A method for real-time optimization of unit consumption of a heating furnace under all operating conditions in oxygen-enriched environments

Abstract

This invention belongs to the field of energy management technology in the iron and steel metallurgy industry, and particularly relates to a real-time optimization method for the unit consumption of a heating furnace under full operating conditions in oxygen-enriched mode. The specific steps are as follows: Step 1: Multi-dimensional data acquisition and preprocessing; Step 2: Heating furnace calorific value sensitivity profiling and classification; Step 3: Based on the classification results of Step 2, execute differentiated gas allocation logic; Step 4: Component reconstruction control based on the "oxygen-enriched energy efficiency inflection point"; Step 5: Dual closed-loop dynamic combustion supplementation of oxygen and natural gas. This method is based on a differentiated routing strategy using the "calorific value sensitivity coefficient," establishes the "oxygen-enriched energy efficiency inflection point" through big data mining, and introduces a dual closed-loop dynamic combustion supplementation mechanism of "natural gas fine-tuning + oxygen feedforward," significantly improving the system's anti-interference capability, realizing differentiated energy scheduling based on equipment characteristics, optimizing the overall plant resource allocation, and achieving global maximization of the plant's energy utilization efficiency.

Description

Technical Field

[0001] This invention belongs to the field of energy management technology in iron and steel metallurgy, and particularly relates to a method for real-time optimization of unit consumption of a heating furnace under full operating conditions in oxygen-enriched conditions. Background Technology

[0002] The heating furnace is a key piece of equipment in the steel rolling process, typically accounting for 60% to 70% of the total energy consumption of the rolling process. To improve production efficiency, reduce pollutant emissions, and minimize oxidation loss, oxygen-enriched combustion technology is usually used to replace traditional regenerative air combustion. Oxygen-enriched combustion utilizes high-purity oxygen to aid combustion, increasing flame temperature, accelerating heat transfer rates, and reducing flue gas heat loss. However, in actual industrial production, the following significant technical bottlenecks and misconceptions still exist regarding energy management and coordinated control of oxygen-enriched heating furnaces: (1) The proportioning strategy ignores the "nonlinear energy efficiency" characteristic under oxygen-enriched conditions. Current technology generally believes that the high-temperature characteristics of oxygen-assisted combustion can compensate for the unstable combustion of low-calorific-value fuels. Therefore, in order to reduce fuel procurement costs, production enterprises often tend to excessively blend cheap blast furnace gas or converter gas into mixed gas. However, actual operating data shows that this linear thinking fails under certain operating conditions. When the calorific value of the mixed gas is below a certain critical threshold, even with oxygen-assisted combustion, the flame rigidity is still insufficient, resulting in a lag in furnace temperature response and a passive extension of heating time. This directly leads to a sharp increase in gas consumption per ton of steel (GJ / t), resulting in a false energy-saving phenomenon of "lower unit price but higher total cost." Existing control systems lack an energy efficiency inflection point constraint mechanism based on big data.

[0003] (2) Lack of “differentiated energy dispatching” methods tailored to the characteristics of oxygen-enriched furnaces In production lines with multiple heating furnaces, existing scheduling systems typically employ an egalitarian approach or allocate gas flow solely based on production capacity load. In reality, due to factors such as equipment aging, burner characteristics, and furnace structure, different heating furnaces exhibit significant differences in their sensitivity to gas calorific value. The existing extensive scheduling method fails to prioritize the allocation of high-quality, high-calorific-value gas (such as coke oven gas) to "sensitive" equipment, resulting in low utilization efficiency of high-quality energy and hindering further reductions in overall plant energy consumption.

[0004] (3) Lack of deep coupling between oxygen enrichment and coal gas composition control Currently, oxygen-enriched combustion control mainly focuses on the real-time adjustment of the "oxygen-fuel ratio," that is, simply matching the amount of oxygen based on the amount of input gas. This "passive" control cannot solve the problem of combustion deterioration caused by fluctuations in gas composition (especially the excessively high proportion of converter gas flow) at the source. It lacks an active control strategy that simultaneously optimizes both the "source gas composition" and the "end oxygen flow." Summary of the Invention

[0005] The purpose of this invention is to provide a method for real-time optimization of unit consumption of a heating furnace under all operating conditions in oxygen-enriched conditions, thereby addressing the shortcomings in the aforementioned background technology.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: A method for real-time optimization of unit consumption of a heating furnace under full operating conditions in oxygen-enriched conditions, the specific steps of which are as follows: Step 1: Multidimensional Data Acquisition and Preprocessing Step 2: Profiling and Classification of Heating Furnace Calorific Value Sensitivity (1) Establish a correlation analysis model of "calorific value-unit consumption" and calculate the calorific value sensitivity coefficient λ of each heating furnace. The calculation formula is as follows: , where i represents the furnace number, ΔUC represents the change in gas consumption per ton of steel, and ΔHV represents the change in the average calorific value of the mixed gas; (2) The system calculates the average sensitivity coefficient of all online heating furnaces in the plant in real time and uses it as the dynamic classification threshold. Calculation formula: Subsequently, the control system compares the absolute value of the actual sensitivity coefficient of each heating furnace with the dynamic classification threshold. By comparison, the heating furnace was divided into two types of control units: a. When |λ|<λ th The heating furnace is a base load absorption unit, which is not sensitive to calorific value fluctuations and has a strong anti-interference ability against calorific value fluctuations. b. When |λ|≥λ th The heating furnace is a precision control unit that is extremely sensitive to fluctuations in calorific value and must be a key target for ensuring gas supply. Step 3: Differentiated Energy Routing Strategy Based on the grading results from step 2, execute the differentiated gas allocation logic: (1) Implement a “low cost priority” strategy for the base load consumption unit. Under the premise of meeting the minimum combustion temperature, prioritize the allocation of converter gas and blast furnace gas, undertake the task of consuming low-calorific-value by-product gas of the whole plant, and maintain full-load production to take advantage of economies of scale. (2) Implement the "energy efficiency inflection point priority" strategy for the precision control unit. The system locks the lower limit of the calorific value of its inlet mixed gas, prioritizes the allocation of coke oven gas and natural gas, strictly prohibits operation in the low calorific value range, and sets the oxygen-enriched energy efficiency inflection point calorific value threshold (Q). critical As operational constraints, the lower limit of the calorific value of the inlet mixed gas and the calorific value threshold of the oxygen-enriched energy efficiency inflection point are explained as follows: ①Lower limit of calorific value of inlet mixed gas: a. Physical definition: refers to the minimum calorific value of the mixed gas required to maintain stable combustion in the heating furnace, ensure that the flame does not go out, and enable the steel billet to reach the target temperature at the furnace outlet; b. Nature: It is a rigid physical and technological constraint; c. Triggering consequences: If the actual calorific value falls below this lower limit, the heating furnace will face the danger of deteriorating combustion, a sharp drop in furnace temperature, or even flameout, directly resulting in "unheated steel"; d. Traditional approach: Traditional automated control systems (PLCs) usually strictly adhere to this bottom line. As long as the calorific value is above the lower limit, the gas is mixed according to the conventional ratio; once it approaches the lower limit, an alarm is immediately triggered and a high-calorific-value gas is forcibly switched in. ②Inflection point calorific value threshold a. Physical definition: It refers to the critical point at which the heat exchange efficiency of the system drops sharply during the process of the gradual decrease of the calorific value of the gas, resulting in a sharp increase in the consumption per ton of steel. This critical point is the inflection point of the nonlinear curve that is mined by fitting massive amounts of historical data through machine learning (such as random forest). b. Properties: It is a dynamic algorithm trigger point based on economic efficiency and energy efficiency optimization; c. Triggering consequences: When the calorific value drops to this inflection point, although the furnace can still burn normally (far from reaching the physical lower limit), the large amount of ineffective nitrogen and carbon dioxide brought in by the low-calorific-value gas (such as blast furnace gas) leads to a sharp increase in flue gas heat loss, extremely low thermal efficiency, and soaring unit consumption. d. The approach of this invention: Instead of waiting for the calorific value to fall below the lower limit, once the calorific value is detected to have touched the "inflection point", it will take the initiative to start "dynamic ratio reconstruction" (for example, forcibly introducing about 6% natural gas as conditioning ballast), thereby pulling it back to the lowest range before the unit consumption deteriorates; Step 4: Component Reconfiguration Control Based on the "Oxygen-Enriched Energy Efficiency Inflection Point" Step 5: Dynamic combustion of oxygen and natural gas in a dual closed loop.

[0007] Preferably, the specific operation of data acquisition in step 1 is as follows: The system collects the following four types of data in real time through field instruments and performs time-series synchronization processing: (1) Energy medium data: instantaneous flow rate, pressure and online calorific value analysis data of coke oven gas, blast furnace gas, converter gas and natural gas; pressure and flow rate of combustion-supporting oxygen; (2) Equipment operation data: furnace temperature, flue gas temperature, and residual oxygen content of each heating furnace; (3) Production cycle data: real-time steel loading, steel tapping rhythm, waiting / stopping signals, steel grade (such as ordinary steel, stainless steel, special steel); (4) Energy efficiency feedback data: Real-time calculation of gas consumption per ton of steel (GJ / t) for each heating furnace.

[0008] Preferably, the oxygen-enriched energy efficiency inflection point calorific value threshold (Q) in step 3 is... critical The setting range is 2500 kcal / m³. 3 Up to 2600Kcal / m 3 .

[0009] Preferably, the oxygen-enriched energy efficiency inflection point calorific value threshold (Q) in step 3 is... critical ) is 2550 kcal / m 3 .

[0010] Preferably, the component reconstruction operation in step 4 is as follows: The calorific value of the mixed gas at the inlet of each branch pipe of each precision control unit is monitored in real time; when the real-time calorific value of the gas in a certain heating furnace is lower than the preset oxygen-enriched energy efficiency inflection point calorific value threshold... At that time, the system triggers component reconfiguration control logic for that specific heater branch pipe; if multiple heaters trigger warnings simultaneously and the high-calorific-value gas source is limited, the system calculates according to step 2. The priority order of values ​​from high to low is executed as follows: automatically reduce the proportion of converter gas branch flow and simultaneously increase the proportion of coke oven gas branch flow until the real-time calorific value at the furnace inlet returns to above the threshold, while simultaneously calculating the theoretical combustion oxygen demand after the gas is injected.

[0011] Preferably, the component reconstruction logic in step 4 is executed as follows: (1) Coke oven gas setpoint control: Forcefully increase the instantaneous flow rate ratio of coke oven gas in the mixed gas and lock it in the high-efficiency range of 34%-36%; (2) Converter gas meltdown control: Set the upper limit of the instantaneous flow rate of converter gas. When the flow rate of converter gas exceeds the threshold, even if the total calorific value meets the standard, the system will force a reduction in the flow rate of converter gas to prevent the rigidity of the oxygen-enriched combustion flame from decreasing due to excessive inert gas.

[0012] Preferably, the upper limit of the instantaneous flow rate of converter gas in step 4 (2) is 45%.

[0013] Preferably, the dual closed-loop dynamic afterburning operation in step 5 is as follows: When the coke oven gas regulation rate in step 4 reaches the physical upper limit, and the real-time gas calorific value is still lower than the oxygen-enriched energy efficiency inflection point calorific value threshold, the "oxygen-gas linkage" compensation mechanism is activated: (1) Natural gas fine-tuning loop: The natural gas regulating valve is automatically opened to inject natural gas in a pulse or linear manner, and the flow rate ratio is controlled at 3.0%~4.5% to quickly increase the real-time calorific value of the gas; (2) Oxygen-fuel ratio correction loop: The oxygen flow rate setting value is dynamically corrected based on the actual real-time calorific value of the coal gas after natural gas injection and the theoretical oxygen demand for combustion.

[0014] Preferably, the correction logic for dynamically correcting the oxygen flow rate setpoint in step 5 (2) is as follows: ,in Total oxygen demand for theoretical combustion (unit: m³) 3 / h or Nm 3 / h), refers to the real-time pure oxygen flow rate required by the system to ensure complete combustion of the gas under the current gas composition; K is the oxygen enrichment compensation coefficient (dimensionless constant), used to characterize the ratio of actual oxygen supply to theoretical oxygen demand. In the normal steady-state stage, this value is usually set to 1.03-1.05 (to ensure slightly oxygen-rich combustion); in the dynamic compensation stage triggered by the "energy efficiency inflection point", the K value is appropriately increased to utilize the high temperature characteristics of oxygen-rich combustion to eliminate the thermal lag caused by low calorific value. The aim is to improve the thermal intensity of the flue gas per unit volume through the oxygen-rich environment and eliminate furnace temperature fluctuations. The instantaneous inlet flow rate of the i-th type of gas (unit: m³) 3 / h), i corresponds to the real-time flow meter readings of coke oven gas (COG), blast furnace gas (BFG), converter gas (LDG), and supplementary combustion natural gas (NG), respectively; Let be the theoretical oxygen demand coefficient per unit volume (dimensionless) for the i-th type of gas. This coefficient is determined by the stoichiometric ratio of the combustible components (such as CO, H2, CH4, etc.) in the gas composition. For example, for coke oven gas with a high calorific value... The value is relatively large; for blast furnace gas containing a large amount of inert gas, The value is relatively small; The total theoretical oxygen demand of multi-source coal gas refers to the theoretical oxygen consumption baseline value calculated by weighted summation based on the instantaneous flow rate of the current mixed coal gas and its respective chemical characteristics.

[0015] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: (1) Based on measured data, oxygen-assisted combustion is quantified, which has natural energy-saving advantages. Combined with "oxygen-gas linkage" control, this advantage is further amplified. In particular, by limiting the proportion of converter gas flow, the inhibitory effect of inert gas on oxygen-enriched combustion is eliminated, so that the equipment always operates in the optimal thermal zone, a quantitative benchmark for oxygen-assisted combustion relative to air-assisted combustion is established, and the potential for deep energy saving is explored. (2) Abandoning the traditional fixed judgment threshold, it pioneered a dynamic relative sensitivity threshold based on the average value of the entire plant. It effectively overcomes the problem of absolute base deviation caused by steel billet material switching and flow meter calibration error in industrial sites, avoids classification failure of a single fixed threshold under complex working conditions, and achieves true advanced adaptive control. (3) Based on the differentiated routing strategy of “calorific value sensitivity coefficient”, the insensitive heating furnace is used as the “consumer” of low calorific value gas and its full-load production is guaranteed first; the sensitive heating furnace is used as the “protection zone” of high calorific value gas. This “tiered energy supply” strategy achieves differentiated energy scheduling based on equipment characteristics without increasing external energy input, optimizes the allocation of plant resources, and maximizes the overall energy utilization efficiency of the plant. (4) By establishing the “oxygen-enriched energy efficiency inflection point” through big data mining and forcibly locking the proportion of coke oven gas, although the cost of gas per unit volume increases slightly, the gas consumption per ton of steel is greatly reduced due to the qualitative change in combustion efficiency, thus overcoming the “false energy saving” caused by blindly mixing low-calorific-value gas and achieving a substantial reduction in gas consumption per ton of steel. (5) A dual closed-loop dynamic combustion supplementation mechanism of "natural gas fine-tuning + oxygen feedforward" is introduced. When the trend of calorific value falling below the inflection point is detected, a high-energy medium is injected in milliseconds to quickly stabilize the furnace temperature. This mechanism effectively solves the production interruption problem caused by gas fluctuations, greatly reduces the ineffective energy consumption caused by shutdown for heat preservation, significantly improves the system's anti-interference ability, and reduces unplanned shutdowns. Detailed Implementation

[0016] The technical solution of the present invention will be described in detail below with reference to the embodiments.

[0017] The method of this invention was applied to heating furnaces #1-#3 in a hot strip mill. The specific steps of this method for real-time optimization of unit energy consumption under oxygen-enriched conditions across all operating conditions of the heating furnaces are as follows: Step 1: Multidimensional Data Acquisition and Preprocessing The system collects the following four types of data in real time through field instruments and performs time-series synchronization processing: (1) Energy medium data: instantaneous flow rate, pressure and online calorific value analysis data of coke oven gas, blast furnace gas, converter gas and natural gas; pressure and flow rate of combustion-supporting oxygen; (2) Equipment operation data: furnace temperature, flue gas temperature, and residual oxygen content of each heating furnace; (3) Production cycle data: real-time steel loading, steel tapping rhythm, waiting / stopping signals, steel grade (such as ordinary steel, stainless steel, special steel); (4) Energy efficiency feedback data: Real-time calculation of gas consumption per ton of steel (GJ / t) for each heating furnace.

[0018] Step 2: Profiling and Classification of Heating Furnace Calorific Value Sensitivity (1) Establish a correlation analysis model of "calorific value-unit consumption" and calculate the calorific value sensitivity coefficient λ of each heating furnace. The calculation formula is as follows: Where i represents the furnace number, ΔUC represents the change in gas consumption per ton of steel, and ΔHV represents the change in the average calorific value of the mixed gas; the actual calculation process for each furnace is as follows: a.1# Heating Furnace: Actual measured data: When the calorific value increases from 2350 kcal / m³ 3 Increased to 2450Kcal / m 3 ( When ), the unit consumption of heating furnace #1 decreased from 1.05 to 1.03. ).

[0019] Calculation results: .

[0020] b.2# Heating Furnace: Actual measured data: When the calorific value increases from 2350 kcal / m³ 3 Increased to 2450Kcal / m 3 ( When the unit consumption of boiler #2 dropped rapidly from 1.35 to 1.28, the unit consumption of boiler #2 also dropped rapidly. ).

[0021] Calculation results: .

[0022] c.3# Heating Furnace (High Sensitivity Protection Unit): Actual test data: Heating furnace #3 exhibits the strongest dependence on calorific value, when the calorific value increases from 2350 kcal / m³. 3 Increased to 2450Kcal / m 3 ( When the unit consumption drops dramatically from 1.42 to 1.31, the unit consumption decreases dramatically. ).

[0023] Calculation results:

[0024] A horizontal comparison of the data shows that heating furnaces #1, #2, and #3 exhibit distinctly different thermal response characteristics under the same fuel fluctuation conditions: #1 Heating Furnace: Its sensitivity coefficient With a calorific value of only 0.020, it means that when the calorific value of the mixed gas changes... Even during periods of extreme volatility, its steel consumption per ton fluctuates by only 0.02 GJ / t.

[0025] Heating furnaces #2 and #3: their sensitivity coefficients It is 0.070, while The sensitivity to calorific value is as high as 0.110, especially for heating furnace #3, which is 5.5 times more sensitive to calorific value than heating furnace #1.

[0026] (2) The system calculates the average sensitivity coefficient of all online heating furnaces in the plant in real time and uses it as the dynamic classification threshold. Calculation formula: Extract the arithmetic mean of the sensitivity coefficients of the currently online heating furnaces #1, #2, and #3. , The control system then compares the absolute value of the actual sensitivity coefficient of each heating furnace with the dynamic classification threshold. By comparing (dynamic grading based on relative sensitivity), the heating furnace is divided into two types of control units: a. The No. 1 heating furnace is characterized as a base load absorption unit and is determined to be insensitive to calorific value fluctuations. That is, the heating furnace has a strong buffering and anti-interference ability against fuel calorific value decay. b. , Heating furnaces #2 and #3 are classified as precision control units and are determined to be sensitive to fluctuations in calorific value, requiring priority protection. This means that these heating furnaces are extremely sensitive to low calorific value conditions, and if the calorific value is lost, it can easily lead to nonlinear degradation of unit consumption. Compared with the results obtained by setting a threshold in the traditional way, the accuracy is higher. The reasons for the failure of a single fixed threshold under complex working conditions are as follows: a. Steel billet material (and specifications): Different steel grades (such as carbon steel vs. silicon steel) have different heating curve requirements, different specific heat capacities, and different absolute heat absorption requirements, resulting in a huge shift in the unit consumption base under the same calorific value. b. Calibration error of flow meters: After a period of use, gas flow meters in industrial sites (such as orifice plate flow meters and vortex flow meters) will accumulate errors, causing the absolute values ​​of the calculated ΔHV and ΔUC to deviate from the true values.

[0027] Step 3: Differentiated Energy Routing Strategy Based on the grading results from step 2, execute the differentiated gas allocation logic: (1) Implement the "low cost priority" strategy for No. 1 heating furnace. When the total amount of high calorific value gas in the whole plant pipeline is limited or the supply drops, the control module prioritizes reducing the high calorific value gas source ratio weight of the "base load absorption unit" (i.e. No. 1 heating furnace) and uses it as a buffer to absorb the fluctuation of the calorific value of the whole plant. This allows the system to achieve the optimal allocation of global resources under the constraint of unbalanced gas source, and ensures that the total unit consumption of the whole plant is maintained in the target minimum range. (2) Implement the "energy efficiency inflection point priority" strategy for No. 3 heating furnace, and lock the lower limit of the calorific value of the inlet mixed gas at 2550 kcal / m³. 3Priority should be given to allocating coke oven gas and natural gas, and operation in the low calorific value range is strictly prohibited. An oxygen-enriched energy efficiency inflection point calorific value threshold (Q) should also be set. critical As an operational constraint, when the system has a reserve of high-calorific-value gas sources (such as coke oven gas), the control module will allocate the high-calorific-value gas sources according to... The weighted tiered allocation, which forces priority supply to the sensitive peak unit (i.e., No. 3 heating furnace), aims to maximize the marginal benefit of energy saving for the entire system by utilizing the limited high-potential energy fuel.

[0028] Step 4: Component Reconfiguration Control Based on the "Oxygen-Enriched Energy Efficiency Inflection Point" In this embodiment, the mixed gas in each heater is dynamically blended from blast furnace gas, converter gas, coke oven gas, and natural gas. The calorific value of the mixed gas at the inlet of each branch pipe of each precision control unit (heater #2 and #3) is monitored in real time. When the real-time calorific value of the gas in a certain heater is lower than the preset oxygen-enriched energy efficiency inflection point calorific value threshold... ( When a warning is triggered simultaneously by multiple furnaces and the high-calorific-value gas supply is limited, the system will initiate component reconfiguration control logic for that specific furnace branch pipe. The priority order of values ​​from high to low (3# heating furnace > 2# heating furnace) is executed as follows: the proportion of converter gas branch flow is automatically reduced, and the proportion of coke oven gas branch flow is increased simultaneously until the real-time calorific value at the furnace inlet returns to above the threshold. At the same time, the theoretical combustion oxygen demand after the gas is injected is calculated in real time.

[0029] The component reconfiguration logic is executed as follows: The unit consumption is lower than that selected through big data screening (i.e., the golden ratio structure at the top 10% energy efficiency level): (1) High calorific value core layer: The proportion of coke oven gas (COG) in the mixed gas is forced to be stabilized at 34.6%, proving that high-quality fuel is the basis for maintaining the rigidity of oxygen-rich flame; (2) Low calorific value constraint layer: The proportion of converter gas (LDG) is limited to 43.9%, which confirms the proposed "45% melting line". That is, if this proportion is exceeded, too much inert gas will offset the heat transfer advantage of oxygen-enriched combustion. (3) Dynamic compensation layer: Natural gas (NG) accounts for 3.9%, which, together with blast furnace gas (BFG) of 17.6%, forms a stable calorific value supplement echelon.

[0030] Step 5: Dynamic supplementary combustion of oxygen and natural gas in a dual closed loop When the coke oven gas regulation rate in step 4 reaches its physical upper limit due to insufficient pipeline pressure, and the real-time gas calorific value is still lower than the oxygen-enriched energy efficiency inflection point calorific value threshold, the "oxygen-gas linkage" compensation mechanism is activated: (1) Natural gas fine-tuning loop: The natural gas regulating valve corresponding to the precision control unit (heater #2 or #3) is automatically opened, and natural gas is injected into the inlet mixing manifold of the heater in a pulse or linear manner, controlling the flow rate ratio at 3.0%~4.5% to quickly increase the real-time calorific value of the gas.

[0031] (2) Oxygen-fuel ratio correction loop: Based on the actual real-time calorific value of the gas after natural gas injection and the theoretical oxygen demand for combustion, and in conjunction with the preset oxygen enrichment coefficient, the oxygen flow rate setpoint of each heating section of the heater is dynamically corrected to maintain the optimal oxygen-fuel ratio environment in the furnace. The correction process is as follows: By using a feedforward control model, the increase in theoretical oxygen demand is pre-calculated at the instant the mixed gas composition changes (such as when natural gas is injected), and an oxygen enrichment compensation coefficient is superimposed to achieve the desired oxygen flow rate. Precise tracking.

[0032] a. Set operating condition baseline parameters Assuming the heating furnace is currently in normal production, the theoretical oxygen demand coefficients for each gas ratio are... The volume of pure oxygen required for the complete combustion of a unit volume of coal gas is set as follows: Coke oven gas (COG):

[0033] Converter gas (LDG):

[0034] Natural gas (NG): (Highest calorific value, highest oxygen demand) Typical oxygen enrichment coefficient K: 1.05 b. Dynamic Correction Process Drill When the calorific value is detected to have fallen below the inflection point, the proportioning is reconfigured and natural gas is injected.

[0035] Status A (before correction): The gas ratio is: , There is no natural gas.

[0036] The theoretical total oxygen demand at this point is:

[0037] Set oxygen flow rate .

[0038] State B (corrected - triggers energy efficiency inflection point protection): The system performs a reconfiguration process, injecting 4% natural gas (approximately 350m³). 3 / h) to increase the calorific value, and simultaneously increase the oxygen enrichment coefficient K to 1.10 to eliminate thermal hysteresis.

[0039] The new theoretical total oxygen demand is:

[0040] New oxygen flow rate setting .

[0041] c. Technical Effect Analysis Incremental control: At the moment of natural gas injection, the oxygen setpoint is actively increased by approximately 22.8% (5354.25 vs 4357.5).

[0042] Response speed: This correction logic directly skips the lag in furnace temperature feedback and ensures that the burner has sufficient oxygen concentration to support high-temperature combustion while the calorific value of the gas increases through the path of "composition change → oxygen demand calculation → flow command", thereby quickly smoothing furnace temperature fluctuations within 30-60 seconds.

[0043] In this embodiment, the heating furnaces are divided into two types of control units to achieve "tiered energy supply" and "differentiated energy routing" decisions. The system no longer applies an average distribution to all furnaces, but instead prioritizes directing the highly fluctuating low-calorific-value converter gas (LDG) to the extremely low-sensitivity No. 1 heating furnace, ensuring the continuity of production throughout the plant; it also precisely protects highly sensitive equipment. The control system of the No. 3 heating furnace uses an algorithm to lock it into "high calorific value mode" to avoid a sharp drop in energy efficiency of highly sensitive equipment due to fluctuations in fuel quality, thus eliminating the "weakest link" effect in the overall plant energy efficiency from the root.

[0044] By utilizing component restructuring logic to overcome the "low-price misconception," traditional processes often use LDG (Liquid Dioxide) exceeding 55% to pursue low fuel costs. By increasing COG (Coal Gas) to over 34%, although the instantaneous fuel price increases, the total energy consumption per ton of steel decreases by 20% due to a significant improvement in combustion thermal efficiency. Furthermore, this formulation locks in the "energy efficiency inflection point," maintaining a constant calorific value of the mixed gas at 2550 kcal / m³. 3 Under this ratio, the flame center temperature of oxygen-enriched combustion can be stably increased by 50-80℃, greatly shortening the residence time of the steel billet in the soaking zone and achieving true systemic energy saving.

[0045] After adopting this method, the combustion efficiency has undergone a qualitative change. Actual measurement data shows that the gas consumption per ton of steel has been reduced by 15% to 20%, and the gas consumption per ton of heating furnace, which is sensitive to calorific value, has been reduced from 1.38 GJ / t to 1.08 to 1.10 GJ / t, reaching the industry-leading level.

Claims

1. A method for real-time optimization of unit consumption of a heating furnace under all operating conditions in oxygen-enriched conditions, characterized in that, The specific steps are as follows: Step 1: Multidimensional Data Acquisition and Preprocessing Step 2: Profiling and Classification of Heating Furnace Calorific Value Sensitivity (1) Establish a correlation analysis model of "calorific value-unit consumption" and calculate the calorific value sensitivity coefficient λ of each heating furnace. The calculation formula is as follows: , where i represents the furnace number, ΔUC represents the change in gas consumption per ton of steel, and ΔHV represents the change in the average calorific value of the mixed gas; (2) The system calculates the average sensitivity coefficient of all online heating furnaces in the plant in real time and uses it as the dynamic classification threshold. Calculation formula: Subsequently, the control system compares the absolute value of the actual sensitivity coefficient of each heating furnace with the dynamic classification threshold. By comparison, the heating furnace was divided into two types of control units: a. When |λ|<λ th The heating furnace is a base load absorption unit, which is not sensitive to calorific value fluctuations and has a strong anti-interference ability against calorific value fluctuations. b. When |λ|≥λ th The heating furnace is a precision control unit that is extremely sensitive to fluctuations in calorific value and must be a key target for ensuring gas supply. Step 3: Differentiated Energy Routing Strategy Based on the grading results from step 2, execute the differentiated gas allocation logic: (1) Implement a "low cost priority" strategy for the base load consumption unit. Under the premise of meeting the minimum combustion temperature, prioritize the allocation of converter gas and blast furnace gas, undertake the task of consuming low-calorific-value by-product gas of the whole plant, and maintain full-load production to take advantage of economies of scale. (2) Implement the "energy efficiency inflection point priority" strategy for the precision control unit. The system locks the lower limit of the calorific value of its inlet mixed gas, prioritizes the allocation of coke oven gas and natural gas, strictly prohibits operation in the low calorific value range, and sets the oxygen-enriched energy efficiency inflection point calorific value threshold (Q). critical ) as operational constraints; Step 4: Component Reconfiguration Control Based on the "Oxygen-Enriched Energy Efficiency Inflection Point" Step 5: Dynamic combustion of oxygen and natural gas in a dual closed loop.

2. The method for real-time optimization of unit consumption of a heating furnace under full operating conditions in oxygen-enriched conditions according to claim 1, characterized in that, The specific operations for data collection in step 1 are as follows: The system collects the following four types of data in real time through field instruments and performs time-series synchronization processing: (1) Energy medium data: instantaneous flow rate, pressure and online calorific value analysis data of coke oven gas, blast furnace gas, converter gas and natural gas; pressure and flow rate of combustion-supporting oxygen; (2) Equipment operation data: furnace temperature, flue gas temperature, and residual oxygen content of each heating furnace; (3) Production cycle data: real-time steel loading, steel tapping rhythm, waiting / stopping signals, steel grade, such as ordinary steel, stainless steel, and special steel; (4) Energy efficiency feedback data: Real-time calculation of gas consumption per ton of steel (GJ / t) for each heating furnace.

3. The method for real-time optimization of unit consumption of a heating furnace under full operating conditions in oxygen-enriched conditions according to claim 1, characterized in that, The oxygen-enriched energy efficiency inflection point calorific value threshold (Q) mentioned in step 3 critical The setting range is 2500 kcal / m³. 3 Up to 2600Kcal / m 3 .

4. The method for real-time optimization of unit consumption of a heating furnace under full operating conditions in oxygen-enriched conditions according to claim 3, characterized in that, The oxygen-enriched energy efficiency inflection point calorific value threshold (Q) mentioned in step 3 critical ) is 2550 kcal / m 3 .

5. The method for real-time optimization of unit consumption of a heating furnace under full operating conditions in oxygen-enriched conditions according to claim 1, characterized in that, The component reconstruction operation in step 4 is as follows: The calorific value of the mixed gas at the inlet of each branch pipe of each precision control unit is monitored in real time; when the real-time calorific value of the gas in a certain heating furnace is lower than the preset oxygen-enriched energy efficiency inflection point calorific value threshold... At that time, the system triggers component reconfiguration control logic for that specific heater branch pipe; if multiple heaters trigger warnings simultaneously and the high-calorific-value gas source is limited, the system calculates according to step 2. The priority order of values ​​from high to low is executed as follows: automatically reduce the proportion of converter gas branch flow, and simultaneously increase the proportion of coke oven gas branch flow until the real-time calorific value at the furnace inlet returns to above the threshold, while simultaneously calculating the theoretical combustion oxygen demand after the gas is injected.

6. The method for real-time optimization of unit consumption of a heating furnace under full operating conditions in oxygen-enriched conditions according to claim 5, characterized in that, The component reconstruction logic in step 4 is executed as follows: (1) Coke oven gas setpoint control: Forcefully increase the instantaneous flow rate ratio of coke oven gas in the mixed gas and lock it in the high-efficiency range of 34%-36%; (2) Converter gas meltdown control: Set the upper limit of the instantaneous flow rate of converter gas. When the flow rate of converter gas exceeds the threshold, even if the total calorific value meets the standard, the system will force a reduction in the flow rate of converter gas to prevent the rigidity of the oxygen-enriched combustion flame from decreasing due to excessive inert gas.

7. The method for real-time optimization of unit consumption of a heating furnace under full operating conditions in oxygen-enriched conditions according to claim 6, characterized in that, The upper limit of the instantaneous flow rate of converter gas in step 4 (2) is 45%.

8. The method for real-time optimization of unit consumption of a heating furnace under full operating conditions in oxygen-enriched conditions according to claim 1, characterized in that, The operation of step 5, dual closed-loop dynamic afterburning, is as follows: When the amount of coke oven gas adjusted in step 4 reaches the physical upper limit, and the real-time calorific value of the gas is still lower than the calorific value threshold of the oxygen-enriched energy efficiency inflection point, the "oxygen-gas linkage" compensation mechanism is activated: (1) Natural gas fine-tuning loop: The natural gas regulating valve is automatically opened to inject natural gas in a pulse or linear manner, and the flow rate ratio is controlled at 3.0%~4.5% to quickly increase the real-time calorific value of the gas; (2) Oxygen-fuel ratio correction loop: The oxygen flow rate setting value is dynamically corrected based on the actual real-time calorific value of the coal gas after natural gas injection and the theoretical oxygen demand for combustion.

9. The method for real-time optimization of unit consumption of a heating furnace under full operating conditions in oxygen-enriched conditions according to claim 8, characterized in that, The correction logic for dynamically correcting the oxygen flow rate setpoint in step 5 (2) is as follows: ,in Total oxygen demand for theoretical combustion (unit: m³) 3 / h or Nm 3 / h), refers to the real-time pure oxygen flow rate required by the system to ensure complete combustion of the gas under the current gas composition; K is the oxygen enrichment compensation coefficient (dimensionless constant), used to characterize the ratio of actual oxygen supply to theoretical oxygen demand. In the normal steady-state stage, this value is usually set to 1.03-1.05; in the dynamic compensation stage triggered by the 'energy efficiency inflection point', the K value is stepped up to 1.05-1.10, utilizing the high temperature characteristics of super-oxygen-enriched combustion to eliminate the thermal lag caused by low calorific value. The aim is to improve the thermal intensity of the flue gas per unit volume through the super-oxygen-enriched environment and eliminate furnace temperature fluctuations. The instantaneous inlet flow rate of the i-th type of gas, in m³ / s. 3 / h, i corresponds to the real-time flow meter readings of coke oven gas (COG), blast furnace gas (BFG), converter gas (LDG), and supplementary combustion natural gas (NG), respectively; Let be the theoretical oxygen demand coefficient per unit volume of the i-th type of gas (dimensionless), which is determined by the stoichiometric ratio of the combustible components in the gas composition.