EVALUATION AND OPTIMIZATION OF ENERGY EFFICIENCY FOR
IRON AND STEEL PRODUCTION
BY
XU HAILUN*1, SHAO YUANJING*2, YE LIDE*3, LI JUYAN*4
SYNOPSIS
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
*1XU
HAILUN, vice chief engineer of R&D Institute, WISDRI Engineering& Research
Incorporation Limited, Wuhan, China;
*2SHAO
YUANJING, director of R&D Institute, WISDRI Engineering& Research
Incorporation Limited, Wuhan, China;
*3YE
LIDE, vice director of R&D Institute, WISDRI Engineering& Research
Incorporation Limited, Wuhan, China;
*4LI
JUYAN, engineer of R&D Institute, WISDRI Engineering& Research Incorporation
Limited, Wuhan, China;
1
1. Introduction
With more and more strict restrictions for energy source and environmental protection,
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. G.J.M. 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 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 process product/steel
ratio, process energy consumption and amount of qualified casting semis. Another cg 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
2
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:
Comprehens ive energy consumptio n per ton of steel 
self - consumed energy amount
steel output
(1)
Where, the amount of self-consumed energy is calculated as the following formula
with various energy media converted into standard coal according to specified
conversion coefficient:
3
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 16 GJ to 21 GJ 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
References
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,
[7]
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,
[3]
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
4
[8]
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
[9]
energy consumption of mining & dressing as well as that of non-steel production
processes like carbon product, refractory, machine repairing and ferroalloy
production process.
(2) Process flow difference not taken into account
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
5
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 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.
6
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-widelyused 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
7
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 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
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
Fig.1 System division of iron & steel production flow
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
8
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.
(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 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 subprocess, 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
9
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:
EEIi =
Ei
⁄E
bi
(4)
EEIi —— Energy efficiency index of a process or unit, zero dimension;
Ei —— Actual energy consumption of a process or unit, kgce/t;
Ebi——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 Ei could be obtained from local measurement or statistics
analysis, and the key point is to determine the benchmark energy consumption Ebi
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.
Table 2 Energy efficiency index of modules at various levels of steel production flow
Production flow
Actual energy
Benchmark energy
division
consumption
consumption
Full process flow
E0
Eb0
10
Energy efficiency index
EEI0
System
E1
Eb1
EEI1
Process
E2
Eb2
EEI2
Sub-process
E3
Eb3
EEI3
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 − eout )
⁄Q
Ei = in
(5)
i
Ei —specific energy cosnumption of module in the statistical period, kgce/unit product;
ein —Input energy of module in the statistical period, kgce;
eout —recovered energy for external supply of module in the statistical period, kgce;
Qi —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 lowerlevel 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:
Ei−1 = ∑𝑛𝑗=1(𝐸𝑖 𝑗 × 𝑞 𝑗 )
(6)
Ei−1——specific energy consumption of upper-level module in the statistical period,
kgce/t;
𝑞 𝑖 —— quantity of level i product required for producing unit level i-1 product,
kgce/unit product;
𝑛 ——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
11
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
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
12
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.
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 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;
13
 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
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
14
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 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.
15