Heating furnace combustion gas usage amount prediction device, energy use optimization system, energy use optimization device, display terminal device, heating furnace combustion gas usage amount prediction method, and energy use optimization method

Abstract

A device for predicting the amount of combustion gas used in a heating furnace is provided with: a slab information acquisition means for acquiring information relating to a slab; a temperature increase amount calculation means for calculating, on the basis of each piece of slab information, an energy-converted temperature increase amount obtained by converting the energy required for heating in the heating furnace; a temperature increase amount editing means for expanding the calculated energy-converted temperature increase amount for each slab as an energy-converted temperature increase amount for each predetermined calculation interval, and editing the energy-converted temperature increase amount for the entire heating furnace for each calculation interval; and a gas usage amount prediction means for predicting the gas usage amount in the heating furnace on the basis of the energy-converted temperature increase amount of the entire heating furnace for each calculation interval and the past actual gas usage amount.

Description

Technical Field

[0001] The present invention relates to a heating furnace combustion gas usage prediction device, an energy utilization optimization system, an energy utilization optimization device, a display terminal device, a heating furnace combustion gas usage prediction method and an energy utilization optimization method. Background Art

[0002] In an iron and steel plant, blast furnace gas (B gas) generated from a blast furnace, coke oven gas (C gas) generated from a coke oven, and converter gas (LD gas) generated from a converter, or a mixture of these and purchased gas from a gas company (M gas) is used in workshops and power generation equipment. At this time, when the gas storage capacity exceeds the gas container and the gas becomes excessive, the excess gas is released into the atmosphere. On the contrary, when the gas demand is greater than the gas supply and the gas is insufficient, it will affect the operation of the factory. Therefore, in an iron and steel plant, it is necessary to use the gas appropriately according to the supply and demand of the gas.

[0003] In this regard, the following technology is known: evaluating the cost of energy utilization such as gas generated by an ironworks, gas used in each factory, purchased electricity, generated electricity, steam generated, and used steam to achieve optimization of operation (for example, refer to Patent Documents 1 and 2).

[0004] Patent Document 1 discloses a technology that obtains energy operation optimization conditions that minimize costs based on operation prediction values ​​such as production plans, and issues an alarm when the error between the predicted value and the actual value of energy operation cost is larger than a predetermined value.

[0005] Patent document 2 is a technology that also includes the optimization calculation of energy use in future plans, for example, in the case of continuing the prediction calculation at a specified calculation cycle (e.g., 5 minutes, etc.). In Patent document 2, in order to solve the problem that the calculation load becomes higher and the prediction accuracy of the production plan becomes worse as time goes by, the energy utilization decision interval is set to be coarser for the prediction calculation after the specified period in the future.

[0006] In particular, in the heating furnace of an ironworks, semi-finished products called slabs are heated by mixed gas (M gas) from the time they are loaded to the time they are extracted. If there is an excess or deficiency of mixed gas, proper combustion cannot be performed, which may also affect the quality of the product. Therefore, it is required to predict the amount of mixed gas to be used in the future and produce it at an appropriate time.

[0007] Prior art literature

[0008] Patent Literature

[0009] Patent Document 1: International Publication No. 2015 / 174359

[0010] Patent Document 2: Japanese Patent Application Publication No. 2021-163085 Summary of the invention

[0011] Problems to be solved by the invention

[0012] There is no specific description of using future operation plans in Patent Documents 1 and 2. In particular, the gas generated in an ironworks also needs to take into account the operation of gas containers, and more accurate prediction is required.

[0013] In addition, in the heating furnace of the ironworks, as described above, when the mixed gas is excessive or insufficient, proper combustion cannot be performed, which may also affect the product quality. Therefore, it is required to accurately predict the amount of mixed gas to be used in the future and to optimize the energy operation in the ironworks while manufacturing at the appropriate timing.

[0014] However, slabs of various heating conditions are sequentially loaded into the heating furnace, and multiple slabs are heated simultaneously and continuously in the furnace, and the heated slabs are sequentially extracted. Therefore, it is not easy to predict the temporal change of the combustion gas usage, and it is also necessary to correct the planned value based on actual performance.

[0015] The present invention is made in view of the above situation, and its purpose is to provide a heating furnace combustion gas usage prediction device, an energy utilization optimization system, an energy utilization optimization device, a display terminal device, a heating furnace combustion gas usage prediction method and an energy utilization optimization method that can predict the gas usage in the heating furnace with high accuracy.

[0016] Means for solving problems

[0017] In order to solve the above-mentioned problems and achieve the purpose, the heating furnace combustion gas usage prediction device of the present invention is a heating furnace combustion gas usage prediction device for the energy utilization optimization system of an iron and steel plant, and the heating furnace combustion gas usage prediction device comprises: a slab information acquisition unit, which acquires information related to slabs loaded into the heating furnace and extracted in a predetermined future period from the current moment; a temperature rise calculation unit, which calculates the energy-converted temperature rise required for heating in the heating furnace for each slab based on the acquired information of each slab; a temperature rise editing unit, which, based on the loading time of each slab into the heating furnace and the extraction time of each slab from the heating furnace, expands the calculated energy-converted temperature rise of each slab as the energy-converted temperature rise of each predetermined calculation interval, and edits it as the energy-converted temperature rise of the heating furnace as a whole for each calculation interval; and a gas usage prediction unit, which predicts the gas usage in the heating furnace based on the energy-converted temperature rise of the heating furnace as a whole for each calculation interval and the past actual gas usage.

[0018] In addition, the heating furnace combustion gas usage prediction device of the present invention is that in the above invention, the temperature rise calculation unit refers to the slab information, and based on the loading temperature and extraction temperature of a specified number of slabs before and after the slab, the loading temperature that takes into account the properties of the slab and the use of the insulation device during transportation until the slab is loaded into the heating furnace, and the extraction temperature based on the heating target temperature of the slab are corrected, and the energy conversion temperature of each slab is calculated based on the corrected loading temperature and extraction temperature.

[0019] In addition, the heating furnace combustion gas usage prediction device of the present invention is that, in the above invention, regarding the loading temperature in the temperature rise calculation unit, the slab information is referred to so that: when the heating furnace loading time is in the past, the loading temperature is set to the actual value; when the heating furnace loading time is in the future, the properties of the slab are referred to; when the slab is a hot plate, the loading temperature taking into account the insulation time and the conveying time is calculated based on whether the insulation device is used; when the slab is a cold plate, the loading temperature is set to a specified value.

[0020] In addition, the heating furnace combustion gas usage prediction device of the present invention is that in the above invention, the temperature rise editing unit considers a predetermined time allocation plan when expanding the calculated energy-converted temperature rise of each slab as the energy-converted temperature rise of each calculation interval, and considers the deviation of the loading time and the extraction time from the calculation interval.

[0021] In addition, the heating furnace combustion gas usage prediction device of the present invention is that in the above invention, the gas usage prediction unit uses a learned model to predict the gas usage after performance compensation, and the learned model is learned in a manner that takes the energy converted temperature rise of the heating furnace as a whole for each of the calculation intervals edited by the temperature rise editing unit as input, considers the energy required to maintain the temperature in the furnace, and outputs the gas usage.

[0022] In order to solve the above-mentioned problems and achieve the purpose, the energy utilization optimization system of the present invention is an energy utilization optimization system having the above-mentioned heating furnace combustion gas usage prediction device and the iron and steel plant energy utilization optimization device, wherein the energy utilization optimization device obtains the gas usage of the heating furnace predicted by the heating furnace combustion gas usage prediction device, and optimizes the energy utilization conditions of the iron and steel plant.

[0023] In order to solve the above-mentioned problems and achieve the purpose, the energy utilization optimization device of the present invention is an energy utilization optimization device of an iron and steel plant, which comprises: a slab information acquisition unit, which acquires information related to slabs loaded into a heating furnace and extracted in a predetermined future period from the current moment; a temperature increase calculation unit, which calculates, for each slab, an energy-converted temperature increase converted from the energy required for heating in the heating furnace based on the acquired information of each slab; a temperature increase editing unit, which, based on the loading time of each slab into the heating furnace and the extraction time of each slab from the heating furnace, expands the calculated energy-converted temperature increase of each slab as the energy-converted temperature increase of each predetermined calculation interval, and edits it as the energy-converted temperature increase of the heating furnace as a whole for each calculation interval; a gas usage prediction unit, which predicts the gas usage in the heating furnace based on the energy-converted temperature increase of the heating furnace as a whole for each calculation interval and the past actual gas usage; and an energy utilization optimization unit, which optimizes the energy utilization conditions of the iron and steel plant based on the predicted gas usage.

[0024] In order to solve the above-mentioned problems and achieve the purpose, the display terminal device of the present invention obtains and displays various information from a heating furnace combustion gas usage prediction device that predicts the future gas usage of the heating furnace and an energy operation optimization device that optimizes the energy operation conditions of the iron and steel plant based on the future gas usage, wherein the display terminal device comprises: an information acquisition unit that acquires information, the information at least including an energy conversion temperature rise based on the overall heating furnace, a gas usage predicted by past actual gas usage, and a mixed amount of by-product gas based on the predicted gas usage, the energy conversion temperature rise of the overall heating furnace being calculated for each predetermined calculation interval and edited as the energy conversion temperature rise of the overall heating furnace for each of the calculation intervals; and a display unit that displays the information acquired by the information acquisition unit.

[0025] In order to solve the above-mentioned problems and achieve the purpose, the heating furnace combustion gas usage prediction method of the present invention is a heating furnace combustion gas usage prediction method executed by a heating furnace combustion gas usage prediction device constructed by using a computer and used in the energy utilization optimization system of an iron and steel plant, which includes: a slab information acquisition step, in which the slab information acquisition unit of the computer acquires information related to slabs that are loaded into the heating furnace and extracted in a future period predetermined from the current moment; a temperature rise calculation step, in which the temperature rise calculation unit of the computer calculates the temperature rise required for heating in the heating furnace for each slab based on the acquired information of each slab. The energy-converted temperature rise obtained by energy conversion; a temperature rise editing step, in which the temperature rise editing unit of the computer expands the calculated energy-converted temperature rise of each slab as the energy-converted temperature rise of each predetermined calculation interval based on the time when each slab is loaded into the heating furnace and the time when it is extracted from the heating furnace, and edits it as the energy-converted temperature rise of the heating furnace as a whole for each of the calculation intervals; and a gas usage prediction step, in which the gas usage prediction unit of the computer predicts the gas usage in the heating furnace based on the energy-converted temperature rise of the heating furnace as a whole for each of the calculation intervals and the past actual gas usage.

[0026] In order to solve the above-mentioned problems and achieve the purpose, the energy utilization optimization method of the present invention is an energy utilization optimization method executed by an energy utilization optimization device of an iron and steel plant constructed using a computer, which includes: a slab information acquisition step, in which a slab information acquisition unit of the computer acquires information related to slabs loaded into a heating furnace and extracted in a predetermined future period from the current moment; a temperature rise amount calculation step, in which the temperature rise amount calculation unit of the computer calculates, for each slab, an energy-converted temperature rise amount converted from the energy required for heating in the heating furnace based on the acquired information of each slab; and a temperature rise amount editing step, in which the temperature rise amount editing unit of the computer calculates, for each slab, an energy-converted temperature rise amount converted from the energy required for heating in the heating furnace; Based on the time when each slab is loaded into the heating furnace and the time when each slab is taken out from the heating furnace, the calculated energy conversion temperature rise of each slab is expanded as the energy conversion temperature rise of each predetermined calculation interval, and edited as the energy conversion temperature rise of the heating furnace as a whole for each of the calculation intervals; a gas usage prediction step, in which the gas usage prediction unit of the computer predicts the gas usage in the heating furnace based on the energy conversion temperature rise of the heating furnace as a whole for each of the calculation intervals and the past actual gas usage; and an energy utilization optimization step, in which the energy utilization optimization unit of the computer optimizes the energy utilization conditions of the iron and steel plant based on the predicted gas usage.

[0027] Effects of the Invention

[0028] According to the heating furnace combustion gas usage prediction device and heating furnace combustion gas usage prediction method of the present invention, it is possible to accurately predict the future gas usage after performance compensation. In addition, according to the energy operation optimization system, energy operation optimization device and energy operation optimization method of the present invention, it is possible to optimize the energy operation conditions of the iron and steel plant based on the highly accurately predicted gas usage. In addition, according to the display terminal device of the present invention, it is possible to indicate information such as the future gas usage and the mixed amount of by-product gas based on the future gas usage. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is a diagram showing a schematic configuration of an energy utilization optimization system according to an embodiment of the present invention.

[0030] Figure 2 This is a block diagram showing the specific functions of the heating furnace combustion gas usage prediction device according to the embodiment of the present invention.

[0031] Figure 3 This is a block diagram showing the specific functions of the energy utilization optimization device according to the embodiment of the present invention.

[0032] Figure 4 This is a flowchart showing the flow of a method for predicting the amount of combustion gas used in a heating furnace according to an embodiment of the present invention.

[0033] Figure 5 This is a flowchart showing details of a temperature increase amount calculation step in the heating furnace combustion gas usage amount prediction method according to the embodiment of the present invention.

[0034] Figure 6 This is a flowchart showing the details of the charging temperature simulation in the temperature increase amount calculation step in the heating furnace combustion gas usage prediction method according to the embodiment of the present invention.

[0035] Figure 7 This is a diagram showing the relationship between the slab charging plan to the heating furnace and the total value of the energy-converted temperature increase amount of each slab per calculation interval (ΔT) in the heating furnace combustion gas usage prediction method according to the embodiment of the present invention.

[0036] Figure 8 This is a graph comparing the root mean square error (RMSE) of the example of the heating furnace combustion gas usage prediction method according to the embodiment of the present invention when only the actual average value is used and when rolling information is used in addition to the actual average value. DETAILED DESCRIPTION

[0037] Referring to the accompanying drawings, a heating furnace combustion gas usage prediction device, an energy operation optimization system, an energy operation optimization device, a display terminal device, a heating furnace combustion gas usage prediction method, and an energy operation optimization method according to an embodiment of the present invention are described. It should be noted that the constituent elements in the following embodiments include elements that can be and are easily replaced by those skilled in the art or elements that are substantially the same.

[0038] (Energy utilization optimization system)

[0039] Reference Figure 1 and Figure 2 The energy utilization optimization system of the embodiment is described. The energy utilization optimization system is a system used in, for example, an iron and steel plant. Figure 1 As shown, there are a heating furnace combustion gas usage prediction device 1, an energy operation optimization device 2 and a display terminal device 3.

[0040] The heating furnace combustion gas usage prediction device 1, the energy operation optimization device 2 and the display terminal device 3 are configured to be able to communicate via a network N such as an Internet network. The display terminal device 3 in the energy operation optimization system is disposed in a steelmaking plant, for example.

[0041] (Heating furnace combustion gas usage prediction device)

[0042] The heating furnace combustion gas usage prediction device 1 is implemented, for example, using a general-purpose computer such as a workstation or a personal computer, or a server configured on the cloud. Figure 2 As shown, the heating furnace combustion gas usage prediction device 1 includes an input unit 10 , a storage unit 20 , a display unit 30 , and a calculation unit 40 .

[0043] The input unit 10 is input means for the calculation unit 40 and is realized by an input device such as a keyboard, a mouse, or a numeric keypad.

[0044] The storage unit 20 is composed of recording media such as EPROM (Erasable Programmable ROM), hard disk drive (Hard Disk Drive: HDD) and removable media. Examples of removable media include disk recording media such as USB (Universal Serial Bus) memory, CD (Compact Disc), DVD (Digital Versatile Disc), and BD (Blu-ray (registered trademark) Disc). The storage unit 20 can store an operating system (Operating System: OS), various programs, various tables, and various databases. In addition, the storage unit 20 stores an operation DB (database) 21.

[0045] In the operation DB 21, for example, information related to slabs loaded into the heating furnace and extracted in a predetermined future period from the current time (hereinafter referred to as "slab information") is stored. Figure 2 As shown, for example, an operation planning device 4, an operation performance device 5 and a collection device 6 are provided outside the heating furnace combustion gas usage prediction device 1. Then, the operation plan data stored in the operation planning device 4 and the operation performance data stored in the operation performance device 5 are collected by the collection device 6 and stored in the operation DB 21 as slab information.

[0046] The display unit 30 is realized by, for example, a liquid crystal display (LCD), an organic EL display (OLED), a touch panel display, etc. The display unit 30 displays, for example, the calculation results of the calculation unit 40 and a tuning screen during calculation.

[0047] The calculation unit 40 is realized by, for example, a processor including a CPU (Central Processing Unit) or the like, and a memory (main storage unit) including a RAM (Random Access Memory) and a ROM (Read Only Memory).

[0048] The operation unit 40 loads the program into the working area of ​​the main storage unit and executes it, and controls each component through the execution of the program, thereby realizing the functions that meet the specified purpose. The operation unit 40 functions as the pre-processing unit 41, the model generation unit 42, and the gas usage prediction unit 43 through the execution of the above program. It should be noted that Figure 2 In the embodiment, an example is shown in which the functions of each unit are implemented by one computer (computing unit), but the specific method of implementing the functions of each unit is not particularly limited, and for example, the functions of each unit may be implemented by multiple computers.

[0049] Specifically, the pre-processing unit 41 functions as a slab information acquiring unit 411 , a temperature increase amount calculating unit 412 , and a temperature increase amount editing unit 413 .

[0050] The slab information acquisition unit 411 acquires slab information of a slab inserted into the heating furnace in the target time period (hereinafter referred to as a "target slab") from the operation DB 21. It should be noted that the details of the processing (slab information acquisition step) performed by the slab information acquisition unit 411 will be described later.

[0051] The temperature increase amount calculation unit 412 calculates the energy-converted temperature increase amount converted into the energy required for heating in the heating furnace for each target slab, based on the slab information acquired by the slab information acquisition unit 411 .

[0052] The temperature rise calculation unit 412 refers to the slab information and corrects the loading temperature obtained by taking into account the properties of the slab and the use of a heat retention device (such as a heat retention pit) during transportation until the slab is loaded into the heating furnace, and the extraction temperature based on the heating target temperature of the slab. The temperature rise calculation unit 412 corrects the loading temperature and extraction temperature based on the respective loading temperatures and extraction temperatures of a specified number of slabs before and after the target slab. Then, the temperature rise calculation unit 412 calculates the energy conversion temperature rise of each slab based on the corrected loading temperature and extraction temperature. It should be noted that the details of the processing (temperature rise calculation step) performed by the temperature rise calculation unit 412 will be recorded later.

[0053] The temperature rise amount editing unit 413 expands the energy-converted temperature rise amount of each slab calculated by the temperature rise amount calculating unit 412 as the energy-converted temperature rise amount of each predetermined calculation interval based on the time when each slab is loaded into the heating furnace and the time when each slab is taken out of the heating furnace. Then, the temperature rise amount editing unit 413 edits it as the energy-converted temperature rise amount of the entire heating furnace for each calculation interval.

[0054] When the temperature rise amount editor 413 expands the calculated energy conversion temperature rise amount of each slab as the energy conversion temperature rise amount of each calculation interval, it considers the predetermined time allocation plan and the deviation of the loading time and the extraction time from the calculation interval. It should be noted that the details of the processing (temperature rise amount editing step) implemented by the temperature rise amount editor 413 will be recorded later.

[0055] The model generation unit 42 generates a learned model using machine learning. The model generation unit 42 generates a learned model by taking the energy conversion temperature increase of the entire heating furnace for each calculation interval edited by the temperature increase editing unit 413 as input, taking into account the energy required to maintain the temperature in the furnace and outputting the gas usage. For example, linear regression, linear regression with regularization (Lasso regression, etc.), nonlinear regression (neural network, support vector machine, etc.), regression tree (decision tree, random forest, etc.) and other methods can be used in machine learning.

[0056] The gas usage prediction unit 43 predicts the gas usage in the heating furnace based on the energy-converted temperature increase of the heating furnace as a whole for each calculation interval edited by the temperature increase editing unit 413 and the past actual gas usage. In addition, the gas usage prediction unit 43 can predict the gas usage after the actual performance compensation using the learning model pre-generated by the model generation unit 42. It should be noted that the details of the processing (gas usage prediction step) performed by the gas usage prediction unit 43 will be described later.

[0057] (Energy utilization optimization device)

[0058] The energy operation optimization device 2 is implemented, for example, using a general-purpose computer such as a workstation or a personal computer or a server configured on the cloud. The energy operation optimization device 2 obtains the gas usage of the heating furnace predicted by the heating furnace combustion gas usage prediction device 1, and optimizes the energy operation conditions of the iron and steel plant. It should be noted that the optimization of the energy operation conditions of the iron and steel plant can use, for example, the method described in Japanese Patent Application No. 2020-062922.

[0059] Here, in Figure 1 and Figure 2 In the description, the heating furnace combustion gas usage prediction device 1 and the energy operation optimization device 2 are described as independent devices, but for example, the function of the heating furnace combustion gas usage prediction device may be incorporated into the energy operation optimization device.

[0060] Figure 3 The functional blocks of the energy operation optimization device 2A incorporating the functions of the heating furnace combustion gas usage prediction device are shown. The energy operation optimization device 2A includes an input unit 10, a storage unit 20, a display unit 30, and a computing unit 40A. The computing unit 40A functions as an energy operation optimization unit 44 in addition to a pre-processing unit 41, a model generation unit 42, and a gas usage prediction unit 43. It should be noted that since the structure of the energy operation optimization device 2A other than the energy operation optimization unit 44 is the same as that of the heating furnace combustion gas usage prediction device 1, the description thereof is omitted.

[0061] The energy operation optimization unit 44 optimizes the energy operation conditions of the ironworks based on the gas usage predicted by the gas usage prediction unit 43. The energy operation conditions of the ironworks can be optimized using the method described in Japanese Patent Application No. 2020-062922, for example.

[0062] (Display terminal device)

[0063] The display terminal device 3 is used to obtain and display various information from the heating furnace combustion gas usage prediction device 1 for predicting the future gas usage of the heating furnace and the energy operation optimization device 2, 2A for optimizing the energy operation conditions of the ironworks based on the future gas usage. The display terminal device 3 is implemented, for example, by a liquid crystal display (LCD), an organic EL display (OLED), a touch panel display, etc.

[0064] The display terminal device 3, for example, has the functions of an information acquisition unit and a display unit. The information acquisition unit acquires information from the heating furnace combustion gas usage prediction device 1, and the information includes at least the gas usage predicted based on the energy conversion temperature rise of the entire heating furnace and the past actual gas usage. The "energy conversion temperature rise of the entire heating furnace" is calculated for each predetermined calculation interval and edited as the energy conversion temperature rise of the entire heating furnace for each of the calculation intervals. In addition, the information acquisition unit can also acquire information related to the energy conversion temperature rise of each slab required for heating before the energy conversion temperature rise of the entire heating furnace is edited from the heating furnace combustion gas usage prediction device 1.

[0065] The display terminal device 3 acquires information including at least the mixed amount of by-product gas based on the predicted gas usage amount from the energy utilization optimization device 2, 2A, and displays the information acquired by the information acquisition unit on the display unit.

[0066] (Heating furnace combustion gas usage prediction method)

[0067] Reference Figure 4 to Figure 7 The method for predicting the amount of combustion gas used in a heating furnace according to an embodiment is described. Here, in order to avoid a sudden change in the set temperature in the heating furnace, the heating furnace is basically divided into a furnace dedicated to hot plates and a furnace dedicated to cold plates, and only hot plates / cold plates are loaded in each. In addition, hot plates and cold plates are sometimes loaded into the same heating furnace. In this case, in order to avoid a sudden change in the set temperature in the heating furnace, a dummy slab is loaded between the hot plates and the cold plates. In addition, when multiple heating furnaces are used for operation, the prediction of the amount of combustion gas used in the heating furnace is calculated for each heating furnace, and it can also be applied to any heating furnace among the heating furnaces dedicated to hot plates, the heating furnaces dedicated to cold plates, or the heating furnaces with both hot plates and cold plates.

[0068] like Figure 4 As shown, the heating furnace combustion gas usage prediction method includes a slab information acquisition step (step S1), a temperature rise calculation step (step S2), a temperature rise editing step (step S3) and a gas usage prediction step (step S4). It should be noted that in the heating furnace combustion gas usage prediction method, the model generation step can be pre-implemented before the gas usage prediction step is implemented as needed.

[0069] <Slab Information Acquisition Step>

[0070] In the slab information acquisition step, the slab information acquisition unit 411 acquires slab information from the operation DB 21 (step S1). As the slab information, the following information can be cited, for example.

[0071] (1) Expected extraction temperature (extraction target temperature)

[0072] (2) Slab weight

[0073] (3) Slab size (thickness, width, length)

[0074] (4) Loading and extraction time

[0075] (5) Actual gas usage: Actual gas (mixed gas) usage in the heating furnace from a specified time before (e.g., one hour ago)

[0076] (6) Whether the slab is hot or cold

[0077] (7) When the slab is a hot sheet, the slab temperature during continuous casting, whether it passes through a holding pit (holding device), the slab transfer time corresponding to whether it passes through a holding pit (production preparation stage), and the slab transfer route

[0078] (8) Parameters required for heating energy calculation (e.g. steel type, specific heat, heat transfer parameters (e.g. thermal conductivity, heat transfer coefficient, etc.))

[0079] <Temperature Rise Calculation Procedure>

[0080] In the temperature rise amount calculation step, the temperature rise amount calculation unit 412 calculates the energy conversion temperature rise amount based on the slab information, etc. (step S2). Figure 5 Calculate the energy-converted temperature rise by following the steps shown.

[0081] First, the temperature increase amount calculation unit 412 refers to the slab information to select a target slab (step S21). Next, the temperature increase amount calculation unit 412 determines whether the heating furnace loading time of the target slab is in the past (step S22).

[0082] When it is determined in step S22 that the heating furnace loading time of the target slab is in the past (YES in step S22 ), the temperature increase amount calculation unit 412 refers to the actual value of the loading temperature of the target slab in the slab information (step S23 ).

[0083] Next, the temperature increase amount calculation unit 412 performs correction of the charging temperature and the extraction temperature (step S24). The temperature increase amount calculation unit 412 obtains the charging temperature and extraction temperature of all target slabs extracted from the heating furnace, including the slabs charged into the heating furnace and extracted in the future period predetermined from the current time, and the slabs currently charged into the heating furnace, by implementing the above steps S23 and S24. Regarding the charging temperature, when the charging time of the heating furnace is in the past, the actual value is used (refer to step S23), and when the charging time of the heating furnace is in the present or in the future, the calculated value in the charging temperature simulation is used (refer to step S26). In addition, regarding the extraction temperature, the planned value is obtained from the slab information and used. It should be noted that, regarding the charging temperature, it is set to "set to the actual value when the charging time of the heating furnace is in the past", but in the case where the actual value cannot be obtained, for example, the calculated value calculated in advance by the charging temperature simulation can be used.

[0084] In step S24, the temperature rise amount calculation unit 412 refers to the slab information, and corrects the charging temperature of the target slab to the minimum value of the charging temperatures of the slabs before and after the target slab, for example, as shown in the following (1). In addition, the temperature rise amount calculation unit 412 refers to the slab information, and corrects the extraction temperature of the target slab to the maximum value of the extraction temperatures (predetermined extraction temperatures) of the slabs before and after the target slab, for example, as shown in the following (2).

[0085] (1) Charging temperature correction value = Min (charging temperature of a predetermined number of slabs before and after the target slab)

[0086] (2) Extraction temperature correction value = Max (extraction temperature of a predetermined number of slabs before and after the target slab)

[0087] In the heating furnace, the slabs are arranged and sequentially loaded, but the loading temperature and the expected extraction temperature of each slab may be different. In addition, in the heating furnace, the slabs arranged in the preheating zone, the heating zone, and the soaking zone are heated simultaneously. Therefore, the loading temperature is corrected to the minimum value of the loading temperature of the slabs around the target slab (see (1) above), and the extraction temperature is corrected to the maximum value of the extraction temperature of the slabs around the target slab (see (2) above).

[0088] Next, the temperature rise calculation unit 412 uses the corrected loading temperature and extraction temperature to calculate the energy-converted temperature rise (step S25). In step S25, the furnace time is calculated based on the corrected loading time and extraction time of the target slab. Then, as shown in the following formula (1), the temperature rise in each predetermined calculation interval (ΔT) in the furnace time is multiplied by the slab weight and converted into a temperature rise equivalent to the heating energy, thereby calculating the energy-converted temperature rise A (ΔT) of each target slab. b and c in the following formula (1) are coefficients.

[0089] [Mathematical formula 1]

[0090] Energy conversion temperature rise A(ΔT)

[0091] = {b×(extraction temperature correction value-loading temperature correction value)

[0092] × slab weight + c × slab thickness} / furnace time × calculation interval (ΔT)…(1)

[0093] It should be noted that, here, the distribution of each energy conversion temperature rise amount to each calculation interval (ΔT) is equal, but when the loading time and extraction time to the heating furnace deviate from the calculation interval (ΔT), the time existing in the furnace (set as ΔT1) is used, and (ΔT1 / ΔT) is used for adjustment. In addition, when the slab thickness is different, even with the same slab weight, the heating energy will be different. Therefore, as shown in the above formula (1), it is preferable to introduce a correction term based on the slab thickness. In addition, considering the situation that the specific heat changes in accordance with the temperature rise, it can also be set as a weighted distribution.

[0094] Here, if it is determined in step S22 that the heating furnace loading time of the target slab is not in the past (i.e., in the present or in the future) (No in step S22), the temperature rise amount calculation unit 412 performs a loading temperature simulation on the target slab (step S26). Then, the process proceeds to step S24. In the loading temperature simulation, specifically, the Figure 6 The steps shown are used to implement the loading temperature simulation.

[0095] First, the temperature rise amount calculation unit 412 determines whether the target slab is a hot sheet (hot sheet or cold sheet) (step S261). If it is determined in step S261 that the target slab is a hot sheet (yes in step S261), the temperature rise amount calculation unit 412 determines whether to use the insulation pit, that is, whether to load the target slab into the insulation pit (step S262).

[0096] When it is determined in step S262 that the holding pit is used (Yes in step S262), the temperature rise amount calculation unit 412 calculates the charging temperature to the holding pit in consideration of the slab temperature when it is extracted from the continuous casting and the transportation time of the slab from the continuous casting to the charging into the holding pit (step S263). In step S263, for example, the theory of heat conduction and heat transfer can be used as a concentrated heat capacity model to calculate the charging temperature to the holding pit in the following manner.

[0097] (1) Temperature of the inlet to the heat preservation pit = (initial temperature - stable temperature) × EXP (-Fourier number × Biot number) + stable temperature

[0098] in,

[0099] (2) Fourier number = thermal diffusivity × transport time / (slab thickness) 2

[0100] (3) Biot number = heat transfer coefficient × slab thickness / thermal conductivity

[0101] (4) Thermal diffusivity = thermal conductivity / density / specific heat

[0102] (5) Transport time = The time from continuous casting to loading into the holding pit

[0103] (6) Initial temperature = slab temperature during continuous casting

[0104] The initial temperature may be, for example, a value obtained by inversely calculating the above formula (1) based on past performance, or may be an average value or a mode value with reference to a frequency distribution, as shown below.

[0105] Initial temperature = (charging temperature into the holding pit - stabilization temperature) / EXP (-Fourier number x Biot number) + stabilization temperature

[0106] In addition, when the coefficients of (2) to (4) are unknown, a learning model using past performance may be used instead of (1). In this case, for example, a learning model g shown below is generated in advance to calculate the loading temperature.

[0107] Loading temperature into the holding pit = g(transportation time, slab thickness, initial temperature)

[0108] Next, the temperature rise amount calculation unit 412 calculates the extraction temperature from the insulation pit by taking into account the temperature of the slab loaded into the insulation pit and the residence time of the slab in the insulation pit (step S264). In step S264, the extraction temperature from the insulation pit can be calculated using the same method as the loading temperature into the insulation pit (refer to the above (1)). In step S264, the "transportation time = insulation time in the insulation pit" in the above (5) is set, and the "initial temperature = the temperature of the slab loaded into the insulation pit" in the above (6) is set.

[0109] Next, the temperature rise amount calculation unit 412 calculates the loading temperature into the heating furnace by taking into account the extraction temperature from the holding pit and the transport time from the holding pit to the heating furnace (step S265). In step S265, the loading temperature into the heating furnace can be calculated using the same method as the loading temperature into the holding pit (see (1) above). In step S265, the "transport time = the transport time from the holding pit to the heating furnace" in (5) above, and the "initial temperature = the temperature of the slab extracted from the holding pit" in (6) above.

[0110] When it is determined in step S262 that the holding pit is not used (No in step S262), the temperature rise calculation unit 412 calculates the charging temperature to the heating furnace by taking into account the slab temperature when it is extracted from the continuous casting and the slab transportation time from the continuous casting to the heating furnace (step S266). In step S266, the charging temperature to the heating furnace can be calculated using the same method as the charging temperature to the holding pit (refer to (1) above). In step S266, the "stable temperature = ambient temperature in the space where the slab exists" in (1) above, the "transportation time = transportation time from continuous casting to loading into the heating furnace" in (5) above, and the "initial temperature = slab temperature during continuous casting" in (6) above.

[0111] When it is determined in step S261 that the target slab is not a hot slab (but a cold slab) (No in step S261), the temperature rise calculation unit 412 sets the charging temperature to the heating furnace to a predetermined value (step S267). Thus, in the charging temperature simulation, the appropriate charging temperature is calculated according to whether the slab passes through the holding pit from the continuous casting.

[0112] <Energy conversion temperature rise editing steps>

[0113] return Figure 4 In the energy conversion temperature rise amount editing step, the temperature rise amount editing unit 413 expands the energy conversion temperature rise amount of each target slab calculated in step S2 into the energy conversion temperature rise amount of each calculation interval (ΔT). Then, it is edited as the energy conversion temperature rise amount of the entire heating furnace for each calculation interval (ΔT) (step S3).

[0114] Here, in step S2, the energy conversion temperature rise amount of each calculation interval (ΔT) between the loading time and the extraction time is calculated for each target slab. Then, as shown in the following formula (2), the temperature rise amount editing unit 413 arranges them by time and adds the energy conversion temperature rise amounts of each target slab existing in each calculation interval (ΔT). Thus, from the current time to a predetermined future period, the required energy conversion temperature rise amount in the entire heating furnace (hereinafter referred to as "energy conversion temperature rise amount of all slabs in the furnace") is edited and calculated.

[0115] [Mathematical formula 2]

[0116] Energy conversion temperature rise of all slabs in the furnace (k×ΔT)

[0117] =∑Energy conversion temperature rise A(k×ΔT)…(2)

[0118] Here, k in the above formula (2) is an integer such as k=1, 2, ... In the above formula (2), the start time to be predicted is set to k=1, and the future period to be predicted is determined in advance, and is sequentially added to determine the end time and calculate.

[0119] Figure 7 The relationship between the plan for charging slabs to the heating furnace and the total value of the energy conversion temperature rise of each slab per calculation interval (ΔT) calculated by the above formula (2) is shown. The bar shown in the "plan for charging slabs to the heating furnace" in the figure represents the slab, and the number in the bar represents the number of the slab. In addition, in the figure, the future hour is set as the future period, and the calculation interval (ΔT) is set to 5 minutes.

[0120] <Gas Usage Forecasting Steps>

[0121] In the gas usage prediction step, the gas usage prediction unit 43 uses the energy conversion temperature rise of all slabs in the furnace at each calculation interval (ΔT) and the actual gas usage before the specified time in the past to predict the future gas usage according to the calculation interval (ΔT) (step S4). Here, the gas usage predicted in the gas usage prediction step can be any one of C gas, LD gas, and B gas generated in the ironworks, or M gas mixed therefrom. In addition, it can also be city gas or other gas purchased from outside.

[0122] In the gas usage prediction step, the gas usage can be predicted using the learned model generated in advance in the model generation step. The learned model can be generated using machine learning methods such as linear regression, regularized linear regression (Lasso regression, etc.), nonlinear regression (neural network, support vector machine, etc.), regression tree (decision tree, random forest, etc.). For example, when linear regression is used, the model can be formed as shown in the following formula (3). a and d in the following formula (3) are coefficients.

[0123] [Mathematical formula 3]

[0124] Gas usage prediction value (k×ΔT)

[0125] = Total slab energy conversion temperature rise in the furnace (k×ΔT)

[0126] +a×actual gas usage ΔT before the specified time+d…(3)

[0127] In the above formula (3), the first item on the right is the predicted value of the gas usage required for heating the slab, and the second item on the right is an item for reflecting the actual gas usage. Here, the "gas usage ΔT performance before the specified time" of the second item on the right can be assigned the actual value of the gas usage within the ΔT time before the specified time (for example, one hour before) of each loading time of the target slab. In addition, the "gas usage ΔT performance before the specified time" can be assigned the average value of the specified time in the past from the current time with the amount at the ΔT time, or the "gas usage ΔT performance before the specified time" can be assigned a value that reflects other performance and the current operating performance.

[0128] In the above formula (3), the third term on the right is a constant term, which is a term used to consider the amount of energy required for heating the slab, such as heat dissipation from the furnace body and furnace temperature maintenance. It should be noted that in other machine learning models other than linear regression, it is not considered that when a constant term is not explicitly assigned, a unit input value (such as "1" or the like) can be assigned and learned.

[0129] Through the above steps, the predicted value of the gas usage after performance compensation for each calculation interval (ΔT) from the current moment to a predetermined future period can be calculated. The predicted value of the gas usage calculated in the gas usage prediction step is used as the gas usage plan value of the heating furnace, and the data is saved in, for example, the operation DB 21. In addition, the gas usage prediction step is implemented for each predetermined calculation interval (ΔT), and the data is updated each time.

[0130] The saved planned gas usage value of the heating furnace can be used, for example, in energy utilization optimization calculations. The planned gas usage value can be reflected, for example, in the planned gas consumption value in the iron and steel plant in the energy utilization condition optimization device described in Japanese Patent Application No. 2020-062922. For example, in the case of using a mixed gas (M gas) as the combustion gas of the heating furnace, the computer performing the optimization calculation can obtain the planned gas usage value as the M gas consumption of the heating furnace, and use it as part of the whole, and use it in the optimization calculation of energy utilization in the iron and steel plant.

[0131] It should be noted that, when there are multiple heating furnaces, for example, the M gas usage amount can be calculated using "predicted value of M gas usage amount = f (energy conversion temperature increase amount planned value of heating furnace No. 1, ..., energy conversion temperature increase amount planned value of heating furnace No. N, M gas actual value).

[0132] According to the heating furnace combustion gas usage prediction device and heating furnace combustion gas usage prediction method of the embodiment described above, it is possible to predict the future gas usage after performance compensation with high accuracy. In addition, according to the heating furnace combustion gas usage prediction device and heating furnace combustion gas usage prediction method of the embodiment, for example, the future usage of M gas is predicted, and the time series (increase / decrease) is guided. As a result, the operator in the iron and steel plant can grasp the future demand for M gas and adjust the mixture of M gas (by-product gas / city gas). As a result, by-product gas can be used efficiently in the iron and steel plant, and the purchase of fuels such as city gas can be reduced.

[0133] In addition, according to the energy utilization optimization system, energy utilization optimization device, and energy utilization optimization method of the embodiment, it is possible to optimize the energy utilization conditions of the iron and steel plant based on the gas usage predicted with high accuracy. In addition, according to the energy utilization optimization system, energy utilization optimization device, and energy utilization optimization method of the embodiment, the future gas usage is used in the optimization of energy utilization in the iron and steel plant. Thus, for example, since the mixed amount of by-product gas can be numerically calculated and guided, it also leads to labor-saving judgment for the operator. It should be noted that as display items for guidance, for example, the predicted value of the usage of M gas, the mixed amount of by-product gas (B gas amount, C gas amount, LD gas amount), the city gas amount, etc. can be listed.

[0134] Furthermore, according to the display terminal device of the embodiment, it is possible to provide information such as the future gas usage amount and the mixed amount of by-product gas based on the future gas usage amount.

[0135] (Example)

[0136] Reference Figure 7 The following is an example of a method for predicting the amount of combustion gas used in a heating furnace according to the present invention. In this example, a learning model is created based on 7,000 pieces of operation data in 5-minute units using a random forest, which is a type of regression tree, and accuracy verification is performed. The target variable of the learning model is the amount of mixed gas used in a hot rolling heating furnace, and the explanatory variables are the actual average value and rolling information.

[0137] In the accuracy verification of the learned model, the past 3000 pieces of operation data in 5-minute units different from the operation data used in the learning were used. In addition, regarding the rolling information, the rolling performance was used assuming an ideal situation in which the plan was 100% completed.

[0138] The figure shows the comparison results of the errors obtained by the accuracy verification of the learned model. The root mean square error (RMSE) when only the actual average value is used without using the rolling information is set to "100" and the error is calculated as the accuracy index. Figure 8 As shown, it can be seen that the error is reduced when the rolling information is used in addition to the actual average value in learning, compared with the case where only the actual average value is used in learning. In addition, it can be seen that the prediction of the usage of the mixed gas 15 minutes in advance is improved by about 37%, the prediction 30 minutes in advance is improved by about 48%, and the prediction 45 minutes in advance is improved by about 56%. Therefore, according to the method for predicting the usage of heating furnace combustion gas of the present invention, the future usage of the mixed gas can be predicted with high accuracy.

[0139] The above specifically describes the heating furnace combustion gas usage prediction device, energy utilization optimization system, energy utilization optimization device, display terminal device, heating furnace combustion gas usage prediction method and energy utilization optimization method of the present invention using the methods and embodiments for implementing the invention, but the purpose of the present invention is not limited to these records and must be interpreted broadly based on the records of the claims. In addition, solutions formed by various changes and modifications based on these records are of course also included in the purpose of the present invention.

[0140] It should be noted that the present technology can also be configured as follows.

[0141] (1) A heating furnace combustion gas usage prediction device, which is used in an energy utilization optimization system of an ironworks, comprising:

[0142] a slab information acquisition unit that acquires information related to a slab that is loaded into the heating furnace and extracted in a future period predetermined from the current time;

[0143] a temperature increase amount calculation unit for calculating, based on the acquired information of each slab, an energy-converted temperature increase amount converted into energy required for heating in the heating furnace for each slab;

[0144] A temperature rise amount editing unit, which expands the calculated energy-converted temperature rise amount of each slab as the energy-converted temperature rise amount of each predetermined calculation interval based on the time when each slab is loaded into the heating furnace and the time when each slab is extracted from the heating furnace, and edits it as the energy-converted temperature rise amount of the heating furnace as a whole for each of the calculation intervals; and

[0145] The gas usage amount prediction unit predicts the gas usage amount in the heating furnace based on the energy-converted temperature increase of the entire heating furnace at each calculation interval and the past actual gas usage amount.

[0146] (2) The heating furnace combustion gas usage prediction device according to (1), wherein:

[0147] The temperature rise calculation unit refers to the slab information, and based on the loading temperature and extraction temperature of a specified number of slabs before and after the slab, corrects the loading temperature that takes into account the properties of the slab and the use of the insulation device during transportation until the slab is loaded into the heating furnace, and the extraction temperature based on the heating target temperature of the slab, and calculates the energy conversion temperature rise of each slab based on the corrected loading temperature and extraction temperature.

[0148] (3) The heating furnace combustion gas usage prediction device according to (2), wherein:

[0149] Regarding the charging temperature in the temperature increase amount calculation unit, the slab information is referred to so that:

[0150] If the heating furnace loading time is in the past, the loading temperature is set to the actual value.

[0151] In the case where the heating furnace loading time is in the future, referring to the properties of the slab,

[0152] When the slab is a hot plate, the loading temperature is calculated taking into account the heat preservation time and the conveying time according to whether the heat preservation device is used or not.

[0153] When the slab is a cold slab, the charging temperature is set to a predetermined value.

[0154] (4) The heating furnace combustion gas usage prediction device according to (2), wherein:

[0155] Regarding the charging temperature in the temperature rise amount calculation means, referring to the slab information,

[0156] In the case where the heating furnace loading time is in the future, referring to the properties of the slab,

[0157] In the case where the slab is a hot plate, if the insulation device is not used, the loading temperature is calculated taking into account the transportation time from continuous casting to the heating furnace. In the case where the insulation device is used, the loading temperature is calculated taking into account the transportation time from continuous casting to loading into the insulation device, the insulation time in the insulation device, and the transportation time from being extracted from the insulation device to being loaded into the heating furnace.

[0158] (5) The heating furnace combustion gas usage prediction device according to any one of (1) to (4), wherein:

[0159] When expanding the calculated energy-converted temperature rise of each slab as the energy-converted temperature rise of each calculation interval, the temperature rise editing unit considers a predetermined time allocation plan and considers the deviation of the loading time and the extraction time from the calculation interval.

[0160] (6) The heating furnace combustion gas usage prediction device according to any one of (1) to (5), wherein:

[0161] The gas usage prediction unit uses a learned model to predict the gas usage after performance compensation. The learned model is learned by taking the energy-converted temperature rise of the heating furnace as a whole for each calculation interval edited by the temperature rise editing unit as input, considering the energy required to maintain the temperature in the furnace and outputting the gas usage.

[0162] (7) An energy utilization optimization system, comprising a heating furnace combustion gas usage prediction device as described in any one of (1) to (6) and an energy utilization optimization device for an iron and steel plant, wherein:

[0163] The energy operation optimization device obtains the gas usage of the heating furnace predicted by the heating furnace combustion gas usage prediction device, and optimizes the energy operation conditions of the iron and steel plant.

[0164] (8) An energy utilization optimization device for an ironworks, comprising:

[0165] a slab information acquisition unit that acquires information related to slabs that are loaded into the heating furnace and extracted in a future period that is predetermined from the current time;

[0166] a temperature increase amount calculation unit that calculates, for each slab, an energy-converted temperature increase amount converted from energy required for heating in the heating furnace based on the acquired information of each slab;

[0167] A temperature rise editing unit, based on the time when each slab is loaded into the heating furnace and the time when each slab is taken out from the heating furnace, expands the calculated energy-converted temperature rise of each slab as the energy-converted temperature rise of each predetermined calculation interval, and edits it as the energy-converted temperature rise of the heating furnace as a whole for each of the calculation intervals;

[0168] a gas usage prediction unit that predicts the gas usage in the heating furnace based on the energy-converted temperature increase of the entire heating furnace at each calculation interval and the past actual gas usage; and

[0169] The energy utilization optimization unit optimizes the energy utilization conditions of the steelworks based on the predicted gas usage.

[0170] (9) a display terminal device that obtains and displays various information from a heating furnace combustion gas usage prediction device that predicts the future gas usage of the heating furnace and an energy operation optimization device that optimizes the energy operation conditions of the ironworks based on the future gas usage, wherein the display terminal device comprises:

[0171] an information acquisition unit that acquires information including at least an energy-converted temperature increase amount of the heating furnace as a whole, a gas usage amount predicted based on past actual gas usage amounts, and a mixed amount of by-product gas based on the predicted gas usage amount, wherein the energy-converted temperature increase amount of the heating furnace as a whole is calculated for each predetermined calculation interval and compiled as the energy-converted temperature increase amount of the heating furnace as a whole for each of the calculation intervals; and

[0172] The display unit displays the information acquired by the information acquisition unit.

[0173] (10) A method for predicting the amount of combustion gas used in a heating furnace, which is executed by a device for predicting the amount of combustion gas used in a heating furnace constructed by a computer and used in an energy utilization optimization system of an ironworks, comprising:

[0174] a slab information acquisition step, wherein the slab information acquisition unit provided in the computer acquires information related to slabs that are loaded into the heating furnace and extracted in a future period predetermined from the current time;

[0175] A temperature increase amount calculation step, wherein the temperature increase amount calculation unit provided in the computer calculates an energy-converted temperature increase amount converted from energy required for heating the slab in the heating furnace based on the acquired information of each slab;

[0176] A temperature rise amount editing step, wherein the temperature rise amount editing unit of the computer expands the calculated energy-converted temperature rise amount of each slab as the energy-converted temperature rise amount of each predetermined calculation interval based on the time when each slab is loaded into the heating furnace and the time when each slab is extracted from the heating furnace, and edits it as the energy-converted temperature rise amount of the heating furnace as a whole for each of the calculation intervals; and

[0177] In the gas usage prediction step, the gas usage prediction unit included in the computer predicts the gas usage in the heating furnace based on the energy-converted temperature increase of the entire heating furnace at each calculation interval and the past actual gas usage.

[0178] (11) An energy utilization optimization method, which is executed by an energy utilization optimization device for an ironworks constructed using a computer, comprising:

[0179] a slab information acquisition step, wherein the slab information acquisition unit provided in the computer acquires information related to slabs that are loaded into the heating furnace and extracted in a future period predetermined from the current time;

[0180] A temperature increase amount calculation step, wherein the temperature increase amount calculation unit provided in the computer calculates, for each slab, an energy-converted temperature increase amount converted from energy required for heating in the heating furnace based on the acquired information of each slab;

[0181] A temperature rise amount editing step, wherein the temperature rise amount editing unit of the computer expands the calculated energy-converted temperature rise amount of each slab as the energy-converted temperature rise amount of each predetermined calculation interval based on the time when each slab is loaded into the heating furnace and the time when each slab is extracted from the heating furnace, and edits it as the energy-converted temperature rise amount of the heating furnace as a whole for each of the calculation intervals;

[0182] a gas usage prediction step, wherein the gas usage prediction unit provided in the computer predicts the gas usage in the heating furnace based on the energy-converted temperature increase of the entire heating furnace at each calculation interval and the past actual gas usage; and

[0183] In the energy operation optimization step, the energy operation optimization unit included in the computer optimizes the energy operation conditions of the ironworks based on the predicted gas usage.

[0184] Description of Reference Numerals

[0185] 1 Heating furnace combustion gas usage prediction device

[0186] 2. 2A Energy Utilization Optimization Device

[0187] 3 Display terminal device

[0188] 4 Operation planning device

[0189] 5 Operational performance device

[0190] 6 Collection device

[0191] 10 Input section

[0192] 20 Storage

[0193] 21 Operation DB

[0194] 30 Display unit

[0195] 40 Operation unit

[0196] 41 Pre-processing unit

[0197] 411 Slab Information Acquisition Department

[0198] 412 Temperature rise calculation unit

[0199] 413 Temperature Rise Editorial Department

[0200] 42 Model Generation Department

[0201] 43 Gas Usage Forecasting Department

[0202] 44 Energy Optimization Department

[0203] N Network

Claims

1. A heating furnace combustion gas usage prediction device, which is used in an energy utilization optimization system of an iron and steel plant, the heating furnace combustion gas usage prediction device comprising: a slab information acquisition unit that acquires information related to a slab that is loaded into the heating furnace and extracted in a future period predetermined from the current time; a temperature increase amount calculation unit for calculating, based on the acquired information of each slab, an energy-converted temperature increase amount obtained by converting energy required for heating in the heating furnace for each slab; A temperature rise amount editing unit, which expands the calculated energy-converted temperature rise amount of each slab as the energy-converted temperature rise amount of each predetermined calculation interval based on the loading time of each slab into the heating furnace and the extraction time of each slab from the heating furnace, and edits it as the energy-converted temperature rise amount of the heating furnace as a whole for each of the calculation intervals; and The gas usage amount prediction unit predicts the gas usage amount in the heating furnace based on the energy-converted temperature increase of the entire heating furnace at each calculation interval and the past actual gas usage amount.

2. The heating furnace combustion gas usage prediction device according to claim 1, wherein: The temperature rise calculation unit refers to the slab information, and based on the loading temperature and extraction temperature of a specified number of slabs before and after the slab, corrects the loading temperature that takes into account the properties of the slab and the use of the insulation device during transportation until the slab is loaded into the heating furnace, and the extraction temperature based on the heating target temperature of the slab, and calculates the energy conversion temperature rise of each slab based on the corrected loading temperature and extraction temperature.

3. The heating furnace combustion gas usage prediction device according to claim 2, wherein: Regarding the charging temperature in the temperature increase amount calculation unit, the slab information is referred to so that: If the heating furnace loading time is in the past, the loading temperature is set to the actual value. In the case where the heating furnace loading time is in the future, referring to the properties of the slab, When the slab is a hot plate, the loading temperature is calculated taking into account the heat preservation time and the conveying time according to whether the heat preservation device is used or not. When the slab is a cold slab, the charging temperature is set to a predetermined value.

4. The heating furnace combustion gas usage prediction device according to claim 1, wherein: When expanding the calculated energy-converted temperature rise of each slab as the energy-converted temperature rise of each calculation interval, the temperature rise editing unit considers a predetermined time allocation plan and considers the deviation of the loading time and the extraction time from the calculation interval.

5. The heating furnace combustion gas usage prediction device according to claim 1, wherein: The gas usage prediction unit uses a learned model to predict the gas usage after performance compensation. The learned model is learned by taking the energy-converted temperature rise of the heating furnace as a whole for each calculation interval edited by the temperature rise editing unit as input, considering the energy required to maintain the temperature in the furnace and outputting the gas usage.

6. An energy operation optimization system comprising a heating furnace combustion gas usage prediction device according to any one of claims 1 to 5 and an energy operation optimization device for an ironworks, wherein: The energy operation optimization device obtains the gas usage of the heating furnace predicted by the heating furnace combustion gas usage prediction device, and optimizes the energy operation conditions of the iron and steel plant.

7. An energy utilization optimization device for an ironworks, comprising: a slab information acquisition unit that acquires information related to a slab that is loaded into the heating furnace and extracted in a future period predetermined from the current time; a temperature increase amount calculation unit for calculating, based on the acquired information of each slab, an energy-converted temperature increase amount obtained by converting energy required for heating in the heating furnace for each slab; A temperature rise amount editing unit, which expands the calculated energy-converted temperature rise amount of each slab as the energy-converted temperature rise amount of each predetermined calculation interval based on the loading time of each slab into the heating furnace and the extraction time of each slab from the heating furnace, and edits it as the energy-converted temperature rise amount of the heating furnace as a whole for each of the calculation intervals; a gas usage prediction unit for predicting the gas usage in the heating furnace based on the energy-converted temperature increase of the entire heating furnace at each calculation interval and the past actual gas usage; and The energy utilization optimization unit optimizes the energy utilization conditions of the steelworks based on the predicted gas usage.

8. A display terminal device that obtains and displays various information from a heating furnace combustion gas usage prediction device that predicts the future gas usage of the heating furnace and an energy operation optimization device that optimizes the energy operation conditions of the ironworks based on the future gas usage, wherein: The display terminal device comprises: an information acquisition unit that acquires information including at least an energy-converted temperature increase amount of the heating furnace as a whole, a gas usage amount predicted based on past actual gas usage amounts, and a mixed amount of by-product gas based on the predicted gas usage amount, wherein the energy-converted temperature increase amount of the heating furnace as a whole is calculated for each predetermined calculation interval and compiled as the energy-converted temperature increase amount of the heating furnace as a whole for each of the calculation intervals; and A display unit displays the information acquired by the information acquisition unit.

9. A method for predicting the amount of combustion gas used in a heating furnace, which is executed by a device for predicting the amount of combustion gas used in a heating furnace constructed by a computer and used in an energy utilization optimization system of an iron and steel plant, wherein: The heating furnace combustion gas usage prediction method comprises: a slab information acquisition step, wherein the slab information acquisition unit provided in the computer acquires information related to slabs that are loaded into the heating furnace and extracted in a future period predetermined from the current time; A temperature increase amount calculation step, wherein the temperature increase amount calculation unit provided in the computer calculates, for each slab, an energy-converted temperature increase amount converted from energy required for heating in the heating furnace based on the acquired information of each slab; A temperature rise amount editing step, wherein the temperature rise amount editing unit of the computer expands the calculated energy-converted temperature rise amount of each slab as the energy-converted temperature rise amount of each predetermined calculation interval based on the loading time of each slab into the heating furnace and the extraction time of each slab from the heating furnace, and edits it as the energy-converted temperature rise amount of the heating furnace as a whole for each of the calculation intervals; and In the gas usage prediction step, the gas usage prediction unit included in the computer predicts the gas usage in the heating furnace based on the energy-converted temperature increase of the entire heating furnace at each calculation interval and the past actual gas usage.

10. A method for optimizing energy use, which is performed by an energy use optimization device for an ironworks constructed using a computer, wherein: The energy utilization optimization method comprises: a slab information acquisition step, wherein the slab information acquisition unit provided in the computer acquires information related to slabs that are loaded into the heating furnace and extracted in a future period predetermined from the current time; A temperature increase amount calculation step, wherein the temperature increase amount calculation unit provided in the computer calculates, for each slab, an energy-converted temperature increase amount converted from energy required for heating in the heating furnace based on the acquired information of each slab; A temperature rise amount editing step, wherein the temperature rise amount editing unit of the computer expands the calculated energy-converted temperature rise amount of each slab as the energy-converted temperature rise amount of each predetermined calculation interval based on the time when each slab is loaded into the heating furnace and the time when each slab is extracted from the heating furnace, and edits it as the energy-converted temperature rise amount of the heating furnace as a whole for each of the calculation intervals; a gas usage prediction step, wherein the gas usage prediction unit provided in the computer predicts the gas usage in the heating furnace based on the energy-converted temperature increase of the entire heating furnace at each calculation interval and the past actual gas usage; and In the energy operation optimization step, the energy operation optimization unit included in the computer optimizes the energy operation conditions of the steelworks based on the predicted gas usage.

Images