WO2024048214A1

WO2024048214A1 - Process control method, blast furnace operation method, molten pig iron production method, and process control apparatus

Info

Publication number: WO2024048214A1
Application number: PCT/JP2023/028830
Authority: WO
Inventors: 佳也橋本; 稜介益田; 玄弥大和; 健木津
Original assignee: Ｊｆｅスチール株式会社
Priority date: 2022-08-31
Filing date: 2023-08-07
Publication date: 2024-03-07

Abstract

Provided is a process control method, a blast furnace operation method, a molten pig iron production method, and a process control apparatus, which are for achieving suppression of variability in molten pig iron temperature while reducing a reduction material ratio in a blast furnace. This process control method comprises: a response prediction step for determining a predictive value of a future molten pig iron temperature by using a physical model with which it is possible to calculate the internal state of a blast furnace; and a manipulation degree determination step for determining the deviation between a target value and the predictive value of the molten pig iron temperature determined in the response prediction step, and determining the degrees by which a fine powdered coal ratio and a blown air moisture are to be manipulated, so as to minimize or maximize an evaluation function having a term corresponding to the deviation and a term for reducing a reduction material ratio or the blown air moisture.

Description

Process control method, blast furnace operating method, hot metal production method, and process control device

The present disclosure relates to a process control method, a blast furnace operating method, a hot metal manufacturing method, and a process control device.

Hot metal temperature (HMT) is an important management index in the blast furnace process in the steel industry, and is mainly controlled by adjusting the pulverized coal ratio and air humidity. In recent years, blast furnace operations have been carried out under conditions of low coke ratios and high pulverized coal ratios in order to pursue rationalization of raw material and fuel costs, and the furnace conditions tend to become unstable. Therefore, it is necessary to suppress variations in hot metal temperature.

In addition, the blast furnace process operates with solids filled, so the heat capacity of the entire process is large, and the time constant of response to action is long. Furthermore, it may take several hours, for example, for the raw material charged in the upper part of the furnace to descend to the lower part of the furnace. Therefore, in order to control the hot metal temperature, appropriate operations based on future furnace heat predictions are required.

In order to take into account the response delay resulting from the long time constant of the blast furnace, there is a method of controlling the blast furnace based on predictions using a physical model such as that disclosed in Patent Document 1, for example.

Japanese Patent Application Publication No. 11-335710

Here, due to recent social demands for CO ₂ reduction, reduction of the reducing agent ratio (total of coke ratio and pulverized coal ratio) is required in the blast furnace process. In order to reduce the reducing agent ratio, it is effective to reduce the amount of moisture blown into the furnace or reduce the heat loss of the furnace body so as not to consume excess heat source. However, in the blast furnace process, it is required to control the hot metal temperature and to maintain the pig iron production rate (hereinafter referred to as "pig iron making rate") near a target value. Therefore, the pulverized coal ratio and the air humidity tend to be controlled in a way that gives priority to reducing variations in hot metal temperature over reducing the reducing agent ratio. Further, Patent Document 1 discloses a technique for controlling only the hot metal temperature, and does not propose a control method that takes into consideration reducing the reducing agent ratio.

The purpose of the present disclosure, which has been made to solve the above problems, is to provide a process control method, a blast furnace operating method, a hot metal manufacturing method, and a process control method that suppress variation in hot metal temperature while reducing the reducing agent ratio in a blast furnace. The purpose is to provide a control device.

(1) A process control method according to an embodiment of the present disclosure includes:
a response prediction step of calculating a predicted value of the future hot metal temperature using a physical model capable of calculating the internal state of the blast furnace;
The deviation between the predicted value of the hot metal temperature obtained in the response prediction step and the target value is determined, and an evaluation function having a term corresponding to the deviation and a term for reducing the reducing agent ratio or the blast humidity is calculated. The method includes a step of determining a manipulated variable of the pulverized coal ratio and the blown moisture so as to minimize or maximize it.

(2) As an embodiment of the present disclosure, in (1),
The response prediction step uses the physical model to predict the future hot metal temperature based on a predicted value of the future hot metal temperature when the current manipulated variable is held and a predicted value of the hot metal temperature when the current manipulated variable is changed. A predicted value of the hot metal temperature is determined.

(3) As an embodiment of the present disclosure, in (1) or (2),
In the operation amount determining step, the evaluation function, which is a quadratic function regarding the unknown variables, is determined, using the operation amounts of the pulverized coal ratio and the blast moisture as unknown variables, and under the constraint of a linear expression regarding the unknown variables. is used to determine the unknown variable.

(4) As an embodiment of the present disclosure, in any one of (1) to (3),
The method further includes the step of manipulating the blowing flow rate so that the predicted value of the pig iron making speed matches the target value, and manipulating the coke ratio so that the predicted value of the air permeability becomes equal to or less than the upper limit.

(5) A blast furnace operating method according to an embodiment of the present disclosure includes:
Operating conditions are changed using the manipulated variables operated by the process control method of any one of (1) to (4).

(6) The method for producing hot metal according to an embodiment of the present disclosure includes:
Hot metal is produced using the blast furnace operated by the blast furnace operating method of (5).

(7) A process control device according to an embodiment of the present disclosure includes:
a storage unit that stores a physical model capable of calculating the internal state of the blast furnace;
A hot metal temperature control unit that obtains a target hot metal temperature that is a target value of hot metal temperature and calculates the manipulated variables of the pulverized coal ratio and the air humidity so that the hot metal temperature becomes the target hot metal temperature,
The hot metal temperature control section is
Using the physical model to obtain a predicted value of the future hot metal temperature,
The deviation between the predicted value and the target value of the hot metal temperature is determined so that an evaluation function having a term corresponding to the deviation and a term for reducing the reducing agent ratio or the blast moisture is minimized or maximized. , find the manipulated variables of the pulverized coal ratio and the air humidity.

According to the present disclosure, it is possible to provide a process control method, a blast furnace operating method, a hot metal manufacturing method, and a process control device that realize suppression of hot metal temperature variations while reducing the reducing agent ratio in a blast furnace.

FIG. 1 is a diagram showing manipulated variables and control variables in a blast furnace process. FIG. 2 is a diagram illustrating a process control method according to an embodiment of the present disclosure. FIG. 3 is a diagram showing input/output information of a physical model used in the present disclosure. FIG. 4 is a diagram showing the results of a control simulation based on simultaneous manipulation of the pulverized coal ratio and the air humidity. FIG. 5 is a diagram showing the results of a control simulation using only the pulverized coal ratio (comparative example). FIG. 6 is a diagram for explaining the effect of reducing the reducing agent ratio (RAR). FIG. 7 is a diagram illustrating a configuration example of a process control device according to an embodiment of the present disclosure.

Hereinafter, a process control method, a blast furnace operating method, a hot metal manufacturing method, and a process control device according to an embodiment of the present disclosure will be described with reference to the drawings.

Figure 1 shows the basic operating variables and control variables in the blast furnace process (steps in blast furnace operation). A control variable is a variable that must be controlled in operation, but cannot be or is difficult to manipulate directly, and is changed through a correlated manipulated variable. In the operation of a blast furnace, the pulverized coal ratio or the air humidity is mainly manipulated in order to set the hot metal temperature to a target value. In order to maintain good air permeability (air permeability) of the blast furnace, the coke ratio or the air flow rate is mainly controlled. Moreover, in order to set the pig iron making speed to the target value, the air flow rate is mainly manipulated. Here, as the air permeability, in this embodiment, the pressure loss in the furnace, which directly affects the blow-through, is used. Furnace pressure loss is the difference between blast pressure and furnace top pressure (furnace top pressure). In addition to the pressure drop in the furnace, there are various indicators of ventilation, such as ventilation resistance and shaft-to-face differential pressure. Therefore, as the air permeability, another air permeability index may be used instead of the furnace pressure drop, or a combination of a plurality of air permeability indices may be used. The process control method according to the present embodiment focuses on the pulverized coal ratio and the air humidity, which are operational variables for controlling the hot metal temperature, and controls the pulverized coal ratio and air humidity to reduce the reducing agent ratio while controlling the hot metal temperature. Determine the optimal operating amount of ratio and air humidity.

FIG. 2 is a diagram showing the processing of the process control method according to the present embodiment. The process control method according to the present embodiment uses, for example, cascade control described in Reference Document 1 (Japanese Patent No. 7107444). In the cascade control, control for calculating the target pulverized coal ratio (PCR) (hot metal temperature control in Figure 2) and control for calculating the pulverized coal flow rate required for the target PCR (PCR follow-up control in Figure 2) are performed. It is done continuously. Hot metal temperature control can obtain a target hot metal temperature, which is a target value of hot metal temperature (HMT), and calculate a target PCR using a physical model described below. Moreover, the hot metal temperature control not only calculates the target PCR (in addition to calculating the manipulated variable of the pulverized coal ratio), but also calculates the manipulated variable of the air humidity.

The process control method according to the present embodiment also includes iron making speed control and air permeability control. In pig iron making speed control, a target pig iron making speed which is a target value of pig iron making rate (Production rate: Prod) is acquired, and a manipulated variable of a blowing flow rate (BV) is calculated using a physical model described below. The air permeability control obtains the upper limit of the furnace pressure drop (ΔP), and calculates the manipulated variables of the air flow rate and coke ratio using a physical model to be described later. Here, the actual value (which may be an observed value or a calculated value) in a plant including a blast furnace may be fed back for updating the physical model used in each control. In the example in Figure 2, the actual values of pulverized coal ratio (PCR), hot metal temperature (HMT), pressure drop in the furnace (ΔP), and iron making rate (Prod) are expressed as actual PCR, actual HMT, actual ΔP, and actual Prod, respectively. It is shown. Furthermore, the correspondence between control variables and correlated manipulated variables in the blast furnace process is not limited to that shown in FIGS. 1 and 2. For example, in pig iron making speed control, it is possible to manipulate the blown oxygen flow rate instead of the blown air flow rate.

In this embodiment, in constructing a multivariable control system as shown in FIG. 2, an individual controller (hot metal temperature control , air permeability control, pig iron making speed control). The hot metal temperature is controlled by a cascade control that manipulates the blast moisture and the pulverized coal ratio (PCR) and pulverized coal flow rate. Air permeability is controlled by manipulating the air flow rate and coke ratio. The pig iron making speed is controlled by manipulating the air flow rate. Here, for example, when the blast flow rate is manipulated in pig iron making speed control, a change in the blast flow rate affects the hot metal temperature. This effect is reflected by the physical model in hot metal temperature control and calculated as the manipulated variable of the pulverized coal ratio or blast moisture. is maintained near the target value. In this embodiment, although individual controllers are constructed as described above, it is possible to realize control that takes into account the interference between the respective manipulated variables. In other words, for example, hot metal temperature control and pig iron making speed control interfere, but the control system is constructed as a control system that has a disturbance removal characteristic that absorbs fluctuations caused by the manipulation of the other's manipulated variables by manipulating its own manipulated variables. can reduce the impact of The same applies to air permeability control.

In the process control method according to the present embodiment, a physical model of a blast furnace based on reaction kinetics is used to predict the future hot metal temperature and iron making rate, and fine powder is adjusted so that the predicted values are close to the target values. Determine the amount of change in coal ratio and air humidity. By using a quadratic programming method that minimizes an evaluation function that takes the reducing agent ratio into consideration when determining the manipulated variable, it is possible to both reduce the reducing agent ratio and suppress variations in hot metal temperature. The outline of the processing flow in the process control method according to the present embodiment is as shown in steps 1 to 3 below.

First, in step 1, the future hot metal temperature is predicted using a physical model. Step 1 is a response prediction step. The response prediction step uses a physical model to predict the future hot metal temperature based on the predicted value of the future hot metal temperature when the current manipulated variable is held and the predicted value of the hot metal temperature when the current manipulated variable is changed. Find the predicted value of the hot metal temperature. The predicted value of future hot metal temperature if the current manipulated variables are held is a free response described below. The predicted value of the hot metal temperature when the current operating variable is changed is a step response described later in this embodiment, but is not limited to this.

Next, in step 2, the manipulated variables are manipulated using quadratic programming so that the predicted value of the hot metal temperature in step 1 matches the target value and the reducing agent ratio is minimized. . Step 2 is a manipulated variable determination step in which the deviation between the predicted value and the target value is determined, the manipulated variable for eliminating the deviation is determined, and the manipulated variable is adjusted. In this embodiment, the manipulated variables are pulverized coal ratio and blast moisture.

In addition, in step 3, in order to simulate the actual operation of a blast furnace, the blast flow rate is controlled so that the predicted value of iron making rate matches the target value, and at least the coke ratio is adjusted so that the predicted value of air permeability is below the upper limit. may be operated. In this embodiment, the air permeability is the pressure loss in the furnace, and when the predicted value of the pressure loss in the furnace exceeds a set upper limit, the ventilation state is determined to be abnormal. When the ventilation condition is determined to be abnormal, an operation to increase the coke ratio may be performed. When it is determined that the ventilation condition is not abnormal, that is, when the predicted value of the pressure drop in the furnace is less than or equal to the upper limit, an operation to reduce the coke ratio may be performed. The manipulation of the air flow rate and coke ratio in step 3 becomes a disturbance to the hot metal temperature control. As will be described later, it was verified through simulation that the influence of this disturbance could be canceled by manipulating the pulverized coal ratio and the air humidity.

The physical model used in the present disclosure is similar to the model of the method described in Reference 2 (Michiharu Hadano et al., "Study of burning operation using an unsteady blast furnace model", Tetsu-to-Hagane, vol. 68, p. 2369). It is. In other words, it calculates the state inside the blast furnace (furnace) in an unsteady state, which is composed of a group of partial differential equations that take into account physical phenomena such as reduction of ore, heat exchange between ore and coke, and melting of ore. A possible physical model is used. This physical model may be referred to as an unsteady model below.

As shown in Figure 3, among the input variables given to the unsteady model, the main ones that change over time are blast flow rate, blast oxygen flow rate, pulverized coal flow rate, blast moisture, blast temperature, coke ratio, and furnace top pressure. It is. These input variables are operating variables or operating factors of the blast furnace. The blast flow rate, the blast oxygen flow rate, and the pulverized coal flow rate are the flow rates of air, oxygen, and pulverized coal sent to the blast furnace, respectively. The blast humidity is the humidity of the air sent to the blast furnace. The blowing temperature is the temperature of the air sent to the blast furnace. The coke ratio is the coke ratio at the top of the furnace, and is the weight of coke used for one ton of hot metal production.

In addition, the main output variables of the unsteady model are gas utilization rate, solution loss carbon amount (sol loss carbon amount), reducing agent ratio, pig iron making rate, hot metal temperature, and furnace pressure drop. Using the unsteady model, it is possible to calculate the ever-changing hot metal temperature, iron making rate, and furnace pressure drop. Although the time interval of calculation is not particularly limited, it is 30 minutes in this embodiment. In this embodiment, the time difference between "t+1" and "t" in the unsteady model equation described later is 30 minutes.

The unsteady model can be expressed by the following equations (1) and (2).

Here x(t) is a state variable calculated within the unsteady model. State variables include, for example, coke temperature, iron temperature, ore oxidation degree, and raw material fall rate. y(t) is the control variables: hot metal temperature, pig iron making rate, and air permeability (furnace pressure drop). u(t) is the input variable described above, and is a variable that can be operated by the operator who operates the blast furnace. In other words, the input variables are blast flow rate BV (t), blast oxygen flow rate BVO (t), pulverized coal flow rate PCI (t), blast moisture BM (t), blast temperature BT (t), and coke ratio CR (t). , the furnace top pressure TGP(t). It can be expressed as u(t)=(BV(t), BVO(t), PCI(t), BM(t), BT(t), CR(t), TGP(t)) ^T .

First, a predictive calculation of future control variables is performed assuming that the current values of input variables are kept constant. Setting the current time step t ₀ to 0, future control variables are predicted using equations (3) and (4) below. The response y _f (t) of the control variable determined in this way is called a free response.

Below, a method for determining the current and future manipulated variables of pulverized coal ratio (PCR) and blast moisture (BM) will be described. An example of predicting the future two hours later will be explained. By introducing unknown variables θ=(ΔPCR ₀ , ΔBM ₀ , ΔPCR ₁ , ΔBM ₁ ), the manipulated variables of the pulverized coal ratio (PCR) and the blast moisture (BM) are determined by quadratic programming. The subscript 0 indicates the current state. Moreover, the subscript 1 indicates 2 hours later.

As a premise of predictive control using this physical model, it may be assumed that the future hot metal temperature can be approximated by superposing the response y _f (t), which is a free response, and the step response. y _pre (t), which is a predicted value of hot metal temperature every 2 hours up to 10 hours ahead, is expressed by the following equation (5).

Here, S _PCR (t) is the amount of change in hot metal temperature when the pulverized coal ratio (PCR) is manipulated by a unit amount (1 [kg/t]). Further, S _BM (t) is the amount of change in the blown air moisture (BM) when the blown air moisture (BM) is manipulated by a unit amount (1 [g/Nm ³ ]). S _PCR and S _BM can be determined by, for example, another physical model or a step response test in actual operation. In the calculations in this disclosure, reference 3 (Y. Hashimoto, Online prediction of hot metal temperature using transient model and moving horizon estimation. ISIJ The simulation results described in Int. 2019, vol. 59, p. 1534) were used. .

In the following, when formula (5) is expressed as formula (6) below using step response matrix S, the deviation between the predicted value of hot metal temperature and the target value y _pre (t) is as shown in formula (7). Become.

Here, the deviation of the free response y _f (t) from the target value y _pre (t) is defined as δy. The square of the deviation between the predicted value of the hot metal temperature and the target value y _pre (t) is expressed by the following equation (8).

In order to both reduce the variation in hot metal temperature and minimize the reducing agent ratio, the evaluation function J used in the quadratic programming method is set to the first and second terms of equation (8), as shown in equation (9). In addition, it includes a term (third term) for reducing air humidity. Furthermore, the evaluation function J includes a fourth term for suppressing excessive operation.

Here, a and R are coefficients. When comparing the responsiveness of hot metal temperature to changes in pulverized coal ratio (PCR) and blast moisture (BM), it is known that blast moisture has a faster response. However, in order to secure an operable range in the increasing direction and the decreasing direction so that the blown air humidity can be increased or decreased, it is necessary to increase the average value of the blown air humidity. When the average value of the air humidity is increased, heat absorption occurs due to the steam decomposition reaction of the air humidity, and a problem arises in that a large amount of reducing agent must be added to compensate for the decrease in heat due to heat absorption. Therefore, in order to limit the manipulated amount of air humidity, the third term is introduced, and the weighting of ΔPCR and ΔBM included in the vector θ is changed depending on the size of the elements of the coefficient vector a, and the manipulation of both Distribution can be adjusted.

Furthermore, θ is determined using equation (9) under the constraints of equations (10) to (13) below.

Here, the subscript i in equations (10) to (13) is 0 or 1. Moreover, the subscript "now" means the current value of pulverized coal ratio (PCR) or blast moisture (BM). PCR _max and PCR _min are the upper and lower limits of the target range of the pulverized coal ratio (PCR), respectively. ΔPCR _max is the upper limit of the allowable change in the pulverized coal ratio (PCR). BM _max and BM _min are the upper and lower limits of the target range of the blast moisture (BM), respectively. ΔBM _max is the upper limit of the allowable change amount of the air humidity (BM). Using quadratic programming to minimize the evaluation function J, which is a quadratic function regarding the unknown variable θ, under the constraint conditions of the linear expression regarding the unknown variable θ shown in equations (10) to (13). An unknown variable θ is determined. Control for determining the unknown variable θ using equation (9) corresponds to the hot metal temperature control in FIG. 2.

Here, in this embodiment, the evaluation function J was designed to reduce the air humidity in order to reduce the reducing agent ratio. However, for example, by giving a penalty to an increase in the pulverized coal ratio, A similar effect can be obtained by using an evaluation function J that reduces . In addition, in this embodiment, the unknown variable θ was obtained when the evaluation function J is minimized, but the deviation between the predicted value of the hot metal temperature and the target value, the minimizing of the reducing agent ratio (or the air humidity), and the evaluation The evaluation function J may be designed so that it corresponds to the maximization of the function J. That is, the manipulated variables of the pulverized coal ratio and the air humidity may be determined so that the evaluation function J is minimized or maximized. Furthermore, in the evaluation function J, a quasi-optimal value may be evaluated as an optimal value. In other words, even if the evaluation function J does not necessarily take the maximum or minimum value, as long as the value of the evaluation function J is near the maximum value or near the minimum value (if semi-optimization is performed), the control objective is achieved. You can treat it if you do. Therefore, the evaluation function J is minimized or maximized not only when the value of the evaluation function J is the maximum value or the minimum value, but also when the value of the evaluation function J is near the maximum value or near the minimum value. It may be possible to include cases.

In order to verify the effect of reducing the reducing agent ratio by the present disclosure through simulation under operating conditions close to actual operations, the following method was used to change the manipulated variables ( The blast flow rate and coke ratio) are controlled.

Regarding the pig iron making speed, ΔBV, which is the manipulated variable of the blast flow rate (BV) [Nm ³ /min], is determined by the following equation (14) so as to eliminate the deviation between the target value and the predicted value.

Here, Prod (t+T) is a predicted value of the iron making speed T steps ahead. As an example, T may be 4, which means a predicted value for 2 hours (30 minutes x 4) ahead. Prod _ref is the target iron making speed (target value of the iron making speed). Further, S _BV is the amount of change in the iron making speed when the blowing flow rate (BV) is manipulated by a unit amount (1 [Nm ³ /min]). The _SBV can be determined using another physical model or a step response test in actual operation. Moreover, b is a coefficient and is a positive number. The control for determining ΔBV according to equation (14) corresponds to the iron making speed control in FIG. 2.

Furthermore, with respect to the pressure drop in the furnace (ΔP), the manipulated variables of the coke ratio (CR) and the blowing flow rate (BV) are determined by comparison with the upper limit (threshold). When the pressure drop (ΔP) in the furnace exceeds the upper limit, the manipulated variable is determined so as to increase the coke ratio and simultaneously decrease the blowing flow rate. This corresponds to the operation of stabilizing the unloading of raw materials in the operation of a blast furnace. Moreover, when the pressure drop in the furnace is below the upper limit, the manipulated variable is determined so as to gradually reduce the coke ratio. In principle, control is performed so that the pressure loss in the furnace does not exceed the upper limit, but when the pressure loss in the furnace is below the upper limit, it becomes possible to reduce the cost of operation by gradually reducing the coke ratio. When such control is performed, the value of the pressure drop in the furnace changes near the upper limit. Control that determines the manipulated variables of the coke ratio (CR) and the blowing flow rate (BV) by comparison with the upper limit of the pressure drop in the furnace corresponds to the air permeability control in FIG. 2 .

FIG. 4 is a diagram showing simulation results based on the above process control. In other words, in the simulation shown in Fig. 4, the blast moisture (BM) is , pulverized coal ratio (PCR), blast flow rate (BV), and coke ratio (CR) were manipulated. The target hot metal temperature was 1500°C. The target pig iron making speed was 7 [t/min]. Further, the upper limit of the pressure drop in the furnace was 100 [kPa].

As shown in Figure 4, the hot metal temperature (HMT) is operated near the target value, and based on the evaluation function J shown in equation (9), the blast moisture (BM) is controlled while suppressing the variation in the hot metal temperature. It can be seen that the value is maintained near the lower limit value. When the air humidity is close to the lower limit value, heat absorption due to the steam decomposition reaction that requires the introduction of a reducing agent is less likely to occur, leading to a reduction in the reducing agent ratio. Further, the iron making rate (Prod) is controlled near the target value, and the pressure loss in the furnace (ΔP) is also kept below the upper limit.

For comparative verification, a simulation was performed for a comparative example in which only the pulverized coal ratio (PCR) was manipulated and the blast moisture (BM) was not manipulated. FIG. 5 is a diagram showing simulation results obtained by control of a comparative example. In the simulation shown in Fig. 5, the pulverized coal ratio (PCR) is , the blast flow rate (BV) and coke ratio (CR) were manipulated. The simulation conditions are the same as in FIG. 4 except for the blast moisture (BM). The air humidity was set at a constant value of 15.5 [g/Nm ³ ].

FIG. 6 is a diagram for explaining the effect of reducing the reducing agent ratio (RAR), and shows the reducing agent ratio of the simulation results of FIG. 4 (process control method according to the present embodiment) and FIG. 5 (comparative example). This is a comparison of changes over time. As shown in FIG. 6, the average value of the reducing agent ratio in the process control method according to the present embodiment is lower than the average value of the reducing agent ratio in the comparative example. It has been shown that the reducing agent ratio can be reduced by simultaneously controlling the pulverized coal ratio and the air humidity. By reducing the reducing agent ratio, the amount of oxygen (oxygen basic unit) [Nm ³ /t] required to be blown from the tuyere to produce 1 ton of hot metal is reduced. Therefore, the target iron making speed can be reached with a smaller air flow rate. As a result, there is a margin for pressure loss, and the coke ratio can also be reduced (see CR in Figures 3 and 4).

FIG. 7 is a diagram illustrating a configuration example of a process control device 10 according to an embodiment. As shown in FIG. 7, the process control device 10 according to the present embodiment includes a communication section 11, a storage section 12, and a control section 13. The control section 13 includes a hot metal temperature control section 14, an iron making speed control section 15, an air permeability control section 16, and a PCR follow-up control section 17. The process control device 10 executes the process control method described above. Here, the process control device 10 may display information such as the operation amount on a display unit such as a liquid crystal display when operating the blown humidity, the blown air flow rate, the coke ratio, or the pulverized coal ratio.

The communication unit 11 is configured to include a communication module for communicating with the host system. The host system includes a process computer that manages processes in the plant including the blast furnace. The communication unit 11 may include a communication module compatible with mobile communication standards such as 4G (4th Generation) and 5G (5th Generation). The communication unit 11 may include, for example, a communication module compatible with wired or wireless LAN standards. The control unit 13 can obtain information such as a target hot metal temperature, a target iron making rate, and an upper limit of pressure drop in the furnace from the host system via the communication unit 11. Further, the control unit 13 can output information on the manipulated variables that have been operated, that is, the manipulated variables that reflect the calculated manipulated variables, to the host system via the communication unit 11.

The storage unit 12 stores the above physical model. The storage unit 12 also stores programs and data related to control of the blast furnace process. The storage unit 12 may include any storage device such as a semiconductor storage device, an optical storage device, and a magnetic storage device. A semiconductor storage device may include, for example, a semiconductor memory. The storage unit 12 may include multiple types of storage devices.

The control unit 13 controls and manages each functional unit constituting the process control device 10 and the entire process control device 10. The control unit 13 may also acquire data used for control. That is, the control unit 13 may acquire the hot metal temperature, iron making rate, and air permeability of the blast furnace using observed values or calculated values. The control unit 13 is configured to include at least one processor such as a CPU (Central Processing Unit) to control and manage various functions. The control unit 13 may be composed of one processor or a plurality of processors. The processor that constitutes the control section 13 functions as a hot metal temperature control section 14, an ironmaking speed control section 15, an air permeability control section 16, and a PCR follow-up control section 17 by reading out and executing a program from the storage section 12. It's fine.

The hot metal temperature control unit 14 obtains a target hot metal temperature, which is a target value of the hot metal temperature, and calculates the manipulated variables of the blast moisture and pulverized coal ratio so that the hot metal temperature becomes the target hot metal temperature. The hot metal temperature control section 14 is a functional section that executes "hot metal temperature control" in FIG. 2.

The pig iron making speed control unit 15 obtains a target pig iron making speed which is a target value of the pig iron making speed, and calculates the manipulated variable of the air blowing flow rate so that the pig iron making speed becomes the target pig iron making speed. The pig iron making speed control section 15 is a functional section that executes the "pig making speed control" shown in FIG. 2 .

The air permeability control unit 16 obtains the upper limit of the air permeability (in the present embodiment, the pressure loss in the furnace) and calculates at least the manipulated variable of the coke ratio so that the air permeability does not exceed the upper limit. The air permeability control unit 16 may further calculate the manipulated variable of the air flow rate as in this embodiment. The air permeability control section 16 is a functional section that executes the "air permeability control" shown in FIG.

The PCR follow-up control unit 17 acquires the pulverized coal ratio (target PCR), which is a target value determined by the hot metal temperature control unit 14, and controls the pulverized coal flow rate (PCI) to follow the target PCR by PCR follow-up control. Calculate the amount of operation. The PCR follow-up control section 17 is a functional section that executes "PCR follow-up control" in FIG.

The hot metal temperature control section 14, pig iron making speed control section 15, and air permeability control section 16 are individual controllers for controlling the hot metal temperature (HMT), pig iron making speed (Prod), and furnace pressure drop (ΔP), respectively. . To explain using steps 1 to 3 above, the hot metal temperature control unit 14 executes step 1 (response prediction step) using a physical model to obtain a predicted value of the hot metal temperature. The hot metal temperature control unit 14 executes step 2 (operation amount determination step) to determine the operation amounts of the pulverized coal ratio and the blast moisture. The pig iron making speed control unit 15 executes step 3 and obtains the manipulated variable of the air flow rate so as to eliminate the deviation between the target value and the predicted value of the pig iron making speed. Furthermore, the air permeability control unit 16 executes step 3 to determine the manipulated variables of the air flow rate and coke ratio so that the predicted value of the pressure loss in the furnace does not exceed the upper limit. Here, as described above, the hot metal temperature control section 14, pig iron making speed control section 15, and air permeability control section 16, which are constructed as individual controllers, automatically control fluctuations based on the manipulation of operating variables by other control sections. This is a control system that has a disturbance removal characteristic that absorbs by manipulating the manipulated variables. Therefore, the hot metal temperature control section 14, pig iron making speed control section 15, and air permeability control section 16 can reduce the influence of interference of operating variables from other control sections.

A process control method executed by the process control device 10 may be used as part of the blast furnace operating method. For example, the manipulated variables manipulated in the process control method described above may be used to change operating conditions in the operation of a blast furnace. Moreover, such a method of operating a blast furnace can be carried out as part of a manufacturing method of manufacturing hot metal. In a blast furnace, raw material iron ore is melted and reduced to become pig iron, which is tapped as hot metal, and the blast furnace may be operated according to this operating method.

The process control device 10 may be realized, for example, by a computer separate from the process computer that controls the operation of the blast furnace, or may be realized by the process computer. A computer includes, for example, a memory, a hard disk drive (storage device), a CPU (processing unit), and a display device such as a display. Various functions can be realized by organically cooperating hardware such as a CPU and memory with a program. The storage unit 12 may be realized, for example, by a storage device. The control unit 13 may be realized by, for example, a CPU.

As described above, the process control method, blast furnace operating method, hot metal manufacturing method, and process control device 10 according to the present embodiment reduce the reducing agent ratio in the blast furnace while reducing the variation in hot metal temperature. suppression can be achieved.

Although the embodiments according to the present disclosure have been described based on the drawings and examples, it should be noted that those skilled in the art can easily make various changes or modifications based on the present disclosure. It should therefore be noted that these variations or modifications are included within the scope of this disclosure. For example, the functions included in each component or each step can be rearranged to avoid logical contradictions, and multiple components or steps can be combined or divided into one. It is. Embodiments according to the present disclosure can also be realized as a program executed by a processor included in the device or a storage medium recording the program. It is to be understood that these are also encompassed within the scope of the present disclosure.

The configuration of the process control device 10 shown in FIG. 7 is an example. The process control device 10 may not include all of the components shown in FIG. Further, the process control device 10 may include components other than those shown in FIG. For example, the process control device 10 may further include a display section.

10 Process control device 11 Communication section 12 Storage section 13 Control section 14 Hot metal temperature control section 15 Iron making speed control section 16 Air permeability control section 17 PCR follow-up control section

Claims

a response prediction step of calculating a predicted value of the future hot metal temperature using a physical model capable of calculating the internal state of the blast furnace;
The deviation between the predicted value of the hot metal temperature obtained in the response prediction step and the target value is determined, and an evaluation function having a term corresponding to the deviation and a term for reducing the reducing agent ratio or the blast humidity is calculated. A method for controlling a process, comprising: determining a manipulated variable for a pulverized coal ratio and a blown moisture so as to minimize or maximize it.
The response prediction step uses the physical model to predict the future hot metal temperature based on a predicted value of the future hot metal temperature when the current manipulated variable is held and a predicted value of the hot metal temperature when the current manipulated variable is changed. 2. The process control method according to claim 1, further comprising determining a predicted value of the hot metal temperature.
In the operation amount determining step, the evaluation function, which is a quadratic function regarding the unknown variables, is determined, using the operation amounts of the pulverized coal ratio and the blast moisture as unknown variables, and under the constraint of a linear expression regarding the unknown variables. The method for controlling a process according to claim 1 or 2, wherein the unknown variable is determined by using the unknown variable.
Any one of claims 1 to 3, further comprising the step of manipulating the air flow rate so that the predicted value of pig iron making speed matches the target value, and manipulating the coke ratio so that the predicted value of air permeability is below the upper limit. A method for controlling the process described in item 1.
A method for operating a blast furnace, comprising changing operating conditions using manipulated variables operated by the process control method according to any one of claims 1 to 4.
A method for producing hot metal, comprising producing hot metal using the blast furnace operated by the blast furnace operating method according to claim 5.
a storage unit that stores a physical model capable of calculating the internal state of the blast furnace;
A hot metal temperature control unit that acquires a target hot metal temperature that is a target value of hot metal temperature and calculates the manipulated variables of the pulverized coal ratio and the air humidity so that the hot metal temperature becomes the target hot metal temperature,
The hot metal temperature control section is
Using the physical model to obtain a predicted value of the future hot metal temperature,
The deviation between the predicted value and the target value of the hot metal temperature is determined so that an evaluation function having a term corresponding to the deviation and a term for reducing the reducing agent ratio or the blast humidity is minimized or maximized. , a process control device that determines the manipulated variables of pulverized coal ratio and air humidity.