Coal Polygeneration With Decarbonisation-Tables-revised 11082012
Optimal Design and Operation of a Polygeneration System in ...
Transcript of Optimal Design and Operation of a Polygeneration System in ...
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Åbo Akademi University - Thermal and Flow Engineering Lab, Biskopsgatan 8, FI-20500, Åbo, Finland
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Optimal Design and Operation of a
Polygeneration System
in a Steel Plant
H. Ghanbari
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Åbo Akademi University - Thermal and Flow Engineering Lab, Biskopsgatan 8, FI-20500, Åbo, Finland
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Motivation Model Description Case study Remarks
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7-Nov-13 Åbo Akademi University - Thermal and Flow Engineering Biskopsgatan 8, FI-20500, Åbo, Finland
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Sustainable Development
Motivation
Sustainable Process Design
Society
Enviroment
Economy
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7-Nov-13 Åbo Akademi University - Thermal and Flow Engineering Biskopsgatan 8, FI-20500, Åbo, Finland
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Looking for holistic approach to process design and operation
that emphasizes the unity of the process and optimizes its
design and operation
Motivation JR
C report by N
. Pardo et al, 2012
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7-Nov-13 Åbo Akademi University - Thermal and Flow Engineering Biskopsgatan 8, FI-20500, Åbo, Finland
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Numerous alternative
A systematic methodology to extract optimum solution
Process must be treated as an integrated system
BIG PICTURE FIRST,
DEATAILS LATER
Flexibility
Expenses
Motivation
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CP: Coke Plant, SP: Sinter Plant, ST: Hot Stoves, CCP: CO2 Capturing Plant, BF: Blast Furnace, BOF: Basic Oxygen Furnace and CHP: Combined Heat and Power Plant, GR: Gas Reforming unit, MP: Methanol Plant
Åbo Akademi University - Thermal and Flow Engineering Lab, Biskopsgatan 8, FI-20500, Åbo, Finland
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Model Description
PC/
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Åbo Akademi University - Thermal and Flow Engineering Lab, Biskopsgatan 8, FI-20500, Åbo, Finland
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Superstructure for suggested Integrated Steelmaking with polygeneration plant.
Model Description
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Åbo Akademi University - Thermal and Flow Engineering Lab, Biskopsgatan 8, FI-20500, Åbo, Finland
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Model Description
Mathematical Programming
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Åbo Akademi University - Thermal and Flow Engineering Lab, Biskopsgatan 8, FI-20500, Åbo, Finland
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𝑡𝑡𝑡𝑡𝑡𝑡ℎ𝑓𝑓𝑓𝑓𝑡𝑡𝑓𝑓
∨ �𝑌𝑌(𝑡𝑡𝑡𝑡𝑡𝑡ℎ, 𝑓𝑓𝑓𝑓𝑡𝑡𝑓𝑓, 𝑡𝑡𝑖𝑖)ℎ𝑚𝑚�𝑓𝑓𝑗𝑗 ,𝑥𝑥𝑗𝑗 , 𝑡𝑡𝑖𝑖�ℎ𝑡𝑡�𝑓𝑓𝑗𝑗 ,𝐻𝐻𝑗𝑗 , 𝑡𝑡𝑖𝑖�
� = 0
𝐴𝐴𝑗𝑗 𝑓𝑓(𝑗𝑗, 𝑡𝑡𝑖𝑖) = 𝑏𝑏𝑗𝑗 ℎ𝑡𝑡�𝑓𝑓𝑗𝑗 , 𝑡𝑡𝑖𝑖� = 0
⎣⎢⎢⎢⎡
𝑌𝑌(𝑃𝑃𝑃𝑃𝐴𝐴, 𝑡𝑡𝑖𝑖)ℎ𝑚𝑚(𝑓𝑓𝑃𝑃𝑃𝑃𝐴𝐴 ,𝑅𝑅𝑃𝑃𝑃𝑃𝐴𝐴 , 𝑡𝑡𝑖𝑖) = 0
ℎ𝑝𝑝(𝑓𝑓𝑃𝑃𝑃𝑃𝐴𝐴 , 𝑥𝑥𝑃𝑃𝑃𝑃𝐴𝐴 ,𝑅𝑅𝑃𝑃𝑃𝑃𝐴𝐴 ,𝛽𝛽𝑃𝑃𝑃𝑃𝐴𝐴 , 𝑡𝑡𝑖𝑖) = 0ℎ𝑡𝑡(𝑓𝑓𝑃𝑃𝑃𝑃𝐴𝐴 ,𝑇𝑇𝑃𝑃𝑃𝑃𝐴𝐴 , 𝑡𝑡𝑖𝑖) = 0ℎ𝑡𝑡(𝑓𝑓𝑃𝑃𝑃𝑃𝐴𝐴 , 𝑡𝑡𝑖𝑖) = 0 ⎦
⎥⎥⎥⎤
∨
⎣⎢⎢⎢⎢⎡
𝑌𝑌(𝑀𝑀𝑀𝑀𝑀𝑀, 𝑡𝑡𝑖𝑖)𝐴𝐴𝑓𝑓𝑓𝑓(𝑀𝑀𝑀𝑀𝑀𝑀, 𝑡𝑡𝑖𝑖) = 𝑏𝑏𝑓𝑓
ℎ𝑝𝑝(𝑓𝑓𝑀𝑀𝑀𝑀𝑀𝑀 , 𝑥𝑥𝑀𝑀𝑀𝑀𝑀𝑀 , 𝑡𝑡𝑖𝑖) = 0ℎ𝑡𝑡(𝑓𝑓𝑀𝑀𝑀𝑀𝑀𝑀 ,𝑇𝑇𝑀𝑀𝑀𝑀𝑀𝑀 , 𝑡𝑡𝑖𝑖) = 0
ℎ𝑡𝑡(𝑓𝑓𝑀𝑀𝑀𝑀𝑀𝑀 , 𝑡𝑡𝑖𝑖) = 0 ⎦⎥⎥⎥⎥⎤
𝑟𝑟𝑡𝑡𝑟𝑟𝑡𝑡∨
⎣⎢⎢⎡
𝑌𝑌(𝑟𝑟𝑡𝑡𝑟𝑟𝑡𝑡, 𝑡𝑡𝑖𝑖)𝐴𝐴𝑟𝑟𝑡𝑡𝑟𝑟𝑡𝑡 𝑓𝑓(𝑟𝑟𝑡𝑡𝑟𝑟𝑡𝑡, 𝑡𝑡𝑖𝑖) = 𝑏𝑏𝑟𝑟𝑡𝑡𝑟𝑟𝑡𝑡ℎ𝑡𝑡(𝑓𝑓𝑟𝑟𝑡𝑡𝑟𝑟𝑡𝑡 ,𝑇𝑇𝑟𝑟𝑡𝑡𝑟𝑟𝑡𝑡 , 𝑡𝑡𝑖𝑖) = 0ℎ𝑡𝑡(𝑓𝑓𝑟𝑟𝑡𝑡𝑟𝑟𝑡𝑡 , 𝑡𝑡𝑖𝑖) = 0 ⎦
⎥⎥⎤
𝑠𝑠𝑡𝑡𝑝𝑝∨
⎣⎢⎢⎢⎡
𝑌𝑌(𝑠𝑠𝑡𝑡𝑝𝑝, 𝑡𝑡𝑖𝑖)𝐴𝐴𝑠𝑠𝑡𝑡𝑝𝑝 𝑓𝑓(𝑠𝑠𝑡𝑡𝑝𝑝, 𝑡𝑡𝑖𝑖) = 𝑏𝑏𝑠𝑠𝑡𝑡𝑝𝑝
ℎ𝑡𝑡�𝑓𝑓𝑠𝑠𝑡𝑡𝑝𝑝 ,𝑇𝑇𝑠𝑠𝑡𝑡𝑝𝑝 , 𝑡𝑡𝑖𝑖� = 0ℎ𝑡𝑡�𝑓𝑓𝑠𝑠𝑡𝑡𝑝𝑝 , 𝑡𝑡𝑖𝑖� = 0 ⎦
⎥⎥⎥⎤
⎣⎢⎢⎡
𝑌𝑌(𝐷𝐷𝑀𝑀𝑀𝑀, 𝑡𝑡𝑖𝑖)𝐴𝐴𝐷𝐷𝑀𝑀𝑀𝑀𝑓𝑓(𝐷𝐷𝑀𝑀𝑀𝑀, 𝑡𝑡𝑖𝑖) = 𝑏𝑏𝐷𝐷𝑀𝑀𝑀𝑀ℎ𝑡𝑡(𝑓𝑓𝐷𝐷𝑀𝑀𝑀𝑀 ,𝑇𝑇𝐷𝐷𝑀𝑀𝑀𝑀 , 𝑡𝑡𝑖𝑖) = 0ℎ𝑡𝑡(𝑓𝑓𝐷𝐷𝑀𝑀𝑀𝑀 , 𝑡𝑡𝑖𝑖) = 0 ⎦
⎥⎥⎤∨ �
¬𝑌𝑌𝐷𝐷𝑀𝑀𝑀𝑀𝑓𝑓𝐷𝐷𝑀𝑀𝑀𝑀 = 0ℎ𝑡𝑡 = 0ℎ𝑡𝑡 = 0
�
𝑡𝑡𝑐𝑐𝑚𝑚𝑝𝑝∨
⎣⎢⎢⎢⎢⎡
𝑌𝑌(𝑡𝑡𝑐𝑐𝑚𝑚𝑝𝑝, 𝑡𝑡𝑖𝑖)𝐴𝐴𝑡𝑡𝑐𝑐𝑚𝑚𝑝𝑝 𝑓𝑓(𝑡𝑡𝑐𝑐𝑚𝑚𝑝𝑝, 𝑡𝑡𝑖𝑖) = 𝑏𝑏𝑡𝑡𝑐𝑐𝑚𝑚𝑝𝑝
ℎ𝑝𝑝�𝑃𝑃𝑡𝑡𝑐𝑐𝑚𝑚𝑝𝑝 ,𝑇𝑇𝑡𝑡𝑐𝑐𝑚𝑚𝑝𝑝 , 𝑡𝑡𝑖𝑖� = 0ℎ𝑡𝑡�𝑓𝑓𝑡𝑡𝑐𝑐𝑚𝑚𝑝𝑝 ,𝑇𝑇𝑡𝑡𝑐𝑐𝑚𝑚𝑝𝑝 ,𝑃𝑃𝑡𝑡𝑐𝑐𝑚𝑚𝑝𝑝 , 𝑡𝑡𝑖𝑖� = 0
ℎ𝑡𝑡�𝑓𝑓𝑡𝑡𝑐𝑐𝑚𝑚𝑝𝑝 . , 𝑡𝑡𝑖𝑖� = 0 ⎦⎥⎥⎥⎥⎤
𝑗𝑗 ∈ {𝐵𝐵𝐵𝐵,𝐶𝐶𝐻𝐻𝑃𝑃,𝑃𝑃𝑌𝑌𝑅𝑅𝑃𝑃}
𝑓𝑓𝑓𝑓𝑡𝑡𝑓𝑓 ∈ {𝐶𝐶𝐶𝐶𝐶𝐶,𝐵𝐵𝑀𝑀,𝐶𝐶𝑂𝑂𝑂𝑂,𝑁𝑁𝐶𝐶,𝑃𝑃𝐶𝐶𝑂𝑂} 𝑡𝑡𝑟𝑟𝑡𝑡ℎ ∈ {𝑠𝑠𝑡𝑡𝑟𝑟𝑡𝑡𝑡𝑡 𝑛𝑛𝑐𝑐. 1, 𝑠𝑠𝑡𝑡𝑟𝑟𝑡𝑡𝑡𝑡 𝑛𝑛𝑐𝑐. 2, 𝑠𝑠𝑡𝑡𝑟𝑟𝑡𝑡𝑡𝑡 𝑛𝑛𝑐𝑐. 3}
𝑗𝑗 ∈ � 𝐴𝐴𝑃𝑃𝑃𝑃,𝑊𝑊𝑃𝑃𝑃𝑃,𝐶𝐶𝑃𝑃𝑃𝑃,𝐶𝐶1,𝐶𝐶7,
𝑀𝑀𝑀𝑀𝐶𝐶𝐻𝐻,𝐶𝐶𝐶𝐶𝐶𝐶,𝐵𝐵𝐶𝐶𝐵𝐵,𝑃𝑃𝑃𝑃,𝐻𝐻𝑃𝑃� 𝑗𝑗 ∈ {𝐴𝐴𝑃𝑃𝑃𝑃,𝑊𝑊𝑃𝑃𝑃𝑃,𝐶𝐶𝑃𝑃𝑃𝑃,𝐶𝐶1,𝐶𝐶7,𝑀𝑀𝑀𝑀𝐶𝐶𝐻𝐻}
∀ 𝑟𝑟𝑡𝑡𝑟𝑟𝑡𝑡.∈ {𝑃𝑃𝑀𝑀𝑅𝑅,𝐶𝐶𝐷𝐷𝑅𝑅,𝑃𝑃𝐶𝐶𝑅𝑅} ∀ 𝑟𝑟𝑡𝑡𝑟𝑟𝑡𝑡.∈ {𝑂𝑂𝑃𝑃𝑀𝑀𝑀𝑀𝐶𝐶𝐻𝐻,𝐶𝐶𝑃𝑃𝑀𝑀𝑀𝑀𝐶𝐶𝐻𝐻}
∀ 𝑠𝑠𝑡𝑡𝑝𝑝 ∈ {𝑇𝑇𝑃𝑃𝐴𝐴,𝐶𝐶𝐶𝐶𝑃𝑃𝑃𝑃𝑅𝑅𝑀𝑀} ∀ 𝑠𝑠𝑡𝑡𝑝𝑝 ∈ {𝐶𝐶𝐶𝐶𝐴𝐴,𝐶𝐶𝐶𝐶𝑀𝑀}
∀ 𝑡𝑡𝑐𝑐𝑚𝑚𝑝𝑝 ∈ {𝐶𝐶2:𝐶𝐶6}
𝑌𝑌𝑠𝑠𝑡𝑡𝑝𝑝 ⇒ �𝑃𝑃𝑚𝑚𝑖𝑖𝑛𝑛 ≤ 𝑃𝑃𝑠𝑠𝑡𝑡𝑝𝑝 ≤ 𝑃𝑃𝑚𝑚𝑟𝑟𝑥𝑥 , 𝑇𝑇𝑚𝑚𝑖𝑖𝑛𝑛 ≤ 𝑇𝑇𝑠𝑠𝑡𝑡𝑝𝑝 ≤ 𝑇𝑇𝑚𝑚𝑟𝑟𝑥𝑥 � 𝑌𝑌𝑟𝑟𝑡𝑡𝑟𝑟𝑡𝑡 ⇒ (𝑃𝑃𝑚𝑚𝑖𝑖𝑛𝑛 ≤ 𝑃𝑃𝑟𝑟𝑡𝑡𝑟𝑟𝑡𝑡 ≤ 𝑃𝑃𝑚𝑚𝑟𝑟𝑥𝑥 , 𝑇𝑇𝑚𝑚𝑖𝑖𝑛𝑛 ≤ 𝑇𝑇𝑟𝑟𝑡𝑡𝑟𝑟𝑡𝑡 ≤ 𝑇𝑇𝑚𝑚𝑟𝑟𝑥𝑥 ) ¬ 𝑌𝑌𝑠𝑠𝑡𝑡𝑝𝑝 ⇒ 𝑌𝑌𝑡𝑡𝑐𝑐𝑚𝑚𝑝𝑝 ¬ 𝑌𝑌𝑟𝑟𝑡𝑡𝑟𝑟𝑡𝑡 ⇒ 𝑌𝑌𝑡𝑡𝑐𝑐𝑚𝑚𝑝𝑝 𝑌𝑌𝐶𝐶𝑃𝑃𝑀𝑀𝑀𝑀𝐶𝐶𝐻𝐻 ⇒ 𝑌𝑌𝐷𝐷𝑀𝑀𝑀𝑀 𝑌𝑌𝑠𝑠𝑡𝑡𝑝𝑝 ,𝑌𝑌𝑡𝑡𝑐𝑐𝑚𝑚𝑝𝑝 ,𝑌𝑌𝑟𝑟𝑡𝑡𝑟𝑟𝑡𝑡 ,𝑌𝑌𝐷𝐷𝑀𝑀𝑀𝑀 ,𝑌𝑌𝑃𝑃𝑃𝑃𝐴𝐴 ,𝑌𝑌𝑀𝑀𝑀𝑀𝑀𝑀 ,𝑌𝑌𝑓𝑓𝑓𝑓𝑡𝑡𝑓𝑓 ∈ {𝑇𝑇𝑟𝑟𝑓𝑓𝑡𝑡,𝐵𝐵𝑟𝑟𝑓𝑓𝑠𝑠𝑡𝑡} 𝑓𝑓𝑂𝑂 ≤ 𝑓𝑓 ≤ 𝑓𝑓𝑃𝑃 𝑥𝑥𝑂𝑂 ≤ 𝑥𝑥 ≤ 𝑥𝑥𝑃𝑃
∀ 𝑠𝑠𝑡𝑡𝑝𝑝 ∀ 𝑟𝑟𝑡𝑡𝑟𝑟𝑡𝑡
∀ 𝑠𝑠𝑡𝑡𝑝𝑝, 𝑡𝑡𝑐𝑐𝑚𝑚𝑝𝑝 ∀ 𝑟𝑟𝑡𝑡𝑟𝑟𝑡𝑡, 𝑡𝑡𝑐𝑐𝑚𝑚𝑝𝑝
∀ 𝑠𝑠𝑡𝑡𝑝𝑝, 𝑡𝑡𝑐𝑐𝑚𝑚𝑝𝑝, 𝑟𝑟𝑡𝑡𝑟𝑟𝑡𝑡, 𝑓𝑓𝑓𝑓𝑡𝑡𝑓𝑓,𝑃𝑃𝑃𝑃𝐴𝐴,𝑀𝑀𝑀𝑀𝑀𝑀,𝐷𝐷𝑀𝑀𝑀𝑀,𝐶𝐶𝐻𝐻𝑃𝑃,𝐵𝐵𝐵𝐵
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Åbo Akademi University - Thermal and Flow Engineering Lab, Biskopsgatan 8, FI-20500, Åbo, Finland
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HS BF GS Air
O2 State no.2
O2
HS BF GS Air
O2 State no.1
O2
HS BF GS
State no.3 Air+O2
State Hot Stoves
State NO. 1 TGR+BL
State NO. 2 BL
State NO. 3 TGR
Model Description
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Case study
Model Description
- GDP transferred to MINLP using bigM
- 86 binary variables
- 2797 continuous variables
- 4475 constraints
- GMAS/Solvers
Piece wise linear regression approach
- Three level of oxygen enrichment and top gas recycling
from 21-32% (blast enrichment) to full oxygen operation
- conventional blast to high TGR rate
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Case study
Comparison of polygeneration properties in cold (S1) and warm (S2) season
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Carbon flow percentage in the system for liquid steel production rate of 170 t/h for cold (S1) and warm season (S2). The percentage of emission from non-fossil fuels carbon carrier is excluded.
Case study
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Variable (S1) (S2) Oxygen volume [km3n/h] 34.4 35.6 Specific coke rate [kg/thm] 270 261 Specific oil rate [kg/thm] 120 42.1 Specific pellet rate [kg/thm] 456 456 Coal flow rate [t/h] 81.5 81.5 Ore flow rate [t/h] 153 153 Limestone Rate [t/h] 21.3 21.3 Quartzite Rate [t/h] 1.1 9.6 Sinter flow rate [t/h] 160 160 Flame temperature [ºC] 2067 1800 Blast/Recycled top gas temp. [ºC] 1200 1200 Recycled top gas volume [km3n/h] 86 180 Bosh gas volume [km3n/h] 162 181 Top gas temperature [ºC] 115 194 Burden residence time [h] 8.5 8.7 Slag rate [kg/thm] 211 213 COG volume [km3n/h] 17.5 17.5
Optimal process variables for the system for cold (S1) and warm (S2) season. Boldface denotes values at their constraints.
Case study
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- The model is implemented in GAMS considering different Objective Functions
(a) minimize specific carbon dioxide emission,
(b) maximize net present value,
(c) minimize carbon dioxide emission based on fossil fuels.
- OBF concept
- Model has 29 binary variables, 1174 continuous variables and 2009
constraints.
- GAMS/BARON is used as global solver to find the optimal solution.
Case study
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Optimal design and main flow for gasification, CCS and methanol plant for Max
NPV; Min Emission, CDR reactor replacing POR with stream CO2 (dottedline)
Case study
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Carbon flow percentage in the system for liquid steel production rate of 170 t/h for (a) minimum specific
emission, (b) maximum net present value, and (c) minimum specific emission for fossil fuels. For cases a
and b, the percentage of emission from non-fossil fuels carbon carrier is excluded.
Case study
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Increase in Net Present Value. Lower specific emission. Flexibility of integrated system to get higher profit. Methanol production is estimated 7 times more for warm
season in compare to cold season.
Remarks
Current Works
Modify model for all possible reducing agent BF injection Integrate with a torrefaction process.
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Thank you very much for your attention!
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Variable (a) (b) (c) Oxygen volume [km3n/h] 39.7 34.7 37.0 Specific coke rate [kg/thm] 214.3 213.1 319.5 Specific fuel rate [kg/thm] 120 120 0.0 Specific pellet rate [kg/thm] 544.9 457.5 521.1 Coal flow rate [t/h] 81.5 81.5 81.5 Ore flow rate [t/h] 140.16 153.6 143.8 Limestone Rate [t/h] 20.30 21.3 20.6 Quartzite Rate [t/h] 0.42 1.57 0.1 Sinter flow rate [t/h] 146 160 149.8 Flame temperature [ºC] 1800 1847.1 1877 Recycled top gas temperature [ºC] 1059 1112 1104 Recycled top gas volume [km3n/h] 164.6 160 176.9 Bosh gas volume [km3n/h] 173.5 169 185.1 Top gas temperature [ºC] 170.9 150.8 124.8 Burden residence time [h] 9.5 9.5 7.3 Slag rate [kg/thm] 193.1 207.8 202.1 COG volume [km3n/h] 17.58 17.58 17.58 BOFG volume [km3n/h] 6.15 6.15 6.15 Aux. fuel excluding BF [t/h] 19.4 20 8.85 CO2 Sequestrated [t/h] 107.3 101.9 110.8 Sold coke [t/h] 16.47 15.99 0.7 Sold methanol [t/h] 16.8 14.8 12.9 Sold electricity [MW] 0.0 0.0 0.0 Sold district heat [MW] 0.0 0.0 0.0
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Pareto frontiers for maximization of net present value and minimization of specific emission rate for a steel plant integrated with a polygeneration system, at a hot metal production rate of 150 thm/h and constant costs of emission and sequestration of (52 and 26 $/ tCO2).
Case study
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Results from the model for four selected point in the frontier diagram Data is estimated by using MINLP solvers in GAMS and maximum NPV is reported.
1 2 3 4
NPV (G$) 0.49 1.28 1.89 2.04 Specific emission
(tCO2/tls) 0.45 0.55 0.75 0.975
Coal flow rate
(t/h) 0.0 0.0 80.1 80.16
Ore flow rate
(t/h) 133.1 133.1 153.6 153.6
External Coke
Rate (t/h) 56.14 52.6 0.0 0.0
Limestone Rate
(t/h) 25.13 24.8 23.5 23.5
Quartzite Rate
(t/h) 0.012 0.07 0.03 0.03
Pellet Rate (t/h) 90.0 90.0 70.2 70.2 Air Volume Rate
(knm3/h) 106.5 113.0 113.0 113.0
Oxygen flow
Rate (knm3/h) 21.96 17.3 17.8 18.7
Slag Rate
(kg/thm) 220 218.4 216.2 216.2
Scrap Rate (t/h) 37.5 37.5 37.5 37.5 Nitrogen flow
rate (t/h) 47.2 56.0 56.0 56.0
DME flow rate
(t/h) 0.0 0.0 0.0 0.6
Oil flow rate
(t/h) 21.64 21.9 18.0 18.0
CO2
Sequestrated
(t/h)
148.7 118.8 116.1 81.6
Methanol
production (t/h) 23.38 20.86 21.15 19.34
Steel Cost ($/tls) 358.4 355.1 300.3 311.0
Case study
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Some Results
Optimal specific emission at different carbon dioxide emission and sequestration cost for the hot metal production rate of 𝟏𝟏𝟏 𝒕𝒉𝒉/𝒉.
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Some Results (Sensitivity Analysis)
Optimal net present value for a ±100 $ change in main raw material and products at constant hot metal production rate of 150 thm/h and cost of emission and sequestration of 10 $/tCO2.
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Conceptual Design of Polygeneration System
Superstructure for suggested polygeneration plant.