TRT unit gas-excitation linkage anti-tripping control method and system

Abstract

This invention discloses a gas-excitation linkage anti-shutdown control method and system for TRT units. Addressing the problem of demagnetization-induced shutdown in existing TRT units due to gas pressure fluctuations and delayed excitation regulation response, this invention employs a three-pronged technical solution integrating hardware buffering and pressure stabilization, data prediction and forecasting, and linkage control. Specifically, a nitrogen and steam dual-medium energy storage and pressure stabilization buffer tank is installed in the main gas pipe before the unit to absorb pressure shocks; an LSTM neural network dynamic prediction model is constructed based on blast furnace operating parameters to predict gas condition fluctuation trends 3-5 seconds in advance; a gas pressure-excitation current linkage control model is established to issue advance regulation commands to the excitation system 0.3-0.5 seconds before the fluctuation arrives, and a demagnetization protection linkage interlocking unit is set up to distinguish between regulation faults and actual demagnetization. This invention achieves gas condition prediction and advance coordinated regulation of the excitation system, eliminating timing asynchrony problems and effectively preventing demagnetization-induced shutdown of TRT units, ensuring continuous and stable operation of the blast furnace and power generation system.

Description

Technical Field

[0001] This invention relates to the field of power equipment control technology in energy and power engineering, and in particular to a gas-excitation linkage anti-shutdown control method and system for TRT units. Background Technology

[0002] Blast furnace gas pressure turbine generator (TRT) units are energy-saving devices that utilize the pressure and heat energy of the gas at the top of the blast furnace to drive a generator to generate electricity through turbine expansion. They are currently an important waste energy recovery and utilization device for steel enterprises.

[0003] Currently, TRT units face the following technical challenges: frequent fluctuations in blast furnace gas pressure and sudden changes in gas volume, coupled with a lack of synchronization and lag in the response of gas pressure and flow rate changes with the generator excitation system. When gas pressure drops or rises abruptly, the unit's active power changes dramatically. The excitation system's response lags behind the rate of active power fluctuation, leading to an imbalance in generator terminal voltage and reactive power. This can easily trigger the loss-of-excitation protection system, causing unplanned unit shutdowns, blast furnace gas venting, and power generation capacity losses, severely impacting the continuous and stable operation of both the blast furnace and power generation systems.

[0004] Upon on-site investigation, the causes of the above problems can be divided into two levels: First, the lack of hardware buffering means that the blast furnace gas pipeline network lacks pressure stabilization and energy storage facilities, and the instantaneous pressure impact on the pipeline network cannot be buffered; second, the isolated control logic means that the data of the blast furnace gas generation operation and the TRT excitation control system are disconnected and there is no prediction mechanism, so the excitation adjustment can only be passively and laggingly adjusted, and cannot adapt to the dynamic fluctuations of the gas.

[0005] There is currently no effective solution to the above problems in existing technologies. Therefore, there is an urgent need for a control method and system that can achieve predictive control of gas operating conditions and proactive coordinated regulation of the excitation system. Summary of the Invention

[0006] In view of this, the purpose of this invention is to provide a gas-excitation linkage anti-shutdown control method and system for TRT units, which realizes the prediction of gas operating conditions and the advanced coordinated adjustment of the excitation system, eliminates the problem of timing asynchrony, effectively prevents TRT units from losing excitation and tripping, and ensures the continuous and stable operation of the blast furnace and power generation system.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: a gas-excitation linkage anti-shutdown control method for TRT units, comprising the following steps: Data acquisition steps: Collect blast furnace operating parameters and TRT unit operating parameters. The blast furnace operating parameters include blast furnace feed rate, air volume, air pressure, pulverized coal injection rate and furnace top temperature. The TRT unit operating parameters include inlet gas pressure, gas flow rate, unit active power, terminal voltage, reactive power and excitation current. Operating condition prediction steps: Based on the collected blast furnace operating parameters, the dynamic prediction model of blast furnace gas is used to predict the instantaneous gas generation, pipeline pressure change trend and fluctuation amplitude in the next 3 to 5 seconds, and output a gas fluctuation early warning signal. Hardware buffering steps: Based on the fluctuation level corresponding to the gas fluctuation warning signal, control the energy storage and pressure stabilizing buffer tank set in the gas main pipe in front of the TRT unit to put into the corresponding level of buffering and pressure stabilizing operation, so as to control the gas pressure fluctuation amplitude in front of the unit within ±2kPa. Linkage adjustment steps: Based on the predicted trend of gas pressure and active power change, the target excitation current is calculated based on the gas pressure-excitation current linkage control model. 0.3 to 0.5 seconds before the gas pressure fluctuation arrives, the excitation adjustment command is sent to the excitation system to control the excitation system to perform advance adjustment. Steady-state feedback steps: Collect the unit's active power, terminal voltage, reactive power, and excitation parameters to perform closed-loop correction and maintain the unit's static stability.

[0008] In a preferred embodiment, the energy storage and pressure stabilizing buffer tank is a nitrogen and steam dual-medium energy storage and pressure stabilizing buffer tank; the buffering and pressure stabilizing operation includes: when the gas pressure rises instantaneously, the energy storage tank stores and absorbs pressure energy; when the gas pressure drops instantaneously, the nitrogen and / or steam energy storage unit releases energy to compensate for the pressure loss.

[0009] In a preferred embodiment, the dynamic prediction model for blast furnace gas is built based on the blast furnace production process mechanism and big data machine learning algorithms. Its input variables include blast furnace air volume, air pressure, material speed, pulverized coal injection volume, furnace top temperature and historical gas generation data. Its output variables include the instantaneous generation of blast furnace gas in the next 3 to 5 seconds, the trend of pipeline pressure change and the predicted value of fluctuation amplitude. The blast furnace gas dynamic prediction model is a time-series prediction model based on the blast furnace production process mechanism and an LSTM neural network. The LSTM neural network structure includes an input layer, a first LSTM layer, a Dropout layer, a second LSTM layer, a fully connected layer, and an output layer. The first LSTM layer contains 32-128 hidden units, the second LSTM layer contains 16-64 hidden units, the Dropout layer has a dropout ratio of 0.1-0.5, the fully connected layer contains 8-32 neurons using the ReLU activation function, and the output layer contains 3 neurons using a linear activation function. The model's time step size is 10-20 historical time steps, and the output frequency is 100ms. The model's training process involves extracting continuous operating data from the blast furnace DCS system over a considerable time span. Over a period of 3 months, outliers were removed using the 3σ criterion, and all input variables were Z-score standardized. The preprocessed dataset was then divided chronologically into a 70% training set, a 15% validation set, and a 15% test set. Mean squared error was used as the loss function, and the Adam optimization algorithm was employed for parameter optimization. The initial learning rate was 0.001, and the batch size was 32 or 64. Training was terminated early when the validation set loss no longer decreased within 20 consecutive training epochs. After model training, performance was evaluated on the test set using mean absolute percentage error (MASE) and root mean square error (RMSE). The acceptance criterion was an MSE ≤ 5%. After the model was deployed online, it was retrained periodically using newly added field data, with retraining occurring monthly or quarterly, or the model parameters were updated online using incremental learning.

[0010] In a preferred embodiment, the gas fluctuation warning signal includes three levels of fluctuation warning: slight fluctuation, moderate fluctuation, and severe fluctuation.

[0011] In a preferred embodiment, the buffer voltage regulation operation and the linkage adjustment step are executed in stages according to the fluctuation warning level: During slight fluctuations, the nitrogen unit in the energy storage tank independently stabilizes the pressure, and the excitation system maintains steady-state operation; During moderate fluctuations, the nitrogen in the energy storage tank continuously buffers and stabilizes the pressure, and the linkage model issues a micro-incremental excitation adjustment command, and the excitation system completes the fine adjustment within 100ms; During severe fluctuations, nitrogen and steam are used to release or store energy simultaneously. The linkage model issues large-scale excitation adjustment commands in advance, and the excitation system is quickly excited or de-excited.

[0012] In a preferred embodiment, the target excitation current is calculated according to the following dynamic correction formula: Ifd = Ifd0 + ΔIfd1 + ΔIfd2 Wherein, Ifd is the real-time target excitation current, Ifd0 is the current steady-state reference excitation current of the unit, ΔIfd1 is the gas pressure fluctuation correction amount dynamically calculated based on the real-time pressure deviation and pressure change rate, and ΔIfd2 is the predictive advance correction amount superimposed based on the future 3-second pressure and active power change trend of the gas prediction model.

[0013] In a preferred embodiment, during the linkage adjustment step, when the gas pressure sensor detects a pressure fluctuation rate greater than 10 kPa / s, the protection device sends a pre-magnetization command to the excitation system 0.3 to 0.5 seconds in advance.

[0014] This invention also provides a gas-excitation linkage anti-shutdown control system for TRT units, which includes the above-mentioned gas-excitation linkage anti-shutdown control method for TRT units, comprising: The data acquisition unit is used to collect blast furnace operating parameters and TRT unit operating parameters. The blast furnace operating parameters include blast furnace feed rate, air volume, air pressure, pulverized coal injection rate, and furnace top temperature. The TRT unit operating parameters include inlet gas pressure, gas flow rate, unit active power, terminal voltage, reactive power, and excitation current. The blast furnace gas dynamic prediction model unit predicts the instantaneous gas generation, pipeline pressure change trend and fluctuation amplitude in the next 3-5 seconds based on the collected blast furnace operating parameters, and outputs a gas fluctuation early warning signal. The energy storage and pressure stabilizing buffer tank is installed in the main gas pipe in front of the TRT unit. It is used to perform buffering and pressure stabilizing operations according to the fluctuation level corresponding to the gas fluctuation warning signal, and control the fluctuation amplitude of the gas pressure in front of the unit within ±2kPa. The gas pressure-excitation current linkage control model unit is used to calculate the target excitation current based on the predicted gas pressure and active power change trends, and to send an excitation adjustment command to the excitation system 0.3 to 0.5 seconds before the gas pressure fluctuation arrives. The closed-loop feedback correction unit is used to collect the unit's active power, terminal voltage, reactive power, and excitation parameters for closed-loop correction to maintain the unit's static stability.

[0015] In a preferred embodiment, the energy storage and pressure stabilizing buffer tank is a nitrogen and steam dual-medium energy storage and pressure stabilizing buffer tank, and the blast furnace gas dynamic prediction model unit is connected to the blast furnace control room DCS system for real-time data communication.

[0016] In a preferred embodiment, the system further includes a loss-of-excitation protection device linkage interlocking unit, which shares data with the excitation system and acquires dynamic curve data of excitation current and voltage in real time; when the gas pressure sensor detects a pressure fluctuation rate greater than 10 kPa / s, the loss-of-excitation protection device linkage interlocking unit sends a pre-magnetization command to the excitation system 0.3 to 0.5 seconds in advance to distinguish between regulation faults and actual loss of excitation.

[0017] Compared with the prior art, the present invention has the following beneficial effects: 1) Safety benefits: By predicting gas operating conditions and coordinating the excitation system in advance, the problem of demagnetization and tripping caused by gas pressure fluctuations and asynchronous excitation regulation is solved, unplanned unit shutdowns are eliminated, the risk of blast furnace gas venting and impact damage to unit equipment is eliminated, and the safety of system operation is improved.

[0018] 2) Economic benefits: Eliminating power generation losses during downtime significantly increases the annual effective operating time of the unit; reducing gas emission losses, equipment start-up and shutdown losses, and maintenance costs, resulting in increased annual energy-saving and efficiency benefits.

[0019] 3) Technological benefits: It enables coordinated linkage and pre-control of blast furnace conditions and TRT power generation system, breaks the bottleneck of independent operation of the two systems, and improves the automation and intelligent control level of the entire cogeneration system. Attached Figure Description

[0020] Figure 1 The diagram shows the control principle of the TRT gas-excitation linkage stabilization system according to a preferred embodiment of the present invention. Detailed Implementation

[0021] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0022] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0023] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations according to this application; as used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise; furthermore, it should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0024] This invention adopts a three-in-one transformation approach of hardware buffering and voltage regulation, data prediction and judgment, and linkage control, abandoning the traditional passive excitation adjustment mode and constructing a closed-loop control system of "pre-voltage buffering, dynamic prediction of operating conditions, and synchronous pre-adjustment of excitation".

[0025] Hardware aspect: A nitrogen + steam dual-medium energy storage and pressure stabilizing buffer tank is added to the main gas pipe in front of the TRT unit to absorb instantaneous pressure fluctuations in the pipeline network and stabilize the basic operating conditions of the unit's gas intake.

[0026] At the data level: Establish a real-time dynamic data sharing mechanism between the blast furnace control room and the TRT power generation control system to collect core parameters such as blast furnace material speed, air volume, air pressure, pulverized coal injection volume, and furnace top pressure; based on big data of blast furnace operation, build a dynamic prediction model for blast furnace gas generation and gas pressure to predict the trend of gas condition fluctuations 3-5 seconds in advance.

[0027] The interlocking logic of the loss-of-excitation protection device considers the correlation between dynamic processes (such as the rate of change of reactive power) or pressure fluctuations and excitation regulation, distinguishing between "regulation faults" and "true loss of excitation." It achieves "data sharing" between the protection device and the excitation system, acquiring data such as the dynamic curves of excitation current / voltage in real time. When the gas pressure sensor detects a fluctuation rate >10 kPa / s, the protection device sends a "pre-excitation command" to the excitation system (0.3-0.5 seconds in advance) to offset the risk of voltage drop and avoid false tripping due to "false loss of excitation" caused by transient pressure fluctuations.

[0028] Control level: A gas pressure-excitation current linkage control model is established. Based on the predicted trends of gas pressure and active power changes, excitation adjustment commands are issued in advance to achieve advance prediction of gas pressure fluctuations and gas volume changes and rapid synchronous adjustment of excitation current.

[0029] Specific principles: 1. Working principle of hardware (pressure stabilizing buffer tank): When the blast furnace gas pressure rises instantaneously, the energy storage tank quickly stores energy, absorbs excess pressure energy from the pipeline network, and suppresses pressure overshoot; when the gas pressure drops instantaneously, the nitrogen and steam energy storage units quickly release energy to compensate for pipeline pressure loss, control the gas pressure fluctuation amplitude within ±2kPa, reduce the sudden change amplitude of the unit's active power from the source, and reduce the excitation regulation load and regulation lag risk.

[0030] 2. Data sharing and gas prediction model: Based on data transmitted from the blast furnace, and grounded in the blast furnace production process mechanism and big data machine learning algorithms, a dynamic prediction model is built. Its core functions include: 1.) Input variables: blast furnace air volume, air pressure, material velocity, pulverized coal injection rate, furnace top temperature, and historical gas generation data; 2.) Output variables: instantaneous blast furnace gas generation in the next 3-5 seconds, pipeline pressure change trend, and predicted fluctuation amplitude; 3.) Early warning classification: It can accurately identify two types of operating conditions: small fluctuations and large sudden changes, and set three levels of fluctuation early warning (slight, moderate and severe), and match different excitation adjustment strategies accordingly.

[0031] 3. Gas-excitation linkage control model and logic 3.1 Core Principle of Linkage Control: Gas condition prediction → pressure buffer pre-compensation → excitation current pre-adjustment → real-time steady-state correction, to achieve excitation regulation ahead of or synchronized with gas power fluctuations, completely eliminate the problem of asynchronous regulation, maintain the static stability limit of the generator, and avoid demagnetization conditions.

[0032] Establish a dynamic correction formula for excitation current, based on multiple corrections including gas pressure deviation, pressure change rate, and active power prediction values: Ifd = Ifd0 + ΔIfd1 + ΔIfd2 Where: Ifd: real-time target excitation current; Ifd0: current steady-state reference excitation current of the unit; ΔIfd1: gas pressure fluctuation correction amount (dynamically calculated based on real-time pressure deviation and fluctuation rate before the unit); ΔIfd2: predictive advance correction amount (according to the pressure and active power change trends of the gas prediction model in the next 3 seconds).

[0033] 3.2 Hierarchical linkage control logic 1.) Slight fluctuations (pressure fluctuations ≤ ±2 kPa) The nitrogen unit of the energy storage tank is independently pressure-stabilized, the gas conditions are basically stable, the excitation system maintains steady-state operation, the model is monitored in real time and is on standby, without any significant adjustment actions.

[0034] 2.) Moderate fluctuations (pressure fluctuations ±2~5 kPa) (1) The nitrogen gas in the energy storage tank continuously buffers and stabilizes the pressure, suppressing the expansion and fluctuation of pressure; (2) The prediction model outputs a small fluctuation forecast value; (3) The linkage model issues a micro-incremental excitation adjustment command, and the excitation system completes the fine adjustment within 100ms to match the small change in active power and stabilize the generator terminal voltage and reactive power balance.

[0035] 3.) Severe fluctuations (pressure fluctuations > ±5 kPa, sudden changes in gas volume) (1) Nitrogen + steam dual-medium synchronous energy release / storage, strongly stabilizes pipeline pressure, and reduces impact amplitude; (2) The prediction model outputs a warning of large fluctuations 3 seconds in advance; (3) The linkage model issues excitation adjustment commands in advance, and the excitation system quickly strengthens / reduces excitation to offset the stability impact caused by sudden changes in active power in advance. 1.) Data acquisition phase: The blast furnace DCS and TRT field sensors collect furnace conditions, gas pressure and flow, and unit electrical parameters in real time, and synchronize them to the control system every 100ms; 2.) Operating condition prediction stage: The prediction model performs real-time calculations to predict the trend and amplitude of gas fluctuations and outputs early warning signals; 3.) Hardware buffering stage: Based on the fluctuation level, the energy storage tank is equipped with dual media for pressure stabilization, reducing pressure shocks at the source; 4.) Linkage Adjustment Stage: The linkage model calculates the optimal excitation current based on the predicted value and real-time operating conditions, and issues a rapid adjustment command; 5.) Steady-state feedback stage: Collect active power, voltage, reactive power, and excitation parameters of the unit, and adjust the parameters in a closed loop to maintain the static stability of the unit.

Claims

1. A TRT unit gas-field linkage anti-tripping control method, characterized in that, Includes the following steps: Data acquisition steps: Collect blast furnace operating parameters and TRT unit operating parameters. The blast furnace operating parameters include blast furnace feed rate, air volume, air pressure, pulverized coal injection rate and furnace top temperature. The TRT unit operating parameters include inlet gas pressure, gas flow rate, unit active power, terminal voltage, reactive power and excitation current. Operating condition prediction steps: Based on the collected blast furnace operating parameters, the dynamic prediction model of blast furnace gas is used to predict the instantaneous gas generation, pipeline pressure change trend and fluctuation amplitude in the next 3 to 5 seconds, and output a gas fluctuation early warning signal. Hardware buffering steps: Based on the fluctuation level corresponding to the gas fluctuation warning signal, control the energy storage and pressure stabilizing buffer tank set in the gas main pipe in front of the TRT unit to put into the corresponding level of buffering and pressure stabilizing operation, so as to control the gas pressure fluctuation amplitude in front of the unit within ±2kPa. Linkage adjustment steps: Based on the predicted trend of gas pressure and active power change, the target excitation current is calculated based on the gas pressure-excitation current linkage control model. 0.3 to 0.5 seconds before the gas pressure fluctuation arrives, the excitation adjustment command is sent to the excitation system to control the excitation system to perform advance adjustment. Steady-state feedback steps: Collect the unit's active power, terminal voltage, reactive power, and excitation parameters to perform closed-loop correction and maintain the unit's static stability.

2. The TRT unit gas-field linkage anti-tripping control method according to claim 1, characterized in that, The energy storage and pressure stabilizing buffer tank is a dual-medium energy storage and pressure stabilizing buffer tank of nitrogen and steam; the buffering and pressure stabilizing operation includes: when the gas pressure rises instantaneously, the energy storage tank stores and absorbs pressure energy; when the gas pressure drops instantaneously, the nitrogen and / or steam energy storage unit releases energy to compensate for the pressure loss.

3. The TRT unit gas-field linkage anti-tripping control method according to claim 1, characterized in that, The dynamic prediction model for blast furnace gas is built based on the blast furnace production process mechanism and big data machine learning algorithm. Its input variables include blast furnace air volume, air pressure, material speed, pulverized coal injection, furnace top temperature and historical gas generation data. The output variables include the instantaneous generation of blast furnace gas in the next 3 to 5 seconds, the trend of pipeline pressure change and the predicted value of fluctuation amplitude. The dynamic prediction model for blast furnace gas is a time-series prediction model based on the blast furnace production process mechanism and an LSTM neural network. The LSTM neural network structure includes an input layer, a first LSTM layer, a Dropout layer, a second LSTM layer, a fully connected layer, and an output layer. The first LSTM layer contains 32-128 hidden units, the second LSTM layer contains 16-64 hidden units, the Dropout layer has a dropout ratio of 0.1-0.5, the fully connected layer contains 8-32 neurons and uses the ReLU activation function, and the output layer contains 3 neurons and uses a linear activation function. The model's time step is... The model has 10-20 historical time steps and an output frequency of 100ms. The training process is as follows: extract continuous operation data from the blast furnace DCS system with a time span of no less than 3 months, use the 3σ criterion to remove outliers and perform Z-score standardization on all input variables, divide the preprocessed dataset into a training set of 70%, a validation set of 15%, and a test set of 15% in chronological order, use mean squared error as the loss function and Adam optimization algorithm to optimize parameters, with an initial learning rate of 0.001 and a batch size of 32 or 64. Training is terminated early when the validation set loss no longer decreases within 20 consecutive training cycles. After the model is trained, its performance is evaluated on the test set using mean absolute percentage error and root mean square error. The acceptance criterion is mean absolute percentage error ≤ 5%. After the model is deployed and launched, it is regularly retrained using newly added field operation data. The retraining cycle is monthly or quarterly, or the model parameters are updated online using incremental learning.

4. The TRT unit gas-field linkage anti-tripping control method according to claim 1, characterized in that, The gas fluctuation warning signal includes three levels of fluctuation warning: slight fluctuation, moderate fluctuation, and severe fluctuation.

5. The TRT unit gas-field linkage anti-tripping control method according to claim 4, characterized in that, The buffer voltage stabilization operation and the linkage adjustment steps are executed in stages according to the fluctuation warning level: During slight fluctuations, the nitrogen unit in the energy storage tank independently stabilizes the pressure, and the excitation system maintains steady-state operation; During moderate fluctuations, the nitrogen in the energy storage tank continuously buffers and stabilizes the pressure, and the linkage model issues a micro-incremental excitation adjustment command, and the excitation system completes the fine adjustment within 100ms; During severe fluctuations, nitrogen and steam are used to release or store energy simultaneously. The linkage model issues large-scale excitation adjustment commands in advance, and the excitation system is quickly excited or de-excited.

6. The TRT unit gas-field linkage anti-tripping control method according to claim 1, characterized in that, The target excitation current is calculated according to the following dynamic correction formula: Ifd = Ifd0 + ΔIfd1 + ΔIfd2 Wherein, Ifd is the real-time target excitation current, Ifd0 is the current steady-state reference excitation current of the unit, ΔIfd1 is the gas pressure fluctuation correction amount dynamically calculated based on the real-time pressure deviation and pressure change rate, and ΔIfd2 is the predictive advance correction amount superimposed based on the future 3-second pressure and active power change trend of the gas prediction model.

7. The gas-excitation linkage anti-shutdown control method for a TRT unit according to claim 1, characterized in that, In the linkage adjustment step, when the gas pressure sensor detects a pressure fluctuation rate greater than 10 kPa / s, the protection device sends a pre-magnetization command to the excitation system 0.3 to 0.5 seconds in advance.

8. A gas-excitation linkage anti-shutdown control system for a TRT unit, characterized in that, The method for preventing turbine tripping in a TRT unit using gas-excitation linkage as described in any one of claims 1-7 includes: The data acquisition unit is used to collect blast furnace operating parameters and TRT unit operating parameters. The blast furnace operating parameters include blast furnace feed rate, air volume, air pressure, pulverized coal injection rate, and furnace top temperature. The TRT unit operating parameters include inlet gas pressure, gas flow rate, unit active power, terminal voltage, reactive power, and excitation current. The blast furnace gas dynamic prediction model unit predicts the instantaneous gas generation, pipeline pressure change trend and fluctuation amplitude in the next 3-5 seconds based on the collected blast furnace operating parameters, and outputs a gas fluctuation early warning signal. The energy storage and pressure stabilizing buffer tank is installed in the main gas pipe in front of the TRT unit. It is used to perform buffering and pressure stabilizing operations according to the fluctuation level corresponding to the gas fluctuation warning signal, and control the fluctuation amplitude of the gas pressure in front of the unit within ±2kPa. The gas pressure-excitation current linkage control model unit is used to calculate the target excitation current based on the predicted gas pressure and active power change trends, and to send an excitation adjustment command to the excitation system 0.3 to 0.5 seconds before the gas pressure fluctuation arrives. The closed-loop feedback correction unit is used to collect the unit's active power, terminal voltage, reactive power, and excitation parameters for closed-loop correction to maintain the unit's static stability.

9. A gas-excitation linkage anti-shutdown control system for a TRT unit according to claim 8, characterized in that, The energy storage and pressure stabilizing buffer tank is a dual-medium energy storage and pressure stabilizing buffer tank using nitrogen and steam. The blast furnace gas dynamic prediction model unit is connected to the DCS system in the blast furnace control room for real-time data communication.

10. A gas-excitation linkage anti-shutdown control system for a TRT unit according to claim 8, characterized in that, The system also includes a loss-of-excitation protection device linkage interlocking unit, which shares data with the excitation system and acquires dynamic curve data of excitation current and voltage in real time. When the gas pressure sensor detects a pressure fluctuation rate greater than 10 kPa / s, the loss-of-excitation protection device linkage interlocking unit sends a pre-magnetization command to the excitation system 0.3 to 0.5 seconds in advance to distinguish between regulation faults and actual loss of excitation.

Images