprise to efficiently and economically carry out energy saving activities according to their own conditions. The software could provide comprehensive analysis and comparison for typical energy efficiency optimization technology and offer related techno-economic evaluation data for enterprise so as to help the 10
enterprise to make reasonable prejudgment for avoiding confusion or setback in preparation of energy efficiency optimization technical program. Fig.5 shows the techno-economic index calculation for energy efficiency optimization technologies in the software system and Fig. 6 shows the preview for technical solution of steel production energy efficiency optimization system in the software. Main functions of the software are briefly described as follows: It could recommend targeted energy-efficiency optimization technology according to energy efficiency evaluation & diagnostics result and it could set several energy efficiency optimization technologies in the system; It could calculate the energy saving effect, project investment cost, operating cost and comprehensive economic benefit of using the energy efficiency optimization technology for enterprise under the current conditions; It could allow for preview of the energy efficiency optimization solution based on the calculation result and for direct print out of relevant documents. Fig. 5 Techno-economic index calculation for energy efficiency optimization technologies 11
Fig. 6 Preview for technical solution of steel production energy efficiency optimization system 7 Conclusions and recommendations (1) The conventional extensive energy management mode is difficult to sustain, and deepening of energy conservation should be guided by scientific and reasonable energy consumption evaluation index & method which is an effective way to help steel plant out of the energy saving dilemma and to continuously tap energy saving potential. (2) It could perform calculation analysis and elaborate diagnosis for production energy efficiency of steel producer through establishing hierarchical and modular energy efficiency evaluation system and multiple-stage energy efficiency index to help the enterprise find out specific problem and provide targeted energy efficiency optimization solution. (3) Improving delicacy energy management level of enterprise and increasing energy efficiency of steel production by combining management energy saving and technical energy saving is the inevitable choice for promoting transformation and upgrading, cost reduction & benefit increasing and taking green, healthy sustainable development path of the steel industry. Acknowledgements This work was supported by the National High Technology Research and Development Program of China (863 Program) under Grant No. 2014AA041803. References [1] G.J.M.Phylipsen, K.Blok, E.Worrell. International comparisons of energy efficiency-methodologies for the manufacturing industry[j]. Energy Policy.1997, Vol.25.nos.7-9: 715-725. [2] Mikael LARSSON, Jan DAHL. Reduction of the Specific Energy Use in an Integrated Steel Plant-The Effect of an Optimisation Model[J]. ISIJ International, Vol.43(10): 1664-1673. [3] Lu Zhong-wu, Cai Jiu-ju. The foundations of systems energy conservation[m]. Shenyang: Northeastern University Press, 2010, 47. [4] CAI Jiu-ju, SUN Wen-qiang. Systems Energy Conservation and Scientific Energy Utilization of Iron and Steel Industry in 12
China[J]. Iron and Steel, 2012, Vol.47 (5): 1-8. [5] GB 21256. The norm of energy consumption per unit product of major individual process of crude steel manufacturing process [S], Beijing: Standards Press of China, 2013. [6] Kanako Tanaka. Assessment of energy efficiency performance measures in industry and their application for policy[j]. Energy Policy. 2008, 36: 2887-2902. [7] 牛泽群. 钢铁工业能耗指标体系 [J]. 节能, 1987, 8: 12-14. [8] 兰德年. 中国钢铁工业节能目标及完善能源指标体系的建议 [J]. 冶金管理, 2007, 7: 17-23. [9] 国家发展和改革委员会资源节约和环境保护司. 重点耗能行业能效对标指南 [M], 北京 : 中国环境科学出版社, 2009, 150. [10] 李世俊. 钢铁行业节能减排现状 目标和工作思路 [J]. 冶金管理, 2: 18-24. [11] Qiu Jingchang, Cai Jiuju. The Comprehensive Energy Consumption per ton of Steel Influenced by Technological Process and Structure[J]. Energy for Metallurgical Industry, 1998, 17 (3): 3-5. [12] Dian Phylipsen, Kornelis Blok, Ernst Worrell et.al. Benchmarking the energy efficiency of Dutch industry: an assessment of the expected effort on energy consumption and CO2 emissions [J]. Energy Policy, 2002, 30(8): 663-679. [13] GB/T 28924. Guides for calculating energy efficiency index of an iron and steel enterprise[s], Beijing: Standards Press of China, 2012. 13