Energy application assisting device, method, and steel mill operating method
By constructing the income and expenditure conditions and optimizing the calculations for energy-assisted materials, the problem of energy imbalance in steel plants was solved, providing necessary operational plan change schemes, optimizing energy use, and reducing production costs.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- JFE STEEL CORP
- Filing Date
- 2020-12-22
- Publication Date
- 2026-05-26
Smart Images
Figure CN116745785B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to an energy utilization auxiliary device, an energy utilization auxiliary method, and an operating method for steel plants that optimizes the cost of energy utility in the application of energy utility. Background Technology
[0002] Steel plants have many workshops from upstream processes (blast furnace, coke oven, steelmaking) to downstream processes (rolling, surface treatment). In the upstream processes, by-product gases containing heat-generating components are produced, namely B gas (blast furnace gas), C gas (coke oven gas), and LD gas (LD converter gas).
[0003] These gases are being used directly or as a mixture of gases with adjusted heat (M gas) as fuel for heating furnaces in rolling mills and power generation equipment.
[0004] Here, in adjusting for discrepancies between the amount of gas produced and the amount used, a gas storage device that functions as a gas storage tank is used. For example, in a situation where the amount of by-product gas produced is greater than the amount used, by accumulating the by-product gas in the gas storage device, the storage volume (gas storage device level) increases.
[0005] Conversely, in situations where the consumption of by-product gases exceeds their production, the consumption can be met by venting gases from the gas storage tank.
[0006] When the amount of by-product gas produced exceeds the amount used and reaches the upper limit of the gas storage tank, the remaining gas is burned and diffused into the atmosphere. Conversely, in the opposite situation, due to insufficient gas production, the output of the power generation equipment is reduced to suppress the amount used. If this is not enough, the plant's operating level declines.
[0007] Besides the use of by-product gases, there are applications such as electricity and steam generation. In electricity generation, the power generation equipment is used to increase output by reducing electricity purchases during periods of high electricity prices (generally daytime). During periods of low electricity prices (generally nighttime), power generation is reduced. The usage strategy for such power generation equipment depends on the electricity price. In steam generation, steam is generated in boilers that utilize the exhaust heat from converters, sintering furnaces, etc., and is used in the insulation of pickling tanks and RH (vacuum degassing) equipment in cold rolling mills, etc. Furthermore, in cases of insufficient steam, steam is extracted from the power generation equipment (operations that obtain steam from the turbine section, resulting in reduced power generation) and purchased from outside the steel mill.
[0008] Several technologies for using energy-assisted materials in such steel mills or factories in a way that minimizes costs have been disclosed (e.g., Patent Documents 1-3).
[0009] In the technology of Patent Document 1, in the apparatus for optimizing the use of factory equipment, the optimal solution obtained through optimization is re-evaluated based on a re-evaluation function incorporating an evaluation index that takes into account deviations in state variables, including the operating quantities of the factory equipment. This allows for understanding the impact of deviations in state variables on the optimal solution, resulting in a more stable evaluation function value for the optimal solution. In other words, it identifies solutions with minimal fluctuations in the evaluation function value.
[0010] Furthermore, Patent Document 2 proposes an optimal design method that minimizes operating costs and gas emissions. In Patent Document 2, the optimal capacity of the equipment under different load modes (start-up and stop-down plans for each piece of equipment) is determined.
[0011] Furthermore, Patent Document 3 proposes a method for creating an operation plan even when the required reserve capacity of the power generation equipment cannot be guaranteed. In Patent Document 3, when the adjustment amount of the guaranteed power generation is smaller than the required adjustment amount, the operation plan is generated in a way that minimizes the value of the expanded objective function obtained by adding a penalty function to the original objective function, which calculates a value corresponding to the deficiency amount relative to the required adjustment amount.
[0012] In the technology of Patent Document 1, a stable solution can be obtained even under conditions of operational deviation, using the cost function as the value. Furthermore, in the technology of Patent Document 2, when an operating plan for factory equipment is given, the optimal capacity of the equipment that minimizes cost is determined. While these technologies in Patent Documents 1 and 2 perform optimization calculations under given operating plans and conditions, they fail to meet the cost-benefit condition representing energy balance, which is one of their operating conditions, regardless of the operating volume. Therefore, their optimal calculations result in a state where there is no optimal solution.
[0013] Furthermore, in the technology of Patent Document 3, when the adjustment amount of power generation is smaller than the specified value, the objective function obtained by considering it as a penalty is avoided to avoid the state of having no optimal solution. However, if the condition becomes such that even the adjustment amount of power generation disappears, then the state of having no optimal solution will be reached.
[0014] Existing technical documents
[0015] Patent documents
[0016] Patent Document 1: Japanese Patent Application Publication No. 2009-70200
[0017] Patent Document 2: Japanese Patent Application Publication No. 2006-48475
[0018] Patent Document 3: Japanese Patent Application Publication No. 2016-93016 Summary of the Invention
[0019] The problem that the invention aims to solve
[0020] In steel plant operations, when a plant stops due to unforeseen factors (malfunctions) or when the plant's operating plan is poor, the energy balance equation, representing insufficient gas, electricity, and steam production, no longer holds true, and no solution can be found in optimal calculations. In such cases, the operator modifies the operating plans of each plant to reduce consumption and restore the energy balance equation. At this point, the change in operating plan should be based on insufficient production; if an excessive operating plan is implemented that causes plants to stop, the overall cost of the steel plant will increase due to the decrease in production. Therefore, the operating plan should be limited to the minimum necessary level.
[0021] However, while the technologies in the aforementioned patent documents 1 to 3 can operate effectively under fault-free conditions, they will not be effective solutions if the operating conditions become such that the optimal solution disappears.
[0022] The following problem exists: even if the calculations in Patent Document 3 are performed to avoid the state without an optimal solution, it is still impossible to provide the user with the application assistance strategy for changing the operation plan of each factory.
[0023] This invention addresses the unresolved issues of the aforementioned prior art and aims to provide an energy utilization auxiliary device, energy utilization auxiliary method, and steel plant operation method that can prompt users of each plant with the necessary minimum changes to the operation plan of energy equipment in situations where there is a shortage of energy auxiliary materials (at least one of by-product gas, steam, and electricity).
[0024] Methods for solving problems
[0025] To achieve the above objectives, one aspect of the present invention relates to an energy utilization assistance device comprising: a performance value and prediction value acquisition unit, which acquires performance values of the production and consumption of energy auxiliary materials at the current moment for each workshop constituting a steel plant, and prediction values of the production and consumption of energy auxiliary materials from the current moment to a specified moment; a unit price information acquisition unit, which acquires unit price information required to calculate the total cost involved in energy utilization of the steel plant; an operation information acquisition unit, which acquires operation information of the energy equipment of the steel plant; an optimization calculation unit, which, based on the information obtained from the performance value and prediction value acquisition unit, the unit price information acquisition unit, and the operation information acquisition unit, uses the operation conditions of the energy equipment as determining variables to constitute the income and expenditure conditions of energy auxiliary materials, adds the deficiency determination variable of energy auxiliary materials to the production variable side of the income and expenditure conditions as a constraint condition, determines an objective function including the total cost involved in energy utilization of the steel plant and the deficiency determination variable, and calculates the determining variables in a manner that makes the objective function gradually approach the optimal value in a way that satisfies the constraint condition; and an utilization policy communication unit, which communicates the utilization policy to the user based on the deficiency calculated by the optimization calculation unit.
[0026] Furthermore, one aspect of the present invention relates to an energy utilization assistance method comprising: a step for obtaining actual and predicted values, which obtains actual values of the production and consumption of energy auxiliary materials at the current moment for each workshop constituting a steel plant, and predicted values of the production and consumption of energy auxiliary materials from the current moment to a specified moment; a step for obtaining unit price information, which obtains unit price information required to calculate the total cost involved in the energy utilization of the steel plant; a step for obtaining operational information, which obtains operational information of the energy equipment of the steel plant; an optimization calculation step, which, based on the information obtained from the steps for obtaining actual and predicted values, unit price information, and operational information, uses the operational conditions of the energy equipment as determining variables to constitute the income and expenditure conditions of energy auxiliary materials, adds the deficiency determination variable of energy auxiliary materials to the production variable side of the income and expenditure conditions as a constraint, determines an objective function including the total cost involved in the energy utilization of the steel plant and the deficiency determination variable, and calculates the determining variables in a way that the objective function gradually approaches the optimal value in a way that satisfies the constraint conditions; and a step for communicating the utilization policy, which communicates the utilization policy to the user based on the deficiency calculated in the optimization calculation step.
[0027] Furthermore, one aspect of the present invention relates to a steel plant operation method based on the aforementioned energy utilization auxiliary method to change the operating conditions of energy equipment or the operating conditions of manufacturing equipment within the steel plant.
[0028] Invention Effects
[0029] According to the energy utilization auxiliary device, energy utilization auxiliary method, and steel plant operation method of the present invention, in the event of a shortage of energy auxiliary materials in a steel plant, the necessary minimum modification plan for the operation of energy equipment can be provided to the users of each plant. Attached Figure Description
[0030] Figure 1 This is a block diagram illustrating the structure of the energy utilization auxiliary device involved in the present invention.
[0031] Figure 2 The data on energy auxiliary materials of a specified factory are stored in the energy auxiliary material performance and prediction database of the energy utilization auxiliary device involved in this invention.
[0032] Figure 3 This is a flowchart illustrating the optimization calculation process performed by the optimization calculation unit of the energy utilization auxiliary device involved in this invention.
[0033] Figure 4 It is a graph showing the time-varying changes in the amount of C gas produced and the amount of insufficient C gas when a malfunction occurs in the coking oven of a steel plant.
[0034] Figure 5 It is a graph showing the historical level changes of gas storage tanks containing gases B, C, converter gas A, and converter gas B in a steel plant.
[0035] Figure 6 It is a graph showing the historical change in the power generation of the generator when a malfunction occurs in the coking oven of a steel plant.
[0036] Figure 7 It is a graph showing the historical change in the amount of by-product gas when a malfunction occurs in the coking oven of a steel plant.
[0037] Figure 8 It is a graph showing the historical change in the amount of externally purchased fuel, i.e., heavy oil, when a malfunction occurs in the coking oven of a steel plant.
[0038] Figure 9 The data refers to the application policy data stored in the application policy production section of the energy utilization auxiliary device involved in this invention. Detailed Implementation
[0039] Next, embodiments of the present invention will be described with reference to the accompanying drawings. In the following description of the drawings, the same or similar parts are labeled with the same or similar reference numerals.
[0040] Furthermore, the embodiments shown below illustrate apparatus and methods for embodying the technical concept of the present invention. The technical concept of the present invention does not limit the materials, shapes, structures, and arrangements of the constituent components to the following: Various modifications can be made to the technical concept of the present invention within the scope defined by the claims.
[0041] As one embodiment of the present invention, the energy utilization auxiliary device is a device that assists in the use of energy auxiliary materials in steel plants in a way that optimizes the cost of energy auxiliary materials.
[0042] Energy-assisted materials include at least one of by-product gases, steam, and electricity generated within the steel plant.
[0043] like Figure 1 As shown, the energy utilization assistance device 1 of this embodiment consists of an information processing device such as a personal computer and a workstation, and includes an energy assistance material performance and prediction database DB1, a unit price information database DB2, an operation information database DB3, an optimization calculation unit 4, an utilization policy creation unit 5, and a guidance unit 6. The optimization calculation unit 4 and the utilization policy creation unit 5 are implemented by executing computer programs through a computing device such as a CPU within the information processing device.
[0044] The Energy Auxiliary Materials Performance and Prediction Database DB1 consists of non-volatile storage devices that store the performance values of the production and consumption of energy auxiliary materials (byproduct gases, steam, electricity) in multiple workshops of the steel plant, as well as the predicted values of the production and consumption of energy auxiliary materials from the current time to a specified time.
[0045] Given the amount of gas B produced, predictions are made using the current production rate and blast furnace operation information. When the blast furnace is operating, predictions are made assuming the current production rate continues into the future; however, when the blast furnace is shut down, predictions are made to make the production rate zero.
[0046] Given the amount of C gas produced, predictions are made using the current production amount and the amount of coal charged in each coke oven.
[0047] The blowing schedule is used to predict the amount of LD gas produced.
[0048] The consumption of M gas in the plant is predicted using the slab loading schedule in the heating furnace and the current M gas consumption.
[0049] Figure 2This data pertains to the energy auxiliary materials of Plant A in a steel plant, stored in the Energy Auxiliary Materials Performance and Prediction Database DB1. The byproduct gases from this energy auxiliary materials data are B gas (blast furnace gas), C gas (coke oven gas), LD gas (LD converter gas), and M gas (mixed gas) obtained by directly or by mixing these gases and then adjusting their heat. Additionally, electricity is generated from the TRT (Top Pressure Recovery Turbine Generator) and CDQ (Cokes Dry Quenching System). Furthermore, steam is generated according to the operation of the converter and sintering furnace. Figure 2 The data for energy auxiliary materials in Plant A includes the current production performance value SJ and consumption performance value DJ, as well as the predicted production value SY and consumption value DY of energy auxiliary materials from the current time to a specified time (e.g., 180 minutes later).
[0050] Additionally, in the DB1 database of energy-assisted materials performance and predictions, with Figure 2 Along with the data on energy auxiliary materials for Factory A, the system also stores the current production figures SJ and consumption figures DJ for energy auxiliary materials from other factories (Factory B, Factory C, etc.), as well as the predicted production figures SY and consumption figures DY for energy auxiliary materials from the current time to a specified time.
[0051] The unit price information database DB2 stores information such as the unit price of electricity, the unit price of steam, the unit price of heavy oil, and the unit price of pure water supplied to boilers.
[0052] The DB3 operation information database stores operation information such as the shutdown time and restart time of energy equipment (power generation equipment, TRT, CDQ, gas storage, mixed gas production equipment) when there are plans to stop them due to periodic inspections, failures, etc.
[0053] The optimization calculation unit 4 performs optimization calculations, outputting the operating conditions of energy equipment as determining variables to minimize or near minimize the total cost of energy use in the steel plant. Specifically, the optimization calculation unit 4 inputs information from the energy auxiliary material performance and prediction database DB1, the unit price information database DB2, and the operation information database DB3 into a mathematical formula obtained by pre-formulating a mixed integer programming problem that includes constraints related to energy use assistance and total cost as one of the mathematical calculation problems. It then calculates the deficiency determination variables and consumption variables, and calculates the total cost F that should be optimized.
[0054] It should be noted that solutions to mixed integer programming problems can be found using methods such as branch and bound, as described in existing technical literature, "Predictive Control of Hybrid Power Systems and Its Application to Process Control, Systems / Control / Information, Vol.46, No.3, pp.110-119, 2002".
[0055] The application policy creation unit 5 creates an application policy based on the insufficient amount X of the specified energy auxiliary materials calculated by the optimization calculation unit 4. Specifically, in the application policy creation unit 5, multiple application policy data, such as application policies that purchase external energy, application policies that purchase external energy and reduce the usage of specified energy equipment, or application policies that reduce the usage of specified energy equipment, are tabled and stored (for example, referring to...). Figure 9 ).
[0056] Furthermore, the policy production unit 5 selects application policy data corresponding to the insufficient amount X of energy auxiliary material calculated by the optimization calculation unit 4.
[0057] The guidance unit 6 displays the application policy data corresponding to the insufficient quantity X selected by the application policy production unit 5 on the guidance screen.
[0058] Furthermore, users can refer to the usage policy data entered into the guidance screen to change the operating conditions of the energy device.
[0059] Next, regarding the optimization calculation process performed by the optimization calculation unit 4, refer to... Figure 3 The flowchart will be used to illustrate this.
[0060] First, in step ST1, the current production performance value SJ and consumption performance value DJ of all energy auxiliary materials in factories A, B, C, etc., stored in the energy auxiliary material performance and prediction database DB1, are read in. The current production performance value SY and consumption prediction value DY of energy auxiliary materials from the current time to the specified time are also read in.
[0061] Next, in step ST2, the purchase prices of electricity, steam, and pure water for private boiler supply stored in the unit price information database DB2 are read in.
[0062] Next, in step ST3, the operating information of the energy equipment (power generation equipment, TRT, CDQ, gas storage, and mixed gas production equipment) stored in the operating information database DB3 is read in.
[0063] Next, in step ST4, to establish constraints, the generation variable Si (i = 1, 2, ..., N) is set based on the information read in step ST1. Here, i = 1, 2, ..., N are suffixes representing factories and energy equipment. It should be noted that in the case of factories, these become actual or predicted values, but in the case of energy equipment, they become determining variables.
[0064] Next, in step ST5, to establish constraints, the consumption variable Di (i = 1, 2, ..., M) is set based on the information read in step ST1. Here, i = 1, 2, ..., M is also a suffix representing a factory or energy equipment. It should be noted that in the case of a factory, this becomes the actual value or predicted value, but in the case of energy equipment, it becomes the determining variable.
[0065] Next, in step ST6, based on the information read in steps ST1, 2, and 3, the insufficient quantity determination variable X (X≥0) is added to the left side of the equation representing the cost-benefit condition of energy auxiliary materials, where the production variable Si on the left and the consumption variable Di on the right are equal, thereby establishing the constraint condition shown in equation (1) below. This constraint condition is the condition that should hold at each time point.
[0066] X + S1 + S2 + … + S N =D1+D2+…+D M …(1)
[0067] Next, in step ST7, an objective function is defined that should be a value that is at or near the minimum. This is the value obtained by adding the total cost F, which uses unit price information and usage quantity, to the weighting constant C multiplied by the deficiency determination variable X.
[0068] (Objective function) = F + CX
[0069] Next, in step ST8, under the constraints of equation (1), the total cost F and the insufficient quantity determination variable X are calculated to make the objective function the minimum or near minimum.
[0070] Here, if we assume that the deficiency variable X is a small value, and set the weighting constant C such that CX at this time becomes sufficiently large compared to the total cost F, then in the optimal calculation when there is no gas shortage, the deficiency variable X is essentially 0. On the other hand, in the case of gas shortage, the deficiency variable X can be a deficiency value greater than 0.
[0071] Next, in step ST9, the operating conditions of the energy equipment (power generation equipment, TRT, CDQ, gas storage, mixed gas manufacturing equipment) calculated in step ST8 are set, and then the optimization calculation process ends.
[0072] Here, the actual value and predicted value acquisition unit and the actual value and predicted value acquisition step described in this invention correspond to the energy auxiliary material actual value and predicted value database DB1, and the unit price information acquisition unit and the unit price information acquisition step described in this invention correspond to the unit price information database DB2. Furthermore, the operation information acquisition unit and operation information acquisition step described in this invention correspond to the operation information database DB3, and the application policy communication unit and application policy communication step described in this invention correspond to the application policy creation unit 5 and the guidance unit 6.
[0073] Next, the situation when a malfunction occurs during the operation of the steel plant will be referenced. Figures 4-8 To illustrate.
[0074] Figure 4 The diagram illustrates a situation where a malfunction occurred in a coking oven at a steel plant, resulting in a planned decrease in C gas production. Within 30 to 50 minutes, C gas production decreased while the insufficient amount increased.
[0075] Figure 5 This is a graph showing the historical level changes of gas storage tanks containing gases B, C, converter gas A, and converter gas B when a malfunction occurs in the coking oven. The operator anticipates a decrease in gas C production, maintains a high gas level in the C storage tank beforehand, and gradually uses the C gas from the storage tank starting 30 minutes after the start of operation.
[0076] Figure 6 This shows the historical variation in power generation from the generator set when a malfunction occurs in the coking oven. Figure 7 This shows the amount of fuel, i.e., by-product gas, used when a malfunction occurs in the coke oven. Figure 8 This shows the amount of externally purchased heavy oil fuel, which is required in the event of a malfunction in the coke oven. From these... Figures 6-8 It is clear that even if the production of carbon gas decreases, a drastic change in power generation is undesirable. Therefore, the output of power generation is gradually reduced, while the purchase of heavy oil is increased. Here, as... Figure 4 As shown, the average amount of C gas during the period of insufficient quantity in the first 30 to 50 minutes after the start of application is approximately 500 [GJ / h].
[0077] Next, the operation of the energy utilization auxiliary device 1 when a coking oven malfunction occurs as described above will be explained.
[0078] In the optimization calculation unit 4 of the energy utilization auxiliary device 1, the current actual production value SJ and consumption value DJ of all energy auxiliary materials from factory A, factory B, factory C, etc., and the predicted production value SY and consumption value DY of energy auxiliary materials from the current time to a specified time are read in. Figure 3Step ST1). Next, read in the purchase price per unit for electricity, steam, and pure water supplied to the boiler, etc. Figure 3 Step ST2) reads in the operating information of the energy equipment (power generation equipment, TRT, CDQ, gas storage, mixed gas production equipment). Figure 3 Step ST3). Then, set the generation variable Si (i = 1, 2, ... N) ( Figure 3 Step ST4), set the consumption variable Di (i = 1, 2, ..., M) Figure 3 Step ST5), using the insufficient determinant variable X to formulate the constraints of the aforementioned equation (1) ( Figure 3 Step ST6).
[0079] Then, the objective function (total cost F + the value obtained by multiplying the insufficient determinant variable X by the weighting constant C) is minimized or near minimized under the constraints of equation (1). Then, the operating conditions of the obtained energy equipment (power generation equipment, TRT, CDQ, gas storage tank, mixed gas production equipment) are set ( Figure 3 Step ST9).
[0080] Furthermore, the energy utilization auxiliary device 1's utilization policy production unit 5 uses the insufficient amount X (500 [GJ / h]) calculated by the optimization calculation unit 4 and... Figure 9 The data corresponding to the multiple application policies shown are as follows: Select "2" for the application policy that reduces the city's gas purchases and hot air furnace usage.
[0081] Then, the guidance unit 6 of the energy utilization assistance device 1 displays "decreased city gas purchases and hot air furnace usage" on the guidance screen.
[0082] As a result, users in each factory can refer to the "reduction in city gas purchases and hot air furnace usage" policy entered into the guidance screen and quickly change the operating conditions of energy equipment.
[0083] It should be noted that although the situation of insufficient C gas in the operation of the steel plant has been described, the energy utilization auxiliary device 1 will also be used to assist even when other energy auxiliary materials such as by-product gases, steam, and electricity are insufficient.
[0084] Therefore, the energy utilization auxiliary device 1 of this embodiment calculates the shortage based on constraints such as the generation variable Si, the consumption variable Di, and the shortage determination variable X, and sets the operating conditions for energy equipment (power generation equipment, TRT, CDQ, gas storage tank, and mixed gas production equipment). Thus, in situations where there is a shortage of energy auxiliary materials (at least one of by-product gas, steam, or electricity) in a steel plant, it can provide operators in each plant with the necessary minimum modification plan for the operation of the energy equipment.
[0085] Furthermore, by changing the operating conditions of energy equipment or the operating conditions of manufacturing equipment within a steel plant through a change plan based on suggested operating conditions, it is possible to operate the steel plant in a way that optimizes the use of energy equipment.
[0086] Explanation of reference numerals in the attached figures
[0087] 1. Energy utilization auxiliary device
[0088] 4. Optimization Calculation Department
[0089] 5. Policy Production Department
[0090] 6th Guidance Department
[0091] C weighting constant
[0092] F should optimize the total cost
[0093] Insufficient X determines the variable
[0094] DB1 Energy-Assisted Materials Performance and Prediction Database
[0095] DB2 Unit Price Information Database
[0096] DB3 Operation Information Database
[0097] Si (i = 1, 2, ..., N) generates variables
[0098] Di(i=1,2,…M) is the consumption variable.
Claims
1. An energy utilization auxiliary device, characterized in that, have: The Actual Value and Forecast Value Acquisition Department acquires the actual values of the production and consumption of energy auxiliary materials for each workshop constituting the steel plant at the current moment, and the forecast values of the production and consumption of energy auxiliary materials from the current moment to a specified moment. The unit price information acquisition unit acquires the unit price information required to calculate the total cost of energy use in the steel plant. The operation information acquisition unit acquires the operation information of the energy equipment in the steel plant. The optimization calculation unit, based on information obtained from the actual and predicted value acquisition unit, the unit price information acquisition unit, and the operation information acquisition unit, uses the operating conditions of the energy equipment as determining variables to constitute the income and expenditure conditions of the energy auxiliary materials. It then adds the deficiency determination variable of the energy auxiliary materials to the variable generating the income and expenditure conditions as a constraint, and determines an objective function including the total cost related to the energy use of the steel plant and the deficiency determination variable. The unit calculates the determining variables in a way that the objective function gradually approaches the optimal value in a manner that satisfies the constraint conditions. The policy communication unit communicates the application policy to the user based on the deficiencies calculated by the optimization calculation unit.
2. The energy utilization auxiliary device according to claim 1, characterized in that, The application policy communication department selects one application policy from multiple application policies based on the insufficient quantity and communicates it to the user.
3. An auxiliary method for energy utilization, characterized in that, include: The steps for obtaining actual and predicted values are as follows: obtain the actual values of the production and consumption of energy auxiliary materials for each workshop that constitutes the steel plant at the current moment, and the predicted values of the production and consumption of energy auxiliary materials from the current moment to the specified moment. The step of obtaining unit price information involves obtaining the unit price information required to calculate the total cost of energy use in the steel plant. The operation information acquisition step involves acquiring the operation information of the energy equipment in the steel plant. The calculation steps are optimized based on the information obtained from the steps of obtaining actual and predicted values, obtaining unit price information, and obtaining operation information. The operating conditions of the energy equipment are used as determining variables to constitute the income and expenditure conditions for the energy auxiliary materials. The deficiency determination variable of the energy auxiliary materials is added to the variable generating the income and expenditure conditions as a constraint. An objective function is determined, including the total cost involved in the energy use of the steel plant and the deficiency determination variable. The determining variables are calculated in a way that the objective function gradually approaches the optimal value in a manner that satisfies the constraints. The policy communication step uses the deficiency calculated in the optimization calculation step to communicate the application policy to the user.
4. The energy utilization auxiliary method according to claim 3, characterized in that, The application policy communication step selects one application policy from multiple application policies based on the insufficient quantity and communicates it to the user.
5. An operating method for a steel plant, characterized in that, The energy utilization auxiliary method described in claim 3 or 4 is used to change the operating conditions of energy equipment or the operating conditions of manufacturing equipment in a steel plant.