US 12,571,060 B2 · Joint regulation method of material flow, energy flow, and carbon emission flow in long-process iron and steel enterprises

Abstract

Provided are a joint regulation method of material flow, energy flow, and carbon emission flow in a long-process steel enterprise, which belongs to a field of intelligent regulation and control technology of electric power system in the steel industry. The method includes: coupling a material-energy characteristic model of each production process of a steel enterprise and a carbon emission model of the steel enterprise, constructing a material flow-energy flow-carbon emission flow coupling model of the long-process steel enterprise, establishing an objective function using a minimize sum of an electricity purchase cost from a superior grid, a park carbon emission cost, and a production raw material cost as an object, and solving and obtaining an optimal operation mode of a joint regulation of the material flow-energy flow-carbon emission flow in the steel enterprise.

A joint regulation method of material flow, energy flow, and carbon emission flow in a steel enterprise, wherein the joint regulation of the material flow, the energy flow, and the carbon emission flow is performed by constructing a plurality of models, wherein production processes of the steel enterprise include a coking process, a sintering process, a pelletizing process, a blast furnace iron-making process, a converter steel-making process, an electric arc furnace steel-making process, a steel-rolling process, and an air compressor oxygen-making process that provides oxygen in the coking process, the sintering process, the pelletizing process, the blast furnace iron-making process, the converter steel-making process, the electric arc furnace steel-making process, and the steel-rolling process, wherein process numbers of the coking process, the sintering process, the pelletizing process, the blast furnace iron-making process, the converter steel-making process, the electric arc furnace steel-making process, and the steel-rolling process are from 1 to 7 in sequence, wherein the coking process and the electric arc furnace steel-making process belong to an intermittent output process, the sintering process, the pelletizing process, the blast furnace iron-making process, the converter steel-making process, and the steel-rolling process belong to a continuous output process;

the method comprising the following steps, the following steps being carried out in turn,
step 1. constructing a material flow model of the electric arc furnace steel-making process, wherein the material flow model of the electric arc furnace steel-making process includes the following constraints:
(1) constructing a continuous constraint for starting and stopping of the electric arc furnace steel-making process:
ds
6
,
t
+
d
⁢
c
6
,
t
≤
1
,
(
1
)
ds
6
,
t
-
d
⁢
c
6
,
t
=
o
⁢
p
6
,
t
-
o
⁢
p
6
,
t
-
1
,
(
2
)
wherein ds6,t is a starting variable of the electric arc furnace steel-making process;
dc6,t is a stopping variable of the electric arc furnace steel-making process;
op6,t is a running variable of the electric arc furnace steel-making process;
and 6 is a process number corresponding with the electric arc furnace steel-making process;
(2) constructing a minimum running time constraint of the electric arc furnace steel-making process:
ds
6
,
t
+
∑
τ
=
t
+
1
t
+
Min
⁢
⁢
op
6
-
1
⁢
d
⁢
c
6
,
τ
≤
1
,
(
3
)
wherein Minop6 is a minimum running time of the electric arc furnace steel-making process;
(3) constructing a maximum running time constraint of the electric arc furnace steel-making process:
∑
τ
=
t
t
+
Max
⁢
⁢
op
6
-
1
⁢
d
⁢
c
6
,
τ
≥
ds
6
,
t
,
(
4
)
wherein Maxop6 is a maximum running time of the electric arc furnace steel-making process;
(4) constructing a minimum downtime constraint of the electric arc furnace steel-making process:
d
⁢
c
6
,
t
+
∑
τ
=
t
+
1
t
+
Dp
6
-
1
⁢
d
⁢
s
6
,
τ
≤
1
,
(
5
)
wherein Dp6 is a minimum downtime of the electric arc furnace steel-making process;
(5) constructing a material flow constraint of the electric arc furnace steel-making process:
G
6
,
t
=
∑
t
⁢
o
⁢
p
6
,
t
·
G
6
,
(
6
)
wherein G6,t is a product output of the electric arc furnace steel-making process;
and G6 is a unit output of the electric arc furnace steel-making process;
step 2. constructing a material model of a steel enterprise process:
(1) constructing a material flow constraint model of the coking process:
Y
1
,
t
×
k
=
G
1
,
t
∀
t
,
(
7
)
G
min
⁢
⁢
1
≤
G
1
,
t
≤
G
max
⁢
1
∀
t
,
(
8
)
G
1
,
t
×
λ
jt
⁢
2
=
M
jt
⁢
2
∀
t
,
(
9
)
G
1
,
t
×
λ
jt
⁢
3
=
M
jt
⁢
3
∀
t
,
(
10
)
G
1
,
t
×
λ
jt
⁢
4
=
M
jt
⁢
4
∀
t
,
(
11
)
wherein Y1,t is an input raw material quantity of the coking process, wherein the input raw material is coking coal;
k is a coking ratio;
G1,t is a product output of the coking process;
λjt2 is a coke supply and demand ratio of the sintering process;
λjt2 is a coke supply and demand ratio of the pelletizing process;
λjt4 is a coke supply and demand ratio of the blast furnace iron-making process;
Mjt2 is a quantity of coke input into the sintering process;
Mjt3 is a quantity of coke input into the pelletizing process;
Mjt4 is a quantity of coke input into the blast furnace iron-making process;
Gmin 1 and Gmax 1 are an output lower limit and a output upper limit of the coking process, respectively;
(2) constructing a material flow constraint model of the sintering process:
(
M
j
⁢
t
⁢
2
+
Y
2
,
t
×
λ
tks
⁢
2
)
×
v
2
=
G
2
,
t
∀
t
,
(
12
)
G
min
⁢
⁢
2
≤
G
2
,
t
≤
G
max
⁢
2
∀
t
,
(
13
)
G
2
,
t
×
λ
sjk
⁢
4
=
M
sjk
⁢
4
∀
t
,
(
14
)
wherein Y2,t is an input raw material quantity of the sintering process, wherein the input raw material is iron ore;
v2 is a material conversion rate of the sintering process;
λtks2 is an iron ore supply and demand ratio of the sintering process;
G2,t is a product output of the sintering process;
λsjk4 is an sinter ore supply and demand ratio of the blast furnace iron-making process;
Msjk4 is a quantity of sinter ore input into the blast furnace iron-making process, and Gmin 2 and Gmax 2 are an output lower limit and an output upper limit of the sintering process, respectively;
(3) constructing a material flow constraint model of the pelletizing process:
(
M
jt
⁢
3
+
Y
2
,
t
×
λ
tks
⁢
3
)
×
v
3
=
G
3
,
t
∀
t
,
(
15
)
G
min
⁢
⁢
3
≤
G
3
,
t
≤
G
max
⁢
3
∀
t
,
(
16
)
G
3
,
t
×
λ
qtk
⁢
4
=
M
qtk
⁢
4
∀
t
,
(
17
)
wherein v3 is a material conversion rate of the pelletizing process;
G3,t is a product output of the pelletizing process;
λtks3 is an iron ore supply and demand ratio of the pelletizing process;
λgtk4 is a pellet ore supply and demand ratio of the blast furnace iron-making process;
Mqtk4 is a quantity of pellet ore input into the blast furnace iron-making process;
Gmin 3 and Gmax 3 are an output lower limit and an output upper limit of the pelletizing process, respectively;
(4) constructing a material flow constraint model of the blast furnace iron-making process:
(
M
jt
⁢
4
+
M
sjk
⁢
4
×
M
qtk
⁢
4
)
×
v
4
=
G
4
,
t
∀
t
,
(
18
)
G
min
⁢
⁢
4
≤
G
4
,
t
≤
G
max
⁢
4
∀
t
,
(
19
)
wherein v4 is a material conversion rate of the blast furnace iron-making process;
G4,t is a product output of the blast furnace iron-making process;
Gmin 4 and Gmax 4 are an output lower limit and an output upper limit of the blast furnace iron-making process, respectively;
(5) constructing a material flow constraint model of the converter steel-making process:
G
4
,
t
×
v
5
=
G
5
,
t
∀
t
,
(
20
)
G
min
⁢
⁢
5
≤
G
5
,
t
≤
G
max
⁢
5
∀
t
,
(
21
)
wherein v5 is a material conversion rate of the converter steel-making process;
G5,t is a product output of the converter steel-making process;
Gmin 5 and Gmax 5 are an output lower limit and an output upper limit of the converter steel-making process, respectively;
(6) constructing a material flow constraint model of the steel-rolling process:
(
G
5
,
t
+
G
6
,
t
)
×
v
7
=
G
7
,
t
⁢
∀
t
,
(
22
)
G
min
⁢
7
≤
G
7
,
t
≤
G
max
⁢
7
⁢
∀
t
,
(
23
)
wherein v7 is a material conversion rate of the steel-rolling process;
G7,t is a product output of the steel-rolling process;
Gmin 7 and Gmax 7 are an output lower limit and an output upper limit of the steel-rolling process, respectively;
step 3. combining a plurality of constraints obtained in step 2 to construct warehouse storage models, an air compression system model, a gas system model, a cogeneration unit model, and a coke dry quenching waste heat recovery model, wherein the warehouse storage models include a coke warehouse storage model, a sinter ore warehouse storage model, and a pellet ore warehouse storage model:
(1) constructing the warehouse storage models:
S
0
,
c
+
∑
m
M
m
,
c
,
t
-
∑
n
Y
n
,
c
,
t
=
S
c
,
t
,
c
∈
{
1
,
2
,
3
}
,
m
∈
j
,
n
∈
j
,
j
∈
{
1
,
2
,
3
,
4
,
5
,
6
,
7
}
,
_
t
=
1
,
(
24
)
S
c
,
t
-
1
+
∑
m
M
m
,
c
,
t
-
∑
n
Y
n
,
c
,
t
=
S
c
,
t
,
c
∈
{
1
,
2
,
3
}
,
m
∈
j
,
n
∈
j
,
j
∈
{
1
,
2
,
3
,
4
,
5
,
6
,
7
}
,
_
t
≥
2
,
(
25
)
S
min
,
c
≤
S
c
,
t
≤
S
max
,
c
⁢
c
∈
{
1
,
2
,
3
}
,
∀
t
,
(
26
)
wherein Equations (24) and (25) are storage link balance equations;
Equation (26) is an storage link upper and lower limit equation;
c is a warehouse serial number;
S0,c is an initial storage volume of a warehouse c;
Mm,c,t is an output of a previous mth process of the warehouse c at the time t;
Yn,c,t is an amount of a material required for a following nth process of the warehouse c at the time t;
Sc,t is a capacity of the warehouse c at the time t;
Smin,c is an storage capacity lower limit of the warehouse c;
and Smax,c is an storage capacity upper limit of the warehouse c;
wherein j, m, and n are values of the process numbers, m and n are taken from values of j, which is taken from a set {1, 2, 3, 4, 5, 6, 7}, and the set {1, 2, 3, 4, 5, 6, 7} is composed of the process numbers of the coking process, the sintering process, the pelletizing process, the blast furnace iron-making process, the converter steel-making process, the electric arc furnace steel-making process, and the steel-rolling process;
(2) constructing the air compression system model:
SA
ca
,
t
=
SA
ca
,
t
-
1
-
SU
ca
,
t
⁢
Δ
⁢
t
+
α
ca
⁢
P
ca
,
t
⁢
Δ
⁢
t
,
(
27
)
0.8
SA
ca
,
ini
≤
SA
ca
,
end
≤
1.2
SA
ca
,
ini
,
(
28
)
V
ca
⁢
P
ca
,
min
≤
SA
ca
,
t
≤
V
ca
,
t
≤
V
ca
⁢
p
ca
,
max
,
(
29
)
SA
ca
,
t
+
op
ca
,
t
⁢
V
ca
⁢
p
ca
,
max
≤
1.1
V
ca
⁢
p
ca
,
max
,
(
30
)
1.1
V
ca
⁢
p
ca
,
max
≤
Sa
ca
,
t
+
op
ca
,
t
⁢
V
ca
⁢
p
ca
,
min
,
(
31
)
wherein Equation (27) is a gas storage volume balance equation;
Equations (28) and (29) are gas storage volume upper and lower limit equations;
Equations (30) and (31) are air compressor starting and stopping equations;
SAca,t is a gas storage volume of a gas storage tank at the time t;
SUca,t is a system gas consumption at the time t;
αca is an efficiency of the air compressor;
Pca,t is an output power of the air compressor at the time t;
Δt is an optimization step size of 1 hour;
SAca,ini is a gas storage volume of the gas storage tank at an initial time;
SAca,end is a gas storage volume of the gas storage tank at an ending time;
Vca is a volume of the gas storage tank;
pca,min and pca,max are a allowable minimum pressure and a allowable maximum pressure in the gas storage tank;
opca,t is a running variable of the air compressor at the time t;
(3) constructing the gas system model:
f
COG
,
t
prod
=
μ
COG
⁢
P
1
,
t
,
(
32
)
f
BFG
,
t
prod
=
μ
BFG
⁢
P
4
,
t
,
(
33
)
f
LDG
,
t
prod
=
μ
LDG
⁢
P
5
,
t
,
(
34
)
V
o
,
t
=
V
o
,
t
-
1
+
f
o
,
t
prod
-
∑
j
f
j
,
o
,
t
-
f
o
,
t
chp
,
(
35
)
V
min
,
o
≤
V
o
,
t
≤
V
max
,
o
,
(
36
)
wherein μCOG, μBFG, μLDG are a by-product gas yield of coke oven gas (COG) of the coking process, a by-product gas yield of blast furnace gas (BFG) of the blast furnace iron-making process, and a by-product gas yield of Linz-Donawitz process gas (LDG) of the converter steel-making process, respectively;
o is by-product gas;
Vo,t is the gas storage capacity;
f
o
,
t
prod
is the gas output;
fj,o,t is a demand of the process j to the by-product gas o;
f
o
,
t
chp
is a volume or gas input into a cogeneration unit;
Vmin,o and Vmax,o are a capacity lower limit and a capacity upper limit of a corresponding gas storage tank;
(4) constructing the cogeneration unit model:
P
t
chp
⁢
δ
=
θ
chp
⁢
∑
o
f
o
,
t
chp
⁢
β
o
,
(
37
)
P
min
chp
≤
P
t
chp
≤
P
max
chp
,
(
38
)
Q
t
chp
=
P
t
chp
⁢
θ
chp
,
heat
,
(
39
)
wherein Equation (37) is a conversion formula for conversion of thermal energy to electrical energy, wherein the thermal energy is generated from the combustion of the by-product gas as a fuel in the cogeneration unit;
Equation (38) is an upper and lower output limit constraint of the cogeneration unit;
Equation (39) is a conversion formula for conversion of the electrical energy to the thermal energy in the cogeneration unit;
Q
t
chp
is steam heat generated by the cogeneration unit;
P
t
chp
is electric power of the cogeneration unit;
δ is an optimized cycle length;
P
min
chp
⁢
and
⁢
P
max
chp
are a lower output limit and an upper output limit of the cogeneration unit, respectively;
θchp is an electrical efficiency of the cogeneration unit;
θchp,heat is a thermal efficiency of the cogeneration unit;
βo is a calorific value of the by-product gas o;
(5) constructing the coke dry quenching waste heat recovery model:
P
t
cdq
=
λ
cdq
⁢
P
1
,
t
,
(
40
)
P
min
cdq
≤
P
t
cdq
≤
P
max
cdq
,
(
41
)
wherein
P
t
cdq
is a waste heat power generation power;
λcdq is a power generation coefficient;
P1,t is a coking power;
P
min
chp
⁢
and
⁢
P
max
chp
are a lower output limit and an upper output limit of a coke dry quenching waste heat unit, respectively;
step 4. introducing the electric arc furnace steel-making process into the material model of the steel enterprise process to form a material-energy characteristic model of a steel enterprise production process based on the warehouse storage model, the air compression system model, the gas system model, the cogeneration unit model, and the coke dry quenching waste heat recovery model, wherein the energy includes electrical energy, heat energy, and oxygen energy;
wherein constraints of the material-energy characteristic model of the steel enterprise production process are as follows:
P
total
,
t
=
∑
j
=
1
G
j
,
t
·
P
j
⁢
∀
t
,
∀
j
∈
{
1
,
2
,
3
,
4
,
5
,
6
,
7
}
,
(
42
)
P
t
pv
+
P
t
chp
+
P
t
grid
+
P
t
cdq
=
P
ca
,
t
+
P
total
,
t
+
P
load
,
(
43
)
V
o
,
t
=
V
o
,
t
-
1
+
f
o
,
t
prod
-
∑
j
f
j
,
o
,
t
-
f
o
,
t
chp
,
(
44
)
Q
t
chp
=
∑
j
=
1
G
j
,
t
·
Q
j
+
H
load
⁢
∀
t
,
∀
j
∈
{
1
,
2
,
3
,
4
,
5
,
6
,
7
}
,
(
45
)
P
ca
,
t
·
ψ
ca
=
∑
j
=
1
G
j
,
t
·
A
j
⁢
∀
t
,
∀
j
∈
{
1
,
2
,
3
,
4
,
5
,
6
,
7
,
}
(
46
)
G
7
,
t
≤
F
sum
,
task
,
(
47
)
wherein Equations (42) and (43) are active power balance constraints;
Equation (44) is a gas energy balance constraint;
Equation (45) is a heat energy balance constraint;
Equation (46) is a compressed air energy balance constraint;
and Equation (47) is a total production task constraint;
Gj,t is an output of the production process j, wherein j∈{1,2,3,4,5,6,7};
Ptotal,t is a total production load of the process;
Pj is an unit production fixed load of the production process j∈{1,2,3,4,5,6,7};
P
t
vv
is a photovoltaic output power;
P
t
chp
is an output power of the cogeneration unit;
P
t
grid
is a power of electricity purchased from the higher grid;
Pload is a rest electrical load of enterprise operation;
Qj is thermal energy required for the production process j, j∈{1,2,3,4,5,6,7};
Hload is a rest thermal load of enterprise operation;
ψca is an efficiency of conversion of electrical energy into gas energy;
Aj is a unit gas consumption of the production process j, j∈{1,2,3,4,5,6,7};
Fsum,task is a total task volume of the processes;
step 5. constructing a carbon emission model of the steel enterprise, wherein the carbon emission model of the steel enterprise includes:
an indirect carbon emission model of purchased electricity consumption, a direct carbon emission model of coke consumption, a carbon emission model of a production process, and a carbon emission model of the by-product gas;
(1) constructing the indirect carbon emission model of the purchased electricity consumption:
E
carbon
grid
,
t
=
ρ
elec
,
t
⁢
P
t
grid
,
(
48
)
wherein
E
carbon
grid
,
t
is a carbon emission or purchased electricity;
ρelec,t is a carbon content coefficient of the purchased electricity;
(2) constructing the direct carbon emission model of the coke consumption:
E
carbon
coke
,
t
=
ρ
coke
⁢
F
t
coke
,
(
49
)
wherein
E
carbon
coke
,
t
is a carbon emission of coke;
ρcoke is a carbon content coefficient of the coke;
F
t
coke
is coke consumption;
(3) constructing the carbon emission model of the production process:
E
carbon
y
,
t
=
∑
j
=
1
⁢
G
j
,
t
·
ρ
j
⁢
∀
t
,
∀
j
∈
{
1
,
2
,
3
,
4
,
5
,
6
,
7
}
,
(
50
)
wherein
E
carbon
y
,
t
is a total carbon emission of the production process;
ρj is a fixed carbon emission coefficient of the production process j;
(4) constructing the carbon emission model of the by-product gas:
E
carbon
gas
,
t
=
∑
o
⁢
ρ
o
gas
(
∑
j
⁢
f
j
,
o
,
t
+
f
o
,
t
chp
)
-
∑
o
⁢
ρ
o
gas
⁢
f
o
,
t
prod
,
(
51
)
wherein
E
carbon
gas
,
t
is a carbon emission of the by-product gas;
ρ
o
gas
is a carbon content coefficient of the by-product gas;
(5) constructing a total carbon emission model of the steel enterprise:
E
carbon
total
,
t
=
E
carbon
grid
,
t
+
E
carbon
gas
,
t
+
E
carbon
coke
,
t
+
E
carbon
y
,
t
,
(
52
)
wherein
E
carbon
total
,
t
is a total carbon emission of the steel enterprise;
wherein the carbon emission coefficient used in the production process of the steel enterprise is set by referring to actual data from a real steel enterprise;
step 6:
constructing a material flow-energy flow-carbon emission flow coupling model of the steel enterprise, wherein the constructing a material flow-energy flow-carbon emission flow coupling model of the steel enterprise includes:
introducing the carbon emission model of the steel enterprise based on the material-energy characteristic model of the steel enterprise production process to construct the material flow-energy flow-carbon emission flow coupling model of the steel enterprise;
constructing an energy characteristic model based on the actual data from the steel enterprise;
converting heat demand of the steel enterprise production process to a thermodynamic limit energy consumption, which considers the energy that is consumed by a process of raw materials forming a product through a series of physicochemical reactions, containing heat of warming, heat of phase change, heat of reaction, heat of dissolution, and rolling deformation work;
constructing the energy flow-carbon emission flow coupling model of the steel enterprise by incorporating the carbon emission model;
performing the joint regulation of the energy flow and the carbon emission flow in response to a time-of-use tariff signal and a carbon price signal through the regulation of the material flow as well as starting and stopping of the electric arc furnace steel-making process;
and optimizing scheduling of the steel enterprise operation mode based on daily deliveries, weekly deliveries, monthly deliveries, quarterly deliveries, and yearly deliveries of the enterprise steel;
establishing an objective function, wherein the objective function is a function that optimizes an optimal operation mode of the joint regulation of the material flow, the energy flow, and the carbon emission flow in the steel enterprise;
an optimization object of the objective function is to minimize a sum of an electricity purchase cost from a superior grid, a park carbon emission cost, and a production raw material cost, and solving and obtaining the optimal operation mode of the joint regulation of the material flow, the energy flow, and the carbon emission flow in the steel enterprise to realize the joint regulation of the material flow, the energy flow, and the carbon emission flow in the steel enterprise;
wherein the park carbon emission cost is obtained by subtracting the total carbon emission of the steel enterprise from a free carbon emission allowance;
the free carbon emission allowance is preset cost free carbon emission;
the production raw material cost is a sum of the input raw material quantity of the coking process and an unit ton price of the coking coal, the input raw material quantity of the sintering process and an unit ton price of the sintering process, and the input raw material quantity of the electric arc furnace steel-making process and an unit ton price of the electric arc furnace steel-making process;
wherein the objective function is:
C
min
=
∑
t
P
t
grid
·
C
gird
,
t
⁢
∑
t
(
E
carbon
total
,
t
-
E
pei
,
t
)
·
C
carbon
+
∑
t
⁢
Y
1
,
t
·
C
ljm
+
∑
t
⁢
Y
2
,
t
·
C
tks
+
∑
t
⁢
Y
3
,
t
·
C
fg
,
(
53
)
wherein:
Cmin denotes a minimum sum of the electricity purchase cost from the superior grid, the park carbon emission cost, and the production raw material cost;
Cgird,t is a time-sharing electricity price, Epei,t is the free carbon emission allowance;
Ccarbon is a fixed carbon price;
Cljm is the unit ton price of the input raw material quantity Y1,t of the coking process, which is the unit ton price of the coking coal;
Ctks is the unit ton price of the input raw material quantity Y2,t of the sintering process, which is the unit ton price of the iron ore;
Cfg is the unit ton price of the input raw material quantity Y3,t of the electric arc furnace steel-making process, which is the unit ton price of a scrap steel;
optimizing scheduling in response to the time-of-use tariff signal and the carbon price signal and realizing the joint regulation of the material flow, the energy flow, and the carbon emission flow through regulating the material flow and the starting and stopping of the electric arc furnace steel-making process;
the method further comprising:
generating a plurality of candidate production plans;
wherein each of the candidate production plans refers to a production plan to be determined as a target production plan;
the target production plan refers to a production plan based on which the steel enterprise performs production;
and the production plan includes material flow parameters and process parameters for each of the production processes of the steel enterprise;
determining the target production plan based on the objective function and the plurality of candidate production plans;
wherein the determining the target production plan based on the objective function and the plurality of candidate production plans including:
substituting, based on the objective function and the plurality of candidate production plans, relevant parameters in the plurality of candidate production plans into the objective function in turn, and taking the candidate production plan whose objective function value satisfies a first screening condition as the target production plan;
wherein the first screening condition includes a minimum objective function value;
and the relevant parameters include the electricity purchase cost from the superior grid, the park carbon emission cost, and the production raw material cost;
controlling at least one of production equipment and conveying equipment to operate based on the target production plan, including:
controlling starting and stopping of the coke oven based on a starting time and a stopping time of the coke oven in the target production plan;
controlling starting and stopping of the electric arc furnace based on a starting time and a stopping time of the electric arc furnace in the target production plan;
controlling the air compressor to operate based on the gas storage volume of the gas storage tank and an out power of the air compressor in the target production plan;
controlling the conveying equipment to obtain the coking coal from a coking coal warehouse and add the coking coal to the coke oven based on an addition amount of the coking coal in the target production plan;
controlling the conveying equipment to obtain molten iron, produced by the blast furnace iron-making process, from the blast furnace and conveying the molten iron to the converter based on an addition amount of the molten iron in the target production plan;
wherein the at least one of production equipment include the coke oven, the electric arc furnace, the air compressor, the blast furnace, the conveying equipment and rolling equipment during the steel-rolling process;
wherein the conveying equipment refers to a device used to convey materials between the coking process, the sintering process, the pelletizing process, the blast furnace iron-making process, the converter steel-making process, the electric arc furnace steel-making process, and the steel-rolling process in the production processes of the steel enterprise;
and the conveying equipment includes a robotic arm and a conveyor belt;
and
controlling a power purchase module to obtain electricity from a grid based on energy allocation data in the target production plan.

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Joint regulation method of material flow, energy flow, and carbon emission flow in long-process iron and steel enterprises

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Joint regulation method of material flow, energy flow, and carbon emission flow in long-process iron and steel enterprises

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Abstract

Claims1