Furnace temperature prediction method, furnace temperature control method, coke manufacturing method, furnace temperature prediction device, and furnace temperature control device.

Abstract

A furnace temperature prediction method, furnace temperature control method, coke manufacturing method, furnace temperature prediction device, and furnace temperature control device are provided, which enable highly accurate furnace temperature prediction using a physical model suitable for control in actual equipment. [Solution] The furnace temperature prediction method is a furnace temperature prediction method performed by a furnace temperature prediction device that predicts the temperature of a combustion chamber or carbonization chamber in a coke oven, which is composed of a combustion chamber (2) having a heat storage chamber at the bottom and a carbonization chamber (3) alternately connected to form a furnace group, using a temperature prediction model. The method includes acquiring operational performance information and making predictions based on the operational performance information. The temperature prediction model is a physical model constructed separately from the combustion chamber and carbonization chamber, with the heat transfer in all connected combustion chambers and carbonization chambers constructed as a two-dimensional heat transfer model in the horizontal and vertical directions perpendicular to the extrusion direction, and the heat transfer in all heat storage chambers constructed as a two-dimensional heat transfer model in the extrusion direction and vertical direction.

Description

Technical Field

[0001] The present disclosure relates to a furnace temperature prediction method, a furnace temperature control method, a method for producing coke, a furnace temperature prediction device, and a furnace temperature control device. In particular, the present disclosure relates to a furnace temperature prediction method, a furnace temperature control method, a method for producing coke, a furnace temperature prediction device, and a furnace temperature control device in a coke oven in which combustion chambers and carbonization chambers are alternately connected to form a furnace group.

Background Art

[0002] In a coke oven in which a plurality of combustion chambers and carbonization chambers are alternately connected to form a furnace group, coke is produced by carbonizing the coal charged into the carbonization chamber with heat from an adjacent combustion chamber. In order to achieve stabilization of the quality of the coke produced in the coke oven, improvement of the production efficiency, and reduction of the carbonization heat quantity, it is important to control the temperature of the combustion chamber or the carbonization chamber to a desired temperature. Since the coke oven has a large heat capacity of the furnace body and a long time constant for the response to an action for operating the furnace temperature, in order to control the temperature of the combustion chamber or the carbonization chamber with high precision, it is necessary to predict the future temperature with high precision and perform an action. However, the temperature of the coke oven fluctuates complicatedly due to a large number of fluctuation factors such as the fuel gas supply situation, the properties of the coal charged, the carbonization situation, and the states of adjacent carbonization chambers and combustion chambers. Therefore, it has been difficult to predict the future temperature with high precision.

[0003] As a method for predicting the future temperature, development of a temperature prediction technique using a statistical method has been carried out. For example, Patent Document 1 calculates target furnace group temperatures for a plurality of future times based on an evaluation function including a term representing the difference between the coke temperature predicted using a coke temperature prediction model and the target temperature, using past performance data.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

[0005] In coke oven operation, the control parameters are adjusted to minimize temperature fluctuations in the coke oven. Statistical methods based on historical data often fail to accurately predict oven temperature because the correlation between temperature fluctuations and control parameters is difficult to discern. However, methods using physical calculations (methods employing physical models) can provide more accurate predictions. Generally, using physical models involves a high computational load, making frequent calculations difficult and thus unsuitable for controlling actual coke ovens.

[0006] In view of these circumstances, the purpose of this disclosure is to provide a furnace temperature prediction method, a furnace temperature control method, a coke manufacturing method, a furnace temperature prediction device, and a furnace temperature control device that enable highly accurate furnace temperature prediction using a physical model suitable for control in actual equipment. [Means for solving the problem]

[0007] (1) A furnace temperature prediction method according to one embodiment of the present disclosure is: A furnace temperature prediction method performed by a furnace temperature prediction device that predicts the temperature of a combustion chamber or a carbonization chamber in a coke oven, in which a combustion chamber having a heat storage chamber at the bottom and a carbonization chamber are alternately connected to form a furnace group, using a temperature prediction model, The temperature prediction model is a physical model capable of transient calculations that performs temperature prediction calculations for the entire furnace assembly, including the combustion chamber, the carbonization chamber, and the heat storage chamber. The acquisition of operational performance information including information on the charging of coal into the carbonization chamber, information related to the coal being charged, information on the fuel supplied to the combustion chamber, the target temperature of the combustion chamber or the carbonization chamber, and the temperature of the combustion chamber or the carbonization chamber at the predicted time, This includes predicting the temperature of each of the multiple combustion chambers or multiple carbonization chambers after a predetermined period, based on the operational performance information, using the respective temperature prediction models for each of the multiple combustion chambers or multiple carbonization chambers. The temperature prediction model is a physical model constructed separately from the combustion chambers and carbonization chambers, in which heat transfer in all connected combustion chambers and carbonization chambers is constructed as a two-dimensional heat transfer model in the horizontal and vertical directions perpendicular to the extrusion direction, and heat transfer in all heat storage chambers is constructed as a two-dimensional heat transfer model in the extrusion direction and vertical direction.

[0008] (2) As one embodiment of the present disclosure, in (1), The aforementioned temperature prediction model is configured so that parameters for heat transfer can be adjusted. The method further includes adjusting the parameters based on an error, which is the difference between the calculated and actual temperatures of the combustion chamber or carbonization chamber from a predetermined time point in the past to the predicted time, up to the predicted time.

[0009] (3) As one embodiment of the present disclosure, in (2), The predetermined time is set to a time that is greater than the time constant of the coke oven.

[0010] (4) In one embodiment of the present disclosure, in any of (1) to (3), The size of the computational domain that constitutes the two-dimensional heat transfer model of the combustion chamber and the carbonization chamber is changed according to the thermal conductivity of the material occupying the computational domain.

[0011] (5) In one embodiment of the present disclosure, in any of (1) to (4), The time step size for the differential calculation using the two-dimensional heat transfer model of the combustion chamber and the carbonization chamber is changed according to the magnitude of the specific heat of the material occupying the calculation domain that constitutes the two-dimensional heat transfer model.

[0012] (6) In one embodiment of the present disclosure, in any of (1) to (5), In the two-dimensional heat transfer model of the combustion chamber and the carbonization chamber, the amount of heat transported within the combustion chamber is calculated from the amount of heat transferred due to the temperature difference with the adjacent computational domain and the amount of heat transported due to the fluid flow.

[0013] (7) The furnace temperature control method according to an embodiment of the present disclosure is Predict the temperature of the combustion chamber or the carbonization chamber by any one of the furnace temperature prediction methods (1) to (6), and calculate the fuel supply amount as an operation amount so that the predicted temperature approaches the target temperature, and control the fuel supply.

[0014] (8) The furnace temperature control method according to an embodiment of the present disclosure is Predict the temperature of the coal charged in the carbonization chamber by any one of the furnace temperature prediction methods (1) to (6), and calculate the fuel or air supply amount as an operation amount so that the predicted temperature is within a predetermined range at the time of extrusion, and control the fuel or air supply.

[0015] (9) The furnace temperature control method according to an embodiment of the present disclosure is Predict the temperature difference between the upper and lower parts of the combustion chamber by any one of the furnace temperature prediction methods (1) to (6), and calculate the fuel or air supply amount as an operation amount so that the predicted temperature difference is within a predetermined range, and control the fuel or air supply.

[0016] (10) The coke production method according to an embodiment of the present disclosure is Control the fuel supply by any one of the furnace temperature control methods (7) to (9) to produce coke.

[0017] (11) The furnace temperature prediction device according to an embodiment of the present disclosure is A furnace temperature prediction device that predicts the temperature of the combustion chamber or the carbonization chamber in a coke oven in which a combustion chamber having a regenerator at the lower part and a carbonization chamber are alternately connected to form a furnace group, using a temperature prediction model, The temperature prediction model is a physical model capable of unsteady calculation that performs overall temperature prediction calculation of the furnace group including the combustion chamber, the carbonization chamber, and the regenerator. An input device that acquires operation performance information including information on coal charging into the carbonization chamber, coal-related information to be charged, fuel information supplied to the combustion chamber, the target temperature of the combustion chamber or the carbonization chamber, and the temperature of the combustion chamber or the carbonization chamber at the time of prediction. Based on the operation performance information, a furnace temperature prediction unit predicts the temperature of each of the plurality of combustion chambers or the plurality of carbonization chambers after a predetermined period using the temperature prediction model of each of the plurality of combustion chambers or the plurality of carbonization chambers. The temperature prediction model is a physical model constructed as a two-dimensional heat transfer model in the horizontal and vertical directions perpendicular to the extrusion direction for heat transfer in all connected combustion chambers and carbonization chambers, and is constructed separately from the combustion chambers and the carbonization chambers as a two-dimensional heat transfer model in the extrusion direction and the vertical direction for heat transfer in all the regenerators.

[0018] (12) The furnace temperature control device according to an embodiment of the present disclosure (11) The furnace temperature prediction device predicts the temperature of the combustion chamber or the carbonization chamber, and calculates the fuel supply amount as an operation amount so that the predicted temperature approaches the target temperature, and controls the fuel supply.

Advantages of the Invention

[0019] According to the present disclosure, it is possible to provide a furnace temperature prediction method, a furnace temperature control method, a method for manufacturing coke, a furnace temperature prediction device, and a furnace temperature control device that enable highly accurate furnace temperature prediction using a physical model suitable for control in an actual machine.

Brief Description of the Drawings

[0020] [Figure 1] FIG. 1 is a schematic diagram showing the configuration of a furnace temperature prediction device according to an embodiment of the present disclosure. [Figure 2] FIG. 2 is a diagram for explaining a configuration example of a temperature prediction model. [Figure 3] FIG. 3 is a diagram for explaining heat transfer in a regenerator. [Figure 4] FIG. 4 is a diagram for explaining a two-dimensional heat transfer model of a regenerator. [Figure 5] FIG. 5 is a diagram for explaining a two-dimensional heat transfer model of a combustion chamber, a carbonization chamber, and bricks surrounding them. [Figure 6]Figure 6 is a flowchart showing an example of the processing of a furnace temperature prediction method according to one embodiment of the present disclosure. [Figure 7] Figure 7 is a flowchart showing another example of the processing of a furnace temperature prediction method according to one embodiment of the present disclosure. [Figure 8] Figure 8 is a flowchart showing another example of the processing of a furnace temperature prediction method according to one embodiment of the present disclosure. [Figure 9] Figure 9 shows the furnace temperature prediction accuracy in Example 1. [Figure 10] Figure 10 shows the temperature prediction accuracy inside the combustion chamber in Example 2. [Modes for carrying out the invention]

[0021] Hereinafter, a furnace temperature prediction method, a furnace temperature control method, a coke manufacturing method, a furnace temperature prediction device 20 (see Figure 1), and a furnace temperature control device according to one embodiment of the present disclosure will be described with reference to the drawings.

[0022] As described above, in order to stabilize the quality of coke produced in a coke oven, improve production efficiency, and reduce the amount of heat required for carbonization, it is important to control the temperature of the combustion chamber 2 (see Figure 1) or carbonization chamber 3 (see Figure 1) to the desired temperature. Because coke ovens have a large heat capacity and a long time constant for response to actions to control the oven temperature, it is necessary to predict future temperatures with high accuracy and take action accordingly. As a method for predicting future temperatures, statistical methods based on actual data, for example, do not easily show a correlation between temperature fluctuations and operational items, limiting the accuracy of oven temperature prediction. Here, methods using physical models can make accurate predictions. However, conventional methods using physical models generally have a high computational load, making frequent calculations difficult and unsuitable for controlling actual coke oven operations. In other words, a coke oven is a massive piece of equipment, and representing all of it as a phenomenon in three-dimensional space using a physical model results in a high computational load. Therefore, it is difficult to predict and control the oven temperature in real time on an actual machine.

[0023] One method for reducing the computational load of a physical model is to simulate phenomena in three-dimensional space in one or two dimensions. However, generally, the computational load and accuracy of a physical model are inversely proportional, and this can lead to a decrease in calculation accuracy. Therefore, to avoid a decrease in calculation accuracy, it is preferable to use a physical model that simulates in two dimensions rather than one. Furthermore, it is preferable to employ a calculation method that suppresses the increase in computational load caused by using a physical model that simulates in two dimensions, to the extent that it does not affect calculation accuracy. Here, when simulating a coke oven in two dimensions, only phenomena in two directions are simulated: the extrusion direction, the vertical direction, and the horizontal direction perpendicular to the extrusion direction (also simply called the horizontal direction). Here, the extrusion direction is the direction in which the coke is pushed out of the coke oven. The vertical direction is the up and down direction perpendicular to the extrusion direction, and corresponds to the stacking direction of the combustion chamber 2 and the heat storage chamber in Figure 1. The vertical direction is along the flow path of combustion gas from the bottom of the heat storage chamber to the combustion chamber 2. Furthermore, the horizontal direction is the left and right direction perpendicular to the extrusion direction and the vertical direction, and corresponds to the direction of connection between the combustion chamber 2 and the carbonization chamber 3 in Figure 1. For example, for the combustion chamber 2 and the carbonization chamber 3, the phenomena in the horizontal direction and the phenomena along the vertical combustion gas flow path can be simulated with a two-dimensional model without considering the extrusion direction, which is less likely to generate large temperature distributions. By simulating with a two-dimensional model, it becomes possible to construct a physical model with a lower computational load and higher computational accuracy than a three-dimensional calculation. In addition, the heat storage chamber below the combustion chamber 2 is partitioned by bricks in the horizontal direction, and there is heat dissipation from the bricks to the fuel gas and air introduced into the combustion chamber 2, and heat storage from the exhaust gas discharged from the combustion chamber 2 to the bricks (see Figure 3). Therefore, for the heat storage chamber as well, by simulating the phenomena in the horizontal direction and the phenomena along the vertical fuel gas and exhaust gas flow paths from the combustion chamber 2 with a two-dimensional model, it becomes possible to construct a physical model with a lower computational load and higher computational accuracy than a three-dimensional calculation. An example of the temperature prediction model configuration in this embodiment (Figure 2) will be described later.

[0024] (Device configuration) Figure 1 is a schematic diagram showing the configuration of the furnace temperature prediction device 20 according to this embodiment. The coke oven shown in Figure 1 comprises N combustion chambers 2 (2-1 to 2-N) and N-1 carbonization chambers 3 (3-1 to 3-(N-1)). Each of the N combustion chambers 2 has a heat storage chamber at its lower part (downward, on the fuel supply side in the vertical direction). The coke oven is composed of a furnace group in which combustion chambers 2 with heat storage chambers at their lower parts and carbonization chambers 3 are alternately connected. Here, N is an integer of 2 or more, but is not limited to a specific number. The coke oven charges coal, which is the raw material, into the carbonization chamber 3 and supplies fuel gas (G in Figure 1) to the combustion chamber 2. The coke oven produces coke by carbonizing the coal in the carbonization chamber 3 by heating the carbonization chamber 3 with the heat generated by the combustion chambers 2 on both sides. The furnace temperature prediction device 20 according to this embodiment predicts the temperature of the combustion chamber 2 or carbonization chamber 3 in the coke oven using a temperature prediction model described later. In controlling the furnace temperature of the coke oven, as described later, it is sufficient to predict the temperature of either the combustion chamber 2 or the carbonization chamber 3. In this embodiment, we will explain assuming that the temperature of the combustion chamber 2 is predicted, but as an alternative example, the temperature of the carbonization chamber 3 may also be predicted.

[0025] The coke oven is equipped with a main gas pipe 4, one end of which is connected to a gas supply source. The other ends of the N-1 branches of the main gas pipe 4 are piped to the combustion chambers 2, supplying fuel gas to the combustion chambers 2. One end of the main gas pipe 4 is provided with a control valve 5 (furnace gas cock) for adjusting the flow rate of fuel gas supplied to the entire furnace group (the total flow rate of fuel gas supplied to the combustion chambers 2). In addition, each of the other branches is provided with individual furnace control valves 6 (6-1 to 6-(N-1)) for fine-tuning the distributed gas flow rate before supplying it to the combustion chambers 2. The fuel gas fine-tuned by the 1st to (N-1)th individual furnace control valves 6 (individual furnace gas cocks) may be supplied to the two combustion chambers 2 adjacent to the corresponding 1st to (N-1)th carbonization chambers 3. The opening degree (control valve opening) of the control valves 5 and 6 is controlled by a control terminal 10. The control terminal 10 functions as a furnace temperature control device, which will be described later.

[0026] The furnace temperature prediction system comprises a control terminal 10, a furnace temperature prediction device 20, and a display device 30 as its main components. The control terminal 10 is composed of an information processing device such as a personal computer or workstation. The control terminal 10 is not an independent device, but may be composed of a part of a computer that functions as both the control terminal 10 and the furnace temperature prediction device 20. The control terminal 10 monitors the state of the combustion chamber 2 and the carbonization chamber 3 and manages the combustion chamber 2 and the carbonization chamber 3 according to the furnace temperature prediction device 20. The control terminal 10 also manages the operation of the coke oven. For example, the control terminal 10 adjusts the opening of the control valve 5 to control the flow rate of fuel gas supplied to the entire furnace group so that the average temperature of the combustion chamber 2 and the carbonization chamber 3 of the entire furnace group reaches the target temperature. The control terminal 10 also manages the operation of the coke oven so that the temperature inside the combustion chamber 2 and the carbonization chamber 3 reaches the individually set target temperature by adjusting the opening of the control valve 6 for each kiln to control the flow rate of fuel gas supplied to the combustion chamber 2. Furthermore, the control terminal 10 may manage the operation schedule obtained from a higher-level computer or entered by an operator.

[0027] The furnace temperature prediction device 20 is composed of an information processing device such as a personal computer or workstation. The furnace temperature prediction device 20 includes an input device 21, a temperature calculation unit 24, a heat transfer calculation unit 23, a furnace temperature prediction unit 25, and an output device 26.

[0028] The input device 21, heat transfer calculation unit 23, temperature calculation unit 24, furnace temperature prediction unit 25, and output device 26 can be implemented by a arithmetic processing unit such as a CPU. The input device 21, heat transfer calculation unit 23, temperature calculation unit 24, furnace temperature prediction unit 25, and output device 26 can be implemented, for example, by executing a computer program in an arithmetic processing unit. Here, as another example, the input device 21, heat transfer calculation unit 23, temperature calculation unit 24, furnace temperature prediction unit 25, and output device 26 may have their own dedicated arithmetic devices or arithmetic circuits.

[0029] The input device 21 is an input interface into which various measurement results and operational performance information related to the coke oven are input. The input device 21 may include a keyboard, mouse, pointing device, data receiving device, and graphical user interface (GUI). The input device 21 receives operational performance information and parameter setting values ​​from an external source and transmits them to the temperature calculation unit 24. Operational performance information is input to the input device 21 from the control terminal 10. The operational performance information may include combustion chamber temperature, carbonization chamber temperature, fuel gas components, fuel gas flow rate, air amount, cock opening degree for each oven, coal charge amount, coal moisture content, volatile component content, particle size, coal density, specific heat, and thermal conductivity. The operational performance information may also include the operation schedule (i.e., the extrusion and coal charging schedule) and the physical properties of the bricks that make up the coke oven. The physical properties of the bricks may include brick density, specific heat, and thermal conductivity. For example, the operational performance information includes information on the coal being charged into the carbonization chamber 3, information related to the coal being charged, information on the fuel supplied to the combustion chamber 2, the target temperature of the combustion chamber 2 or carbonization chamber 3, and the temperature of the combustion chamber 2 or carbonization chamber 3 at the predicted time. In this embodiment, since the temperature of the combustion chamber 2 is predicted as described above, the operational performance information includes the target temperature of the combustion chamber 2 and the temperature of the combustion chamber 2 at the predicted time. In addition, for example, the operational performance information includes the temperatures of the fuel gas and air introduced into the heat storage chamber.

[0030] The temperature calculation unit 24 takes the fuel gas components, furnace group air volume, furnace group fuel gas flow rate, fuel gas flow rate per kiln, air volume per kiln, and pre-combustion mixture temperature as input values ​​and calculates the combustion gas temperature, combustion gas flow rate, post-combustion gas components, specific heat, density, thermal conductivity of the combustion gas, and heat transfer coefficient in the combustion chamber 2. Here, the fuel gas flow rate per kiln may be calculated based on the opening of the cock for each kiln. The air volume per kiln may be calculated from the air valve for each kiln. The pre-combustion mixture temperature may be measured or calculated.

[0031] The heat transfer calculation unit 23 uses the values ​​calculated by the temperature calculation unit 24 and the values ​​obtained from the input device 21 to calculate the temperature, coal moisture content, and volatile component content at each location in the coke oven (calculation mesh such as bricks, coal, and combustion chamber 2). Here, the values ​​calculated by the temperature calculation unit 24 include combustion gas temperature, combustion gas flow rate, post-combustion gas components, specific heat, density, thermal conductivity of the combustion gas, and heat transfer coefficient in combustion chamber 2. The values ​​obtained from the input device 21 include coal charge amount, coal moisture content, volatile component content, particle size, coal density, specific heat, thermal conductivity, operation schedule, and physical properties of the bricks constituting the coke oven.

[0032] The furnace temperature prediction unit 25 takes planned values ​​and the temperature, coal moisture content, and volatile component content at each position of the coke oven calculated by the heat transfer calculation unit 23 as input values ​​to calculate (predict) the future temperature, coal moisture content, and volatile component content at each position of the coke oven. Planned values ​​and the like include future planned values ​​or the latest values ​​of fuel gas components, fuel gas flow rate, air volume, kiln cock opening, charge amount, coal moisture content, volatile component content, particle size, coal density, specific heat, thermal conductivity, operation schedule, and physical properties of the bricks constituting the coke oven. Planned values ​​and the like can be obtained as part of the operational performance information. Based on the operational performance information, the furnace temperature prediction unit 25 predicts the temperature of each of the multiple combustion chambers 2 or multiple carbonization chambers 3 after a predetermined period using the respective temperature prediction models for each of the multiple combustion chambers 2 or multiple carbonization chambers 3. In this embodiment, since the temperature of the combustion chamber 2 is predicted as described above, the furnace temperature prediction unit 25 predicts the temperature of each of the multiple combustion chambers 2 after a predetermined period using a temperature prediction model for each of the multiple combustion chambers 2. Here, the temperature prediction model is a physical model that performs transient calculations (calculations that divide the process into short time periods and gradually advance the time to determine the phenomenon at the next time period) and performs temperature prediction calculations for the entire furnace group, including the combustion chamber 2, carbonization chamber 3, and heat storage chamber.

[0033] The output device 26 outputs to the control terminal 10 the future temperature, coal moisture content, and volatile component content at each position of the coke oven calculated by the furnace temperature prediction unit 25, and the current temperature, coal moisture content, and volatile component content at each position of the coke oven calculated by the heat transfer calculation unit 23.

[0034] The control terminal 10 calculates and adjusts the optimal kiln-specific cock openings, etc., using the future temperature, coal moisture content, and volatile component content at each position of the coke oven obtained from the output device 26, as well as the predicted coal moisture content, volatile component content, and temperature or measured values ​​at each position of the coke oven at the predicted time. In other words, the control terminal 10 adjusts the openings of the control valve 5 and the kiln-specific control valve 6 based on the information transmitted from the output device 26. In this way, the control terminal 10 functions as a furnace temperature control device and executes the furnace temperature control method. In the furnace temperature prediction system, the furnace temperature prediction device 20 predicts the temperature of the combustion chamber 2 or carbonization chamber 3, and the furnace temperature control device calculates the fuel supply amount as a manipulated variable and controls the fuel supply so that the predicted temperature approaches the target temperature. In the coke production method in the coke oven, the control terminal 10, which is a furnace temperature control device, controls the fuel supply (by adjusting the fuel gas supply amount or the opening of the control valve that adjusts the fuel gas supply amount) to produce coke.

[0035] Furthermore, the output device 26 also has the function of transmitting information calculated by the furnace temperature prediction device 20 to the display device 30, and can display the calculation results output from the furnace temperature prediction device 20. At this time, the display device 30 displays the future temperature, coal moisture content, and volatile component content at each position of the coke oven obtained from the output device 26. Here, the display device 30 is, for example, a liquid crystal display.

[0036] (Method for predicting furnace temperature) The furnace temperature prediction device 20 having this configuration predicts the temperature of the combustion chamber 2 or carbonization chamber 3 in the coke oven using a temperature prediction model by performing the processing of the furnace temperature prediction method described below.

[0037] Figure 6 is a flowchart showing an example of the furnace temperature prediction process (furnace temperature prediction process) performed by the furnace temperature prediction device 20 according to this embodiment. The furnace temperature prediction process may be started at regular intervals of calculation cycles, or it may be started at any time by an operator pressing a button. It is desirable that the calculation cycle be longer than the time required for one furnace temperature prediction calculation.

[0038] The furnace temperature prediction process consists of two main calculation flows, shown as Pa and Pb in Figure 6. The first calculation flow (Pa) calculates the temperature from a predetermined time (t=-T) in the past to the predicted time (t=0) for a predetermined period of time (T). The second calculation flow (Pb) performs a prediction calculation from the predicted time (t=0) to a predetermined time in the future (t=T). Here, in a coke oven, for example, it takes about 8 hours or more for the temperature to reach a steady state by varying the gas flow rate. The predetermined time (T) should be set to be greater than the time it takes for the temperature at each position in the coke oven to reach a steady state due to such changes in operating conditions. In other words, assuming that the time constant of the coke oven is about 8 to 12 hours, the predetermined time (T) should be set to a time greater than the time constant of the coke oven, for example, set to 20 hours.

[0039] In the input steps (S11 and S21), the input device 21 acquires operational performance information. The operational performance information may include combustion chamber temperature, carbonization chamber temperature, fuel gas components, fuel gas flow rate, air volume, cock opening for each furnace, coal charge amount, coal moisture content, volatile component content, particle size, coal density, specific heat, thermal conductivity, operation schedule, and physical properties of the bricks constituting the coke oven. In addition, in input step S21, operational performance information beyond the predicted time is input, and is therefore labeled as future operational information in Figure 6. The future operational information may include fuel gas components, fuel gas flow rate, air volume, cock opening for each furnace, coal charge amount, coal moisture content, volatile component content, particle size, coal density, specific heat, thermal conductivity, operation schedule, and physical properties of the bricks constituting the coke oven. The future operational information represents the projected future values ​​of these values. If projected values ​​are not specified, the latest values ​​may be treated as continuing.

[0040] In S11, T is set to the predetermined time, and the time to be predicted is set to t=0, with the calculation starting from t=-T. t represents the time in the transient calculation, and T is a number greater than or equal to 0. A time step Δt is set to be shorter than the predetermined time (T), and the transient calculation is performed by advancing time by Δt from t=-T to t=0, and from t=0 to t=T (S12, S15 No., S22, and S25 No.). In the first calculation flow (Pa), the combustion gas temperature is calculated (S13), the coke oven heat transfer is calculated (S14), and when t=0, the calculation ends (S15 Yes), and the second calculation flow (Pb) begins. In the second calculation flow (Pb), the combustion gas temperature is calculated (S23) and the heat transfer in the coke oven is calculated (S24) as time advances by Δt, and the calculation ends when t=T (Yes in S25).

[0041] (Calculation of combustion gas temperature) The temperature calculation unit 24 calculates the combustion gas temperature using the fuel gas components, fuel gas flow rate, air volume, and pre-combustion mixture temperature. The temperature calculation unit 24 calculates the calorific value of the fuel gas during complete combustion from the fuel gas components and fuel gas flow rate. Specifically, the calorific value during complete combustion is calculated as the sum of "flow rate for each gas component × calorific value for each gas component" obtained for each gas component. The temperature calculation unit 24 also calculates the gas components and flow rate after combustion from the fuel gas components, fuel gas flow rate, and air volume using a chemical reaction equation. Then, the temperature calculation unit 24 calculates the combustion gas temperature such that the amount of heat consumed to raise the temperature of the combustion gas from the pre-combustion mixture temperature is equal to the calorific value of the fuel gas, using the combustion gas components, flow rate, calorific value, and pre-combustion mixture temperature. Here, the pre-combustion mixture temperature is obtained by calculating the heat exchange between the bricks and the fluid in the heat storage chamber, but measured values ​​may be used instead of calculated values. The specific heat and density of the combustion gas are calculated based on the temperature characteristics of each gas component. The heat transfer coefficient of the gas in the combustion chamber 2 may be calculated by selecting a suitable known approximation formula from the shape of the gas pipes in the combustion chamber 2.

[0042] (Temperature prediction model) Figure 2 is a diagram illustrating an example of the configuration of the temperature prediction model in this embodiment. The furnace temperature prediction device 20 predicts the temperatures of the combustion chamber 2 and carbonization chamber 3 (the temperature of the combustion chamber 2 in this embodiment) in the coke oven using the temperature prediction model shown in Figure 2. The temperature prediction model in this embodiment simulates phenomena in the horizontal direction perpendicular to the extrusion direction (the direction in which the combustion chamber 2 and carbonization chamber 3 are connected) and heat transfer in the vertical direction to the thermocouple (an example of a temperature measuring device) in the combustion chamber 2 using a two-dimensional model. That is, in order to predict the temperature of each of the multiple combustion chambers 2, a two-dimensional model of the horizontal and vertical directions perpendicular to the extrusion direction is used. By using a two-dimensional model of the horizontal and vertical directions, the computational load is reduced compared to a three-dimensional model, and it becomes possible to improve the calculation accuracy by considering heat transfer to the thermocouple. In addition, in this embodiment, the heat storage chamber, which is a part that greatly contributes to the calculation accuracy, is also calculated using a two-dimensional model separate from the combustion chamber 2 and carbonization chamber 3. Heat transfer occurs between the combustion chamber 2 and the carbonization chamber 3 and the heat storage chamber located below them, via bricks. However, the amount of heat supplied to the combustion chamber 2 largely depends on the fuel gas flowing from the heat storage chamber into the combustion chamber 2. The contribution of heat transfer via bricks to the heat supplied to the combustion chamber 2 is small. On the other hand, the contribution of heat transfer via bricks from the combustion chamber 2 to the carbonization chamber 3 is large. In the combustion chamber 2, fuel gas burns, generating high-temperature combustion gas. The temperature change of the combustion gas (gas), which has a low specific heat, is rapid, and the thermal response is quick, resulting in a large temperature distribution within the combustion chamber 2. For this reason, the time step size for heat transfer calculations of the combustion gas in the combustion chamber 2 needs to be set small. On the other hand, no gas combustion occurs in the heat storage chamber, and heat storage occurs through heat dissipation from the high-temperature combustion gas (exhaust gas) from the combustion chamber 2 to the bricks. The temperature change of the bricks is slow, and the thermal response is gradual. Therefore, even if the time step size for the heat transfer calculation in the heat storage chamber is set larger than that for combustion chamber 2, it will not have a significant impact on the calculation accuracy. To reduce the computational load, combustion chamber 2 and carbonization chamber 3 of the coke oven may be separated from the two-dimensional model of the heat storage chamber. The temperature prediction model for the heat storage chamber should be a two-dimensional heat transfer model in the extrusion direction and the vertical direction. This is to simulate the heat transfer phenomenon in which combustion gas (exhaust gas) discharged from combustion chamber 2 mixes into the heat storage chamber through flow paths connected to both ends of the heat storage chamber in the extrusion direction and stores heat in the bricks.

[0043] Furthermore, the size of the computational domain (computational mesh) of the 2D model may be set according to the thermal conductivity of the material occupying the domain. Bricks and coal (solids) generally have high thermal conductivity, and heat spreads relatively quickly and uniformly, making it difficult for temperature gradients to form. In addition, their specific heat is high, so the temperature fluctuates slowly. On the other hand, fuel gas and air (fluids) have lower thermal conductivity than solids, and heat transfer is slow, so temperature differences are easily generated, resulting in temperature gradients. Also, their specific heat is low, and temperature fluctuations are drastic. For this reason, in regions with low thermal resistance (bricks and coal), the computational mesh of the 2D model and the time step size of the differential calculation may be made larger to the extent that it does not affect the calculation accuracy. On the other hand, in regions with high thermal resistance (inside the combustion chamber), the computational mesh of the 2D model and the time step size of the differential calculation may be made smaller than the computational domain for bricks and coal.

[0044] The following sections will first explain the details of the heat transfer calculations for the heat storage chamber. Next, the details of the heat transfer calculations for combustion chamber 2 and carbonization chamber 3 will be explained.

[0045] (Heat transfer calculation for a thermal storage chamber) As described above, heat transfer in all heat storage chambers is constructed as a two-dimensional heat transfer model in the extrusion direction and the vertical direction. Here, the heat storage chamber is partitioned by bricks in the horizontal direction (see Figure 1). As shown in Figure 3, there is heat dissipation from the bricks to the fuel gas and air introduced into the combustion chamber 2, and heat storage from the exhaust gas discharged from the combustion chamber 2 to the bricks. The two-dimensional model for the heat storage chamber is a model for performing heat transfer calculations by discretizing the heat storage chamber into two dimensions (see Figure 4). Here, the actual heat storage chamber has a more complex structure with finer flow paths, but in this model, the surface area in contact between the fluid and bricks in the actual heat storage chamber may be made equal to the surface area of ​​the model to simplify the structure. In other words, the computational load may be reduced by making the amount of heat exchange between the heat storage chamber bricks and the fluid equivalent. The temperature calculation unit 24 inputs the heat storage chamber brick temperature, the temperatures of the fuel gas and air introduced into the heat storage chamber, the fuel gas components, the fuel gas flow rate, the air volume, the exhaust gas temperature, the exhaust gas components, and the exhaust gas flow rate into a two-dimensional model, and calculates the heat storage chamber brick temperature, the pre-combustion mixture temperature, etc. Here, the heat storage chamber brick temperature is the value calculated a time step (Δt) earlier (calculated value before Δt), as described later. The exhaust gas temperature is obtained from the combustion chamber temperature during the heat transfer calculation. The exhaust gas components and exhaust gas flow rate correspond to the combustion gas components and combustion gas flow rate calculated when calculating the combustion gas temperature. By using a two-dimensional model, the heat storage situation in the heat storage chamber can be accurately simulated, and temperature fluctuations that occur with a delay in response to changes in the amount of heat supplied to the coke oven and the push-out of coal can be accurately calculated. The two-dimensional model of the heat storage chamber (heat storage chamber heat transfer calculation formula) can be expressed by the following formula.

[0046]

number

[0047] Here, the subscripts i and j indicate variables in the computational domain at row i and column j. The superscript t indicates a variable at time t. ρr is the density [kg / m³]. 3 ]. Cpr is the specific heat at constant pressure [kJ / (kg·K)]. Vr is the volume [m 3]. Tr is the temperature [K]. Δt is the time step [s]. Ar is the length [m] of the boundary [m] that touches the calculation domain at row i, column j. qr is the heat transport rate per unit length and unit time moved to row i, column j [kJ / (m·s)]. Qr is the heat loss per unit time [kJ / s].

[0048] Furthermore, the formula for calculating the amount of heat transport can be expressed as follows, using the calculation area between row i-1 and column j and row i and column j as an example, in the case of heat transport between a solid and a fluid. Here, hr is the heat transfer coefficient [kJ / (K·m·s)].

[0049]

number

[0050] Furthermore, the formula for calculating the amount of heat transport can be expressed as follows, using the calculation region in row i-1, column j and the calculation region in row i, column j as an example, in the case of heat transport between solids or between fluids. Here, λr is the thermal conductivity [kJ / (K·m·s)].

[0051]

number

[0052] (Calculation of heat transfer in a coke oven) The heat transfer calculation unit 23 divides the calculation area of ​​the coke oven into a grid-like mesh by inputting the values ​​calculated by the temperature calculation unit 24 and the values ​​obtained from the input device 21 into the temperature prediction model. The heat transfer calculation unit 23 calculates the temperature, coal moisture content, and volatile component content at each position (calculation point such as bricks, coal, and combustion chamber 2) which is the intersection of the grid. Here, the values ​​calculated by the temperature calculation unit 24 include combustion gas temperature, combustion gas flow rate, post-combustion gas components, specific heat, density, thermal conductivity of the combustion gas, and heat transfer coefficient in combustion chamber 2. The values ​​obtained from the input device 21 include coal charge amount, coal moisture content, volatile component content, particle size, coal density, specific heat, thermal conductivity, operation schedule, and physical properties of the bricks that make up the coke oven.

[0053] The temperature prediction model divides the coke oven into a two-dimensional grid structure (mesh) in the horizontal and vertical directions, representing each of the combustion chamber 2, carbonization chamber 3, and the surrounding bricks as calculation points. In other words, the heat transfer in all connected combustion chambers 2 and carbonization chamber 3 and the surrounding bricks is constructed as a two-dimensional heat transfer model. Figure 5 shows the two-dimensional heat transfer model for combustion chamber 2, carbonization chamber 3, and the surrounding bricks. By solving the heat transfer calculation for each calculation point, the temperature at each position in the combustion chamber 2, carbonization chamber 3, and the surrounding bricks of the coke oven is calculated. Here, the number of horizontal and vertical points (number of calculation points) representing combustion chamber 2, carbonization chamber 3, and the bricks can each be an integer of 1 or more. The temperature of the coal may be calculated using the specific heat obtained by weighting the specific heat of the contained moisture and volatile components, and the specific heat of the coal, based on the volume density of each component. Here, when the boiling point of water is reached, the amount of heat supplied to the coal may be calculated using the latent heat of vaporization. In regions with low thermal resistance or high specific heat where the temperature hardly fluctuates, the computational load may be reduced by increasing the size of the calculation domain and decreasing the number of calculation domains.

[0054] The heat transfer calculation unit 23 performs heat transfer calculations within the fluid (fuel gas, air) flowing inside the combustion chamber 2, and heat transfer calculations between the fluid and the bricks surrounding the combustion chamber 2 (heat transfer calculation inside the combustion chamber). In the heat transfer calculation inside the combustion chamber, at the lower part of the combustion chamber where the combustion gas flows in, the calculation is performed to determine the amount of heat that flows in with the calculated temperature, flow rate, and composition of the combustion gas, and the amount of heat transported to the bricks surrounding the combustion chamber 2 is calculated.

[0055] Next, based on the amount of heat transferred to the bricks calculated by the combustion chamber heat transfer calculation, a heat transfer calculation is performed to the coal filling the carbonization chamber 3 and the coal between the combustion chamber 2 and the carbonization chamber 3 via the bricks (coke oven heat transfer calculation). In the coke oven heat transfer calculation, the temperature of the bricks and coal, and the moisture content of the coal are calculated from the input values. The input values ​​are the amount of coal charged in the carbonization chamber 3, the moisture content of the coal, particle size, density, specific heat and thermal conductivity, the extrusion and charging schedule (operation schedule), the physical properties of the bricks constituting the coke oven, and the temperature inside the combustion chamber and the amount of heat transferred to adjacent bricks calculated in the combustion chamber heat transfer calculation. Here, the physical properties of the bricks constituting the coke oven are density, specific heat and thermal conductivity. In the coke oven heat transfer calculation, when the calculation domain is coal, the temperature becomes a predetermined set value depending on the timing of coal charging, which is an input value. Also, if the coal contains moisture, the calculation is performed using the specific heat or bulk density that takes into account both moisture and coal. When the coal temperature reaches 100°C, the heat supplied to the coal is used for the evaporation of water. When the product of the water content and the latent heat of vaporization equals the supplied heat, water is lost from a small area. Once the water is gone, a solid-to-solid heat transfer calculation is performed, similar to the case of bricks.

[0056] Furthermore, the heat transfer calculation unit 23 performs a heat exchange calculation between the heat storage chamber and the exhaust gas due to the recirculation of exhaust gas from the combustion chamber 2 to the heat storage chamber (heat storage chamber-exhaust gas heat exchange calculation). In the heat storage chamber-exhaust gas heat exchange calculation, the flow rate, composition, and temperature of the exhaust gas introduced from the combustion chamber 2 to the heat storage chamber are used as input values, and the heat storage chamber brick temperature is calculated in the same way as the heat transfer calculation of the heat storage chamber described above. The temperature of the exhaust gas is set to the temperature of the upper calculation area of ​​the combustion chamber 2, which is calculated by the heat transfer calculation inside the combustion chamber.

[0057] For combustion chamber 2, carbonization chamber 3, and the bricks surrounding them, the temperature at each calculation point in the two-dimensional model (furnace heat transfer calculation formula) corresponding to the horizontal and vertical directions of the coke oven can be expressed by the following formula.

[0058]

number

[0059] Here, the subscripts i and j indicate that they are variables of the computational domain (i, j). ρ is the density [kg / m³]. 3 ]. Cp is the specific heat at constant pressure [kJ / (kg·K)]. V is the volume of the calculation domain [m 3 ] is the temperature of the calculation domain [K]. Δt is the time step [s]. q is the amount of heat transported per unit length per unit time to the calculation domain (i, j) [kJ / (m·s)]. Qloss is the amount of heat loss in the calculation domain (i, j) [[kJ / (m·s)]. The distance in the coke oven corresponding to the centroid position of the calculation domain (i, j) and the centroid positions of the surrounding calculation domains (i, j+1), (i+1, j), (i, j-1), and (i-1, j) (distance between calculation domains) can be shortened to improve calculation accuracy. However, the distance between calculation domains can be adjusted according to the computational load and is not limited to a specific value. For example, the distance between calculation domains may be 0.1m.

[0060] Furthermore, the formula for calculating heat transport is such that the calculation domains (i, j) and (i-1, j) are both occupied by fluids (fuel gas and air). For example, the heat transport from calculation domain (i, j) to calculation domain (i-1, j) can be expressed by the following equation. The first term on the right-hand side represents the heat transport due to the temperature difference between adjacent calculation domains. The second term represents the heat transport associated with the fluid flow to the adjacent calculation domain. Detailed calculations of the fluid using numerical methods such as the finite difference method, finite element method, or finite volume method based on the fluid's equations of motion (Navier-Stokes equations) or energy equations are computationally intensive. Therefore, the second term models the phenomenon of the heat contained in the fluid moving at a constant velocity. Here, h is the heat transfer coefficient [kJ / (K·m·s)], L is the length of the boundary shared by calculation domains (i, j) and (i-1, j) [m], and Q · This is the fluid velocity [m] of the fluid flowing from the computational domain (i, j) to the computational domain (i-1, j). 3 / s] is the case.

[0061]

number

[0062] Furthermore, in the formula for calculating heat transport, the calculation domain (i, j) is the region occupied by fluids (fuel gas and air) (for example, inside a combustion chamber), and the calculation domain (i-1, j) is the region occupied by solids (bricks, coal in a carbonization chamber). The amount of heat transported from calculation domain (i, j) to calculation domain (i-1, j) can be expressed by the following formula, for example. Here, h is the heat transfer coefficient [kJ / (K·m·s)]. For bricks in contact with the outside air, heat transfer calculations are performed with outside air at a constant temperature.

[0063]

number

[0064] Furthermore, in the formula for calculating the amount of heat transport, the calculation domains (i, j) and (i-1, j) are both regions occupied by solids (for example, bricks or coal in a carbonization chamber). The amount of heat transported from calculation domain (i, j) to calculation domain (i-1, j) can be expressed by the following formula, where λ is the thermal conductivity [kJ / (K·m·s)].

[0065]

number

[0066] (Optimization of temperature prediction models) The temperature prediction model may be optimized to reflect the temperature, coal moisture content, and volatile component content at each location of the coke oven calculated by the heat transfer calculation unit 23. Optimization is performed to prevent the calculated values ​​from deviating from actual values ​​due to error factors such as the aging of the furnace body or coke adhering to the walls of the carbonization chamber 3. Optimization is performed by adjusting the heat transport amount or heat loss amount at one or more of the above calculation points.

[0067] When optimization is performed, the temperature prediction model is configured so that parameters for heat transfer can be adjusted. The following equations are used for the two-dimensional model (coke oven heat transfer calculation formula) corresponding to the horizontal and vertical directions of the coke oven.

[0068]

number

[0069] Furthermore, the following formula is used to calculate the amount of heat transported.

[0070]

number

[0071] Here, R and S are variables (parameters) that can be adjusted by optimization. By adjusting R or S, the heat transport rate is optimized so that the error between the calculated value and the actual value at the temperature measurement location is reduced. Since increasing the number of parameters to be adjusted complicates the calculation, it is preferable to use as few correction terms as possible while improving accuracy. Here, it is preferable to use the amount of heat loss at the calculation point corresponding to the thermocouple location as the parameter to be adjusted.

[0072] Figure 7 is a flowchart illustrating the furnace temperature prediction method, including the optimization process. The same reference numerals are used for processes identical to those in Figure 6, and their explanations are omitted. The above parameters are adjusted based on the error, which is the difference between the calculated and actual temperatures of combustion chamber 2 (or carbonization chamber 3) from a predetermined time point in the past (t=-T) to the prediction time (t=0).

[0073] In the optimization flag step (S31), it is determined whether to perform an optimization calculation (i.e., optimizing adjustable parameters) based on the number of times the optimization calculation (i.e., optimizing adjustable parameters) has been performed or the time elapsed since the start of the calculation. If the optimization calculation has been performed up to the maximum number of times, or if the maximum time has elapsed since the start of the calculation (No in S31), the process proceeds to the second calculation flow (Pb). If the optimization calculation has not been performed up to the maximum number of times, and the maximum time has not elapsed since the start of the calculation (Yes in S31), the process proceeds to the third calculation flow (Pc, optimal parameter calculation).

[0074] The furnace temperature prediction unit 25 calculates the error between the calculated value and the actual value at the temperature measurement location. The error may be calculated from a predetermined time (T) past point in time (t=-T) to the predicted point in time (t=0). For example, the time average of the calculated value and the actual value of the temperature from t=-T to t=0 may be calculated, and the difference between the calculated time averages may be taken as the error. Alternatively, a weighted difference in time averages may be used, or RMSE (Root Mean Squared Error) may be used. If the error satisfies the judgment condition (Yes in S32), the process proceeds to the second calculation flow (Pb). For example, the judgment condition may be that the error is less than a predetermined threshold. If the error does not satisfy the judgment condition (No in S32), the process proceeds to S33.

[0075] The furnace temperature prediction unit 25 adjusts the parameters (e.g., the coefficient of the heat transport term and the heat loss term) to minimize the error (S33). The furnace temperature prediction unit 25 may repeatedly perform calculations while gradually changing the parameters, or it may perform adjustments based on the correlation between the adjusted parameters and the calculated temperature. Using the adjusted parameters, the time is set back to a predetermined time (T) in the past (t=-T) (S34), and the first calculation flow (Pa) is executed again.

[0076] (Furnace temperature control) The control terminal 10 compares the furnace temperature at the furnace temperature measurement location predicted by the furnace temperature prediction device 20 with the target temperature and calculates the amount of heat to supply so that the furnace temperature becomes the target furnace temperature. Based on the calculated amount of heat to supply, the control terminal 10 adjusts the control valve 5 and the kiln-specific control valve 6.

[0077] As an example of conventional technology, PID control is known, which calculates the amount of heat supplied so that the furnace temperature reaches the target temperature using three elements: the deviation between the furnace temperature at the predicted time and the target temperature, the integral value of the deviation, and the derivative value. In the method disclosed herein, the calculation is performed using the deviation between the future furnace temperature and the target temperature, rather than the furnace temperature at the predicted time. Therefore, it is possible to calculate the amount of heat supplied that takes future temperature fluctuations into account, enabling more accurate furnace temperature control.

[0078] Figure 8 is a flowchart showing the processing of the furnace temperature prediction method (furnace temperature control method), including the furnace temperature control process. The same reference numerals are used for the same processes as in Figure 6, and their explanations are omitted.

[0079] If the control terminal 10 changes the heat supply amount based on the deviation between the future furnace temperature and the target temperature (Yes in S41), it transmits information about the changed heat supply amount to the furnace temperature prediction device 20. The changed heat supply amount may be set to, for example, n times the value before the change (latest value) (n is a positive real number). The furnace temperature prediction device 20 performs a second calculation flow (Pb) reflecting the information about the changed heat supply amount as the time to be predicted (t=0) (S42). If the control terminal 10 does not change the heat supply amount (No in S41), the series of processes ends. The calculated future furnace temperature may be displayed on the display device 30.

[0080] The effects of the present invention will be described in detail below based on examples, but the present invention is not limited to these examples.

[0081] (Example 1) Figure 9 compares the furnace temperature prediction accuracy of the two-dimensional heat transfer calculation method (hereinafter referred to as "two-dimensional temperature prediction") and the one-dimensional heat transfer calculation method (hereinafter referred to as "one-dimensional temperature prediction") of the present invention when the fuel flow rate supplied to the coke oven fluctuates during actual operation, for predictions performed by the furnace temperature prediction unit 25. The prediction performed by the furnace temperature prediction unit 25 is, as described above, to calculate the future temperature at each position of the coke oven using planned values, etc., and the temperature, coal moisture content, and volatile component content at each position of the coke oven calculated by the heat transfer calculation unit 23 as input values. The horizontal axis is time [h]. The first vertical axis (left side) is the temperature prediction error, non-dimensionalized using the standard deviation of the error between the one-dimensional temperature prediction and the actual temperature. The second vertical axis (right side) shows the fuel flow rate, non-dimensionalized using the fuel flow rate at 0h (i.e., steady state when time is 0h). The fuel flow rate changes as shown in the second vertical axis, as indicated by "non-dimensionalized fuel flow rate". Furthermore, as shown by the curves labeled "1D" for the prediction error of the 1D temperature prediction and "2D" for the prediction error of the 2D temperature prediction in Figure 9, the prediction error changes as shown on the first vertical axis. In this embodiment, the fuel flow rate after 10h was reduced by approximately 25% from the steady-state (0h) fuel flow rate, and verification was performed using actual operating conditions. In the 1D temperature prediction, the prediction error increased as the fuel flow rate decreased. In contrast, in the 2D temperature prediction, a somewhat large prediction error occurred during the 40-45h period, but predictions were within ±1 for other periods. In the coke oven used for verification in this embodiment, temperature measurements were taken using thermocouples at the top of the combustion chamber 2, and the temperature difference between the top and bottom of the combustion chamber 2 increased as the fuel flow rate decreased. In the 1D temperature prediction, heat transfer calculations were performed only in the direction in which the combustion chamber 2 and the carbonization chamber 3 were adjacent. Therefore, it is considered that the prediction error is large because it cannot represent (cannot model and calculate) the increase in the temperature difference between the top and bottom of the combustion chamber 2. The 2D temperature prediction method can represent the widening temperature difference between the upper and lower parts of combustion chamber 2, which is considered to contribute to its high prediction accuracy.

[0082] (Example 2) Figure 10 shows the results of verifying the step response of the gas temperature inside the combustion chamber 2 for both one-dimensional and two-dimensional temperature predictions, when only the fuel flow rate supplied to the coke oven is halved, for predictions made by the furnace temperature prediction unit 25. The horizontal axis is time [h]. The vertical axis is the temperature non-dimensionalized using the standard deviation of the error between the steady-state predicted value and the actual value of the combustion chamber gas temperature in the one-dimensional model. In this embodiment, only the fuel flow rate supplied at the timing of 100h is halved under the condition of a constant air ratio. The combustion chamber gas temperature in the one-dimensional model and the lower combustion chamber gas temperature in the two-dimensional model decrease gradually up to 180h due to the halving of the fuel flow rate. In contrast, the upper combustion chamber gas temperature in the two-dimensional model shows a rapid temperature change at 120h. This rapid temperature change is consistent with the actual phenomenon that occurs when the fuel flow rate is halved under the condition of a constant air ratio, the flame inside the combustion chamber 2 becomes shorter, and the temperature in the upper part of the combustion chamber 2 tends to drop more easily than in the lower part. Therefore, by using two-dimensional temperature prediction, the accuracy of temperature prediction for the furnace top bricks (bricks placed at the furnace top, which is the upper part of combustion chamber 2) can be improved.

[0083] As described above, the furnace temperature prediction method, furnace temperature control method, coke manufacturing method, furnace temperature prediction device 20, and furnace temperature control device according to this embodiment enable highly accurate furnace temperature prediction using a physical model suitable for control in an actual machine, through the above configuration.

[0084] Furthermore, if the coke temperature at each position during extrusion predicted by the furnace temperature prediction device 20 falls below a set value, the control terminal 10 may calculate the amount of heat or air to supply so that the coke temperature at each position falls within a predetermined range. Based on the calculated amount of heat or air to supply, the control terminal 10 may adjust the control valve 5 and the kiln-specific control valve 6.

[0085] Furthermore, if the temperature difference between the upper and lower parts of the combustion chamber 2 at the furnace temperature measurement position predicted by the furnace temperature prediction device 20 (upper-lower temperature difference) falls outside a predetermined range, the control terminal 10 may calculate the amount of heat to supply so that the upper-lower temperature difference of the combustion chamber 2 falls within a predetermined range. Based on the calculated amount of heat to supply, the control terminal 10 may adjust the control valve 5 and the kiln-specific control valve 6.

[0086] While embodiments of this disclosure have been described based on the drawings and examples, it should be noted that those skilled in the art will find it easy to make various modifications or alterations based on this disclosure. Therefore, it should be noted that these modifications or alterations are included within the scope of this disclosure. For example, the functions included in each component or step can be rearranged in a logically consistent manner, and multiple components or steps can be combined into one or divided. Embodiments relating to this disclosure can also be realized as programs executed by a processor in the device or as storage media recording such programs. These should also be understood to be included within the scope of this disclosure. [Explanation of Symbols]

[0087] 2 Combustion chambers 3. Carbonization chamber 4. Gas main 5. Adjustment valve 6. Adjustment valve for each kiln 10 Control terminals 20 Furnace temperature prediction device 21 Input device 23 Heat Transfer Calculation Unit 24 Temperature calculation section 25 Furnace Temperature Prediction Section 26 Output device 30 Display device

Claims

1. A furnace temperature prediction method performed by a furnace temperature prediction device that predicts the temperature of a combustion chamber or a carbonization chamber in a coke oven, in which a combustion chamber having a heat storage chamber at the bottom and a carbonization chamber are alternately connected to form a furnace group, using a temperature prediction model, The temperature prediction model is a physical model capable of transient calculations that performs temperature prediction calculations for the entire furnace assembly, including the combustion chamber, the carbonization chamber, and the heat storage chamber. The acquisition of operational performance information including information on the charging of coal into the carbonization chamber, information related to the coal being charged, information on the fuel supplied to the combustion chamber, the target temperature of the combustion chamber or the carbonization chamber, and the temperature of the combustion chamber or the carbonization chamber at the predicted time, This includes predicting the temperature of each of the multiple combustion chambers or multiple carbonization chambers after a predetermined period, based on the operational performance information, using the respective temperature prediction models for each of the multiple combustion chambers or multiple carbonization chambers. The aforementioned temperature prediction model is a physical model constructed separately from the combustion chambers and carbonization chambers, where the heat transfer in all connected combustion chambers and carbonization chambers is constructed as a two-dimensional heat transfer model in the horizontal and vertical directions perpendicular to the extrusion direction, and the heat transfer in all heat storage chambers is constructed as a two-dimensional heat transfer model in the extrusion direction and vertical direction.

2. The aforementioned temperature prediction model is configured so that parameters for heat transfer can be adjusted. The furnace temperature prediction method according to claim 1, further comprising adjusting the parameters based on an error which is the difference between the calculated temperature and the actual temperature of the combustion chamber or carbonization chamber from a point in time a predetermined time prior to the prediction point up to the prediction point.

3. The furnace temperature prediction method according to claim 2, wherein the predetermined time is set to a time greater than the time constant of the coke oven.

4. The furnace temperature prediction method according to claim 1, wherein the size of the computational domain constituting the two-dimensional heat transfer model of the combustion chamber and the carbonization chamber is changed according to the magnitude of the thermal conductivity of the material occupying the computational domain.

5. The furnace temperature prediction method according to claim 1, wherein the time step size for differential calculation using a two-dimensional heat transfer model of the combustion chamber and the carbonization chamber is changed according to the magnitude of the specific heat of the material occupying the calculation domain constituting the two-dimensional heat transfer model.

6. The furnace temperature prediction method according to claim 1, wherein, in a two-dimensional heat transfer model of the combustion chamber and the carbonization chamber, the amount of heat transported in the combustion chamber is calculated from the amount of heat transfer due to the temperature difference with an adjacent calculation domain and the amount of heat transported due to the fluid flow.

7. A furnace temperature control method comprising predicting the temperature of the combustion chamber or the carbonization chamber using the furnace temperature prediction method described in any one of claims 1 to 6, and controlling the fuel supply by calculating the fuel supply amount as a manipulated variable so that the predicted temperature approaches the target temperature.

8. A furnace temperature control method comprising predicting the temperature of the coal charged in the carbonization chamber using the furnace temperature prediction method described in any one of claims 1 to 6, and controlling the supply of fuel or air by calculating the amount of fuel or air to be supplied as an operand so that the predicted temperature falls within a predetermined range during extrusion.

9. A furnace temperature control method comprising predicting the temperature difference between the upper and lower parts of the combustion chamber using the furnace temperature prediction method described in any one of claims 1 to 6, and controlling the supply of fuel or air by calculating the amount of fuel or air to be supplied as a control variable so that the predicted temperature difference falls within a predetermined range.

10. A method for producing coke, comprising controlling the supply of the fuel by the furnace temperature control method described in claim 7 to produce coke.

11. A furnace temperature prediction device for a coke oven in which a combustion chamber having a heat storage chamber at the bottom and a carbonization chamber are alternately connected to form a furnace group, predicts the temperature of the combustion chamber or the carbonization chamber using a temperature prediction model, The temperature prediction model is a physical model capable of transient calculations that performs temperature prediction calculations for the entire furnace assembly, including the combustion chamber, the carbonization chamber, and the heat storage chamber. An input device that acquires operational performance information including information on charging coal into the carbonization chamber, information related to the coal being charged, information on fuel supplied to the combustion chamber, the target temperature of the combustion chamber or the carbonization chamber, and the temperature of the combustion chamber or the carbonization chamber at a predicted time. The furnace temperature prediction unit predicts the temperature of each of the multiple combustion chambers or multiple carbonization chambers after a predetermined period, based on the operational performance information, using the temperature prediction model for each of the multiple combustion chambers or multiple carbonization chambers. The aforementioned temperature prediction model is a physical model constructed separately from the combustion chambers and carbonization chambers, where the heat transfer in all connected combustion chambers and carbonization chambers is constructed as a two-dimensional heat transfer model in the horizontal and vertical directions perpendicular to the extrusion direction, and the heat transfer in all heat storage chambers is constructed as a two-dimensional heat transfer model in the extrusion direction and vertical direction.

12. A furnace temperature control device that predicts the temperature of the combustion chamber or the carbonization chamber using the furnace temperature prediction device described in claim 11, and controls the supply of fuel by calculating the amount of fuel to be supplied as a manipulated variable so that the predicted temperature approaches the target temperature.

Images