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Swedish Experience of Practical application
of Process Integration
Chuan Wang
Jan-Olov Wikström
Swerea MEFOS AB, Luleå, Sweden
IEA GHG/IETS Iron & Steel Industry Workshop, Tokyo , Japan , November 5-7, 2013
What is Process Integration?
IEA:
“Systematic and General Methods for Designing Integrated Production
Systems, ranging from Individual Processes to Total Sites, with special
emphasis on the Efficient Use of Energy and reducing Environmental
Effects.”
Ekonomi
Energi
Uthållig resursanvändning
Miljö
Ekonomi
Energi
Uthållig resursanvändning
Miljö Optimisation: given a system or process, find the best solution to this process within given constraints. Objective function: indicator of performance, e.g. emissions, energy, costs. Decision variables: variables that influence process behaviour and can be adjusted for optimisation.
Material
Sustainability / Environment
Costs Energy
2/24
HRC: 1000 kg
BFG BOFG
HM: 992 kg LS: 1081 kg Slab: 1053 kg
NG
Lime to BOF
Sinter to BF
Unit: /t-HRC
COG
O2
1111 kg
87 kg
Scrap: 205 kg
1.4 GJ
0.55 GJ
3.13 GJ
0.07 GJ
0.75 GJ
0.44 GJ
1.03 GJ0.02 GJ0.21 GJ0.31 GJ0.08 GJ
0.02 GJ
0.66 GJ0.45 GJ
5.5 kWh
337.9 kWh
Pellet : 341 kg
Coke: 345 kg
Sinter: 1111 kg
PCI: 151 kg
47.5 nm3 55.7 nm3 2.6 nm32.2 nm32.3 nm3
Lump ore: 118 kg
BFG COGBOFG Natural gas
Oxygen
Legends
Raw material
available
NT
NT
Holistic perspective for changes - A standard European steel plant
3/24
2013-11-19 4
PRISMA – Centre for Process Integration in Steelmaking
System analysis & optimisation:
Energy, materials, GHG
7 Industrial members
Joint research program
Ruukki
SSAB,
Lulekraft,
MEROX,
LTU
MEFOS
SSAB,
MEROX
LKAB
Höganäs
AGA
Norut
Company specific program
10 full-time researchers
External projects
International networking
Process Integration Forum Annual Information and Project communication forum, open to everyone.
Communication and learning processes
5/24
Mining and benefication
Integrated steel production
Production system models PRISMA
CHP
Scrap based steel
production
6/24
Modelling tools used in the center
Theory
Heuristics
Process data
reMINDModelling
CPLEX SolverOptimization
MS ExcelOutput
Post processing
AnalysisOK?Results
f(x, y)c·x+b·y
c, bmin f(x,y)
Suggested solution
Modify
Solution
Optimization tools:
Mathematical programmering; Pinch analysis; Exergy analysis; GAMS, etc.
Assisting tools:
Aspen, FactSage, HSC, Matlab, Masmod, CFD, RIST, HEATSEP, etc.
7/24
Application examples of Process Integration
PRISMA projects in the area of
Energy efficiency, and
Material efficiency
8/24
Grid
Grid
Grid
Grid
Grid
Grid
Grid
Grid
Grid
Grid
Grid
Grid
Grid
Grid
Case studies at SSAB EMEA in Oxelösund, Sweden
Oxelösund’s integrated plant
Coking plant
Two blast furnaces
Steel plant
Rolling mill
Power plant
Own harbour
9/24
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04
Bla
st t
em
pe
ratu
re, °
C
Serial modeParallel mode
Change of hot stoves’ operation mode - SSAB EMEA, Oxelösund
More energy to the hot stoves
Less BFG to PP
Possibility for increased hot blast
temperature
Reduced coke rate
Improved process gas utilization
• Blast temperature
- calculated + 100 oC
- achieved + 60 oC
• Coke
- achieved – 9 kg/tHM·100 oC
• Cost saving of 6.5 MSEK per year
• Non-investment cost!
28 May 2012
10/24
Optimal coal injection at varying production rates
Question: How does different
coal influence the operation
costs?
Energy saving – Less primary energy required and
increased power generation o High heating value in the BFG when injecting the high
volatile coal makes more COG gas available to the RF at
RM, thus reducing the oil consumption.
o The high volatile coal may lead to the highest electricity
production in PP due to an increased energy in the BFG.
o Fuel rate is slightly increased.
Cost saving – High volatile coal most cost efficient
at low production rate Cost saving:
- 60-80 MSEK at a production rate of 1.5-
2 Mton hot metal per annum
11/24
Case of Ruukki metals, Raahe Steelworks, Finland
- Optimised coal blending at the coking plant
Potential cost saving by optimised coal blending at the coking plant.
Coking plant, Volalites
Blast
furnace
Coke
External Coke
Mill plant
COG
LPG
Coals
Flaring
Power
plantFlaring
BFG
Items
Opti. coal blending
scenario, %
COG production 9.2
COG used at the rolling mill 19.9
Own Coke to BF -1.0
Total purchased coke 8.0
LPG consumption at the strip mill -28.7
Coal blending material cost -5.7
Purchased electricity -5.4
Coke production cost -4.8
Total production cost -2.6
Coal blending reference case
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
No.1
No.2
No.3
No.4
No.5
No.6
No.7
No.8
No.9
No.1
0
Coal types
Co
al b
len
din
g, %
0.0
5.0
10.0
15.0
20.0
25.0
30.0
Vo
lati
le (
dry
), %
Coal percentage Volatile in coal mixing
Coal blending optimized (cost) case
0.0
10.0
20.0
30.0
40.0
50.0
60.0
No.1
No.2
No.3
No.4
No.5
No.6
No.7
No.8
No.9
No.1
0
Coal types
Co
al b
len
din
g, %
0.0
5.0
10.0
15.0
20.0
25.0
30.0
Vo
lati
le (
dry
), %
Coal percentage Volatile in coal mixing
12/24
Case of Stove oxygen enrichment (SOE) at
different sites
Potential economical benefits and effects of SOE application at
different steelworks under different conditions!
Fuel gas
BFG/COG
Combustion air
O2 enrichment
Firing / Blast cycles
O2
Evaluation 1 : Fixed COG rate high Bl.temp . Coke/PCI saved
Evaluation 2 : Fixed Bl.temp.
COG saved for
BF injection
for coke saving
Replace
Oil/LPG/NG
Power plant Hydrogen DRI
production
COG saving
13/24
Economical evaluation of SOE at Ruukki
Preferably use COG
saved from hot stoves
at the reheating
furnaces to substitute
LPG!
The cost saving are
varying at different
production rates!
1.4
5.8
0
1
2
3
4
5
6
7
High prod. rate Medium prod. rate Low prod. rate
Mat
eri
al c
ost
sav
ing,
M€
/ye
ar
3.5
14/24
Grid
Grid
Grid
Grid
Grid
Grid
Grid
Grid
Grid
Grid
Grid
Grid
Grid
Grid
Bird’s-Eye photo of SSAB EMEA Luleå
BF
Steel plant
Coking plant
O2 plant CHP
Bioenergi Lime kiln
15/24
Distribution of COG saved in hot stoves at SSAB Luleå
150
155
160
165
170
175
180
185
190
0 20 40 60 80 100
Hea
t de
mad
, MW
COG saved for BF injection or Power Plant, %BF PP
0
10
20
30
40
50
60
70
80
90
100
-20 -15 -10 -5 0 5 10 15 20
CO
G t
o B
F/P
P, %
Out door temperature, C
COG to PP
COG to BF inj. for coke saving
(-6 °C; 153.3MW)
(-11 °C; 183.8 MW)
16/24
Examples of material efficiency
Ferrovanadium recovery from LD slag for the case of
SSAB EMEA in Luleå
Common Nordic solution
- Regional efforts for untreatable wastes
17/24
Extern BOF slag
FeSi
75 % of the BOF slag
25 % of the BOF slag
HM HM RS
VILD
LUVA
ViLD/EAF
C
LuVA/ViLD at SSAB EMEA, Luleå
Background • High V in LD slag
• Limits the LD slag external use
• Meanwhile, valuable V product.
Aim • Determine the best method to
recover Vanadium
Method • Modeling of
different scenarios
based on:
a) Metallurgical knowledge
b) Industrial trials with two-
slag practice in LD
ViLD FeV
Export?
HM Fe-smälta CS
Red.medel
Extern
V-source
BF LD
V-slag
LD-slag
Red.slag
PI-model
Slagg
18/24
Optimal practice (based on LD trials and modeling)
- Min V-content in HM (~0.36%) can be achieved by recycling of
secondary, stored LD slag and secondary slag fines fraction.
- Requires higher tolerance for P in the hot metal lower tapping
temp and no dolomitic lime in the LD.
Consequences
- Decrease of the LD slag storage,
- Requires 100% MPBO pellet in the BF burden.
Results – LuVA/ViLD
19/24
RHF – a common Nordic solution for untreatable wastes
DRI Cooling
Unit: kton/year
Steelworks Waste amount
SSAB EMEA, Luleå 60
SSAB EMEA, Oxel. 70
Ruukki 80
FN Steel 200
50
100
150
200
250
300
350
400
450
-5.0 0.0 5.0 10.0 15.0 20.0
La
nd
fill (kto
n/a
)
Revenue - cost (M€/a)
20/24
Example of Industrial Symbiosis
Moving on …
Towards the industry symbiosis …
21/24
On-going projects in the area of energy and
CO2 mitigation
Biomass utilization in the BF
Optimisation of BF hot stove operation
Dry slag granulation and heat recovery
Preheating and surface cleaning of scrap
Reuse of low temperature heat (T< 350 °C)
Process integration for resource management
Flue gas recirculation with SOE - a new concept
High efficiency low NOx BFG based combustion systems in steel
reheating furnaces
22/24
Concluding remarks
PI is a useful tool for the steel industry to improve its energy and
material efficiency by finding optimal solutions in a most
economic and sustainable manner.
PI can be used for searching answers on strategic issues, e.g.
how new processes will fit into the site, retrofit questions,
investments, production planning, etc.
The more complex the system, the higher probability to find new
and improved solutions with a system oriented approach.
Global integrated efforts are needed to further reduce CO2
emission from the steel industry.
23/24
Thanks for your attention!
More information about Swerea MEFOS
Please visit www.swerea.se/mefos
Further contact:
Dr. Chuan Wang1; Prof. Jan-Olov Wikström2
Telephone: +46 (0)920 20 19 00
24/24
