JP2015117389A - Hot stove control calculation device, hot stove operation index derivation method, and computer program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To set a heat storage amount of a hot stove using a process state of the hot stove which can be actually measured so as to determine an operation condition of the hot stove.SOLUTION: When mixed cooling is performed, an opening of a cool air butterfly valve 123 is used as an index of a residual heat amount of a heat-storing brick when a blowing period ends. On the other hand, when the mixed cooling is not performed, a blowing butterfly valve 125 or a blowing temperature is used as the index of the residual heat amount of the heat-storing brick when the blowing period ends. An amount of change ΔTof a lower limit Tof a lowest temperature of a stove classified/cycle classified silica brick is derived using a target value and an actual value of the index of the residual heat amount of the heat-storing brick when the blowing period ends, and the lower limit Tof the lowest temperature of the stove classified/cycle classified silica brick is derived from the derived result. A heat input quantity Qis derived using the lower limit Tof the lowest temperature of the stove classified/cycle classified silica brick.

Description

  The present invention relates to a hot stove control calculation apparatus, a hot stove operation index derivation method, and a computer program, and is particularly suitable for use in instructing an operation to a hot stove.

  In order to supply hot air to the blast furnace, the blast furnace is accompanied by a hot air furnace. The hot stove generates hot air by supplying heat to the blast furnace by heat exchange with the heat storage brick through the combustion period in which the heat storage brick is heated by the combustion gas to store heat based on the air blowing conditions required from the blast furnace, and cold air is supplied to the heat storage brick. A period including one blowing period is set as one cycle, and the combustion period and the blowing period are alternately repeated to supply hot air to the blast furnace.

  In the hot blast furnace, hot blast that satisfies the blowing conditions required from the blast furnace must be supplied to the blast furnace. For this reason, it is desirable to appropriately determine the amount of heat input to the hot stove and control the combustion of the hot stove. As a technique for determining the amount of heat input to the hot stove, there is a technique described in Patent Document 1.

  In the technique described in Patent Document 1, first, an optimum value of the minimum temperature of target silica bricks by furnace and cycle is derived in an optimization time range that is longer than the time constant of the hot stove, and the amount of heat stored in the hot stove Optimize the transition in each cycle (target trajectory of heat storage amount). Then, the input heat quantity for each furnace and cycle is derived so that the predicted value of the minimum temperature for silica brick for each furnace / cycle follows the optimum value for the minimum temperature for target silica brick for each furnace / cycle.

  In optimizing the target trajectory of the heat storage amount described above, in Patent Document 1, a constraint equation indicating that the absolute value of the difference between the predicted value of the blowing temperature for each furnace and the cycle and the target blowing temperature is equal to or less than a threshold value, Furnace to satisfy the constraint formula indicating that the absolute value of the difference between the predicted value of the minimum temperature of silica bricks by cycle and by cycle and the target minimum temperature of quartz brick by cycle and by cycle (candidate) is below the threshold. The value of the candidate minimum temperature for the target quarry brick by furnace / cycle is changed until the value of the objective function, which decreases as the amount of heat input by cycle / cycle decreases, is minimized.

JP 2013-82883 A

By the way, when determining the amount of heat input to the hot stove, it is desirable to use an actual measurement value of the process state of the hot stove. This is because it is less susceptible to errors in the prediction model, and the amount of heat input to the hot stove can be made as small as possible.
However, the technique described in Patent Document 1 does not use the actual measurement value of the process state of the hot stove when optimizing the target trajectory of the heat storage amount. For this reason, the amount of heat input to the hot stove cannot always be determined with high accuracy.
As described above, in order to determine the operating conditions of the hot stove, it is desired to be able to grasp the heat storage amount of the hot stove using the actual measured value of the process state of the hot stove.

  The present invention has been made in view of the above problems, and in order to determine the operating conditions of the hot stove, it is possible to grasp the heat storage amount of the hot stove using the measured values of the process state of the hot stove. The purpose is to.

  The hot stove control calculation apparatus according to the present invention includes a combustion period in which heat storage bricks are heated and stored by combustion gas, and a blowing period in which hot air is generated by heat exchange with the heat storage bricks through cold air and supplied to the blast furnace. And a heat storage chamber having a heat storage brick including a silica brick, a combustion chamber for heating the heat storage chamber, and an inflow from the heat storage chamber through the combustion chamber A hot stove control calculation device that performs calculations for controlling the operation of a hot stove comprising a mixed cooling chamber that performs temperature adjustment of the hot air by mixing cold air with the hot air, When operating by mixing cold air, using the first residual heat amount index as an index of the residual heat amount of the heat storage brick when the air blowing period ends, the silica brick when the air blowing period ends Lowest temperature The first deriving means for deriving the amount of change with respect to the limit value as the amount of change of the quartz brick minimum temperature lower limit, and when operating without mixing the cold air in the mixed cooling chamber, the time when the blowing period ends The second residual heat index as an index of the residual heat amount of the heat storage brick is used to derive the change amount with respect to the lower limit value of the minimum temperature of the silica brick when the blowing period ends as the minimum temperature limit value of the quartz brick. 2 derivation means, the change amount with respect to the lower limit value of the minimum temperature of the silica brick when the air blowing period ended, derived by the first derivation means or the second derivation means, and the air blowing period From the current value of the lower limit value of the minimum temperature of the quartz brick when finished, the lower limit value of the lowest temperature of the quartz brick when the blowing period in the next cycle is finished is below the lowest temperature of the quartz brick. And a first residual heat index is determined based on an opening degree of a cold air butterfly valve for adjusting the flow rate of the cold air flowing into the mixed cooling chamber. And the second residual heat index is the opening of a blower butterfly valve for adjusting the flow rate of the cold air flowing into the combustion chamber or the temperature of hot air discharged from the hot air furnace to the blast furnace It is determined based on temperature.

  The hot blast furnace operation index deriving method of the present invention is a method of generating heat air by supplying heat to a blast furnace by generating heat by heat exchange with the heat storage brick through a combustion period in which the heat storage brick is heated and stored by combustion gas and passing cold air to the heat storage brick. Is a hot stove operating as a cycle including a period, a heat storage chamber having a heat storage brick including a silica brick, a combustion chamber for heating the heat storage chamber, and from the heat storage chamber through the combustion chamber A hot stove operation index derivation method for performing calculation for controlling the operation of a hot stove equipped with a mixed cooling chamber for adjusting the temperature of the hot air flowing in by mixing the hot air with cold air, the mixed cooling chamber In the case where the cold air is mixed and operated, the first residual heat amount index as an index of the residual heat amount of the heat storage brick when the air blowing period ends, and the silica stone when the air blowing period ends. The best of brick The first derivation step for deriving the change amount with respect to the lower limit value of the temperature as the change amount of the quartz brick minimum temperature lower limit value, and when the operation is performed without mixing the cold air in the mixed cooling chamber, when the blowing period ends. Using the second residual heat index as an index of the residual heat amount of the heat storage brick, the amount of change with respect to the lower limit value of the minimum temperature of the silica brick when the air blowing period ends is derived as the minimum temperature limit value of the quartz brick A second derivation step, a change amount derived from the first derivation step or the second derivation step with respect to a lower limit value of the minimum temperature of the silica brick when the air blowing period ends, and the air blowing From the current lower limit value of the minimum temperature of the silica brick at the end of the period, the lower limit value of the minimum temperature of the silica brick at the end of the blowing period in the next cycle is determined as the lowest value of the quartz brick. A third deriving step for deriving as a temperature lower limit value, wherein the first residual heat index is based on an opening degree of a cold air butterfly valve for adjusting a flow rate of the cold air flowing into the mixed cooling chamber And the second residual heat index is an opening degree of a blow butterfly valve for adjusting a flow rate of the cold air flowing into the combustion chamber or a temperature of hot air discharged from the hot air furnace to a blast furnace. It is determined based on a certain blowing temperature.

  The computer program of the present invention causes a computer to function as each means of the hot stove control calculation apparatus.

  According to the present invention, when the cold air is mixed in the mixed-cooling chamber, the lower limit value of the minimum temperature of the quartz brick when the air blowing period in the next cycle is ended, using the opening degree of the cold air butterfly valve as the residual heat amount index. Derived and when the cold air is not mixed in the mixed cooling chamber, the lower limit value of the minimum temperature of the quartz brick when the air blowing period in the next cycle is ended, using the opening degree or air temperature of the air blowing butterfly valve as the residual heat amount index. Derived. Therefore, it becomes possible to grasp the heat storage amount of the hot stove using the actual measurement value of the process state of the hot stove.

It is a figure which shows an example of schematic structure of a hot stove. It is a figure which shows an example of the outline | summary of the operation | movement of the combustion period and ventilation period in a hot stove. It is a figure which shows an example of schematic structure of the control system of a hot stove. It is a figure explaining an example of the outline of the operation schedule in a staggered parallel system. It is a figure which shows an example of a functional structure of a hot stove control computer. It is a figure which shows notionally an example of the target quartz brick minimum temperature classified by furnace at the time of the ventilation period end, and an operation target value (operation conditions). Target quartz brick minimum temperature by furnace and cycle at the end of the blowing period, predicted value of minimum temperature of silica brick by furnace and cycle at the end of the blowing period, operation target value (operation conditions), and furnace and cycle It is a figure which shows notionally an example of input heat amount. It is a figure which shows an example of the relationship between the flow rate of the cool air flowing into the mixed cooling chamber and time, and the relationship between the blowing temperature and time. It is a figure which shows the relationship between the opening degree of a cold wind butterfly valve, and time. It is a figure which shows an example of the relationship between the opening degree of a ventilation butterfly valve, and time. It is a figure explaining an example of the specific residual-heat quantity parameter | index in the case of performing mixed cooling. It is a figure which shows an example of the relationship between the opening degree of a cold wind butterfly valve of a certain hot stove in one cycle, and time. It is a figure explaining an example of the concrete residual heat quantity parameter | index when not performing mixed cooling. It is a figure which shows an example of a residual heat amount parameter | index setting screen. It is a figure which shows notionally an example of a hot stove model. It is a figure which shows an example of a detailed functional structure of a 2nd process state estimation part. It is a flowchart explaining an example of a process of the hot stove control computer at the time of deriving | requiring the target quartz brick minimum temperature classified by furnace at the time of completion | finish of each ventilation period. It is a flowchart explaining an example of a silica brick minimum temperature lower limit derivation process. It is a flowchart explaining an example of a process of the hot stove control computer at the time of deriving | requiring the calorie | heat amount classified by furnace and cycle after the present time. It is a flowchart explaining an example of the hot stove simulator execution process of step S1905 of FIG. It is a figure which shows an example of the residual heat amount parameter | index change table.

Hereinafter, an embodiment of the present invention will be described with reference to the drawings.
[Configuration of Hot Air Furnace 100]
FIG. 1 is a diagram illustrating an example of a schematic configuration of a hot stove 100. In each figure, for the convenience of explanation, only necessary portions are simplified as necessary.
In FIG. 1, a hot stove 100 is a regenerative heat exchanger for supplying hot air to a blast furnace (not shown). The hot stove 100 has a heat accumulating chamber 101 that gives heat to the blast furnace air, a combustion chamber 102 for heating the heat accumulating chamber 101, and a mixed cooling chamber 103 for adjusting the temperature of the hot air. .

  In the combustion chamber 102, a mixed gas of BFG, COG, and LDG blown from the gas supply duct 112 (in the following description, these mixed gases are collectively referred to as “combustion gas” as necessary) and combustion air supply The combustion air blown from the duct 113 is combusted by the combustion burner 108, and this combustion gas is passed through the heat storage bricks stacked inside the heat storage chamber 101 to be heated and stored.

In the example shown in FIG. 1, as the heat storage brick, a clay brick 109, a high alumina brick 110, and a silica brick 111 mainly composed of silica are laminated in this order from the bottom, and these clay brick 109, high alumina brick are laminated. 110 and the quartz brick 111 are formed with a plurality of passage openings extending in the vertical direction.
The gas supply duct 112 is provided with a gas shut-off valve 130, a gas butterfly valve 131, and a combustion gas flow meter 132. Can be adjusted.

The combustion air supply duct 113 sends the air blown from the combustion air fan to the hot stove 100.
The combustion air supply duct 113 is provided with an air flow meter 127, an air butterfly valve 128, and an air shut-off valve 129. An amount of air necessary for combustion is introduced into the combustion air supply duct 113 in accordance with the flow rate of the combustion gas.
A duct 114 is provided at the lower end of the heat storage chamber 101, and this duct 114 is provided with a gas discharge duct 119 for discharging combustion gas containing N ₂ , CO _{2 and the} like, and the heat storage chamber via the duct 114. Branched into a cold air introduction duct 116 for supplying cold air to 101.
The gas exhaust duct 119 is provided with a flue valve 126.

The cold air introduction duct 116 is provided with a blower valve 124 and a blower butterfly valve 125, and by opening and closing the blower butterfly valve 125, the inflow amount of the cold wind flowing into the hot air furnace 100 can be adjusted.
The mixed cooling chamber 103 is connected to a hot air discharge duct 117 for discharging hot air for the blast furnace. The hot air discharge duct 117 is provided with a hot air valve 121.
In addition, a duct 118 connected to the mixed cooling chamber 103 is provided on the upstream side of the air blowing butterfly valve 125 of the cold air introduction duct 116. The duct 118 is provided with a cold air valve 122 and a cold air butterfly valve 123.

FIG. 2 is a diagram illustrating an example of an outline of operations in the combustion period and the blowing period in the hot stove 100.
As shown in FIG. 2A, when heat is stored in the heat storage chamber 101 during the combustion period, the air supply valve 124, the cold air valve 122, and the hot air valve 121 are completely closed, and the gas supply duct 112 and the combustion air Combustion gas and combustion air are introduced into the combustion chamber 102 via the supply duct 113.
These combustion gas and combustion air are burned by the burner 108, and this combustion gas passes through the openings formed in the clay brick 109, the high alumina brick 110, and the quartz brick 111 in the heat storage chamber 101, and the clay brick 109, high The alumina brick 110 and the quartz brick 111 are stored with heat. The combustion gas that has passed through the clay brick 109, the high alumina brick 110, and the silica brick 111 is discharged to the flue as an exhaust gas through the gas discharge duct 119. Here, the lowest temperature at the lowermost part of the quartz brick 111 is managed so as not to be lower than the transformation point temperature of the quartz brick 111. In addition, the lower limit value of the temperature at the bottom of the clay brick 109 is controlled to a constant value (as low as possible so that the exhaust gas temperature does not increase). In the following description, the minimum temperature of the lower end portion of the silica brick 111 at the end of the air blowing period is abbreviated as “quartz brick minimum temperature” as necessary.

  When the heat storage in the heat storage chamber 101 is completed, as shown in FIG. 2B, the flue valve 126, the air shut-off valve 129, and the gas shut-off valve 130 are completely closed, and the heat storage chamber is connected via the cold air introduction duct 116. Cold air is caused to flow into 101. The cold air that has flowed into the heat storage chamber 101 passes through openings formed in the clay brick 109, the high alumina brick 110, and the silica brick 111, and is heated to 900 to 1300 ° C. Then, the hot air discharge duct 117 serves as hot air for the blast furnace. Discharged from.

FIG. 3 is a diagram illustrating an example of a schematic configuration of a hot stove control system. In FIG. 3, the solid line indicates the flow of signals, and the broken line indicates the flow of cold air, hot air, combustion gas, and combustion air.
FIG. 3 shows an example in which four hot stoves 100a to 100d are attached to one blast furnace. Moreover, these four hot stove 100a-100d shall operate | move by a staggered parallel system.
FIG. 4 is a diagram for explaining an example of an outline of an operation schedule in the staggered parallel system.
In the example shown in FIG. 4, switching from blowing to combustion from left to right, combustion, switching from combustion to blowing, and blowing are performed in this order, and one cycle is configured by combining these periods. (See “1 cycle = switching time 401 + combustion time 402 + switching time 401 + air blowing time 403” shown in FIG. 4). One cycle is, for example, 180 [min]. And it is made to wrap a part of ventilation time of 2 units | sets (for example, hot stove 1 and hot stove 2) which back and forth (adjacent) in the order which supplies hot air. Further, in the example shown in FIG. 4, the air blowing time and the combustion time are set to the same length for the sake of simplicity, so two units (for example, the hot air furnace 1 and the hot air furnace 3) that are not adjacent in the order in which hot air is supplied. When one hot stove is in the blowing period, the other hot stove is in the burning period, and when one hot stove is in the burning period, the other hot stove is in the blowing period. Moreover, as shown in FIG. 4, it can operate so that the state which only one hot stove among four hot stoves may be in a ventilation period may arise. In the present embodiment, the case where the blowing time is the same in all cycles will be described as an example.

[Configuration of Control Device 300]
Returning to the description of FIG. 3, the control system for the hot stove includes a control device 300 that controls the operation of the hot stoves 100 a to 100 d. The control device 300 includes a hot stove control computer 301, an input / output device 302, a flow rate controller 304, a temperature controller 305, and opening degree controllers 313a to 313d.
The hot stove control computer 301 performs a calculation for deriving an operation index of the hot stove 100a to 100d based on preset input data. Data input to the hot stove control computer 301 is performed via an input / output device 302 as an interface unit. Examples of information input to the input / output device 302 include the following.

First, as information based on the operation of the input device 312 by a hot stove operator, for example, there is the following information.
-Operation target values (target air blowing temperature BT _ref (time), target air flow rate BV _ref (time), target air blowing time BTime _ref when the operation of the hot stove 100a to 100d is changed to a state according to a request from the blast furnace (Time)). In the present embodiment, it is assumed that the target air blowing time BTime _ref (time) is a fixed value.
・ Equipment load (by furnace / thermal efficiency η (i, n + j), furnace / cycle input heat Qin (i, n + j), furnace / cycle heat storage Q _bf (i, n + j), furnace / cycle Initial values of candidates for the separate heat storage share ratio α (i, n + j).

・ Initial value of candidate target quartz brick minimum temperature T _{si, ref} (i, n + j) by furnace ・ Coefficients of linear time series model representing hot stove process model a ₀・_x (i), b0 ・_x (I), c0 · _x (i), a1 · _x (i), b1 · _x (i), c1 · _x (i)
The weighting factors w ₁ (i) and w ₂ (i) of the objective function J ₁ (i)

・ Number of cycles q (q is a positive integer) that defines the optimization time range 602 of the target quartz brick minimum temperature T _{si, ref} (i, n + j) by furnace and cycle
Here, the cycle number q is set so that the cycle number q becomes a cycle number corresponding to a time longer than the time constant of the hot stove 100a to 100d. For example, when the number of cycles corresponding to the cycle to which the current time belongs is n and the time constant of the hot stove 100a to 100d is 3 days, the number of cycles corresponding to the cycle 3 days or more after the cycle to which the current time belongs is The number of cycles q is set so as to be n + q (see FIG. 6). The time constant means that the temperature of each part of the hot stove 100 is in an equilibrium state (without being affected by the disturbance) after the operation instruction (instruction of the air flow rate or air temperature) is given to the hot stove 100a to 100d. Time until it becomes (a state that reflects the operating conditions).

・ Number of cycles s (s is a positive integer) that defines the control section 702 for deriving the input heat quantity Q _{in, p} (i, t) by furnace and cycle after the current time
Here, the cycle number s defines the last cycle of the control section 702, and the cycle number n + s is a value lower than the time constant of the hot stove 100a to 100d and the cycle number n + q (see FIGS. 6 and 7). reference).
・ Number of cycles d and m (d and m are positive integers, d <m) defining the prediction interval 701 of the predicted value T _{si, p} (i, t) of the minimum temperature of silica brick by furnace and cycle
Here, the cycle number d (d is a positive integer) defines the first cycle of the prediction interval 701 (see FIG. 7). The cycle number d is a value larger than the cycle number s (becomes greater than or equal to the cycle number s) (see FIG. 7).
The number of cycles m determines the last cycle of the prediction interval 701 (see FIG. 7). The cycle number m is a value lower than the time constant and the cycle number q of the hot stove 100a to 100d (see FIGS. 6 and 7).
As described above, the prediction interval 701 and the control interval 702 are periods shorter than the time constant and the optimization time range 602 of the hot stove 100a to 100d, and the last cycle of the control interval 702 is more than the first cycle of the prediction interval 701. Is also the previous cycle (in time).

As the prediction interval 701, the predicted value T _{si, p} (i, t) of the minimum temperature of siliceous brick by furnace / cycle is the target value (the minimum temperature of target siliceous brick _{Tsi, ref} (i, n) by furnace / cycle). A section that closely follows)) is appropriately set by the operator. Even if the operating conditions such as the blowing flow rate BV and the blowing temperature BT are changed, the heat storage amount of the hot stove 100a to 100d does not immediately reflect the change of the operating conditions. Therefore, for example, the cycle number corresponding to the time after the heat storage amount of the hot stove 100a to 100d starts to reflect the change of the operation condition can be set as the cycle number d. On the other hand, as the cycle number m, for example, a cycle number corresponding to a time of 8 hours to 1 day ahead can be set.

-Equipment (the clay brick 109, high alumina brick 110, silica brick 111, etc.) constituting the hot stove 100. Known data (physical constants / equipment constants) of gas (combustion gas, combustion air, etc.).
-Physical quantity target values (R1 target to R4 target, R6 target to R11 target, T5 target) that serve as an index of the residual heat amount of the heat storage brick.
Reference time (T1, T3, T6, T8, T9) for defining a physical quantity that serves as an index of the residual heat amount of the heat storage brick.
Correction gain k (k11, k12, k21, k22, k31, k32, k41, k42, k51, k52, k61, k62, k71, k72, k81 when calculating the lower limit value T _{si, m} of the minimum temperature of the quartz brick , K82, k91, k92, k101, k102).
In addition, the target value of the physical quantity that is an index of the residual heat amount of the heat storage brick, the reference time for defining the physical quantity that is the index of the residual heat amount of the heat storage brick, and the lower limit value T _{si, m} of the minimum temperature of the quartz brick are calculated. Details of the correction gain k will be described later with reference to FIGS.
In addition to this, information set by the operator in advance in calculations described later is also input to the input / output device 302.

Here, the subscript ref represents a target value, and the subscript p represents a future value.
Further, i in (i, n + j) and (i) represents that the value may differ depending on the hot stove 100. In this embodiment, since the hot stove 100a-100d is four sets, i becomes 1-4. In addition, n, j, and t in (i, n + j) and (i, t) indicate that values can be different depending on the cycle. n represents the cycle number of the cycle to which the current time belongs, and n + j represents the cycle number of the cycle that is j ahead of the cycle to which the current time belongs. t represents the number of cycles ahead of the cycle to which the current time belongs.
In addition, time of (time) represents that the value can be different depending on the time (for example, time having minute (min) as the minimum unit).

In this embodiment, T _{si, ref} (i, n), T _{si, ref} (i, n + 1) are used as initial values of candidates for the furnace-by-cycle and target-by-cycle target quartz brick minimum temperature T _{si, ref} (i, n + j). ,..., T _{si, ref} (i, n + q) is set.
In addition, in the time corresponding to the number of cycles n to n + q (optimization time range 602), the target blast temperature BT _ref (time) and the target blast flow rate BV _ref (time) are set.

Moreover, T _{si, ref} (i, n), T _{si, ref} (i, n + 1),..., T _{si, ref} as target siliceous brick minimum temperature T _{si, ref} (i, n + j) by furnace and cycle _{. ref} (i, n + q) is derived.
Moreover, T _{si, p} (i, n + d + g), T _{si, p} (i, n + d + 1 + g),..., T, as predicted values T _{si, p} (i, t) _{si, p} (i, n + m + g) is derived. Here, g is an integer from 0 (zero) to q−m. That is, _{Tsi, p} (i, n + d) to Tsi _{, p} (i, n + m), _{Tsi, p} ( _{Tsi, p} (i, n + d) to Tsi _{, p} (i, t)) i, n + d + 1) to Tsi _{, p} (i, n + m + 1), _{Tsi, p} (i, n + d + 2) to Tsi _{, p} (i, n + m + 2),..., T _{si, p} (i, n + d + q−m) ~ T _{si, p} (i, n + m + q-m) is derived in this order. Among the predicted values T _{si, p} (i, t) of the derived furnace-by-furnace and cycle-specific quartz brick minimum temperature, the latest value is adopted as the value of the overlapping cycle.

In addition, as the input heat quantity Q _{in, p} (i, t) by furnace and cycle after the present time, Q _{in, p} (i, n + g), Q _{in, p} (i, n + 1 + g),..., Q _{in, p} (i, n + s + g) is derived. That is, Q _{in, p} (i, n) to Q _{in, p} (i, n + s), Q _{in, p} (i, _p ) are input heat amounts Q _{in, p} (i, t) by furnace and cycle after the present time. n + 1) to Q _{in, p} (i, n + s + 1),..., Q _{in, p} (i, n + g) to Q _{in, p} (i, n + s + g) are derived in this order. Of the input heat amounts Q _{in, p} (i, t) for each furnace and each cycle after the derived current time, the latest value is adopted for the value of the overlapping cycle.

Examples of the information indicating the operation results include the following.
A blowing air temperature BT measured by a hot air thermometer 310 that measures the temperature (air blowing temperature) of hot air discharged from the hot air furnaces 100a to 100d to the blast furnace.
A quartz brick lower end temperature T _si measured by a quartz brick thermometer 315a to 315d that measures the temperature of the lower end of the quartz brick 111 for each furnace.
The cold air flow rate (= the air flow rate BV) measured by the air flow meter 307 that measures the flow rate of the cold air blown from the blower 306 (cold air flow rate).
A cold air temperature measured by a cold air thermometer 308 that measures the temperature of the cold air blown from the blower 306.
The opening degree of the cold air butterfly valve 123 that adjusts the amount of cold air flowing into the mixed cooling chamber 103.
The opening degree of the blower butterfly valve 125 that adjusts the amount of cool air flowing into the hot stove 100.
The opening degree of the valve takes a value of 0 [%] (= fully closed) to 100 [%].
Although not shown, information indicating other operation results output from other sensors attached to the hot stove 100a to 100d is also input to the input / output device 302.

Below, the outline | summary of an example of the process which the hot stove control computer 301 performs is demonstrated.
In the present embodiment, the hot stove control computer 301 executes a heat storage target trajectory derivation program based on the input information and the like, and the hot stove 100a to 100d from the cycle (number of cycles n) to which the current time belongs. In each cycle until a cycle corresponding to a time longer than the time constant (cycle number n + q) elapses (for example, 3 days or more ahead), the target quartz brick-specific minimum temperature T _{si, ref} (i, n + j) is derived. Here, j is expressed by the following equation (1).
j = 0, 1,..., q (1)

Next, the hot stove control computer 301 executes the input heat quantity derivation program based on the input information and the like, and predicts the minimum temperature of the brick bricks for each furnace and for each cycle T _{si, p} (i, t) However, the amount of heat input Q _{in, p} (i, t) after the present time to each hot stove 100a to 100d is set so as to follow the target siliceous brick minimum temperature T _{si, ref} (i, n + j) by furnace and cycle. It calculates for every hot stove 100a-100d. Next, the hot stove control computer 301 individually sets the flow rate of the combustion gas for each hot stove 100a to 100d using the heat input Q _{in, p} (i, t) after the present time to each hot stove 100a to 100d. calculate. Next, the hot stove control computer 301 instructs the flow rate of the combustion gas to the flow rate controllers 304a to 304d provided corresponding to the hot stove 100a to 100d.
The flow rate controllers 304a to 304d adjust the opening and closing operations of the gas butterfly valves 131a to 131d so that the flow rate instructed from the hot stove control computer 301 becomes as instructed.

Moreover, the hot stove control computer 301 sets the temperature obtained based on the operation of the input device 312 by the operator in the temperature controller 305 as a target value of the temperature of the hot air discharged from the hot stove 100a to 100d. The temperature controller 305 instructs the target opening degree to the opening degree controllers 313a to 313d that adjust the opening and closing operations of the blower butterfly valves 125a to 125d. For example, if it is a period during which air is blown by the two hot stoves 100, the temperature controller 305 opens the opening degree of the blow butterfly valve 125 of the hot stove 100 that blows in advance if the blow temperature is high, The opening degree of the blowing butterfly valve 125 of the hot stove 100 that blows and blows the air is closed. On the other hand, if the blowing temperature is low, the temperature controller 305 closes the opening degree of the blowing butterfly valve 125 of the hot stove 100 that blows in advance, and also sets the blowing butterfly valve 125 of the hot stove 100 that blows behind. Open the opening. Since the hot blast furnace 100 that blows air first is undergoing heat exchange, the hot air temperature is low, and the hot blast furnace 100 that blows air afterwards is sufficiently stored, so the hot air temperature is high. The blowing temperature can be controlled by adjusting the opening degree of the blowing butterfly valve 125 (distribution of air volume). Further, during the air blowing period, the cold air butterfly valve 123 is gradually closed to adjust the air blowing temperature.
The air blower 306 blows the cool air of the air volume set in the air flow rate controller 309. The setting of the blower flow rate controller 309 is changed at the blower factory.
Further, the hot stove control computer 301 causes the display device 303 to display a screen based on the calculation result as described above via the input / output device 302.

Below, an example of the process which the hot stove control computer 301 performs is demonstrated in detail. In the following description, among the processes performed by the hot stove control computer 301, only the configuration and operation necessary for describing the present embodiment will be described, and the configuration and operation of portions unnecessary for describing the present embodiment will be described. Detailed description of the operation is omitted.
The hot stove control computer 301 can be realized by using, for example, a computer including a CPU, a ROM, a RAM, and an HDD. The above-described program is stored in, for example, the HDD and executed by the CPU.

[Functional configuration of hot stove control computer 301]
FIG. 5 is a diagram illustrating an example of a functional configuration of the hot stove control computer 301.
As shown in FIG. 5, the hot stove control computer 301 includes a heat storage target trajectory optimization unit 501, a first process state prediction unit 502, an optimal follow-up control unit 503, and a second process state prediction unit 504. Have.

(Heat storage target trajectory optimization unit 501 and first process state prediction unit 502)
The heat storage amount target trajectory optimization unit 501 and the first process state prediction unit 502 are portions for executing the above-described heat storage amount target trajectory derivation program. As described above, by executing the heat storage amount target trajectory derivation program, the furnace-by-cycle target siliceous brick minimum temperature T _{si, ref} (i, n + j) becomes the optimization time range 602 (j = 0, 1, .., Q). The optimization time range 602 is the time from the cycle to which the current time belongs (cycle number n) until the cycle (cycle number n + q) corresponding to a time longer than the time constant of the hot stove 100a to 100d elapses. Thus, the furnace-specific / cycle-specific target quartz brick minimum temperature T _{si, ref} (i, n + j) is derived over a long period of time, because the furnace-specific / cycle-specific target silica brick minimum temperature T _{si, ref} (i , N + j) reflects the state until the temperature of each part of the hot stove 100a to 100d reaches an equilibrium state.
Hereinafter, an example of the functions of the heat storage amount target trajectory optimization unit 501 and the first process state prediction unit 502 will be described.

FIG. 6 is a diagram conceptually illustrating an example of the target quartz brick minimum temperature T _{si, ref} (i, n + j) and the operation target value (operation condition) by furnace and cycle.
In the heat storage target trajectory optimization unit 501, the operation target value 601 varies between the cycle to which the current time belongs (cycle number n) and the cycle to which the time at which the optimization time range 602 passes (cycle number n + q). It is determined whether or not to do. The operation target value 601 indicates an operation condition, and is, for example, a target blowing temperature BT _ref (time), a target blowing flow rate BV _ref (time)), or a target blowing heat amount obtained therefrom.
As a result of this determination, when the operation target value 601 varies, the following processing is executed. In the example illustrated in FIG. 6, the operation target value 601 varies three times within the optimization time range 602. This determination is made, for example, every 1 [min].

When it is determined that the operation target value 601 is fluctuating as described above, the heat storage amount target trajectory optimization unit 501 selects candidates for the furnace- and cycle-specific target quartz brick minimum temperature T _{si, ref} (i, n + j). Output to the first process state prediction unit 502. Initially, the “initial values of candidates for the furnace-by-cycle / target-by-cycle target quartz brick minimum temperature T _{si, ref} (i, n + j)” input to the input / output device 302 are output to the first process state prediction unit 502. To do.

FIG. 7 shows the target quartz brick minimum temperature T _{si, ref} (i, n + j) by furnace and cycle, the predicted value T _{p, ref} (i, t) of the minimum temperature of quartz brick by furnace and cycle, and the operation target. It is a figure which shows notionally an example of a value (operation conditions) and the input calorie | heat amount Qin _{, p} (i, t) according to a furnace and a cycle.
The first process state predicting unit 502 receives a process model that is a calculation model for individually calculating the process state of the hot stove 100a to 100d by inputting the input heat amount Q _in for each hot stove and the cycle for the hot stove 100a to 100d. The predicted value of the process state of each hot stove 100a-100d is derived. In the present embodiment, the predicted value of the process state of each hot stove 100a to 100d is the amount of heat input Q _{in, p} (i, t) by furnace and cycle after the current time and the minimum temperature of quartz brick by furnace and cycle. It includes the predicted value T _{si, p} (i, t) and the predicted value BT _p (i, t) of the blowing temperature by furnace and by cycle. Here, t represents the number of cycles in the prediction interval 701 or the control interval 702, and is expressed by the following equations (2a) and (2b).
Prediction interval; t = n + d + g, n + d + 1 + g,..., N + m + g (2a)
Control period; t = n + g, n + 1 + g,..., N + s + g (2b)

As described above, n is the number of cycles to which the current time belongs. d represents the number of cycles corresponding to the first cycle of the prediction interval 701. m represents the number of cycles corresponding to the last cycle of the prediction interval 701. g is an integer from 0 (zero) to q−m. That is, the prediction interval 701 is an interval in the range of the cycle number md.
As described above, the prediction interval 701 is obtained by shifting the interval in the range of the cycle number md backward by one cycle until the cycle number corresponding to the last cycle becomes n + q−m. Further, the control section 702 is obtained by shifting the section in the range of the cycle number s backward by one cycle until the cycle number corresponding to the last cycle becomes n + s + q−m.

In the present embodiment, the first process state prediction unit 502 uses a linear time series model as a process model. This is one of the statistical analysis models for calculating the predicted value of the process state for each cycle.
Specifically, the predicted value T _{si, p} (i, t) of the minimum temperature of siliceous bricks by furnace and cycle is obtained by using the following equation (3).

In the equation (3), coefficients a0 · _x (i), b0 · _x (i), and c0 · _x (i) are coefficients input based on the operation of the input device 312. For example, as these coefficients, a coefficient when the form of equation (3) best fits the past operation results of the hot stove 100a to 100d is separately obtained, and the obtained coefficient is input based on the operation of the input device 312. The As a method for adjusting the shape of the expression (3) to the past operation results of the hot stove 100a to 100d, a method such as a least square method is used.
ΔT _{si, p} (i, n + j + 1) is expressed by the following equation (4).
ΔT _{si, p} (i, n + j + 1) = T _{si, p} (i, n + j + 1) −T _{si, p} (i, n + j) (4)

ΔT _si (i, n + j−x) is expressed by the following equation (5).
ΔT _si (i, n + j−x) = T _si (i, n + j−x) −T _si (i, n + j−x−1) (5)
The first process state prediction unit 502 sets the bottom temperature of the quartz brick that is input as the operation result for the past value of the minimum temperature T _si (i, n + j−x) of the quartz brick by furnace and cycle. . On the other hand, for the future value, the predicted value T _{si, p} (i, t) of the minimum temperature for each brick and furnace for each cycle obtained by the equation (4) is set.

ΔQ _in (i, n + j + 1−x) is expressed by the following equation (6).
ΔQ _in (i, n + j + 1−x) = Q _in (i, n + j + 1−x) −Q _in (i, n + j−x) (6)
The first process state prediction unit 502 sets the past value of the input heat quantity Q _{in, p} (i, t) for each furnace and cycle for the past value of Q _in (i, n + j + 1−x). To do. On the other hand, with regard to future values, the amount of heat input Q _{in, p} (i, t) by furnace and cycle after the present time already derived at the present time and the present time and later in the control section 702 that is the object of calculation at the present time. Are set as candidates for the heat input Q _{in, p} (i, n + g) to Q _{in, p} (i, n + s + g).

ΔQ _out (i, n + j + 1−x) is expressed by the following equation (7).
ΔQ _out (i, n + j + 1−x) = Q _out (i, n + j + 1−x) −Q _out (i, n + j−x) (7)
Q _out is the blast heat quantity [J]. The first process state prediction unit 502 determines the past value of the blast heat quantity Q _out (i, n + j + 1−x) by furnace and cycle, and the furnace obtained from the blast temperature and the blast flow rate input as the operation results. Set the blast heat quantity for each cycle. On the other hand, for the future value, the blown heat amount for each furnace / cycle determined from the operation target values (target blown temperature BT _ref (time), target blown flow rate BV _ref (time)) is set.
As described above, the first process state prediction unit 502 sets at least the predicted values T _{si, p} (i, t) of the quartz brick minimum temperature by furnace and by cycle at i = 1 to 4, t = n. Each of ˜n + m + g is derived. And the 1st process state prediction part 502 of i = 1-4, t = n + d + g-n + m + g among prediction value Tsi _{, p} (i, t) of the derived siliceous brick minimum temperature classified by furnace and cycle. The value is adopted as the predicted value T _{si, p} (i, t) of the minimum temperature of the silica brick by furnace and cycle in the prediction interval 701.

Moreover, the predicted value BT _p (i, t) of the ventilation temperature by furnace and by cycle is obtained by using the following equation (8).

In the equation (8), coefficients a 1 · _x (i), b 1 · _x (i), and c 1 · _x (i) are coefficients input based on the operation of the input device 312. These coefficients _{a1 · x (i), b1} · x (i), c1 · x (i) be a coefficient _{a0 · x (i), b0} · x (i), in the same manner as c0 · _x (i) It is obtained in advance.
ΔBT _p (i, n + j + 1) is expressed by the following equation (9).
ΔBT _p (i, n + j + 1) = BT _p (i, n + j + 1) −BT _p (i, n + j) (9)

ΔBT (i, n + j−x) is expressed by the following equation (10).
ΔBT (i, n + j−x) = BT (i, n + j−x) −BT (i, n + j−x−1) (10)
The first process state prediction unit 502 sets the blowing temperature input as the operation result for the past value among the blowing temperature BT (i, n + j−x) for each furnace and each cycle. On the other hand, for the future value, the predicted value BT _p (i, t) of the furnace-by-furnace and cycle-by-cycle blowing temperature obtained so far by the equation (8) is set.
ΔQ _in (i, n + j + 1−x) and ΔQ _out (i, n + j + 1−x) are expressed by the above-described equations (6) and (7), respectively.

As described above, the first process state predicting unit 502 performs the predicted values of the minimum temperature of siliceous bricks by furnace and cycle in the prediction interval 701 from T _{si, p} (i, n + d + g) to T _{si, p} (i, n + m + g). ) And predicted values BT _p (i, n + d + g) to BT _p (i, n + m + g) of the blowing temperature by furnace and cycle in the prediction section 701 are derived, the furnace-specific objective function J _{1 of the} following equation (11) In order to minimize the value of the evaluation value of (i) within the range satisfying the constraint conditions of the following equations (12) and (13), the input heat quantity Q _{in, p} (i , T), it is determined using an optimization method how much each candidate value should be changed. This determination logic can be realized by a known method such as GA, hill climbing, and linear programming. The amount of change in candidate heat quantity Q _{in, p} (i, t) for each furnace and cycle after the present time in the control section 702 is determined according to this logic. Based on this change amount, the first process state predicting unit 502 determines whether the evaluation value of the furnace-specific objective function J ₁ (i) in the equation (11) is the minimum value in the control section 702 after the present time. By changing the candidate value of the input heat amount Q _{in, p} (i, t) for different / cycle, the calculation of the above-described equations (3) to (13) is repeated.

In the equation (11), T _{si, err} (i, t) is represented by the following equation (14), and ΔQ _in (i, t) is represented by the following equation (15).
T _{si, err} (i, t) = T _{si, ref} (i, t) −T _{si, p} (i, t) (14)
ΔQ _in (i, t) = Q _in (i, t) −Q _in (i, t−1) (15)
Further, in the expressions (12) and (13), Th ₁ (i) and Th ₂ (i) are threshold values and are set in advance. Moreover, BT _{p, min} (i, t) indicates that it is the lowest value of the predicted value BT _p (i, t) of the blowing temperature by furnace and by cycle. BT _ref (i, t) is a target air temperature. As described above, in the present embodiment, the target blowing temperature BT _ref (time) is dependent on the time without depending on the furnace i time, the target blowing temperature time time corresponding to the cycle t BT _ref (time ) Is adopted as BT _ref (i, t).
The first term on the right side of the equation (11) is the predicted value T _{si, p} (i, t) of the minimum temperature of siliceous bricks by furnace / cycle in the prediction interval 701, and the target minimum temperature T of silica bricks by furnace / cycle. It is an objective function whose purpose is to follow _{si, ref} (i, n + j) well. The second term on the right side of the equation (11) is an objective function that aims to reduce the fluctuation of the input heat quantity Q _in (i, t) for each furnace in cycles adjacent to each other in the same hot stove 100. It is. The furnace specific objective function shown in the equation (11) is expressed by a weighted linear sum of these objective functions. W ₁ (i) and W ₂ (i) in equation (11) are weighting factors for each term of the furnace-specific objective function shown in equation (11).

The first process state predicting unit 502 calculates the “predicted value T of the minimum temperature of quartz brick by furnace and by cycle when the evaluation value of the objective function by furnace J ₁ (i) of equation (11) is minimized. _{Candidates of si, p} (i, n + d + g) to T _{si, p} (i, n + m + g) and furnace and cycle input heat amounts Q _{in, p} (i, n) to Q _in (i, n + s + g) ) ”Is output (returned) to the heat storage target trajectory optimization unit 501.

The derivation of the predicted values of the process states of the hot stoves 100a to 100d as described above is sequentially performed by shifting the prediction interval 701 and the control interval 702 backward by one cycle. For example, a cycle section of the cycle number n + d to n + m is set as the prediction section 701, and a cycle section of the cycle number n to n + s is set as the control section 702, so that the process state of each hot stove 100a to 100d When the predicted value is derived, next, a cycle interval of cycle number n + d + 1 to n + m + 1 is set as prediction interval 701, and a cycle interval of cycle number n + 1 to n + s + 1 is set as control interval 702. A predicted value of the process state of the furnaces 100a to 100d is derived.
When the predicted value of the process state when the last cycle of the prediction section 701 is the cycle of the number of cycles n + q is derived, the derivation of the predicted value of the process state is terminated. By doing in this way, the predicted value of the process state in each cycle of the number of cycles n to n + q−m is derived. Here, the predicted value of the latest process state among the predicted values of the process state derived in the same cycle is adopted.

When the heat storage amount target trajectory optimization unit 501 receives the predicted values of the process states of the hot stove 100a to 100d from the first process state prediction unit 502, the furnace specific objective function J ₂ (Equation 16) below ( In order to minimize the evaluation value of i), optimize how much each candidate value of the target quartz brick minimum temperature T _{si, ref} (i, n + j) should be changed Judge using a method. This determination logic can be realized by a known method such as GA, hill climbing, and linear programming. The candidate change amount of the target quartz brick minimum temperature T _{si, ref} (i, n + j) for each furnace / cycle is determined according to this logic. Based on this change amount, the target quartz brick minimum temperature T _{si, ref} (i) for each furnace / cycle until the value of the evaluation value of the objective function J ₂ (i) for each furnace in equation (16) can be regarded as the minimum. , N + j), the values of the above equations (3) to (16) are repeated.

In the equation (16), T _{si, m} (i, t) is a lower limit value of the minimum temperature of the quartz brick by furnace and by cycle.
The first term on the right side of the equation (16) includes the predicted value T _{si, p} (i, t) of the minimum temperature of silica bricks by furnace and cycle, and the target minimum temperature of bricks T _{si, ref} (i, by cycle and furnace). n + j) represents the maximum value in the optimization time range 602 of the absolute value of the difference from n + j). Therefore, the first term on the right side of equation (16) is that the predicted value T _{si, p} (i, t) of the furnace-by-cycle-by-cycle quartz brick minimum temperature is used as the furnace-by-cycle-by-cycle target quartz brick minimum temperature T _{si, ref.} It is an objective function intended to follow (i, t) well.

Further, the second term on the right side of the equation (16) represents the total sum in the optimization time range 602 of the input heat quantity Q _{in, p} (i, t) by furnace and cycle. Therefore, the second term on the right side of the equation (16) is an objective function for the purpose of reducing the input heat quantity Q _{in, p} (i, t) for each furnace and each cycle.
In addition, the third term on the right side of the equation (16) is the predicted value T _{si , m of the} minimum temperature of silica bricks by furnace / cycle from the lower limit value T _{si, m} (i, t) of each furnace / cycle. _{, p} (i, t) and the maximum value in the optimization time range 602 of the larger value of 0 (zero). Therefore, the third term on the right side of the equation (16) is that the lower limit value T _{si, m} (i, t) of the minimum temperature of siliceous brick by furnace / cycle is the predicted value T _{si of the} minimum temperature of silica brick by furnace / cycle. _{, p} (i, t) is an objective function whose purpose is to suppress the increase. The furnace-specific objective function of equation (16) is represented by these weighted linear sums. W ₃ (i), W ₄ (i), and W ₅ (i) in equation (16) are weighting factors for each term of the furnace-specific objective function shown in equation (16).

When the predicted value T _{si, p} (i, t) of the minimum temperature of siliceous bricks by furnace / cycle is smaller than the lower limit value T _{si, m} (i, t) of the minimum temperature of silica bricks by furnace / cycle, heat storage The amount is insufficient and the hot air necessary for the blast furnace cannot be supplied. Therefore, the objective function shown in the third term of equation (16) is introduced.
Here, an example of a method for deriving the lower limit value T _{si, m} (i, t) of the minimum temperature of the quartz brick by furnace and by cycle will be described.

In the present embodiment, the lower limit value T _{si, m} (i of the minimum temperature of the quartz brick by furnace and by cycle, which is an index of the residual heat amount of the quartz brick at the end of the blowing period and can be measured. , T). In the following description, this index is referred to as “residual heat index” as necessary.
In the present embodiment, any one of the opening degree of the cold air butterfly valve 123, the opening degree of the blowing butterfly valve 125, and the blowing temperature measured by the hot air thermometer 310 is used as the residual heat amount index.
Specifically, when the cold air butterfly valve 123 is opened to allow cold air to flow into the mixed cooling chamber 103 (so-called mixed cooling is performed), the opening degree of the cold air butterfly valve 123 is used as a residual heat amount index. On the other hand, in the case where the cool air butterfly valve 123 is closed and the cool air is not allowed to flow into the mixed cooling chamber 103 (so-called mixed cooling is not performed), the opening degree of the blow butterfly valve 125 and the blowing temperature measured by the hot air thermometer 310 Any of these is used as a residual heat amount index.

Here, the reason why the opening degree of the cold air butterfly valve 123 is used as a residual heat amount index when performing mixed cooling will be described.
FIG. 8 is a diagram illustrating an example of the relationship between the flow rate of cold air flowing into the mixed cooling chamber 103 and time, and the relationship between the blowing temperature measured by the hot air thermometer 310 and time. Note that the waveforms in FIG. 8 are shown for explanation, and the actual waveforms are not necessarily like this.
The first waveform 801 from the top in FIG. 8 shows the waveform of the blowing temperature when the cold-air butterfly valve 123 is fully closed. The second waveform 802 from the top in FIG. 8 is the waveform of the cold air flow rate in one hot stove 100 for changing the first waveform 801 from the top in FIG. 8 to the third waveform 803 from the top in FIG. Show. The blowing temperature shown in the third waveform 803 from the top in FIG. 8 corresponds to the blowing temperature that is an operational target.

  The opening degree of the cold-air butterfly valve 123 is changed every 1 [sec] according to a predetermined opening pattern with the goal that the opening degree at the end of the blowing period becomes a target value (here, 0 (zero)). It is assumed that the blower butterfly valve 125 is maintained at a constant opening while the cold air butterfly valve 123 is open. Further, while the cold air butterfly valve 123 is open in the preceding hot air furnace 100, the cold air butterfly valve 123 is fully closed in the subsequent hot air furnace 100. One mountain of the waveforms 801 and 802 corresponds to one blowing period of the hot stove 100 preceded.

  As shown in FIG. 8, when the air temperature is high, the cold air flow rate is increased. On the other hand, when the air temperature is low, the cold air flow rate is decreased. And if the opening degree of the cold wind butterfly valve 123 of the said hot stove 100 when the ventilation period of one certain hot stove 100 is complete | finished is a target value (here 0 (zero)), the said hot stove 100 The amount of heat stored during the combustion period of the cycle can be supplied to the blast furnace without waste, and the amount of residual heat of the heat storage brick of the hot stove 100 can be regarded as unchanged from the amount of residual heat before one cycle. Strictly speaking, it can be said that the residual heat amount of the regenerative brick of the hot stove 100 does not change from the residual heat amount one cycle before the target value of the opening degree of the cold air butterfly valve 123 is 0 (zero). Is the case. However, in actual operation, a value slightly larger than 0 (zero) may be set as a target value with a margin.

FIG. 9 is a diagram showing the relationship between the opening degree of the cold air butterfly valve 123 and the time, and the waveform of FIG. 9 is also shown for explanation, and the actual waveform is not necessarily in this way. Don't be.
A waveform 901 in FIG. 9 shows a waveform of the opening degree of the cold air butterfly valve 123 of the hot stove 100.
In FIG. 9, time t _E is the time when the blowing period of the preceding hot stove 100 ends, and time t _C is the time when the blowing period of the succeeding hot stove 100 starts (preceding hot stove 100. Is the time when the opening degree of the cold air butterfly valve 123 becomes 0 (zero)).

As shown in FIG. 9, there is a case where the operation is performed with the goal of setting the opening degree of the cold air butterfly valve 123 to 0 (zero) before the air blowing period ends. In this case, if the period (= t _E −t _C ) from when the opening degree of the cold air butterfly valve 123 of a certain hot stove 100 becomes 0 (zero) until the air blowing period ends is as the target, It can be considered that the residual heat amount of the heat storage brick of the hot stove 100 when the air blowing period ends does not change from the residual heat amount of the previous cycle. Further, if this period is longer than the target, the residual heat amount of the heat storage brick of the hot stove 100 at the end of the air blowing period is smaller than the residual heat amount of one cycle before. It can be considered that the residual heat amount of the heat storage brick of the hot stove 100 when the period ends is larger than the residual heat amount one cycle before. In the following description, this period is referred to as a “fully closed period” as necessary.

Further, as described above, even if the opening degree of the cold air butterfly valve 123 is set to 0 (zero) when the air blowing period ends, the opening degree of the cold air butterfly valve 123 becomes 0 before the air blowing period ends. (Zero). In this case, it can be considered that the longer the fully closed period, the smaller the remaining heat amount of the heat storage brick of the hot stove 100 when the blowing period ends is smaller than the remaining heat amount before one cycle.
As described above, since the opening degree of the cold air butterfly valve 123 has a correlation with the residual heat amount of the heat storage brick of the hot stove 100, in the present embodiment, the opening degree of the cold air butterfly valve 123 is used when performing mixed cooling. Is used as a residual heat index.

Next, the reason why either the opening degree of the blower butterfly valve 125 or the blower temperature measured by the hot air thermometer 310 is used as the residual heat amount index when no mixed cooling is performed will be described.
FIG. 10 is a diagram showing an example of the relationship between the opening degree of the blower butterfly valve 125 and time. Note that the waveform of FIG. 10 is also shown for explanation, and the actual waveform is not necessarily like this. It will not be.
A waveform 1001 in FIG. 10 shows a waveform of the opening degree of the blowing butterfly valve 125 of the preceding hot stove furnace 100, and a waveform 1002 shows a waveform of the opening degree of the blowing butterfly valve 125 of the subsequent hot stove furnace 100.
In FIG. 10, time t _E is the time when the blowing period of the preceding hot stove 100 ends, and time t _C is the time when the blowing period of the subsequent hot stove 100 starts.

  As shown in FIG. 10, when the blowing period of the preceding hot stove 100 starts, the opening degree of the blowing butterfly valve 125 of the preceding hot stove 100 is maintained at a constant target value (a value that is fully opened or close to fully opened). Further, the opening degree of the blowing butterfly valve 125 of the hot stove 100 that follows is also maintained at a constant target value (a value that is fully closed or a value close to full closing).

  Thereafter, the opening temperature of the blower butterfly valve 125 of the preceding hot stove 100 and the blower butterfly valve 125 of the succeeding hot stove 100 are adjusted to adjust the blowing temperature. More specifically, since the temperature of the hot air blown from the preceding hot stove 100 to the blast furnace is decreasing, the opening degree of the blow butterfly valve 125 of the preceding hot stove 100 is gradually reduced and the hot hot air is heated. Is gradually increased (see waveforms 1001 and 1002 in FIG. 10).

Here, when the blowing period of the preceding hot stove 100 ends (time t _E ), the opening degree of the blowing butterfly valve 125 of the preceding hot stove 100 is the target value (a value close to or fully closed). In addition, when the blowing period of the preceding hot stove 100 ends (time t _E ), the opening degree of the blowing butterfly valve 125 of the succeeding hot stove 100 is the target value (fully open or close to fully open). Value).

Therefore, if the opening degree of the blower butterfly valve 125 of the hot stove 100 at the end of the blowing period of the preceding hot stove 100 (time t _E ) is the target value (fully closed or close to fully closed), It can be considered that the residual heat amount of the heat storage brick of the hot stove 100 does not change from the residual heat amount one cycle before. Strictly speaking, it can be said that there is no change in the residual heat amount of the heat storage brick of the hot stove 100 from the residual heat amount before one cycle when the target value of the blow butterfly valve 125 is 0 (zero). However, in actual operation, a value slightly larger than 0 (zero) may be set as a target value with a margin. Moreover, if the opening degree of the blowing butterfly valve 125 of the hot stove 100 at the time when the blowing period of the preceding hot stove 100 ends (time t _E ) is larger than the target value, the hot air at the end of the blowing period. If the residual heat amount of the regenerative brick of the furnace 100 is larger than the residual heat amount before one cycle, and if it is smaller, the residual heat amount of the regenerative brick of the hot air furnace 100 when the blowing period ends is larger than the residual heat amount before one cycle. Can also be considered small.

The above also applies to the blowing temperature. If the blowing temperature at the preceding hot stove 100 ends (time t _E ) is the target value, the residual heat amount of the regenerative brick of the hot stove 100 is as follows. It can be considered that there is no change from the amount of residual heat before one cycle. Also, if the blowing temperature at which the blowing period of the hot air furnace 100 the preceding has ended (time t _E) is greater than the target value, the residual heat of the heat storage bricks of the hot air oven 100 when the blowing period is completed, If it is larger and smaller than the remaining heat amount before one cycle, it can be considered that the remaining heat amount of the heat storage brick of the hot stove 100 when the blowing period ends is smaller than the remaining heat amount before one cycle.
As described above, since the opening degree of the blowing butterfly valve 125 and the blowing temperature measured by the hot air thermometer 310 have a correlation with the residual heat amount of the heat storage brick of the hot stove 100, in this embodiment, mixed cooling is performed. When not performing, either the opening degree of the ventilation butterfly valve 125 or the ventilation temperature measured by the hot air thermometer 310 is used as the residual heat amount index.

Next, a specific residual heat index when performing mixed cooling will be described.
FIG. 11 is a diagram for explaining an example of a specific residual heat amount index when mixed cooling is performed.
As shown in FIG. 11, in the present embodiment, any one of the following five is used as a residual heat index when mixed cooling is performed.
(1) N minutes before the end of blowing The n minutes before the end of blowing shown in FIG. 11 means that the opening degree of the cold wind butterfly valve 123 n minutes before the end of the blowing period is used as a residual heat amount index. If the target value of this residual heat index is the R1 target, the actual measurement value is the R1 actual result, and the correction gain is k1_ (> 0 (zero)), the amount of change in the lower limit value T _{si, m} of the minimum brick temperature for each furnace and cycle ΔT _{si, m} is expressed by the following equation (17).
ΔT _{si, m} = k1_ × (R1 target−R1 actual result) (17)
Here, the correction gain k1_ in the case of R1 target ≧ R1 results is k11, and the correction gain k1_ in the case of R1 target <R1 results is k12. These correction gains k11 and k12 may be the same or different. Further, a reference time T1 corresponding to the n is set.

FIG. 12 is a diagram showing an example of the relationship between the opening degree and time of the cold air butterfly valve 123 of a certain hot stove 100 in one cycle. Note that the waveforms in FIG. 12 are also shown for explanation, and the actual waveforms are not necessarily like this.
A waveform 1201 in FIG. 12 shows a waveform of the opening degree of the cold air butterfly valve 123 of the hot stove 100.
In FIG. 12, time t _S is the time when the blowing period of the hot stove 100 starts, and time t _E is the time when the blowing period of the hot stove 100 ends.
As shown in FIG. 12, if the target value of the opening 1202 of the cold air butterfly valve 123 at the time before the reference time T1 before the time t _E when the air blowing period of the hot stove 100 ends is compared with the actual measurement value, It is possible to evaluate how much the measured value of the opening 1202 of the butterfly valve 123 is lower than the target value (how much the residual heat amount of the heat storage brick when the air blowing period ends is smaller than that before one cycle). it can. On the other hand, when the target value of the opening degree 1202 of the cold air butterfly valve 123 is compared with the actual measurement value at time t _E when the air blowing period of the hot stove 100 ends, such an evaluation cannot be performed.

(2) Max for 1 minute to start blowing
The air blowing start n minutes Max shown in FIG. 11 means the maximum value of the opening degree of the cold air butterfly valve 123 in the n minutes after the air blowing period starts. Assuming that the target value of this residual heat index is R2 target, the actual measurement value is R2 actual, and the correction gain is k2_ (> 0 (zero)) _, the change amount of the lower limit value T _{si, m} of the minimum brick temperature for each furnace and cycle ΔT _{si, m} is expressed by the following equation (18).
ΔT _{si, m} = k2_ × (R2 target−R2 actual result) (18)
Here, the correction gain k2_ in the case of R2 target ≧ R2 results is k21, and the correction gain k2_ in the case of R1 target <R1 results is k22. The values of these correction gains k21 and k22 may be the same or different. Also, a reference time T2 corresponding to the n is set.

(3) Single fan Max
The single blower Max shown in FIG. 11 is the maximum opening degree of the cold air butterfly valve 123 during a period when only one hot stove 100 is blowing (while only one hot stove 100 is in the blowing period). Mean value.
If the target value of this residual heat index is the R3 target, the actual measurement value is the R3 actual result, and the correction gain is k3_ (> 0 (zero)), the amount of change in the lower limit value T _{si, m} of the minimum brick temperature for each furnace and cycle ΔT _{si, m} is expressed by the following equation (19).
ΔT _{si, m} = k3_ × (R3 target−R3 result) (19)
Here, the correction gain k3_ in the case of R3 target ≧ R3 results is k31, and the correction gain k3_ in the case of R3 target <R3 results is k32. The values of these correction gains k31 and k32 may be the same or different.

(4) Opening degree at the end of blowing The opening degree at the end of blowing shown in FIG. 11 means the opening degree of the cold air butterfly valve 123 when the blowing period ends.
Assuming that the target value of this residual heat index is R4 target, the actual measurement value is R4 actual, and the correction gain is k4_ (> 0 (zero)) _, the change amount of the lower limit value T _{si, m} of the minimum brick temperature for each furnace and cycle ΔT _{si, m} is expressed by the following equation (20).
ΔT _{si, m} = k4_ × (R4 target−R4 result) (20)
Here, the correction gain k4_ in the case of R4 target ≧ R4 results is k41, and the correction gain k4_ in the case of R4 target <R4 results is k42. The values of these correction gains k41 and k42 may be the same or different. In addition, since there is no negative value for the opening, when the R4 target is 0 (zero), the condition of R4 target> R4 performance is not satisfied.

(5) Fully closed time before the end of blowing The fully closed time before the end of blowing shown in FIG. 11 means the fully closed time when the fully closed time is set.
When the target value of this residual heat index is T5 target, the actual measurement value is T5 actual, and the correction gain is k5_ (> 0 (zero)), the amount of change in the lower limit value T _{si, m} of the minimum brick temperature for each furnace and cycle ΔT _{si, m} is expressed by the following equation (21).
ΔT _{si, m} = k5_ × (T5 result−T5 target) (21)
Here, the correction gain k5_ in the case of T5 target ≧ T5 results is k51, and the correction gain k5_ in the case of T5 target <T5 results is k52. The values of these correction gains k51 and k52 may be the same or different.

FIG. 13 is a diagram for explaining a specific residual heat index when no cooling is performed.
FIG. 13 is a diagram for explaining an example of a residual heat index when no cooling is performed. Specifically, FIG. 13A shows the case where the remaining heat index is the opening degree of the blower butterfly valve 125, and FIG. 13B shows the case where the remaining heat index is the blowing temperature.
As shown in FIGS. 13A and 13B, in the present embodiment, any one of the following five is used as a residual heat amount index when no cooling is performed.
(6) N minutes before the end of air blowing n minutes before the end of air blowing shown in FIG. 13 (a) means that the opening degree of the butterfly valve 125 n minutes before the time when the air blowing period ends is used as a residual heat amount index. To do.
Assuming that the target value of this residual heat index is R6 target, the actual measurement value is R6 actual, and the correction gain is k6_ (> 0 (zero)) _, the change amount of the minimum temperature Tsi _{, m} of the minimum brick temperature for each furnace and cycle ΔT _{si, m} is expressed by the following equation (22).
ΔT _{si, m} = k6_ × (R6 target−R6 actual result) (22)
Here, the correction gain k6_ in the case of R6 target ≧ R6 results is k61, and the correction gain k6_ in the case of R6 target <R6 results is k62. The values of these correction gains k61 and k62 may be the same or different. Further, a reference time T6 corresponding to the n is set.

(7) Opening degree at the end of blowing The opening degree at the end of blowing shown in FIG. 13A means the opening degree of the blowing butterfly valve 125 when the blowing period ends.
Assuming that the target value of this residual heat index is R7 target, the actual measurement value is R7 actual, and the correction gain is k7_ (> 0 (zero)), the amount of change in the lower limit value T _{si, m} of the minimum brick temperature for each furnace and cycle ΔT _{si, m} is expressed by the following equation (23).
ΔT _{si, m} = k7_ × (R7 target−R7 actual result) (23)
Here, the correction gain k7_ in the case of R7 target ≧ R7 results is k71, and the correction gain k7_ in the case of R7 target <R7 results is k72. The values of these correction gains k71 and k72 may be the same or different. In addition, since there is no negative value for the opening, when the R7 target is 0 (zero), the condition of R7 target> R7 performance is not satisfied.

(8) Ave end n minutes Ave
The blast end n minutes Ave shown in FIG. 13B is the average value of the blast temperature in n minutes up to the time when the blast period ends (the period from the time before n minutes to the time when the blast period ends). Means.
If the target value of this residual heat index is R8 target, the actual measurement value is R8 actual result, and the correction gain is k8_ (> 0 (zero)), the amount of change in the lower limit value T _{si, m} of the minimum brick temperature for each furnace and cycle ΔT _{si, m} is expressed by the following equation (24).
ΔT _{si, m} = k8_ × (R8 target−R8 actual result) (24)
Here, the correction gain k8_ in the case of R8 target ≧ R8 results is k81, and the correction gain k8_ in the case of R8 target <R8 results is k82. The values of these correction gains k81 and k82 may be the same or different. Further, a reference time T8 corresponding to the n is set.

(9) Min for min for blowing
The air blowing end n minutes Min in FIG. 13B is the minimum value of the air blowing temperature in n minutes until the time when the air blowing period ends (the period from the time before n minutes to the time when the air blowing period ends). means. If the target value of this residual heat index is R9 target, the actual measurement value is R9 actual, and the correction gain is k9_ (> 0 (zero)), the amount of change in the lower limit value T _{si, m} of the minimum brick temperature for each furnace and cycle ΔT _{si, m} is expressed by the following equation (25).
ΔT _{si, m} = k9_ × (R9 target−R9 actual result) (25)
Here, the correction gain k9_ in the case of R9 target ≧ R9 results is k91, and the correction gain k9_ in the case of R9 target <R9 results is k92. The values of these correction gains k91 and k92 may be the same or different. Further, a reference time T9 corresponding to the n is set.

(10) Air blow end temperature The air blow end temperature in FIG. 13B means the air blow temperature when the air blowing period ends.
Assuming that the target value of this residual heat index is R10 target, the actual measurement value is R10 actual, and the correction gain is k10_ (> 0 (zero)) _, the change amount of the lower limit value T _{si, m} of the minimum brick temperature for each furnace and cycle ΔT _{si, m} is expressed by the following equation (26).
ΔT _{si, m} = k10_ × (R10 target−R10 actual result) (26)
Here, the correction gain k10_ in the case of R10 target ≧ R10 results is k101, and the correction gain k10_ in the case of R10 target <R10 results is k102. These correction gains k101 and k102 may be the same or different.

  In the present embodiment, the air temperature, which is the residual heat index of (6) to (10) described above, is measured by the hot air thermometer 310 as described above. In the present embodiment, the R1 results to the R10 results described above are actual values obtained in the latest blowing period among the blowing periods that have already ended at the current time.

FIG. 14 is a diagram illustrating an example of a residual heat amount index setting screen for setting the above remaining heat amount index.
The hot stove control computer 301 displays the remaining heat amount index setting screen 1400 on the display device 303 before the processing of each unit shown in FIG. 5 is started, and is performed by an operator using the input device 312 for the remaining heat amount index setting screen 1400. Based on the contents of the operation, the remaining heat amount index to be applied is selected and selected from the remaining heat amount indexes of (1) to (10) described above in each of the four hot stove furnaces 100a to 100d (hot air furnaces 1 to 4). A target value and a correction gain corresponding to the remaining heat amount index are acquired. If the selected residual heat index requires a reference time, the hot stove control computer 301 also acquires the reference time.

  In the example illustrated in FIG. 10, the determination condition column is a column for displaying a pull-down menu, and any one of the remaining heat index (1) to (10) described above can be selected. Yes. In the example illustrated in FIG. 10, the case where the above-described (4) opening degree at the time of air blowing is set for all the hot stoves 100 a to 100 d (hot stoves 1 to 4) is shown as an example. As described above, (4) the opening degree at the time of the end of blowing is a residual heat amount index that does not have a reference time, so that the reference time cannot be set.

Here, in this embodiment, it is assumed that different residual heat index can be set for each of the hot stoves 100a to 100d (hot stoves 1 to 4). However, the residual heat index when performing mixed cooling (remaining heat index of (1) to (5) described above) and the remaining heat index when not performing mixed cooling (remaining heat indexes of (6) to (10) described above) It is assumed that the heat quantity index) cannot be set at the same time. Moreover, a different target value shall be set with respect to each hot stove 100a-100d (hot stove 1-4). The same applies to the reference time.
In this embodiment, it is assumed that the correction gains k1_ to k10_ are set in the hot stove control computer 301 in advance. However, an input field for correction gains k1_ to k10_ may be added to the residual heat amount index setting screen 1400, and the correction gains k1_ to k10_ may be set using the input field.
When an OK button 1401 on the remaining heat index setting screen 1400 is pressed, the hot stove control computer 301 sets the content input on the remaining heat index setting screen 1400 as information on the remaining heat index. On the other hand, when the cancel button 1402 on the remaining heat amount index setting screen 1400 is pressed, the hot stove control computer 301 displays the remaining heat amount index setting screen 1400 without accepting the content input to the remaining heat amount index setting screen 1400. Turn off.

The heat storage target trajectory optimizing unit 501 determines the lower limit value T _{si, m} (i, t) of the minimum temperature of the quartz brick by furnace and by cycle based on the residual heat index set for each hot stove i. The amount of change ΔT _{si, m} is derived, and the minimum value of the minimum temperature T _{si, m} (i, t) of the minimum temperature of siliceous bricks by furnace, by furnace and by cycle is changed to the minimum value of siliceous brick by furnace and by cycle. The change amount ΔT _{si, m} of the lower limit value T _{si, m} of the temperature is added to update the lower limit value T _{si, m} (i, t) of the minimum temperature of the quartz brick by furnace, by furnace, and by cycle. The heat storage target trajectory optimizing unit 501 sets the lower limit value T _{si, m} (i, t) of the minimum temperature for each furnace and cycle for the silica brick obtained in this way to the equation (16).

For example, as illustrated in FIG. 14, when the above-described (4) opening degree at the end of blowing is set as the residual heat amount index, the heat storage amount target trajectory optimization unit 501 includes the hot air furnaces 100a to 100d (hot air furnaces 1 to 1). The opening degree of the cold air butterfly valve 123 at the time when the latest blowing period of 4) ends is acquired as the R4 performance, and the R4 target set in the residual heat amount index setting screen 1400 shown in FIG. 14 is acquired. Furthermore, the heat storage amount target trajectory optimization unit 501 acquires the correction gain k41 when the R4 target is equal to or greater than the R4 performance, and acquires the correction gain k42 otherwise. Then, the heat storage target trajectory optimization unit 501 substitutes the acquired information into the equation (20) _, and derives the change amount ΔT _{si, m} of the lower limit value T _{si, m} of the minimum temperature of the silica brick by furnace and by cycle. In addition, it is added to the lower limit value T _{si, m} of the current minimum temperature of silica bricks by furnace and cycle.

However, when the lower limit value T _{si, m of} the furnace-by-furnace and quartz-by-cycle minimum temperature updated as described above is lower than the transformation point temperature of the silica-brick 111, the heat storage target trajectory optimization unit 501 The transformation point temperature of the quartz brick 111 is set as the lower limit value T _{si, m} of the minimum quartz brick temperature by furnace and cycle.
In addition, as an initial value of the lower limit value T _{si, m} of the quartz brick minimum temperature by furnace and cycle, for example, the quartz brick lower end temperature measured by the quartz brick thermometers 315a to 315d at the timing when the control of the input heat amount is started. T _si is adopted.

(Optimal follow-up control unit 503, second process state prediction unit 504)
The optimum follow-up control unit 503 and the second process state prediction unit 504 are portions that execute the aforementioned input heat amount derivation program. As described above, when the heat storage target trajectory optimization unit 501 derives the furnace-by-cycle target siliceous brick minimum temperature T _{si, ref} (i, n + j) in the optimization time range 602, the furnace-by-furnace / cycle A predicted value T _{si, p} (i, n + j) of another minimum temperature of silica brick is derived in the prediction interval 701. As described above, the prediction interval 701 is a period ahead of the cycle number d to m from the cycle (cycle number n) to which the current time belongs. Moreover, the time corresponding to the cycle number n + m is a time shorter than the time constant of the hot stove 100a to 100d. As described above, the time corresponding to the number of cycles n + m is set to be the time that is less than the time constant of the hot stove 100a to 100d. The predicted value T _{si, p} (i, n + j) If too much time is derived, if there is a change in operation or the like, many of the derived values may be wasted.

And, the predicted value T _{si, p} (i, n + j) of the minimum temperature of siliceous bricks by furnace and by cycle follows the target siliceous brick minimum temperature T _{si, ref} (i, n + j) by furnace and cycle, The amount of heat input Q _{in, p} (i, n + g) to Q _{in, p} (i, n + s + g) for each furnace and cycle after the present time in the control section 702 is derived. The control section 702 is a period in the range of the cycle number s.
Hereinafter, an example of the functions of the optimum tracking control unit 503 and the second process state prediction unit 504 will be described.

The optimum tracking control unit 503 determines for each hot stove 100a to 100d whether or not a predetermined time within the switching time before the combustion period of each cycle has started.
As a result of this determination, when any of the hot stoves 100a to 100d reaches a predetermined time within the switching time before the combustion period of each cycle starts, the following processing is executed.

The optimum follow-up control unit 503 sets candidates for the input heat amounts Q _{in, p} (i, n + g) to Q _{in, p} (i, n + s + g) for each furnace and cycle after the current time in the control section 702 as the second process state prediction unit. Output to 504. First, from the cycle (cycle number n-s-1) that is s-1 ahead of the cycle to which the current time belongs (cycle number n-s-1), the cycle that is one cycle before the cycle to which the current time belongs (cycle number). The values of the heat input Q _{in, p} (i, t) for each furnace and cycle after the present time until n-1) Q _{in, p} (i, ns-1) to Q _{in, p} (i, n− 1) is output to the second process state prediction unit 504.

The second process state prediction unit 504 executes a hot stove simulator. The hot stove simulator is constructed using a hot stove model that faithfully reproduces the heat exchange performed in the hot stove 100 by using combustion and blowing by utilizing thermophysics. Similarly to the linear time-series model, the hot stove simulator is a calculation model that inputs the heat input Q _in for each furnace and cycle for the hot stove 100a to 100d and individually calculates the process state of the hot stove 100a to 100d. It is a process model. However, the hot stove simulator calculates the predicted value of the process state at a time interval less than one cycle, and can calculate the predicted value of the process state more strictly than the linear time series model.
FIG. 15 is a diagram conceptually illustrating an example of a hot stove model. Here, an example of a hot stove model in the heat storage chamber 101 is shown.
In the hot stove model described in this embodiment, it is assumed that the shape of the heat storage chamber 101 is a cylinder. And the model formula showing the heat balance in the cross section (two-dimensional plane) which cut the cylinder along the axis is constructed.

  As shown in FIG. 15, for example, the quartz brick 111 is represented by a heat storage brick (silica stone) 1501 and a furnace wall brick 1502, and the furnace wall brick 1502 further includes an iron skin 1502 a, a refractory brick (A) ˜ (C) 1502b to 1502d, castable 1502e, and iron skin 1502f. In the model formula of the quartz brick 111, the above-described two-dimensional plane heat transfer is expressed. For the other clay bricks 109 and high alumina bricks 110, the heat transfer in the two-dimensional plane described above is expressed in the same manner as the silica bricks 111.

  In the hot stove model of this embodiment, during combustion, heat transfer between the combustion gas and the heat storage brick (silica stone) 1501 and between the heat storage brick (silica stone) 1501 and the furnace wall brick 1502 is convection heat transfer. It shall be by radiant heat transfer. Further, during the ventilation, heat transfer between the cold air and the heat storage brick (silica stone) 1501, between the heat storage brick (silica stone) 1501 and the furnace wall 1502, and between the furnace wall 1502 and the atmosphere is convection heat transfer. According to. In addition, heat transfer by heat conduction is performed inside the furnace wall 1502. Further, the heat storage brick (silica stone) 1501 performs dimensional conversion due to the existence of the passage opening. In addition, heat conduction in the height direction is ignored. These assumptions are the same for the other clay bricks 109 and high alumina bricks 110.

  First, a model formula representing the heat balance of gas is represented by the following formula (27). Moreover, the model formula showing the heat balance of a thermal storage brick is represented by the following (28) formulas. Moreover, the model formula showing the heat balance of a furnace wall brick is represented by the following (29) Formula.

  The meanings of symbols in the equations (27) to (29) are as follows.

ρ: Density [kg / m ³ ]
C _p : Specific heat [J / kg · K]
S: Cross-sectional area [m ² ] ((net) cut area of the brick obtained by subtracting the sum of the cross-sectional areas of the passage openings from the cross-sectional area obtained by cutting the above-mentioned cylinder along its axis)
v: Flow velocity [m / s]
T: Temperature [K]
h: Heat transfer coefficient [W / m ² · K]
A: Contact area [m ² ]
L: Height [m] (the furnace bottom is 0)
ε: Emissivity [−]
z: position in the height direction [m]
t: Time [s]
G: Gas CH: Regenerative brick W: Furnace wall brick Wb: Constituent brick of the furnace wall brick (if the quartz brick 111, refractory brick (silica stone) 1502a, heat resistant bricks (A) to (C) 1502b to 1502d, castable 1502e , Iron skin 1502f)
Wb-1, Wb + 1: Brick next to the brick specified by Wb (If heat-resistant brick (A) is Wb, Wb-1 is refractory brick (silica) 1502a, Wb + 1 is heat-resistant brick (B))
δ: Stefan Boltzmann constant

The second process state predicting unit 504 implements the following functions using model equations (27) to (29).
FIG. 16 is a diagram illustrating an example of a detailed functional configuration of the second process state prediction unit 504.
The second process state prediction unit 504 is roughly divided into a combustion simulation unit 1601 and a blowing simulation unit 1602.
((Simulation unit 1601 during combustion))
The combustion simulation unit 1601 is for simulating the state of each hot stove 100a-100b during the combustion period.
The combustion simulation unit 1601 includes a used gas capacity calculation unit 1601a and a model formula calculation unit 1601b.

<Used gas capacity calculation unit 1601a>
The used gas capacity calculation unit 1601a calculates the input heat quantity Q _{in, p} (i, t) by furnace and cycle after the current time already derived at the present time and the current time and later in the control section 702 that is the current calculation target. And a candidate of input heat quantity Q _{in, p} (i, t) by furnace and cycle. Here, the amount of heat input Q _{in, p} (i, t) for each furnace and each cycle after the present time is derived by shifting the control section 702 backward by one cycle. Therefore, if the number of cycles indicating the control section 702 that has already been calculated is n to n + s + v, the control section 702 that is the current calculation target is n + v + 1 to n + s + v + 1.

In addition, the used gas capacity calculation unit 1601a inputs the use ratio [-] of each used gas of BFG, COG, and LDG. The use ratio of the use gas is assumed to change during the combustion period, and can be set individually for each of a plurality of periods obtained by dividing one combustion period.
Further, the used gas capacity calculation unit 1601a inputs gas calories (gas composition unit calorie) [J / Nm ³ ] of each used gas of BFG, COG, LDG, and air.
Based on the above input information, the used gas capacity calculation unit 1601a calculates the capacity [Nm ³ ] of each used gas of BFG, COG, LDG, and air, and outputs it to the model formula calculation unit 1601b.

<Model Formula Calculation Unit 1601b>
The model formula calculation unit 1601b inputs the volume of each gas of BFG, COG, LDG, and air from the used gas capacity calculation unit 1601a.
The model formula calculation unit 1601b inputs the gas combustion temperature T _G [° C.], the density ρ _G [kg / m ³ ], and the specific heat C _{p, G} [J / kg · K]. Here, the subscript G represents gas.
Then, the model formula calculation unit 1601b uses the above-described model formulas (formulas (27) to (29)) using the input information, and from the start of combustion to the end of combustion (one combustion period), The heat balance in the hot stove 100a to 100d is calculated, and the following values at the end of combustion are output.
-Thermal storage brick temperature by furnace and cycle T _CH (i, t)
・ Furnace wall bricks (by component brick) temperature T _Wb (i, t)
・ Exhaust gas temperature T _ex (i, t) by furnace and cycle
・ Combustion efficiency η (i, t) by furnace and cycle

The gas volume V _G is reflected in “S _G × v _G ” on the left side of the equation (27). Further, filtrated cycle by the exhaust gas temperature T _ex (i, t) is the amount of heat which has not been heated in the combustion period to be calculated, and the gas volume V _G, are those calculated by using the components of the gas .
The processing of the used gas capacity calculation unit 1601a and the model formula calculation unit 1601b is repeatedly performed for each cycle.

((Simulation unit 1602 during blowing))
The simulation unit 1602 at the time of ventilation is for simulating the state of each hot stove 100a-100b in a ventilation period.
The blowing simulation unit 1602 includes each furnace operation content instruction unit 1602a, a model formula calculation unit 1602b, and a blowing flow rate / temperature determination unit 1602c.

<Each furnace operation content instruction unit 1602a>
Each furnace operation content instructing section 1602a receives from the model formula calculation section 1601b a furnace-specific / cycle-specific heat storage brick temperature T _CH (i, t) and a furnace-specific / cycle-specific furnace wall brick (component brick) temperature T _Wb (i). , T) (every time when the calculation at the end of combustion in the combustion period is completed in the combustion time simulation unit 1601). Here, it is assumed that the calculation is repeatedly performed so that a calculation result every 3 seconds is obtained.

Each furnace operation content instructing section 1602a includes “furnace / hourly passing blast flow rate BHS (i, time + 3) and furnace / hourly mixed cooling flow Air (i) determined by a blast flow rate / temperature determination unit 1602c, which will be described later. , Time + 3) ”is set as the“ calculation flow rate BHS (i, time) by furnace / time and mixed cooling flow rate Air (i, time) by furnace / time ”of the calculation target time. Here, time represents time (time), and time + 3 represents 3 seconds after time time.
And each furnace operation content instruction | indication part 1602a outputs the passage ventilation flow rate BHS (i, time) classified by furnace and time to the model type | formula calculation part 1602b, and mixed cooling flow Air (i, time) classified by furnace and time. Is output to the air flow rate / temperature determination unit 1602c. Here, the passing air flow rate is the flow rate of cold air that has entered the mixed cooling chamber 103 through the duct 114, the heat storage chamber 101, and the combustion chamber 102 shown in FIG. Further, the mixed cooling flow rate is a flow rate of cold air that has entered the mixed cooling chamber 103 through the duct 118 shown in FIG. The added value of the passing air flow rate and the mixed cooling flow rate becomes the air flow rate BV (i, time).
Incidentally, in the first calculation, “air flow rate by furnace / hourly flow rate BHS (i, time + 3) and air flow rate by mixed cooling by air / air (i, time + 3)” are calculated by the air flow rate / temperature determination unit 1602c described later. Since it has not been determined, each furnace operation content instruction section 1602a adopts initial values of the flow rate BHS (i, time) for each furnace and time and the mixed flow rate Air (i, time) for each furnace and time. To do.

<Model Formula Calculation Unit 1602b>
The model formula calculation unit 1602b obtains, from the model formula calculation unit 1601b, the temperature T _CH (i, t) of the heat storage brick by furnace and cycle and the temperature T _Wb (i, t t).
Further, the model formula calculation unit 1602b inputs the density ρ _G and the specific heat C _{p, G.}
In addition, the model formula calculation unit 1602b inputs the furnace-by-furnace / time-by-hour passage blast flow rate BHS (i, time) from each furnace operation content instruction unit 1602a. Here, filtrated & Hourly pass blower flow BHS (i, time) value obtained by multiplying the time time to become gas volume V _G.
Then, the model formula calculation unit 1602b uses the input information to calculate the heat balance at the time time to be calculated in the blowing period using the above-described model formulas (formulas (27) to (29)). Are repeated, and the furnace-specific / time-specific gas temperature T _G (i, time) and the furnace-specific / cycle-specific heat storage brick temperature T _CH (i, time) are output to the air flow / temperature determining unit 1602c. It should be noted that the values of the model equations (equation (27) and equation (28)) heat transfer coefficient h _{G, CH} differ between combustion and blowing.

<Blowing flow rate / temperature determination unit 1602c>
The blower flow rate / temperature determination unit 1602c inputs an operation target value 601 (target blower temperature BT _ref (time), target blower flow rate BV _ref (time), target blower time BTime _ref (time)).
Also, the blower flow rate / temperature determination unit 1602c receives the furnace-by-furnace / hourly mixed cooling flow Air (i, time) from each furnace operation content instruction unit 1602a.
Further, the blower flow rate / temperature determination unit 1602c inputs the gas temperature T _G (i, time) for each furnace and each time from the model formula calculation unit 1602b.
Further, the blower flow / temperature determination unit 1602c inputs the cold air temperature T _CW .

The blower flow rate / temperature determination unit 1602c uses the input information to obtain the target blower temperature BT _ref (time) and the target blower flow rate BV _ref (time) from the following equations (30) to (32). As shown in the table, “Blast flow rate by furnace / time BV (i, time + 3), Passage flow rate by furnace / time BHS (i, time + 3), Furnace / time mixed cooling flow Air (i, time + 3)” calculate. Then, the calculated “flow rate of blown air per furnace / time BHS (i, time + 3) and mixed cooling air flow per furnace / time Air (i, time + 3)” are as described above, each furnace operation content instruction section. It is output to 1602a. That is, “the furnace-by-furnace / by-hour passage blast flow rate BHS (i, time + 3) and the furnace-by-furnace / hourly mixed cooling flow rate Air (i, time + 3)” It becomes a mixed cooling flow rate.

The blower flow rate / temperature determining unit 1602c obtains “the temperature T _G (i, time) of the gas for each furnace / time, the flow rate BHS (i, time) for each furnace / time, A separate / time mixed cooling airflow Air (i, time) ”is given to the right side of the equations (30) to (32), and the predicted value BT _p (i, t) is calculated.
Also, the blower flow rate / temperature determining unit 1602c calculates the temperature of the lower end of the quartz brick from the furnace-by-cycle heat storage brick temperature T _CH (i, t) obtained at the end of the blowing period (at the end of blowing). The extracted temperature is set as the predicted value T _{si, p} (i, t) of the bottom temperature of the quartz brick by furnace and by cycle. The ventilation flow rate / temperature determination unit 1602c extracts the predicted values T _{si, p} (i, t) of the furnace-by-furnace and cycle-by-cycle silica brick bottom temperatures at the end of the blowing period in the prediction interval 701, respectively. .

The blast flow rate / temperature determination unit 1602c then selects the predicted value BT _p (i, t) of the blast temperature for each furnace / cycle in the prediction section 701, and the bottom of the quartz brick for each furnace / cycle in the prediction section 701. The predicted temperature value T _{si, p} (i, t) ”is output to the optimum tracking control unit 503 as the predicted value of the process state of each hot stove 100a-100d.

Returning to the description of FIG. 5, the optimum follow-up control unit 503, from the second process state prediction unit 504 as described above, predicts the predicted value of the minimum brick temperature for each furnace and cycle in the prediction interval 701 T _{si, p} When (i, n + d + g) to T _{si, p} (i, n + m + g) and predicted values BT _p (i, n + d + g) to BT _p (i, n + m + g) for each furnace and cycle in the prediction interval 701 are input. In order to minimize the value of the evaluation value of the furnace-specific objective function J ₁ (i) of the above-described equation (11) within a range that satisfies the constraint conditions of the equations (12) and (13), It is statistically determined how much each candidate value of the input heat quantity Q _{in, p} (i, t) for each furnace and cycle after the present time should be changed. The optimum follow-up control unit 503 performs the furnace-by-furnace / cycle-by-cycle input heat amount Q _{in, p} after the present time in the control section 702 until the evaluation value of the furnace-specific objective function J ₁ (i) in equation (11) is minimized. The candidate value of (i, t) is changed, and the changed value is output to the second process state prediction unit 504.

Then, the optimum follow-up control unit 503 inputs the amount of heat input Q _{in, p} for each furnace and each cycle after the present time when the value of the evaluation value of the objective function J ₁ (i) for each furnace in the equation (11) becomes the minimum. i, n) to Q _{in, p} (i, n + s + q−m) (candidate values) are instructed to the actual hot stove process 510 as an operation command.

The derivation of the predicted values of the process states of the hot stoves 100a to 100d as described above is sequentially performed by shifting the prediction interval 701 and the control interval 702 backward by one cycle. For example, a cycle section with the cycle number n + d to n + m is set as the prediction section 701, and a cycle section with the cycle number n to n + s is set as the control section 702, so that the process state of each hot stove 100a to 100d is set. When the predicted value is derived, the cycle interval of the cycle number n + d + 1 to n + m + 1 is set as the prediction interval 701, and the cycle interval of the cycle number n + 1 to n + s + 1 is set as the control interval 702, respectively. A predicted value of the process state of ˜100d is derived.
When the predicted value of the process state when the last cycle of the prediction section 701 is a cycle corresponding to the cycle number n + q is derived, the derivation of the predicted value of the process state is terminated. By doing in this way, the predicted value of the process state in each cycle of the number of cycles n to n + q−m is derived. Here, the predicted value of the latest process state is adopted as the predicted value of the plurality of process states derived in the same cycle.

(Operation flowchart)
Next, an example of the process of the hot stove control computer 301 when deriving the furnace-by-cycle / target-by-cycle target quartz brick minimum temperature at the end of each blowing period will be described with reference to the flowchart of FIG.
First, in step S1701, the heat storage amount target trajectory optimization unit 501 determines whether it is time to start the process of deriving the furnace-by-cycle / by-cycle target silica brick minimum temperature. In the present embodiment, whether the operation target value 601 has changed from the cycle to which the current time belongs (cycle number n) until the cycle to which the time at which the optimization time range 602 elapses (cycle number n + q) has elapsed. Determination of step S1701 is performed by determining whether it is 1 [min].

  If it is not the timing to start the process for deriving the target quarry brick minimum temperature for each furnace / cycle as a result of this determination, wait until the timing for starting the process for deriving the target quarry brick minimum temperature for each furnace / cycle is reached. To do. Then, when it is time to start the process for deriving the furnace-by-cycle and target-by-cycle target quartz brick minimum temperature, the process proceeds to step S1702.

In step S1702, the heat storage target trajectory optimization unit 501 determines whether or not an optimum solution for the furnace-by-cycle / by-cycle target silica brick minimum temperature T _{si, ref} (i, n + j) has been derived. In the present embodiment, the determination in step S1703 is performed by determining whether or not the evaluation value of the furnace specific objective function J ₂ (i) in equation (16) is the minimum.
As a result of the determination, when the optimum solution for the furnace-by-cycle and target-by-cycle target quartz brick minimum temperature T _{si, ref} (i, n + j) is derived, the process proceeds to step S1712 described later.

On the other hand, if the optimum solution of the furnace-by-cycle / by-cycle target quartz brick minimum temperature T _{si, ref} (i, n + j) has not been derived, the process proceeds to step S1703.
In step S 1703, the heat storage target trajectory optimization unit 501 outputs (sets) candidates for the furnace-by-cycle and target-by-cycle target silica brick minimum temperature T _{si, ref} (i, n + j) to the first process state prediction unit 502. )

Next, in step S1704, the first process state prediction unit 502 sets an initial value (= 0 (zero)) as a variable g that defines the prediction interval 701 and the control interval 702.
Next, in step S1705, the first process state predicting unit 502 determines whether or not an optimum solution for the furnace-by-furnace and cycle-by-cycle input heat amount Q _{in, p} (i, t) after the current time has been derived. In the present embodiment, the determination in step S1705 is performed by determining whether or not the evaluation value of the furnace-specific objective function J ₁ (i) in equation (11) is the minimum.

As a result of the determination, if the optimum solution of the furnace-by-furnace / cycle-by-cycle input heat amount Q _{in, p} (i, t) after the present time is derived, the process proceeds to step S1709 described later.
On the other hand, if the optimum solution of the input heat quantity Q _{in, p} (i, t) for each furnace and cycle after the current time has not been derived, the process proceeds to step S1706.
When the process proceeds to step S1706, the first process state prediction unit 502 determines whether the furnace-by-furnace and cycle-by-cycle input heat amounts Q _{in, p} (i, n + g) to Q _{in, p} (i, n + s + g) in the control section 702 after the current time. Set candidates.

Next, in step S1707, the first process state prediction unit 502 derives a predicted value of the process state using the linear time series model expressed by the equations (3) to (10). Specifically, in the present embodiment, the predicted values T _{si, p} (i, n + d + g) to T _{si, p} (i, n + m + g) of the minimum temperature for each brick and furnace in the prediction section 701 and the furnace in the prediction section 701 are shown. The predicted values BT _p (i, n + d + g) to BT _p (i, n + m + g) of the blast temperature for different / cycle are derived.

Next, in step S 1708, the first process state predicting unit 502 uses the change amount of the candidate value of the furnace-by-furnace and cycle-by-cycle input heat amount Q _{in, p} (i, t) in the control section 702 after the current time as GA. Judgment is made using optimization techniques such as mountain climbing and linear programming. Specifically, in the present embodiment, the first process state prediction unit 502 performs the processing described using the equations (11) to (13).
Then, the process returns to step S1705, and the first process state predicting unit 502 determines the optimum solution of the input heat quantity Q _{in, p} (i, t) for each furnace and each cycle after the current time based on the change amount determined in step S1708. It is determined whether or not is derived.

As described above, when the optimum solution of the input heat quantity Q _{in, p} (i, t) by furnace and cycle after the present time is derived, the process proceeds to step S1709.
In step S1709, the first process state prediction unit 502 determines whether or not the variable g that defines the prediction interval 701 and the control interval 702 has become q−m. That is, it is determined whether or not the last cycle of the prediction interval 701 is the last cycle of the optimization time range 602. As a result of the determination, if the variable g that defines the prediction interval 701 and the control interval 702 is not q−m, the process proceeds to step S1710.

In step S 1710, the first process state prediction unit 502 adds “1” to the variable g that defines the prediction interval 701 and the control interval 702. Then, the processing after step S1705 is performed, the prediction interval 701 and the control interval 702 are shifted backward by one cycle, and the optimum solution of the input heat quantity Q _{in, p} (i, t) for each furnace and each cycle after the present time is obtained. To derive.
As described above, when the variable g that defines the prediction interval 701 and the control interval 702 becomes q−m, the process proceeds to step S1711.

In step S1711, the heat storage target trajectory optimization unit 501 sets the change amount of the candidate value of the target silicic acid brick minimum temperature T _{si, ref} (i, n + j) by furnace, GA, hill climbing method, and Judgment is made using an optimization method such as linear programming. Specifically, in the present embodiment, the heat storage amount target trajectory optimization unit 501 performs the processing described using Equation (16).
Then, returning to step S1702, the heat storage amount target trajectory optimization unit 501 determines the optimum solution of the furnace-by-cycle and target-by-cycle target quartz brick minimum temperature T _{si, ref} (i, n + j) based on the change amount determined in step S1711. It is determined whether or not is derived.

When the optimum solution for the furnace-by-cycle and target-by-cycle target quartz brick minimum temperature T _{si, ref} (i, n + j) is derived as described above, the process proceeds to step S1712.
In step S1712, the heat storage target trajectory optimization unit 501 stores the optimum solution of the furnace-by-cycle / by-cycle target silica brick minimum temperature T _{si, ref} (i, n + j). Then, the process returns to step S1701.
The process according to the flowchart of FIG. 17 is performed individually for each hot stove 100a to 100d.

Next, referring to the flowchart of FIG. 18, the lowest value of the quartz brick for deriving the lower limit value T _{si, m} (i, t) of the minimum temperature by furnace and cycle in the third term on the right side of the equation (16). An example of the temperature lower limit derivation process will be described. The flowchart of FIG. 18 is performed individually for each hot stove 100a to 100d every time the blowing period of the hot stove 100a to 100d ends. It is assumed that the setting using the residual heat amount index setting screen 1400 has been completed before the flowchart of FIG. 18 starts. Further, it is assumed that “the opening degree of the cold air butterfly valve 123, the opening degree of the blower butterfly valve 125, and the blowing temperature” in the immediately preceding blowing period are measured before the flowchart of FIG. 18 starts.

First, in step S1801, the heat storage target trajectory optimization unit 501 stores the heat stored in the judgment condition column of the remaining heat index setting screen 1400 when the OK button 1401 on the remaining heat index setting screen 1400 is pressed. Read the quantity indicator. Specifically, any one of the heat storage amount indexes (1) to (10) described above is read out.
Next, in step S1802, the heat storage amount target trajectory optimization unit 501 is input to the target value column of the remaining heat amount index setting screen 1400 when the OK button 1401 of the remaining heat amount index setting screen 1400 is pressed. Read the target value. Specifically, any of the R1 target to R10 target described above is read. In addition, when the reference time is set, the heat storage amount target trajectory optimization unit 501 reads the reference time. Specifically, when the residual heat index of (1), (2), (6), (8), (9) described above is read in step S1801, it corresponds to the read residual heat index. Any one of the reference times T1, T2, T6, T8, and T9 is read out.

Next, in step S1803, the heat storage amount target trajectory optimization unit 501 acquires a performance value corresponding to the remaining heat amount index read in step S1801.
Next, in step S1804, the heat storage amount target trajectory optimization unit 501 derives a magnitude relationship between the target value read in step S1802 and the actual value read in step S1803, and the read result is read in step S1801. One correction gain k1_ to k10_ corresponding to the remaining heat amount index is read out.

Next, in step S1805, the heat storage amount target trajectory optimization unit 501 determines the amount of change ΔT _{si, m} of the lower limit value T _{si, m} of the minimum temperature of silica brick by furnace and by cycle from the results read in steps S1801 to S1804. Is derived. Specifically, any one of equations (17) to (26) is calculated according to the remaining heat index read in step S1801.
Next, in step S1806, the heat storage target trajectory optimizing unit 501 uses the current furnace-specific / cycle-specific minimum quartz brick temperature T _{si, m} to calculate the furnace-specific / cycle-specific silica brick derived in step S1805. The change amount ΔT _{si, m} of the lower limit value T _{si, m} of the minimum temperature is added to set (update) the lower limit value T _{si, m} of the minimum temperature of the silica brick by furnace and by cycle.

Next, in step S1807, the heat storage amount target trajectory optimization unit 501 determines whether or not the lower limit value T _{si, m of the} lowest temperature for each brick and cycle set in step S1806 is lower than the transformation point temperature of the quartz brick 111. Determine whether.
As a result of the determination, if the lower limit value T _{si, m of} the furnace-by-cycle / by-cycle minimum quartz brick temperature is lower than the transformation point temperature of the quartz brick 111, the process proceeds to step S1808. When the processing proceeds to step S1808, the heat storage amount target trajectory optimization unit 501 sets the lower limit value T _{si, m} of the furnace-by-cycle-by-cycle quartz brick minimum temperature set at step S1806 as the transformation point temperature of the quartz brick 111. And the process by the flowchart of FIG. 18 is complete | finished.
On the other hand, in step S1807, if the lower limit value T _{si, m of the} minimum temperature of siliceous brick by furnace and by cycle does not fall below the transformation temperature of the siliceous brick 111, the process of step S1808 is not performed and the flowchart of FIG. The process ends.
As described above, the lower limit value T _{si, m} (i, t) of the furnace-by-cycle and quartz-by-cycle minimum temperature bricks finally set in the flowchart of FIG. 18 is expressed by the equation (16) in step S1701 of FIG. Used when performing calculations.

Next, an example of the processing of the hot stove control computer 301 when deriving the input heat quantity Q _{in, p} (i, t) for each furnace and each cycle after the present time will be described with reference to the flowchart of FIG.
First, in step S1901, the optimum tracking control unit 503 sets an initial value (= 0 (zero)) as a variable g that defines the prediction interval 701 and the control interval 702.
Next, in step S1902, the optimum follow-up control unit 503 determines whether or not it is the timing to start the process of deriving the furnace-by-furnace and cycle-by-cycle input heat quantity Q _{in, p} (i, t) after the current time. In the present embodiment, for each hot stove 100a to 100d, the determination in step S1902 is performed by determining whether or not a predetermined time within the switching time before the combustion period of each cycle has started.

As a result of this decision, this time after the furnace another cycle by heat input _{Q in, p (i, t} ) If this is not the time to start the process of deriving the will, the moment after the furnace another cycle by heat input Q _in, Wait until it is time to start the process of deriving _p (i, t). Then, when it is time to start the process of deriving the input heat quantity Q _{in, p} (i, t) for each furnace and each cycle after the current time, the process proceeds to step S1903.

In step S1903, the optimum follow-up control unit 503 determines whether or not an optimum solution for the furnace-by-reactor-by-cycle input heat amount Q _{in, p} (i, t) after the current time has been derived. In the present embodiment, the determination in step S1903 is performed by determining whether or not the evaluation value of the furnace-specific objective function J ₁ (i) in equation (11) is the minimum.
As a result of this determination, if the optimum solution of the input heat quantity Q _{in, p} (i, t) by furnace and cycle after the present time is derived, the process proceeds to step S1907 described later.
On the other hand, if the optimum solution of the input heat quantity Q _{in, p} (i, t) for each furnace and each cycle after the present time has not been derived, the process proceeds to step S1904.

In step S1904, the optimum follow-up control unit 503 sets the candidates for the input heat amounts Q _{in, p} (i, n + g) to Q _{in, p} (i, n + s + g) for each furnace and cycle in the control section 702 after the current time. 2 is output (set) to the process state prediction unit 504.
Next, in step S1905, the second process state prediction unit 504 executes a hot stove simulator process. By the hot stove simulator process, the predicted value BT _p (i, t) of the blown temperature for each furnace and cycle in the predicted section 701 and the predicted value T _{si, p of the} bottom temperature of the quartz brick for each furnace and cycle in the predicted section 701 are calculated. (I, t) is derived. Details of the hot stove simulator process will be described later with reference to FIG.

Next, in step S1906, the optimum follow-up control unit 503 uses the change amount of the candidate value of the input heat quantity Q _{in, p} (i, t) for each furnace and cycle in the control section 702 after the current time as the GA, hill climbing method. And an optimization method such as linear programming. Specifically, in the present embodiment, the optimum tracking control unit 503 performs the processing described using the equations (11) to (13).
Then, returning to step S1903, the optimal follow-up control unit 503 derives an optimal solution for the furnace-by-furnace and cycle-by-cycle input heat quantity Q _{in, p} (i, t) from the present time based on the change amount determined in step S1906. It is determined whether or not.

As described above, when the optimum solution of the input heat quantity Q _{in, p} (i, t) for each furnace and each cycle after the present time is derived, the process proceeds to step S1907.
In step S1907, the optimum tracking control unit 503 determines whether or not the variable g that defines the prediction interval 701 and the control interval 702 has become q−m. That is, it is determined whether or not the last cycle of the prediction interval 701 is the last cycle of the optimization time range 602. As a result of this determination, if the variable g defining the prediction interval 701 and the control interval 702 is not q−m, the process proceeds to step S1908.

In step S1908, the optimum tracking control unit 503 adds “1” to the variable g that defines the prediction interval 701 and the control interval 702. Then, the processing after step S1903 is performed, the prediction interval 701 and the control interval 702 are shifted backward by one cycle, and the optimum solution of the input heat quantity Q _{in, p} (i, t) for each furnace and each cycle after the present time is obtained. To derive.
As described above, when the variable g defining the prediction interval 701 and the control interval 702 becomes q−m, the process proceeds to step S1909. In step S1909, the optimum follow-up control unit 503 instructs the actual hot stove process 510 as the operation command with the optimum solution of the input heat quantity Q _{in, p} (i, t) by furnace and cycle after the present time. Note that the latest value is adopted for the optimum solution in the same cycle. Then, the process returns to step S1901.
The process according to the flowchart of FIG. 19 is performed individually for each hot stove 100a to 100d.

Next, an example of the hot stove simulator execution process in step S1905 of FIG. 19 will be described with reference to the flowchart of FIG.
First, in step S2001, the used gas capacity calculation unit 1601a determines that the used gas capacity calculation unit 1601a determines the input heat amount Q _{in, p} (i, n + g) to Q _{in, p} for each furnace and cycle after the current time in the control section 702. A candidate for (i, n + s + g) is acquired.
Next, in step S2002, the used gas capacity calculation unit 1601a designates “1” indicating the first cycle as the number of cycles t to be calculated.
Next, in step S2003, the used gas capacity calculation unit 1601a calculates the capacity of each used gas of BFG, COG, LDG, and air.

Next, in step S2004, the model formula calculation unit 1601b uses the model formula (formulas (27) to (29)) in the hot stove 100a to 100d from the start of combustion to the end of combustion at the cycle number t. Calculate the heat balance. According to this calculation, at the time of completion of combustion of the cycle of the number t of cycles, “thermal furnace brick temperature by furnace / cycle, T _CH (i, t), furnace wall brick by furnace / cycle temperature (component brick) temperature T _Wb ( i, t), furnace / cycle exhaust gas temperature T _ex (i, t), and furnace / cycle combustion efficiency η (i, t) ”.
Next, in step S2005, the model formula calculation unit 1601b displays “the furnace temperature / cycle-specific thermal storage brick temperature T _CH (i, t), the furnace wall / cycle-specific furnace wall” at the end of the combustion of the cycle of the cycle number t. “Brick (component brick) temperature T _Wb (i, t)” is output to each furnace operation content instruction section 1602a.

Next, in step S2006, the blower flow rate / temperature determination unit 1602c acquires operation target values (target blower temperature BT _ref (time), target blower flow rate BV _ref (time), target blower time BTime _ref (time)). .
Next, in step S2007, each furnace operation content instruction | indication part 1602a sets time = 1 [second] as time time to be calculated.
Next, in step S2008, each furnace operation content instructing unit 1602a displays the “target-by-furnace / hourly passing blast flow rate BHS (i, time) and the furnace-by-furnace / hourly mixed cooling for the calculation target time (time = 1). The initial value of “flow rate Air (i, time)” is determined and given to the model formula calculation unit 1602b.

Next, in step S2009, the model formula calculation unit 1602b uses the model formulas (formulas (27) to (29)) to calculate the heat balance at the time time to be calculated in the blowing period. By this calculation, “furnace / time-specific gas temperature T _G (i, time), furnace-specific / cycle-specific heat storage brick temperature T _CH (i, time)” at the time time to be calculated in the blowing period is obtained.
Next, in step S2010, the model formula calculation unit 1602b determines whether or not the air blowing period has ended. As described above, in the present embodiment, the target blowing period BTime _ref (i, n + j)) is a fixed value, so this blowing period is also a fixed value. If the result of this determination is that the air blowing period has not ended, processing proceeds to step S2011. In step S2011, the blower flow rate / temperature determination unit 1602c adds “3 [seconds]” to the time time to be calculated.

Next, in step S2012, the blast flow rate / temperature determination unit 1602c is configured so that the target blast temperature BT _ref (time) and the target blast flow rate BV _ref (time) are obtained from the equations (30) to (29). (Determine) “Blowing flow rate BV (i, time) by furnace / time, passing flow rate BHS (i, time) by furnace / time, mixed cooling flow rate Air (i, time) by furnace / time” . Then, the blowing flow rate / temperature determination unit 1602c, through each furnace operation content instructing unit 1602a, calculates “time-by-furnace / by-hour passage blowing flow rate BHS (i, time) and by furnace / time-by-furnace. The mixed cooling flow rate Air (i, time) "is given to the model formula calculation unit 1602b. Then, every 3 seconds until the air blowing period ends, “flow rate BV (i, time) by furnace / time, passage flow rate BHS (i, time) by furnace / time, mixed cooling by furnace / time” Until the flow rate Air (i, time) "is obtained, the processes in steps S2009 to S2012 are repeated.

  And if it determines with the ventilation period having been complete | finished in step S2010, it will progress to step S2013. In step S2013, the blast flow / temperature determination unit 1602c determines whether or not the cycle number t has reached the cycle number n + m + g corresponding to the last cycle of the prediction interval 701. As a result of the determination, if the cycle number t is not the cycle number n + m + g corresponding to the last cycle of the prediction interval 701, the process proceeds to step S2014. In step S2014, the used gas capacity calculation unit 1601a adds “1” to the cycle t in which the calculation is performed. Then, the processes in steps S2003 to S2014 are repeated until the cycle number t reaches the cycle number n + m + g corresponding to the last cycle of the prediction interval 701.

When the cycle number t reaches the cycle number n + m + g corresponding to the last cycle of the prediction interval 701, the process proceeds to step S2015. In step S2015, the blower flow rate / temperature determination unit 1602c obtains “the temperature T _G (i, time) of the gas by furnace / time, the flow rate of blown air by furnace / time BHS obtained in each prediction section 701”. (I, time), furnace-specific / time-specific mixed cooling flow rate Air (i, time) "is given to the right side of the equations (30) to (32), and the air temperature for each furnace / cycle in each prediction section 701 The predicted value BT _p (i, t) is calculated.
Also, the blower flow / temperature determining unit 1602c uses the brick-by-furnace and cycle-specific heat storage brick temperature T _CH (i, t) obtained at the end of the blowing period (at the end of blowing) in each prediction section 701. The temperature of the lower end is extracted, and the extracted temperature is set as the predicted value T _{si, p} (i, t) of the minimum temperature of the quartz brick by furnace and by cycle.

The blast flow rate / temperature determination unit 1602c then calculates the predicted values T _{si, p} (i, t) of the minimum temperature of the bricks by furnace and by cycle at the end of the blast period in each prediction section 701, and each prediction section. The predicted value BT _p (i, t) of the blast temperature for each furnace / cycle in 701 is output to the optimum follow-up control unit 503 that requested the information. When the predicted values overlap, the latest value is adopted and output to the optimum tracking control unit 503. Thereby, the process according to the flowchart of FIG.

(Summary)
As described above, in the present embodiment, when performing mixed cooling, the opening degree of the cold wind butterfly valve 123 is used as an index of the residual heat amount of the heat storage brick when the air blowing period ends. On the other hand, when the mixed cooling is not performed, the blower butterfly valve 125 or the blower temperature is used as an index of the residual heat amount of the heat storage brick when the blower period ends. Then, by using the target value and the actual value of the residual heat index of the regenerative brick when the air blowing period ends _, the change amount ΔT _{si, m} of the lower limit value T _{si, m} of the minimum temperature of the silica brick by furnace and by cycle is calculated. The lower limit value T _{si, m} of the minimum temperature of the quartz brick by furnace and by cycle is derived from the derived result. Then, the input heat quantity Q _{in, p} is derived using the lower limit value T _{si, m} of the minimum temperature of silica bricks by furnace and cycle. Therefore, in order to determine the input heat quantity Q _{in, p} for the hot stove 100a to 100d, the lower limit value of the minimum temperature of the quartz brick reflecting the heat storage amount of each cycle in the hot stove 100a to 100d is obtained by actually measuring the process state of the hot stove. It can be derived using the value.

In the present embodiment, the predicted value T _{si, p of the} minimum quartz brick temperature in the predicted interval 701 is close to the candidate of the target minimum temperature of the silica brick T _{si, ref} set in the optimization time range 602 and is in the control interval. 702 so as to minimize the filtrated cycle by heat input Q value of the difference becomes higher evaluation the smaller the filtrated objective function J ₁ of the _in between adjacent cycles in, heat input since the present time in the control section 702 Q _{in, p} is derived using a process model that is a calculation model of the hot stove 100. Then, the sum of the input heat quantity Q _{in, p in} the optimization time range 602 _, the predicted value T _{si, p} (i, t) of the minimum temperature of siliceous bricks by furnace and cycle, and the minimum target silicic brick by furnace and cycle From the maximum value in the optimization time range 602 of the absolute value of the difference from the temperature T _{si, ref} (i, t) and the lower limit value T _{si, m} (i, t) Weight of the maximum value in the optimization time range 602 (and the larger value of 0 (zero)) of the value obtained by subtracting the predicted value T _{si, p} (i, t) of the minimum temperature of silica brick by cycle target silica brick lowest temperature T _si to minimize the value of the linear sum as evaluation increases less filtrated objective function J _2, until _ref is obtained, the target silica brick lowest temperature T _si, by changing the candidate _ref The above-described process is repeated. The optimization time range 602 is a time longer than the time constant of the hot stove 100. Therefore, in order to optimize the target ore-by-cycle target siliceous brick minimum temperature T _{si, ref} (i, t), which is the target trajectory of the heat storage amount, the silica reflecting the heat storage amount of each cycle in the hot stove 100a to 100d. The lower limit value of the brick minimum temperature can be set using the actual value of the process condition of the hot stove.

Further, in the present embodiment, the predicted value T _{si, p of the} minimum temperature of the silica brick in the predicted section 701 is close to the target minimum temperature of the brick brick T _{si, ref} derived as described above and is adjacent in the control section 702. The amount of heat input Q _in, after the current time in the control section 702, which minimizes the value of the furnace-specific objective function J ₁ , the evaluation of which becomes higher as the difference between the furnace and cycle input heat amounts Q _in is smaller _{. p} is derived using a process model which is a calculation model of the hot stove 100. Then, the input heat amount Q _{in, p} after the present time in the derived control section 702 is set as an operation command value for the actual hot stove process 510. Therefore, the amount of heat input Q _in for the hot stove 100 can be determined so that the time change of the physical quantity reflecting the amount of heat stored in the hot stove 100 follows the target.

Further, in the present embodiment, a linear time series model for deriving the predicted value of the process state for each cycle is adopted as a process model used for deriving the target quartz brick minimum temperature _{Tsi, ref} . Therefore, it is possible to reduce the calculation load for prediction for a time longer than the time constant of the hot stove 100.
In the present embodiment, a hot stove simulator that calculates the gas heat balance and the brick heat balance in the hot stove 100 is employed as a process model used when deriving the operation command value of the input heat quantity Q _{in, p.} did. Therefore, the calculation accuracy of the input heat quantity Q _{in, p} can be improved.

(Modification)
[Modification 1]
In the present embodiment, the lower limit value T _{si, m} of the minimum temperature of the quartz brick is calculated. The lower limit value T _{si, m} of the minimum temperature of the quartz brick is a temperature that cannot be further lowered as the minimum temperature of the quartz brick 111. Therefore, the lower limit value T _{si, m} of the minimum temperature of the quartz brick is an index of the amount that can be minimized as the residual heat amount of the heat storage brick when the blowing period ends.
However, in actual operation, it may be better to give a margin to the amount of residual heat of the heat storage brick when the air blowing period ends. For example, in order to prevent the residual heat amount of the heat storage brick when the operation period is severe and the air blowing period ends (temporarily) becoming too small, the residual heat amount of the heat storage brick when the air blowing period ends is increased. There is a need. Also, the exact time is unknown, but if there is a possibility of increasing the wind (increase the blowing temperature / flow rate) in the near future, increase the residual heat amount of the heat storage bricks at the end of the blowing period as soon as possible. There is a need to. This is because the time constant of the hot stove 100a to 100d is as large as about 3 days.

In such a case, if there is no allowance for the amount of residual heat of the heat storage brick when the air blowing period ends, the minimum temperature of the quartz brick 111 becomes low when there are operational fluctuations and wind increases, and in some cases There is a risk that the transformation point temperature of the quartz brick 111 may be lower.
Therefore, the amount of change ΔT _{si, m} of the lower limit value T _{si, m} of the above-mentioned furnace-by-cycle and quartz-by-cycle minimum temperature of bricks may be increased.
Specifically, the operator determines a change amount ΔQ _out (increase) of the blast heat amount determined from the blast temperature (measured by the blast flow meter 307) and the blast flow rate (measured by the cold air thermometer 308).
Then, the operator inputs the determined change amount ΔQ _out of the blast heat amount to the input device 312.

Thereafter, the heat storage amount target trajectory optimization unit 501 reads the remaining heat amount index change table corresponding to the remaining heat amount index read in step S1801.
FIG. 21 is a diagram illustrating an example of a residual heat amount index change table.
In FIG. 21, a residual heat amount index change table 2100 stores the relationship between the change amount ΔQ _out of the blown heat amount and the change amount Δzan of the residual heat amount index for each residual heat amount index. In the above-described example, the relationship between the change amount ΔQ _out of the blown heat amount and the change amount Δzan of the remaining heat amount index is stored for each of the remaining heat amount indexes (1) to (10) described above. The relationship between the change amount ΔQ _out of the blown heat amount and the change amount Δzan of the residual heat amount index can be obtained by, for example, statistical analysis processing using actual data.

The heat storage amount target trajectory optimization unit 501 reads the change amount Δzan of the residual heat amount index corresponding to the change amount ΔQ _out of the blown heat amount determined by the operator, and adds it to the target value read in step S1802.
If it does in this way, even if there is an operational fluctuation and wind increase, it can prevent that the amount of residual heat of the heat storage brick when the ventilation period ends becomes small.

Instead of the residual heat amount index change table 2100, a relational expression indicating the relationship between the change amount ΔQ _out of the blown heat amount and the change amount Δzan of the residual heat amount index may be used. In addition, the relationship between the change amount (increase amount) of the blowing temperature and the change amount Δzan of the residual heat amount index, not the amount of blown heat amount, and the relationship between the change amount (increase amount) of the blown heat amount and the change amount Δzan of the residual heat amount index May be prepared individually.

[Modification 2]
In the present embodiment, the case where the furnace specific objective function J ₂ is expressed by the equation (16) has been described as an example. However, this is not always necessary.
[[Modification 2-1]]
For example, the following formulas (33) to (35) may be adopted instead of the formula (16).

Expression (33) employs only the second term as the objective function among the first to third terms on the right side of Expression (16). The equation (34) corresponds to the third term on the right side of the equation (16), and from the lower limit value T _{si, m} (i, t) of the minimum temperature of the quartz brick by furnace and by cycle, by furnace and by cycle. It is a constraint equation showing a constraint that the value obtained by subtracting the predicted value T _{si, p} (i, t) of the minimum temperature of quartz brick is 0 (zero) or more. Equation (35) corresponds to the first term on the right side of Equation (16), and the predicted value T _{si, p} (i, t) of the minimum temperature of quartz brick by furnace and cycle, and the furnace and cycle It is a constraint equation showing a constraint that the absolute value of the difference from the different target quartz brick minimum temperature T _{si, ref} (i, t) is equal to or less than the threshold Th ₃ (i).
[[Modification 2-2]]
Further, for example, instead of the expression (16), the following expression (36) and the expression (34) may be adopted.

  Expression (36) employs only the first and second terms as the objective function among the first to third terms on the right side of Expression (16).

[Modification 3]
If the input heat quantity Q _{in, p} for each furnace / cycle is determined using the lower limit value T _{si, m} of the minimum temperature of silica brick for each furnace / cycle _, the heat storage target trajectory optimization unit 501 described above is not necessarily required. The calculation by the first process state prediction unit 502, the optimum follow-up control unit 503, and the second process state prediction unit 504 may not be performed. For example, the lower limit value T _{si, m} of the minimum temperature of siliceous brick by furnace / cycle is one of a plurality of variables, and the input heat quantity Q _{in, p} by furnace / cycle is a decision variable, It may be introduced into at least one of the constraint equations, and the optimum value of the input heat quantity Q _{in, p} for each furnace / cycle may be derived by optimization calculation. Also, the lower limit value T _{si, m} of the minimum temperature of silica bricks by furnace and cycle is displayed, and the operator sees the lower limit value T _{si, m} of the minimum temperature of silica bricks by furnace and cycle and operates the hot stove 100. Conditions (furnace / cycle input heat quantity Q _{in, p,} etc.) may be determined.

[Modification 4]
When the target quartz brick minimum temperature T _{si, ref} is derived, the derived target quartz brick minimum temperature T _{si, ref} may be output (displayed). This is because the operator can also determine the operating conditions of the hot stove 100 _{by referring} to the target quartz brick minimum temperature _{Tsi, ref} . As described above, it is not always necessary to derive the input heat amount Q _{in, p} after the current time as the operation command (the functions of the optimum tracking control unit 503 and the second process state prediction unit 504 are not necessarily required).
[Modification 5]
When a period of a predetermined time (for example, several hours) elapses, processing for deriving the target quartz brick minimum temperature _{Tsi, ref} may be started (as determined as Yes in step S1701 in FIG. 17). Also good).

[Modification 6]
The process model used for deriving the target quartz brick minimum temperature _{Tsi, ref} is not limited to the linear time series model. For example, a statistical analysis model other than the linear time series model may be used. Further, a process model (step response model or impulse response model) identified from the operation results in the hot stove 100 may be used. Adopting a process model that derives the predicted value of the process state for each cycle is preferable because the calculation load can be reduced as described above. However, if the calculation load is limited, a hot stove simulator can be used. Good.

[Modification 7]
If the second term on the right side of the equation (11) is included in the furnace-specific objective function, the fluctuation of the heat input Q _in (i, t) for each furnace in each adjacent cycle in the same hot stove 100 is reduced. This is preferable. However, even if this term is not present, the predicted value T _{si, p} (i, t) of the lowest temperature for each furnace and cycle in the prediction interval 701 can be calculated by the first term on the right side of equation (11). -The target quartz brick minimum temperature by cycle T _{si, ref} (i, n + j) can be made to follow well. Therefore, the second term on the right side of equation (11) is not necessarily required.

[Modification 8]
The process model used when deriving the operation command value of the input heat quantity Q _{in, p} is not limited to the hot stove simulator. If the calculation accuracy is limited, a statistical analysis model such as the linear time series model described above may be used.
[Modification 9]
When the staggered parallel method is not used, for example, when the operations of the hot stove 100a to 100d are performed so as not to overlap each other, the operation target value may be a different value in each furnace (that is, It may be the operation target value by furnace and hour).
Moreover, if the number of the hot stove 100 is one or more, it is not necessarily four.

[Modification 10]
As the predicted value of the process state, instead of the predicted value BT _p (i, t) of the blowing temperature by furnace and cycle, the minimum value of the opening degree of the cold air butterfly valve 123 by furnace and cycle (furnace at the end of the blowing period) The predicted value KB _p (i, t) of the opening degree of the cold air butterfly valve 123 for each cycle may be used. In the linear time series model, the predicted value KB _p (i, t) of the minimum value of the opening degree of the cold air butterfly valve 123 by furnace and cycle is obtained by using the following equation (37).

In the equation (37), the coefficients a 2 · _x (i), b 2 · _x (i), and c 2 · _x (i) are input based on the operation of the input device 312. These coefficients a2 · _x (i), b2 · _x (i), and c2 · _x (i) are the same as the coefficients a0 · _x (i), b0 · _x (i), and c0 · _x (i). It is obtained in advance.
ΔKB _p (i, n + j + 1) is expressed by the following equation (38).
ΔKB _p (i, n + j + 1) = KB _p (i, n + j + 1) −KB _p (i, n + j) (38)

ΔKB (i, n + j−x) is expressed by the following equation (39).
ΔKB (i, n + j−x) = KB (i, n + j−x) −KB (i, n + j−x−1) (39)
Further, the blowing temperature and the opening degree of the cold air butterfly valve 123 have a correlation. Therefore, by formulating these relations, even if a hot stove simulator is used, the opening of the cold air butterfly valve 123 for each furnace / cycle is estimated from the predicted value BT _p (i, t) of the air temperature for each furnace / cycle. The predicted value KB _p (i, t) of the lowest value can be obtained.

The embodiment of the present invention described above can be realized by a computer executing a program. Further, a computer-readable recording medium in which the program is recorded and a computer program product such as the program can also be applied as an embodiment of the present invention. As the recording medium, for example, a flexible disk, a hard disk, an optical disk, a magneto-optical disk, a CD-ROM, a magnetic tape, a nonvolatile memory card, a ROM, or the like can be used.
In addition, the embodiments of the present invention described above are merely examples of implementation in carrying out the present invention, and the technical scope of the present invention should not be construed as being limited thereto. Is. That is, the present invention can be implemented in various forms without departing from the technical idea or the main features thereof.

(Relationship with claims)
The first deriving unit, the second deriving unit, the third deriving unit, the selecting unit, and the target heat storage amount deriving unit are realized by, for example, the heat storage target trajectory optimization unit 501.
The first residual heat index is realized by, for example, the residual heat index shown in the determination condition column of FIG. 11, and the second residual heat index is realized by, for example, the residual heat index shown in the determination condition column of FIG. Is done.
Change amount of silica brick minimum temperature limit value when the blowing period has ended, for example, the lower limit value T _si of filtrated cycle by silica brick minimum _temperature change amount of _m [Delta] T _si, is realized by _m.
The first process state prediction unit is realized by the first process state prediction unit 502, for example.
The first process model is realized by, for example, a linear time series model represented by Expressions (3) to (10).
The first objective function is realized by, for example, equation (11).
The second objective function is realized by, for example, Expression (16) (Claim 4), Expression (33) (Claim 5), or Expression (36) (Claim 6).
The constraint equation for the first objective function is realized by, for example, Equation (12) and Equation (13).
The constraint equation for the second objective function is realized by equations (34) and (35).
The optimum tracking control unit is realized by the optimum tracking control unit 503, for example.
The second process state prediction unit is realized by the second process state prediction unit 504, for example.
The second process model is realized by, for example, a hot stove simulator.
The third objective function is realized by, for example, equation (11).
The constraint equation for the third objective function is realized by, for example, Equation (12) and Equation (13).

DESCRIPTION OF SYMBOLS 100 Hot stove 101 Heat storage chamber 102 Combustion chamber 103 Mixed cooling chamber 109 Viscous brick 110 High alumina brick 111 Silica brick 301 Hot stove control computer 501 Heat storage target trajectory optimization section 502 First process state prediction section 503 Optimal tracking control section 504 Second process state prediction unit

Claims (21)

A period including a combustion period in which the heat storage brick is heated by the combustion gas to store heat and a blowing period in which hot air is generated by heat exchange with the heat storage brick through the cold air and supplied to the blast furnace is operated as one cycle. A hot air furnace, a heat storage chamber having a heat storage brick including silica brick, a combustion chamber for heating the heat storage chamber, and temperature adjustment of hot air flowing from the heat storage chamber through the combustion chamber to the hot air A hot stove control calculation device that performs calculations for controlling the operation of a hot stove equipped with a mixed cooling chamber that is performed by mixing cold air,
When the cold air is mixed and operated in the mixed cooling chamber, the air blowing period is ended by using the first residual heat amount index as an index of the residual heat amount of the heat storage brick when the air blowing period ends. First deriving means for deriving the amount of change with respect to the lower limit value of the minimum temperature of the quartz brick as the amount of change of the minimum temperature limit value of the quartz brick;
When operating without mixing the cold air in the mixed-cooling chamber, using the second residual heat amount index as an index of the residual heat amount of the heat storage brick when the air blowing period ends, the air blowing period ends. Second deriving means for deriving the amount of change with respect to the lower limit value of the minimum temperature of the quartz brick as the amount of change of the minimum temperature limit value of the quartz brick;
The amount of change with respect to the lower limit value of the minimum temperature of the silica brick when the air blowing period ends, derived by the first deriving means or the second deriving means, and the silica stone when the air blowing period ends. From the current value of the lower limit value of the minimum brick temperature, a third lower limit value for the minimum temperature of the quartz brick at the end of the blowing period in the next cycle is derived as the lower limit temperature of the quartz brick temperature. Deriving means;
Have
The first residual heat amount index is determined based on an opening degree of a cold air butterfly valve for adjusting a flow rate of the cold air flowing into the mixed cooling chamber,
The second residual heat index is an opening degree of a blow butterfly valve for adjusting a flow rate of the cold air flowing into the combustion chamber, or a blow air temperature which is a temperature of hot air discharged from the hot air furnace to the blast furnace. A hot stove control calculation apparatus characterized by being determined based on the above. The first residual heat index is an opening degree of the cold wind butterfly valve at a predetermined timing or period in the blowing period, or a time when the cold wind butterfly is fully closed in the blowing period,
The second residual heat index is an opening degree of the blow butterfly valve at a predetermined timing or period in the blowing period, or the blowing temperature at a predetermined timing or period in the blowing period. Item 4. The hot stove control calculation apparatus according to Item 1. Selecting means for selecting one residual heat index from the first residual heat index and the second residual heat index based on an input operation by an operator;
The first derivation means or the second derivation means uses the residual heat amount index selected by the selection means to change the amount of change with respect to the lower limit value of the minimum temperature of the silica brick when the blowing period ends. The hot stove control calculation apparatus according to claim 1, wherein the hot stove control calculation apparatus is derived as a change amount of the minimum temperature limit of the quartz brick. The target value of the quartz brick minimum temperature, which is the minimum temperature of the silica brick when the air blowing period ends, is a period longer than the time constant of the hot stove, and is an optimization time range that is a period of the cycle unit A target heat storage amount deriving means derived in
First process state prediction for deriving a predicted value of the process state of the hot stove using a first process model that is a calculation model for calculating the process state of the hot stove by inputting the amount of heat input to the hot stove Means,
The first process state prediction means provides a candidate for the amount of heat input to the hot stove to the first process model, and is a period that is less than the time constant of the hot stove, and is a period of the cycle unit. A predicted value of the minimum temperature of the silica brick in the section is derived, and the predicted value of the minimum temperature of the silica brick in the predicted section is the minimum temperature of the silica brick derived by the target heat storage amount deriving unit in the optimization time range. A candidate for the amount of heat input to the hot stove when the value of the first objective function, the value of which becomes smaller as it approaches the target value, is obtained as the amount of heat input to the hot stove in a predetermined cycle after the present time. Until the heat input candidate for the hot stove is reset, and the heat input to the hot stove in a predetermined cycle after the present time is determined. And,
The target heat storage amount deriving means predicts the quartz brick minimum temperature derived when the candidate value of the minimum temperature of the quartz brick and the input heat amount to the hot stove are determined by the first process state prediction means. An objective function that decreases as the value is closer to the objective function, and an objective that decreases as the total amount of heat input to the hot stove in the predetermined cycle after the present time determined by the first process state predicting means decreases. A minimum temperature of the quartz brick derived from the function and the minimum temperature of the quartz brick derived by the third deriving unit is derived when the amount of heat input to the hot stove is determined by the first process state predicting unit. The value of the second objective function, which is a weighted sum of the objective function that decreases as the amount exceeding the predicted value decreases, is minimized. Until the candidate for the target value of the minimum temperature of the quartz brick is obtained, the target value of the target value of the minimum temperature of the quartz brick is reset, and the target value of the minimum temperature of the quartz brick is determined. The hot stove control calculation apparatus of any one of Claims 1-3. The target value of the quartz brick minimum temperature, which is the minimum temperature of the silica brick when the air blowing period ends, is a period longer than the time constant of the hot stove, and is an optimization time range that is a period of the cycle unit A target heat storage amount deriving means derived in
First process state prediction for deriving a predicted value of the process state of the hot stove using a first process model that is a calculation model for calculating the process state of the hot stove by inputting the amount of heat input to the hot stove Means,
The first process state prediction means provides a candidate for the amount of heat input to the hot stove to the first process model, and is a period that is less than the time constant of the hot stove, and is a period of the cycle unit. A predicted value of the minimum temperature of the silica brick in the section is derived, and the predicted value of the minimum temperature of the silica brick in the predicted section is the minimum temperature of the silica brick derived by the target heat storage amount deriving unit in the optimization time range. A candidate for the amount of heat input to the hot stove when the value of the first objective function, the value of which becomes smaller as it approaches the target value, is obtained as the amount of heat input to the hot stove in a predetermined cycle after the present time. Until the heat input candidate for the hot stove is reset, and the heat input to the hot stove in a predetermined cycle after the present time is determined. And,
The target heat storage amount deriving unit was derived when the minimum temperature of the quartz brick temperature derived by the third deriving unit was determined by the first process state predicting unit as the amount of heat input to the hot stove. When the amount of heat input to the hot stove is determined by a constraint equation indicating a constraint that the predicted value of the minimum temperature of the quartz brick is not exceeded, a candidate for the target value of the minimum temperature of the quartz brick and the first process state prediction means In the range satisfying the constraint equation showing the constraint that the absolute value of the difference between the predicted value of the quartz brick minimum temperature derived in the above is a predetermined value or less, was determined by the first process state prediction means, When the value of the second objective function, which is an objective function that becomes smaller as the total amount of heat input to the hot stove in a predetermined cycle after the present time is smaller, is minimized. The target value of the minimum temperature of the quartz brick is determined by resetting the target value of the minimum temperature of the quartz brick until the candidate of the target value of the minimum temperature of the quartz brick is obtained. The hot stove control calculation apparatus according to any one of? The target value of the quartz brick minimum temperature, which is the minimum temperature of the silica brick when the air blowing period ends, is a period longer than the time constant of the hot stove, and is an optimization time range that is a period of the cycle unit A target heat storage amount deriving means derived in
First process state prediction for deriving a predicted value of the process state of the hot stove using a first process model that is a calculation model for calculating the process state of the hot stove by inputting the amount of heat input to the hot stove Means,
The first process state prediction means provides a candidate for the amount of heat input to the hot stove to the first process model, and is a period that is less than the time constant of the hot stove, and is a period of the cycle unit. A predicted value of the minimum temperature of the silica brick in the section is derived, and the predicted value of the minimum temperature of the silica brick in the predicted section is the minimum temperature of the silica brick derived by the target heat storage amount deriving unit in the optimization time range. A candidate for the amount of heat input to the hot stove when the value of the first objective function, the value of which becomes smaller as it approaches the target value, is obtained as the amount of heat input to the hot stove in a predetermined cycle after the present time. Until the heat input candidate for the hot stove is reset, and the heat input to the hot stove in a predetermined cycle after the present time is determined. And,
In the target heat storage amount deriving unit, the lower limit value of the quartz brick minimum temperature derived by the third deriving unit does not exceed the predicted value of the minimum temperature of the quartz brick derived by the first process state predicting unit. An objective function whose value becomes smaller as the total sum of the input heat amounts to the hot stove furnace in a predetermined cycle after the present time determined by the first process state predicting means is within a range satisfying a constraint equation indicating a constraint. The value of the target value of the minimum temperature of the quartz brick is closer to the predicted value of the minimum temperature of the quartz brick derived when the input heat amount to the hot stove is determined by the first process state prediction means. Until a candidate for the target value of the minimum temperature of the quartz brick is obtained when the value of the second objective function, which is a weighted sum of the objective function that is smaller, is minimized. The hot-blast furnace control calculation apparatus according to any one of claims 1 to 3, wherein a target value of the minimum temperature of the quartz brick is reset and a target value of the minimum temperature of the quartz brick is determined. . The amount of heat input to the hot stove in a predetermined cycle after the current time is a section determined in units of cycles, and in the control section where the last cycle of the section is a cycle before the first cycle of the prediction section The amount of heat input from the amount of heat input to the hot stove,
The first process state predicting unit is configured to differentiate the prediction section and the control section on a cycle basis to derive a predicted value of the quartz brick minimum temperature in the plurality of prediction sections, and in the plurality of control sections. The hot stove control calculation apparatus according to any one of claims 4 to 6, wherein an amount of heat input to the hot stove after the present time is determined for each cycle.   The constraint equation for the value of the first objective function is the absolute difference between the lowest value of the predicted value of the blast temperature in the hot stove and the target of the blast temperature in the hot stove calculated by the first process model. The absolute value of the difference between the constraint equation indicating that the value is less than or equal to the threshold value, the target value of the minimum temperature of the quartz brick and the predicted value of the minimum temperature of the quartz brick calculated by the first process model is equal to or less than the threshold value. The hot stove control calculation apparatus according to any one of claims 4 to 7, further comprising a constraint expression indicating that After the target value of the quartz brick minimum temperature is derived by the target heat storage amount deriving unit, optimum tracking control unit for deriving an operation command value of the input heat amount for the hot stove,
A second process state prediction for deriving a predicted value of the process state of the hot stove using a second process model that is a calculation model for calculating the process state of the hot stove by inputting the amount of heat input to the hot stove Means,
The second process state prediction means gives the second process model a candidate for the amount of heat input to the hot stove, and derives a predicted value of the lowest temperature of the silica brick in the prediction section,
The optimum follow-up control means is configured such that the predicted value of the minimum temperature of the quartz brick in the prediction interval derived by the second process state prediction means is the target of the minimum temperature of the quartz brick derived by the target heat storage amount deriving means. A third objective that is a weighted sum of an objective function that decreases in value as it approaches the value, and an objective function that decreases in value as the change in the amount of heat input to the hot stove in a cycle adjacent to each other after the current time decreases. The input heat quantity candidate for the hot stove is reset until the input heat quantity candidate for the hot stove when the function value is minimized is obtained as the input heat quantity for the hot stove in a predetermined cycle after the present time. The input heat amount for the cycle unit after the present time for the hot stove is determined. A hot-air furnace control computing device. The amount of heat input to the hot stove in a predetermined cycle after the current time is a section determined in units of cycles, and in the control section where the last cycle of the section is a cycle before the first cycle of the prediction section The amount of heat input from the amount of heat input to the hot stove,
The optimal follow-up control means determines the amount of heat input in units of cycles after the current time to the hot stove in the plurality of control sections by varying the control section in units of cycles,
10. The hot air according to claim 9, wherein the second process state prediction unit derives a predicted value of the minimum temperature of the quartz brick in the plurality of prediction sections by changing the prediction sections in units of cycles. Furnace control calculator. A period including a combustion period in which the heat storage brick is heated by the combustion gas to store heat and a blowing period in which hot air is generated by heat exchange with the heat storage brick through the cold air and supplied to the blast furnace is operated as one cycle. A hot air furnace, a heat storage chamber having a heat storage brick including silica brick, a combustion chamber for heating the heat storage chamber, and temperature adjustment of hot air flowing from the heat storage chamber through the combustion chamber to the hot air A hot stove operation index deriving method for performing calculation for controlling the operation of a hot stove equipped with a mixed cooling chamber performed by mixing cold air,
When the cold air is mixed and operated in the mixed cooling chamber, the air blowing period is ended by using the first residual heat amount index as an index of the residual heat amount of the heat storage brick when the air blowing period ends. A first derivation step for deriving a change amount with respect to a lower limit value of the minimum temperature of the quartz brick as a change amount of the minimum temperature limit value of the quartz brick;
When operating without mixing the cold air in the mixed-cooling chamber, using the second residual heat amount index as an index of the residual heat amount of the heat storage brick when the air blowing period ends, the air blowing period ends. A second derivation step of deriving the amount of change with respect to the lower limit value of the minimum temperature of the quartz brick as the change amount of the minimum temperature limit value of the quartz brick;
The amount of change with respect to the lower limit value of the minimum temperature of the silica brick when the air blowing period ends, derived from the first deriving step or the second deriving step, and the silica stone when the air blowing period ends. From the current value of the lower limit value of the minimum brick temperature, a third lower limit value for the minimum temperature of the quartz brick at the end of the blowing period in the next cycle is derived as the lower limit temperature of the quartz brick temperature. A derivation process;
Have
The first residual heat amount index is determined based on an opening degree of a cold air butterfly valve for adjusting a flow rate of the cold air flowing into the mixed cooling chamber,
The second residual heat index is an opening degree of a blow butterfly valve for adjusting a flow rate of the cold air flowing into the combustion chamber, or a blow air temperature which is a temperature of hot air discharged from the hot air furnace to the blast furnace. A method for deriving a hot stove operation index characterized by being determined based on The first residual heat index is an opening degree of the cold wind butterfly valve at a predetermined timing or period in the blowing period, or a time when the cold wind butterfly is fully closed in the blowing period,
The second residual heat index is an opening degree of the blow butterfly valve at a predetermined timing or period in the blowing period, or the blowing temperature at a predetermined timing or period in the blowing period. Item 12. The method for deriving a hot stove operation index according to Item 11. A selection step of selecting one residual heat index from the first residual heat index and the second residual heat index based on an input operation by an operator;
In the first derivation step or the second derivation step, an amount of change with respect to a lower limit value of the minimum temperature of the quartz brick when the air blowing period ends, using the residual heat index selected in the selection step. The method for deriving a hot stove operation index according to claim 11 or 12, wherein the method is derived as a change amount of the minimum temperature limit value of the quartz brick minimum temperature. The target value of the quartz brick minimum temperature, which is the minimum temperature of the silica brick when the air blowing period ends, is a period longer than the time constant of the hot stove, and is an optimization time range that is a period of the cycle unit A target heat storage amount deriving step derived in
First process state prediction for deriving a predicted value of the process state of the hot stove using a first process model that is a calculation model for calculating the process state of the hot stove by inputting the amount of heat input to the hot stove And having a process
In the first process state prediction step, a candidate for the amount of heat input to the hot stove is given to the first process model, and is a period that is less than the time constant of the hot stove, and is a period of the cycle unit. A predicted value of the minimum temperature of the silica brick in the section is derived, and the predicted value of the minimum temperature of the silica brick in the predicted section is the minimum temperature of the silica brick derived in the optimization time range by the target heat storage amount derivation step. A candidate for the amount of heat input to the hot stove when the value of the first objective function, the value of which becomes smaller as it approaches the target value, is obtained as the amount of heat input to the hot stove in a predetermined cycle after the present time. Until the heat input candidate for the hot stove is reset, and the heat input to the hot stove in a predetermined cycle after the present time is determined. And,
In the target heat storage amount deriving step, the candidate for the target value of the minimum temperature of the quartz brick and the prediction of the minimum temperature of the brick brick derived when the input heat amount to the hot stove is determined by the first process state prediction step. An objective function that decreases as the value is closer to the objective function, and an objective that decreases as the total amount of heat input to the hot stove in the predetermined cycle after the present time determined by the first process state prediction step decreases. The minimum temperature of the quartz brick derived from the function and the minimum temperature of the quartz brick derived from the third deriving step is determined when the amount of heat input to the hot stove is determined by the first process state prediction step. The value of the second objective function, which is a weighted sum of the objective function that decreases as the amount exceeding the predicted value decreases, is minimized. Until the candidate for the target value of the minimum temperature of the quartz brick is obtained, the target value of the target value of the minimum temperature of the quartz brick is reset, and the target value of the minimum temperature of the quartz brick is determined. The hot-blast furnace operation parameter | index derivation method of any one of Claims 11-13. The target value of the quartz brick minimum temperature, which is the minimum temperature of the silica brick when the air blowing period ends, is a period longer than the time constant of the hot stove, and is an optimization time range that is a period of the cycle unit A target heat storage amount deriving step derived in
First process state prediction for deriving a predicted value of the process state of the hot stove using a first process model that is a calculation model for calculating the process state of the hot stove by inputting the amount of heat input to the hot stove And having a process
In the first process state prediction step, a candidate for the amount of heat input to the hot stove is given to the first process model, and is a period that is less than the time constant of the hot stove, and is a period of the cycle unit. A predicted value of the minimum temperature of the silica brick in the section is derived, and the predicted value of the minimum temperature of the silica brick in the predicted section is the minimum temperature of the silica brick derived in the optimization time range by the target heat storage amount derivation step. A candidate for the amount of heat input to the hot stove when the value of the first objective function, the value of which becomes smaller as it approaches the target value, is obtained as the amount of heat input to the hot stove in a predetermined cycle after the present time. Until the heat input candidate for the hot stove is reset, and the heat input to the hot stove in a predetermined cycle after the present time is determined. And,
The target heat storage amount derivation step was derived when the silica brick minimum temperature lower limit value derived by the third derivation step was determined when the input heat amount to the hot stove was determined by the first process state prediction step. When the amount of heat input to the hot stove is determined by a constraint equation indicating a constraint that the predicted value of the minimum temperature of the silica brick is not exceeded, a candidate for the target value of the minimum temperature of the silica brick and the first process state prediction step In the range satisfying the constraint equation indicating the constraint that the absolute value of the difference between the predicted value of the quartz brick minimum temperature derived in the above is a predetermined value or less, determined by the first process state prediction step, When the value of the second objective function, which is an objective function that becomes smaller as the total amount of heat input to the hot stove in a predetermined cycle after the present time is smaller, is minimized. The target value for the minimum temperature of the quartz brick is determined by resetting the target value for the minimum temperature of the quartz brick until a candidate for the target value of the minimum temperature of the quartz brick is obtained. The hot-blast furnace operation parameter | index derivation method of any one of ~ 13.   In the target heat storage amount deriving step, the lower limit value of the quartz brick minimum temperature derived by the third deriving step does not exceed the predicted value of the minimum temperature of the quartz brick derived by the first process state prediction step. In a range satisfying a constraint equation indicating a constraint, an objective function, which is determined by the first process state prediction step, has a value that decreases as the total amount of heat input to the hot stove in the predetermined cycle after the current time decreases. In addition, the closer the candidate value of the target value of the minimum temperature of the quartz brick and the predicted value of the minimum temperature of the quartz brick derived when the amount of heat input to the hot stove is determined by the first process state prediction step is, the closer the value is. A candidate for the target value of the minimum temperature of the quartz brick when the value of the second objective function, which is the objective function that is a weighted sum of the objective function that becomes smaller, is minimized. The hot air according to any one of claims 11 to 13, wherein a target value of the minimum temperature of the quartz brick is reset and a target value of the minimum temperature of the quartz brick is determined until it is obtained. Derivation method of furnace operation index. The amount of heat input to the hot stove in a predetermined cycle after the current time is a section determined in units of cycles, and in the control section where the last cycle of the section is a cycle before the first cycle of the prediction section The amount of heat input from the amount of heat input to the hot stove,
In the first process state prediction step, the prediction interval and the control interval are made different for each cycle to derive a predicted value of the minimum temperature of the brick in the plurality of prediction intervals, and in the plurality of control intervals The hot stove operation index derivation method according to any one of claims 14 to 16, wherein an amount of heat input to the hot stove after the present time is determined for each cycle.   The constraint equation for the value of the first objective function is the absolute difference between the lowest value of the predicted value of the blast temperature in the hot stove and the target of the blast temperature in the hot stove calculated by the first process model. The absolute value of the difference between the constraint equation indicating that the value is less than or equal to the threshold value, the target value of the minimum temperature of the quartz brick and the predicted value of the minimum temperature of the quartz brick calculated by the first process model is equal to or less than the threshold value. The hot-blast furnace operation index derivation method according to claim 14, further comprising a constraint expression indicating that After the target value of the quartz brick minimum temperature is derived by the target heat storage amount derivation step, an optimal follow-up control step of deriving an operation command value of the input heat amount for the hot stove,
A second process state prediction for deriving a predicted value of the process state of the hot stove using a second process model that is a calculation model for calculating the process state of the hot stove by inputting the amount of heat input to the hot stove And having a process
In the second process state prediction step, a candidate for the amount of heat input to the hot stove is given to the second process model to derive a predicted value of the quartz brick lowest temperature in the prediction section,
In the optimum follow-up control step, the predicted value of the minimum temperature of the quartz brick in the prediction section derived in the second process state prediction step is the target of the minimum temperature of the quartz brick derived in the target heat storage amount deriving step. A third objective that is a weighted sum of an objective function that decreases in value as it approaches the value, and an objective function that decreases in value as the change in the amount of heat input to the hot stove in a cycle adjacent to each other after the current time decreases. The input heat quantity candidate for the hot stove is reset until the input heat quantity candidate for the hot stove when the function value is minimized is obtained as the input heat quantity for the hot stove in a predetermined cycle after the present time. The heat input for each cycle after the present time for the hot stove is determined. A hot-air furnace operation index derivation method described. The amount of heat input to the hot stove in a predetermined cycle after the current time is a section determined in units of cycles, and in the control section where the last cycle of the section is a cycle before the first cycle of the prediction section The amount of heat input from the amount of heat input to the hot stove,
The optimum follow-up control step determines the amount of heat input in units of cycles after the current time to the hot stove in a plurality of the control sections by changing the control sections in units of cycles.
The hot air according to claim 19, wherein the second process state prediction step derives a predicted value of the minimum temperature of the quartz brick in the plurality of prediction sections by changing the prediction sections in units of cycles. Derivation method of furnace operation index.   A computer program for causing a computer to function as each means of the hot stove control calculation apparatus according to any one of claims 1 to 10.

Images