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

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

Technical Field

[0001] The present disclosure relates to a process control method, a blast furnace operation method, a hot metal manufacturing method, and a process control device.

Background Art

[0002] In the blast furnace process in the iron and steel industry, the hot metal temperature (HMT) is an important management index and is mainly controlled by adjusting the pulverized coal ratio and the blast moisture. In recent years, blast furnace operations have been carried out under conditions of low coke ratio and high pulverized coal ratio in order to pursue rationalization of raw material costs, and the furnace conditions are likely to become unstable. Therefore, it is necessary to suppress variations in the hot metal temperature.

[0003] In addition, the blast furnace process has the characteristics that since the operation is carried out with a solid filled state, the heat capacity of the entire process is large, and the time constant of the response to an action is long. Further, it may take, for example, several hours for the raw materials charged at the upper part of the furnace to descend to the lower part of the furnace. Therefore, for controlling the hot metal temperature, appropriate operations based on future furnace heat prediction are necessary.

[0004] In order to consider the delay in response resulting from the long time constant of the blast furnace, as a method of controlling the blast furnace based on prediction, there is one that uses a physical model such as Patent Document 1.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] Here, in recent years, CO 2Due to social demands for reduction, in the blast furnace process, reduction material ratio (total of coke ratio and pulverized coal ratio) reduction is required. To reduce the reduction material ratio, it is effective to consume surplus heat sources by reducing the blast moisture blown into the furnace or reducing the furnace body heat loss. However, in the blast furnace process, it is required to control the molten iron temperature and keep the production rate of pig iron (hereinafter referred to as "pig iron production rate") near the target value. Therefore, operations of pulverized coal ratio and blast moisture are often carried out with priority given to reducing the variation in molten iron temperature rather than reducing the reduction material ratio. Further, Patent Document 1 discloses a technique for controlling only the molten iron temperature and does not propose a control method considering reduction of the reduction material ratio.

[0007] An object of the present disclosure made to solve the above problems is to provide a process control method, a blast furnace operation method, a molten iron manufacturing method, and a process control device that can reduce the reduction material ratio in a blast furnace and suppress variation in molten iron temperature.

Means for Solving the Problems

[0008] (1) A process control method according to an embodiment of the present disclosure includes: a response prediction step of obtaining a predicted value of future molten iron temperature using a physical model capable of calculating the internal state of a blast furnace; and an operation amount determination step of obtaining a deviation between the predicted value of the molten iron temperature obtained in the response prediction step and a target value, and obtaining operation amounts of pulverized coal ratio and blast moisture so that an evaluation function having a term corresponding to the deviation and a term for reducing the reduction material ratio or blast moisture is minimized or maximized.

[0009] (2) As an embodiment of the present disclosure, in (1), the response prediction step obtains the predicted value of the future molten iron temperature based on the predicted value of the future molten iron temperature when the current operation variables are maintained using the physical model and the predicted value of the molten iron temperature when the current operation variables are changed.

[0010] (3) As an embodiment of the present disclosure, in (1) or (2), In the operation amount determination step, the operation amounts of the pulverized coal ratio and the blast moisture to be obtained are used as unknown variables, and the evaluation function, which is a quadratic function with respect to the unknown variables, is used under the constraint conditions of a linear equation with respect to the unknown variables to determine the unknown variables.

[0011] (4) As one embodiment of the present disclosure, in any one of (1) to (3), further includes a step of operating the blast flow rate so that the predicted value of the casting and milling speed matches the target value, and operating the coke ratio so that the predicted value of the air permeability is equal to or less than the upper limit.

[0012] (5) The operation method of the blast furnace according to one embodiment of the present disclosure is changing the operation conditions by using the operation variables operated by the control method of any one of the processes (1) to (4).

[0013] (6) The method for producing hot metal according to one embodiment of the present disclosure is producing hot metal by using the blast furnace operated by the operation method of the blast furnace in (5).

[0014] (7) The process control device according to one embodiment of the present disclosure is 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 the target value of the hot metal temperature, and calculates the operation amounts of the pulverized coal ratio and the blast moisture so that the hot metal temperature becomes the target hot metal temperature, the hot metal temperature control unit obtains a predicted value of the future hot metal temperature using the physical model, obtains the deviation between the predicted value and the target value of the hot metal temperature, and obtains the operation amounts of the pulverized coal ratio and the blast moisture so that an evaluation function having a term corresponding to the deviation and a term for reducing the reductant ratio or the blast moisture is minimized or maximized.

Advantages of the Invention

[0015] According to the present disclosure, it is possible to provide a process control method, a blast furnace operation method, a hot metal production method, and a process control device that can suppress variations in hot metal temperature while reducing the ratio of reducing agents in a blast furnace.

Brief Description of the Drawings

[0016]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Embodiments for Carrying Out the Invention

[0017] Hereinafter, a process control method, a blast furnace operation method, a hot metal production method, and a process control device according to an embodiment of the present disclosure will be described with reference to the drawings.

[0018] Figure 1 shows the basic operating variables and control variables in the blast furnace process (the processes in the operation of the blast furnace). The control variables are variables that should be controlled in the operation, but are variables that cannot be directly operated or are difficult to directly operate, and are changed through related operating variables. In the operation of the blast furnace, in order to make the hot metal temperature the target value, mainly the pulverized coal ratio or the blast moisture is operated. In order to keep the air permeability (air permeability) of the blast furnace good, mainly the coke ratio or the blast flow rate is operated. Also, in order to make the pig iron production rate the target value, mainly the blast flow rate is operated. Here, as the air permeability, in this embodiment, the in-furnace pressure loss that directly affects the blow-through is used. The in-furnace pressure loss is the difference between the blast pressure and the top pressure (the pressure at the top of the furnace). In addition to the in-furnace pressure loss, there are various air permeability indicators such as the air resistance and the differential pressure between the opposite shafts. Therefore, as the air permeability, another air permeability indicator may be used instead of the in-furnace pressure loss, or a combination of multiple air permeability indicators may be used. In the process control method according to this embodiment, paying attention to the pulverized coal ratio and the blast moisture which are operating variables for controlling the hot metal temperature, the optimal operating amounts of the pulverized coal ratio and the blast moisture are determined so as to reduce the reducing agent ratio while controlling the hot metal temperature.

[0019] Figure 2 is a diagram showing the processing of the process control method according to this embodiment. In the process control method according to this embodiment, for example, the cascade control described in Reference 1 (Japanese Patent No. 7107444) is used. In cascade control, the control for calculating the target pulverized coal ratio (PCR) (hot metal temperature control in Figure 2) and the control for calculating the pulverized coal flow rate required for the target PCR (PCR tracking control in Figure 2) are continuously performed. The hot metal temperature control can obtain the target hot metal temperature which is the target value of the hot metal temperature (HMT), and calculate the target PCR using the physical model described later. Also, the hot metal temperature control not only calculates the target PCR (not only obtains the operating amount of the pulverized coal ratio), but also calculates the operating amount of the blast moisture.

[0020] The process control method according to this embodiment also includes production rate control and ventilation rate control. The production rate control acquires a target production rate, which is a target value of the production rate (Production rate: Prod), and calculates an operation amount of the blast volume (BV) using a physical model described later. The ventilation rate control acquires an upper limit of the furnace pressure loss (ΔP), which is the upper limit of the furnace pressure loss, and calculates operation amounts of the blast volume and the coke ratio using a physical model described later. Here, the actual values (which may be observed values or calculated values) in a plant including a blast furnace may be fed back for updating the physical models used in each control. In the example of FIG. 2, the actual values of the pulverized coal ratio (PCR), the hot metal temperature (HMT), the furnace pressure loss (ΔP), and the production rate (Prod) are shown as the actual PCR, the actual HMT, the actual ΔP, and the actual Prod, respectively. Further, the association between the control variables and the operation variables correlated therewith in the blast furnace process is not limited to that shown in FIGS. 1 and 2. For example, in the production rate control, it is possible to operate the blast oxygen flow rate instead of the blast volume.

[0021] In this embodiment, in the construction of a multivariable control system as shown in FIG. 2, individual controllers (hot metal temperature control, air permeability control, casting speed control) for controlling the hot metal temperature (HMT), the pressure loss in the furnace (ΔP), and the casting speed (Prod) are constructed. The hot metal temperature is controlled by the operation of the blast moisture and cascade control that operates the pulverized coal ratio (PCR) and the pulverized coal flow rate. The air permeability is controlled by the operation of the blast flow rate and the coke ratio. The casting speed is controlled by the operation of the blast flow rate. Here, for example, when the blast flow rate is operated in the casting speed control, the change in the blast flow rate affects the hot metal temperature. This influence is reflected by the physical model in the hot metal temperature control and calculated as the operation amount of the pulverized coal ratio or the blast moisture, and the hot metal temperature is maintained near the target value by reflecting the calculated operation amount of the pulverized coal ratio or the blast moisture. In this embodiment, although individual controllers are constructed as described above, it is possible to realize control considering the interference between the respective operation variables. That is, for example, the hot metal temperature control and the casting speed control interfere with each other, but they are constructed as a control system having disturbance rejection characteristics that absorb fluctuations based on the operation of the other operation variable by the operation of its own operation variable, and the influence of the interference can be reduced. The same applies to the air permeability control.

[0022] In the process control method according to this embodiment, the physical model of the blast furnace based on the reaction rate theory is used to predict the future hot metal temperature and casting speed, and the change amounts of the pulverized coal ratio and the blast moisture are determined so that the predicted values are near the target values. By using the quadratic programming method that minimizes the evaluation function considering the reductant ratio when determining this operation amount, it is possible to achieve both reduction of the reductant ratio and suppression of the variation in the hot metal temperature. The outline of the process flow in the process control method according to this embodiment is as follows in steps 1 to 3 below.

[0023] First, as step 1, the future hot metal temperature is predicted using a physical model. Step 1 is a response prediction step. The response prediction step obtains a predicted value of the future hot metal temperature based on the predicted value of the future hot metal temperature when the current operating variables are held using the physical model and the predicted value of the hot metal temperature when the current operating variables are changed. The predicted value of the future hot metal temperature when the current operating variables are held is the free response described later. The predicted value of the hot metal temperature when the current operating variables are changed is the step response described later in this embodiment, but is not limited thereto.

[0024] Next, as step 2, the operation of the operating variables is executed using quadratic programming so that the predicted value of the hot metal temperature in step 1 matches the target value and the reductant ratio is minimized. Step 2 is an operation amount determination step, which obtains the deviation between the predicted value and the target value, obtains the operation amount for eliminating the deviation, and adjusts the operating variables. In this embodiment, the operating variables are the pulverized coal ratio and the blast moisture.

[0025] Also, as step 3, in order to simulate the actual operation of the blast furnace, the blast flow rate may be operated so that the predicted value of the pig iron production rate matches the target value, and at least the coke ratio may be operated so that the predicted value of the air permeability is below the upper limit. 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 the set upper limit, it is determined that the ventilation state is abnormal. When it is determined that the ventilation state is abnormal, an operation to increase the coke ratio may be executed. When it is determined that the ventilation state is not abnormal, that is, when the predicted value of the pressure loss in the furnace is below the upper limit, an operation to reduce the coke ratio may be executed. The operations of the blast flow rate and the coke ratio in step 3 are disturbances to the hot metal temperature control. As will be described later, it has been verified by simulation that the influence of this disturbance can be canceled by operating the pulverized coal ratio and the blast moisture.

[0026] The physical model used in the present disclosure is the same as the model of the method described in Reference 2 (Michiharu Haneda et al., "Examination of Blowing Operations Using a Blast Furnace Unsteady Model," Iron and Steel, vol. 68, p. 2369). That is, a physical model capable of calculating the state inside the blast furnace (inside the furnace) in an unsteady state, which is composed of a group of partial differential equations considering physical phenomena such as ore reduction, heat exchange between ore and coke, and ore melting, is used. This physical model may be referred to as an unsteady model hereinafter.

[0027] As shown in FIG. 3, among the input variables given to the unsteady model, the main ones that change with time are the blast flow rate, blast oxygen flow rate, pulverized coal flow rate, blast moisture, blast temperature, coke ratio, and top pressure. These input variables are operating variables or operating factors of the blast furnace. The blast flow rate, blast oxygen flow rate, and pulverized coal flow rate are the flow rates of air, oxygen, and pulverized coal sent to the blast furnace, respectively. The blast moisture is the humidity of the air sent to the blast furnace. The blast 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 per ton of hot metal production.

[0028] Also, the main output variables of the unsteady model are gas utilization rate, solution loss carbon amount (solution loss carbon amount), reductant ratio, hot metal production rate, hot metal temperature, and furnace pressure loss. It is possible to calculate the hot metal temperature, hot metal production rate, and furnace pressure loss that change moment by moment using the unsteady model. The time interval of the calculation is not particularly limited, but in this embodiment, it is 30 minutes. The time difference between "t + 1" and "t" in the formula of the unsteady model described later is 30 minutes in this embodiment.

[0029] The unsteady model can be expressed by the following formulas (1) and (2).

[0030]

Number

[0031] Here, \(x(t)\) is a state variable calculated within the non-steady model. The state variables are, for example, the temperature of coke, the temperature of iron, the degree of oxidation of ore, the dropping rate of raw materials, etc. \(y(t)\) is the control variable, which is the hot metal temperature, the pig iron production rate, and the aeration rate (pressure loss in the furnace). \(u(t)\) is the above input variable, which is a variable that can be operated by the operator performing the operation of the blast furnace. That is, the input variables are the blast volume \(BV(t)\), the blast oxygen flow rate \(BVO(t)\), the pulverized coal flow rate \(PCI(t)\), the blast moisture \(BM(t)\), the blast temperature \(BT(t)\), the coke ratio \(CR(t)\), and the top gas pressure \(TGP(t)\). \(u(t)=(BV(t),BVO(t),PCI(t),BM(t),BT(t),CR(t),TGP(t))\) T It can be represented by

[0032] First, assume that the values of the current input variables are kept constant, and perform the predictive calculation of the future control variables. At the current time step \(t\) 0 is set to 0, and the future control variables are predicted using the following equations (3) and (4). The response \(y\) f (t) of the control variable obtained in this way is called the free response.

[0033]

Equation

[0034] Hereinafter, a method for determining the operation amounts of the current and future pulverized coal ratios (PCR) and blast moisture (BM) will be described. An example of predicting two hours later as the future is explained. The unknown variable \(\theta = (\Delta PCR\) 0 , \(\Delta BM\) 0 , \(\Delta PCR\) 1 , \(\Delta BM\) 1 ) is introduced, and the operation amounts of the pulverized coal ratio (PCR) and blast moisture (BM) are determined by the quadratic programming method. The subscript 0 indicates the present. Also, the subscript 1 indicates two hours later.

[0035] As a premise of the predictive control using this physical model, the future hot metal temperature is the response \(y\) which is the free response f(t) may be approximated by superposition with the step response. y is the predicted value of the hot metal temperature every 2 hours up to 10 hours ahead pre (t) is as shown in the following equation (5).

[0036]

Equation

[0037] Here, S PCR (t) is the change in the hot metal temperature when the pulverized coal ratio (PCR) is operated by a unit amount (1 [kg / t]). Also, S BM (t) is the change in the blast moisture when the blast moisture (BM) is operated by a unit amount (1 [g / Nm 3 )). S PCR and S BM can be obtained, for example, by another physical model or a step response test in actual operation. In the calculations in the present disclosure, the simulation results described in Reference 3 (Y. Hashimoto, Online prediction of hot metal temperature using transient model and moving horizon estimation. ISIJ Int. 2019, vol. 59, p. 1534) were used.

[0038] In the following, when Equation (5) is expressed as the following Equation (6) using the step response matrix S, the deviation between the predicted value of the hot metal temperature and the target value y pre (t) is as shown in Equation (7).

[0039]

Equation

[0040] Here, the deviation from the target value y f of the free response 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 as shown in the following Equation (8).

[0041]

Number

[0042] In order to achieve both the reduction of the variation in the molten iron temperature and the minimization of the reducing agent ratio, the evaluation function J used in the quadratic programming method, in addition to the first and second terms of Equation (8), includes a term (the third term) for reducing the blast moisture content as shown in Equation (9). Further, the evaluation function J includes a fourth term for suppressing excessive operations.

[0043]

Number

[0044] Here, a and R are coefficients. Comparing the responsiveness of the molten iron temperature to changes in the pulverized coal ratio (PCR) and the blast moisture content (BM) respectively, it is known that the blast moisture content has higher responsiveness. However, in order to secure an operable range in both the increasing and decreasing directions so that the blast moisture content can be increased or decreased, it is necessary to increase the average value of the blast moisture content. When the average value of the blast moisture content is increased, endothermic heat is generated due to the steam decomposition reaction of the blast moisture content, and the problem arises that more reducing agent must be charged to compensate for the heat reduced by the endothermic heat. Therefore, in order to limit the operation amount of the blast moisture content, the third term is introduced, and by changing the weighting of ΔPCR and ΔBM included in the vector θ according to the magnitude of the elements of the coefficient vector a, the operation allocation of both can be adjusted.

[0045] Also, θ is determined using Equation (9) under the constraint conditions of the following Equations (10) to (13).

[0046]

Number

[0047] Here, the subscript i in Equations (10) to (13) is 0 or 1. Also, the subscript now means the value of the current pulverized coal ratio (PCR) or blast moisture content (BM). PCR max, 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 magnitude of the allowable change in the pulverized coal ratio (PCR). BM max , 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 magnitude of the allowable change in the blast moisture (BM). Under the constraint conditions of the linear equations regarding the unknown variable θ shown in Equations (10) to (13), the unknown variable θ is determined using quadratic programming so as to minimize the evaluation function J, which is a quadratic function regarding the unknown variable θ. The control for obtaining the unknown variable θ using Equation (9) corresponds to the hot metal temperature control in FIG. 2.

[0048] Here, in the present embodiment, the evaluation function J is designed to reduce the blast moisture in order to reduce the reductant ratio. However, for example, the same effect can be obtained by using an evaluation function J that directly reduces the reductant ratio, such as imposing a penalty on an increase in the pulverized coal ratio. Further, in the present embodiment, the unknown variable θ in the case where the evaluation function J is minimized is obtained. However, the evaluation function J may be designed so that the deviation between the predicted value and the target value of the hot metal temperature and the minimization of the reductant ratio (or blast moisture) correspond to the maximization of the evaluation function J. That is, the operation amounts of the pulverized coal ratio and the blast moisture may be obtained 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. That is, even if the evaluation function J does not necessarily take the maximum value or the minimum value, if the value of the evaluation function J is in the vicinity of the maximum value or the minimum value (if quasi-optimization is performed), it may be treated that the control objective is achieved. Therefore, minimizing or maximizing the evaluation function J may include not only the case where the value of the evaluation function J becomes the maximum value or the minimum value, but also the case where the value of the evaluation function J is in the vicinity of the maximum value or the minimum value.

[0049] In order to verify the effect of reducing the reductant ratio according to the present disclosure by simulation under operating conditions close to actual operation, for control variables other than the hot metal temperature (casting speed and in-furnace pressure loss), the operating variables (blast flow rate and coke ratio) are also operated by the following method.

[0050] Regarding the milling speed, in order to eliminate the deviation between the target value and the predicted value, the operation amount ΔBV of the air flow rate (BV) [Nm 3 / min] is obtained by the following formula (14).

[0051]

Equation

[0052] Here, Prod(t + T) is the predicted value of the milling speed at T steps ahead. As an example, T may be 4, and at this time, it means the predicted value 2 hours (30 minutes × 4) ahead. Prod ref is the target milling speed (the target value of the milling speed). Also, S BV is the change amount of the milling speed when the air flow rate (BV) is operated by a unit amount (1 [Nm 3 / min]). S BV can be obtained by another physical model or a step response test in actual operation, etc. Also, b is a coefficient and is a positive number. The control for obtaining ΔBV according to formula (14) corresponds to the milling speed control in FIG. 2.

[0053] Also, regarding the furnace internal pressure loss (ΔP), by comparing with the upper limit (threshold value), the operation amounts of the coke ratio (CR) and the air flow rate (BV) are determined. When the furnace internal pressure loss (ΔP) exceeds the upper limit, the operation amount is determined so as to increase the coke ratio and at the same time decrease the air flow rate. This corresponds to the operation for stabilizing the unloading of raw materials in the operation of the blast furnace. Also, when the furnace internal pressure loss is below the upper limit, the operation amount is determined so as to gradually reduce the coke ratio. In principle, the control is performed so that the furnace internal pressure loss does not exceed the upper limit, but when the furnace internal pressure loss is below the upper limit, it becomes possible to reduce the operation cost by gradually reducing the coke ratio. When such control is performed, the value of the furnace internal pressure loss fluctuates near the upper limit. The control for determining the operation amounts of the coke ratio (CR) and the air flow rate (BV) by comparing with the upper limit of the furnace internal pressure loss corresponds to the air permeability control in FIG. 2.

[0054] Figure 4 shows the simulation results by the above process control. That is, in the simulation of Figure 4, based on the predicted values using an unsteady model of the hot metal temperature (HMT), production rate of pig iron (Prod), and an example of the air permeability, the pressure loss in the furnace (ΔP), the blast moisture (BM), pulverized coal ratio (PCR), blast volume (BV), and coke ratio (CR) were manipulated. The target hot metal temperature was 1500 °C. The target production rate of pig iron was 7 [t / min]. Also, the upper limit value of the pressure loss in the furnace was 100 [kPa].

[0055] As shown in Figure 4, the hot metal temperature (HMT) is manipulated near the target value, and based on the evaluation function J shown in Equation (9), while suppressing the variation in the hot metal temperature, it can be seen that the blast moisture (BM) is maintained near the lower limit value. The fact that the blast moisture is near the lower limit value leads to a reduction in the reducing agent ratio because the endothermic reaction due to the steam decomposition reaction in which the reducing agent must be charged is less likely to occur. Also, the production rate of pig iron (Prod) is controlled near the target value, and the pressure loss in the furnace (ΔP) is also kept below the upper limit.

[0056] For comparative verification, a simulation was carried out for a comparative example in which only the pulverized coal ratio (PCR) was manipulated and the blast moisture (BM) was not manipulated. Figure 5 shows the simulation results by the control of the comparative example. In the simulation of Figure 5, based on the predicted values using an unsteady model of the hot metal temperature (HMT), production rate of pig iron (Prod), and an example of the air permeability, the pressure loss in the furnace (ΔP), the pulverized coal ratio (PCR), blast volume (BV), and coke ratio (CR) were manipulated. The conditions of the simulation were the same as those in the case of Figure 4 except for the blast moisture (BM). The blast moisture was set to a constant value of 15.5 [g / Nm 3 .

[0057] FIG. 6 is a diagram for explaining the reduction effect of the reducing material ratio (RAR), which compares the time change of the reducing material ratio in the simulation results of FIG. 4 (control method of the process according to the present embodiment) and FIG. 5 (comparative example). As shown in FIG. 6, the average value of the reducing material ratio in the control method of the process according to the present embodiment is reduced compared to the average value of the reducing material ratio in the comparative example. It was shown that the reducing material ratio can be reduced by the simultaneous operation of the pulverized coal ratio and the blast moisture. By reducing the reducing material ratio, the amount of oxygen (oxygen unit) blown from the tuyere required to produce 1 t of hot metal [Nm 3 / t] is reduced. Therefore, the target milling rate can be achieved with a smaller blast flow rate. As a result, a margin is created in the pressure loss, and the coke ratio can also be reduced (see CR in FIGS. 3 and 4).

[0058] FIG. 7 is a diagram showing 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 unit 11, a storage unit 12, and a control unit 13. The control unit 13 includes a hot metal temperature control unit 14, a milling rate control unit 15, a permeability control unit 16, and a PCR tracking control unit 17. The process control device 10 executes the above-described process control method. Here, when the process control device 10 operates the blast moisture, the blast flow rate, the coke ratio, or the pulverized coal ratio, for example, information such as the operation amount may be displayed on a display unit such as a liquid crystal display.

[0059] The communication unit 11 is configured to include a communication module for communicating with a higher-level system. The higher-level system includes a process computer that manages the processes in a plant including a blast furnace. The communication unit 11 may include a communication module corresponding to a mobile communication standard such as 4G (4th Generation), 5G (5th Generation), etc. The communication unit 11 may include a communication module corresponding to a wired or wireless LAN standard, for example. The control unit 13 can acquire information such as the target hot metal temperature, the target pig iron production rate, and the upper limit of the pressure loss in the furnace from the higher-level system via the communication unit 11. Also, the control unit 13 can output information on the manipulated variable that has executed an operation, that is, the manipulated variable reflecting the calculated manipulated quantity, to the higher-level system via the communication unit 11.

[0060] The storage unit 12 stores the above physical model. Also, the storage unit 12 stores programs and data related to the 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. The semiconductor storage device may include, for example, a semiconductor memory. The storage unit 12 may include multiple types of storage devices.

[0061] 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 execute the acquisition of data used for control. That is, the control unit 13 may acquire the hot metal temperature, the pig iron production rate, and the air permeability of the blast furnace by measured values or calculated values. The control unit 13 is configured to include at least one processor such as a CPU (Central Processing Unit) in order to control and manage various functions. The control unit 13 may be composed of one processor or multiple processors. The processor constituting the control unit 13 may function as a hot metal temperature control unit 14, a pig iron production rate control unit 15, an air permeability control unit 16, and a PCR tracking control unit 17 by reading and executing a program from the storage unit 12.

[0062] The hot metal temperature control unit 14 acquires the target hot metal temperature which is the target value of the hot metal temperature, and calculates the operation amounts of the blast moisture and the pulverized coal ratio so that the hot metal temperature becomes the target hot metal temperature. The hot metal temperature control unit 14 is a functional unit that executes "Hot metal temperature control" in FIG. 2.

[0063] The casting speed control unit 15 acquires the target casting speed which is the target value of the casting speed, and calculates the operation amount of the blast flow rate so that the casting speed becomes the target casting speed. The casting speed control unit 15 is a functional unit that executes "Casting speed control" in FIG. 2.

[0064] The air permeability control unit 16 acquires the upper limit of the air permeability (the furnace internal pressure loss in this embodiment), and calculates at least the operation amount of the coke ratio so that the air permeability does not exceed the upper limit. As in this embodiment, the air permeability control unit 16 may further calculate the operation amount of the blast flow rate. The air permeability control unit 16 is a functional unit that executes "Air permeability control" in FIG. 2.

[0065] The PCI tracking control unit 17 acquires the pulverized coal ratio (target PCI) which is the target value determined by the hot metal temperature control unit 14, and calculates the operation amount of the pulverized coal flow rate (PCI) so as to follow the target PCI by PCI tracking control. The PCI tracking control unit 17 is a functional unit that executes "PCI tracking control" in FIG. 2.

[0066] The hot metal temperature control unit 14, the pig casting speed control unit 15, and the air permeability control unit 16 are individual controllers for controlling the hot metal temperature (HMT), the pig casting speed (Prod), and the pressure loss in the furnace (ΔP), respectively. Explaining using the above steps 1 to 3, 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 (manipulation variable determination step) to obtain the manipulation variables of the pulverized coal ratio and the blast moisture. The pig casting speed control unit 15 executes step 3 to obtain the manipulation variable of the blast flow rate so as to eliminate the deviation between the target value and the predicted value of the pig casting speed. Also, the air permeability control unit 16 executes step 3 to obtain the manipulation variables of the blast flow rate and the 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 unit 14, the pig casting speed control unit 15, and the air permeability control unit 16 constructed as individual controllers are control systems having disturbance rejection characteristics that absorb fluctuations based on the manipulation of the manipulated variables by other control units by the manipulation of their own manipulated variables. Therefore, the hot metal temperature control unit 14, the pig casting speed control unit 15, and the air permeability control unit 16 can reduce the influence of the interference of the manipulated variables from other control units.

[0067] As part of the operation method of the blast furnace, a process control method executed by the process control device 10 may be used. For example, the manipulated variables manipulated in the above process control method may be used for changing the operating conditions in the operation of the blast furnace. Also, such an operation method of the blast furnace can be executed as part of a manufacturing method for manufacturing hot metal. In the blast furnace, the raw material iron ore is melted and reduced to become pig iron and is tapped as hot metal, but the blast furnace may be operated according to this operation method.

[0068] The process control device 10 may be implemented by a computer different from, for example, a process computer that controls the operation of a blast furnace, or may be implemented by a process computer. The computer includes, for example, a display device such as a memory, a hard disk drive (storage device), a CPU (processing device), and a display. Various functions can be realized by organically collaborating the hardware such as the CPU and the memory with the program. The storage unit 12 may be realized by, for example, a storage device. The control unit 13 may be realized by, for example, a CPU.

[0069] As described above, the process control method, the blast furnace operation method, the hot metal production method, and the process control device 10 according to the present embodiment can realize the suppression of the variation in the hot metal temperature while reducing the reducing agent ratio in the blast furnace with the above configuration.

[0070] 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 modifications or corrections based on the present disclosure. Therefore, it should be noted that these modifications or corrections are included in the scope of the present disclosure. For example, the functions included in each component or each step can be rearranged so as not to be logically contradictory, and a plurality of components or steps can be combined into one or divided. The 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 should be understood that these are also included in the scope of the present disclosure.

[0071] The configuration of the process control device 10 shown in FIG. 7 is an example. The process control device 10 does not have to include all of the components shown in FIG. 7. Further, the process control device 10 may include components other than those shown in FIG. 7. For example, the process control device 10 may have a configuration further including a display unit.

Explanation of Reference Numerals

[0072] 10 Process control device 11 Communication unit 12 Memory unit 13 Control unit 14 Molten iron temperature control unit 15 Milling speed control unit 16 Ventilation degree control unit 17 PCR tracking control unit

Claims

1. A response prediction step of obtaining a predicted value of a future hot metal temperature using a physical model capable of calculating the internal state of a blast furnace; An operation amount determination step of obtaining a deviation between the predicted value of the hot metal temperature obtained in the response prediction step and a target value, and obtaining an operation amount of pulverized coal ratio and blast moisture so that an evaluation function having a term corresponding to the deviation and a term for reducing the reductant ratio or blast moisture is minimized or maximized, including; The operation amount determination step determines the unknown variables using the evaluation function, which is a quadratic function with respect to the unknown variables, under the constraint conditions of a linear expression with respect to the unknown variables, with the operation amounts of the pulverized coal ratio and the blast moisture to be obtained as the unknown variables. A control method for a process.

2. The response prediction step obtains the predicted value of the future hot metal temperature based on the predicted value of the future hot metal temperature when the current operation variables are maintained using the physical model and the predicted value of the hot metal temperature when the current operation variables are changed. The control method for a process according to claim 1.

3. The control method for a process according to claim 1, further including a step of operating the blast flow rate so that the predicted value of the tapping rate matches the target value and operating the coke ratio so that the predicted value of the permeability is below the upper limit.

4. An operating method for a blast furnace, which changes operating conditions using the operation variables operated by the control method for a process according to any one of claims 1 to 3.

5. A method for producing hot metal, which produces hot metal using the blast furnace operated by the operating method for a blast furnace according to claim 4.

6. A storage unit that stores a physical model capable of calculating the internal state of a blast furnace; A hot metal temperature control unit that acquires a target hot metal temperature, which is a target value of the hot metal temperature, and calculates operation amounts of pulverized coal ratio and blast moisture so that the hot metal temperature becomes the target hot metal temperature, including; The hot metal temperature control unit, Obtains a predicted value of a future hot metal temperature using the physical model, Obtains a deviation between the predicted value of the hot metal temperature and the target value, and obtains operation amounts of pulverized coal ratio and blast moisture so that an evaluation function having a term corresponding to the deviation and a term for reducing the reductant ratio or blast moisture is minimized or maximized, Obtaining the operation amounts determines the unknown variables using the evaluation function, which is a quadratic function with respect to the unknown variables, under the constraint conditions of a linear expression with respect to the unknown variables, with the operation amounts of the pulverized coal ratio and the blast moisture to be obtained as the unknown variables. A control device for a process.

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