A multi-variable coupling control method and system for cryogenic air separation nitrogen production

Abstract

The present application relates to the technical field of cryogenic air separation, and discloses a kind of cryogenic air separation nitrogen production multivariable coupling control method and system.The application is by DCS control system and instrument installed on process pipeline real-time collection of the operating parameters of nitrogen production device, based on the parameters collected constructs multidimensional state vector, simultaneously carries out working condition identification to obtain current working condition type, based on working condition type determines the main control variable set and auxiliary control variable set, and then establishes multivariable coupling control model, to the model rolling optimization solution, output each control variable optimal adjustment, and then carries out multivariable linkage adjustment, reaches the effect of adjusting device.

Description

Technical Field

[0001] This invention relates to the field of cryogenic air separation technology, specifically to a multivariable coupling control method and system for cryogenic air separation and nitrogen production. Background Technology

[0002] Nitrogen from the air is widely used in petrochemicals, electronics manufacturing, metallurgy, coal chemicals, pharmaceuticals, and food preservation. With increasing demands from industrial production for nitrogen purity, stable yield, and low energy consumption, cryogenic air separation technology, with its advantage of large-scale continuous production of high-purity nitrogen (purity reaching over 99.999%), has become a crucial technology in industrial nitrogen production. The basic principle of cryogenic air separation nitrogen production is to liquefy compressed, purified, and cooled air, then separate oxygen and nitrogen in a distillation column based on their boiling point differences, thereby obtaining high-purity nitrogen. The equipment typically includes core components such as an air compressor, purifier, main heat exchanger, expander, condenser / evaporator, lower column, and upper column.

[0003] Currently, the control method for cryogenic air separation nitrogen generation units mainly adopts a distributed control system (DCS) for conventional PID single-loop regulation. Key control parameters include distillation column pressure, column liquid level, main heat exchanger temperature difference, expander operating conditions, and product nitrogen purity. Each control loop mostly operates independently, adjusting based on feedback from a single measured parameter. However, in actual production processes, due to factors such as fluctuations in raw material airflow, changes in ambient temperature, equipment scaling, load adjustments, and changes in user gas consumption, the existing control scheme suffers from the following technical shortcomings: First, the system suffers from severe multivariate coupling, making single-loop control difficult to coordinate. The cryogenic air separation nitrogen production system is a tightly coupled refrigeration-distillation complex. Intricate dynamic coupling relationships exist between distillation column pressure, reflux flow rate, cooling balance, and product purity. Adjusting the reflux valve to change the reflux ratio simultaneously affects the column temperature distribution, product purity, and column pressure. Adjusting the expander speed to change the cooling supply affects the rising vapor flow rate in the distillation column, thus altering the reflux ratio requirement. Traditional single-loop PID control independently adjusts only a single variable, lacking a coordination mechanism between loops. When one loop operates, it often disturbs another, resulting in poor control quality.

[0004] Secondly, energy consumption is high and cooling capacity utilization is low. Existing control systems typically set operating parameters based on experience, failing to dynamically optimize compressor load, expander conditions, and reflux ratio according to the real-time operating status of the unit. The cooling capacity provided by the expander directly affects the distillation process; insufficient cooling capacity prevents the establishment of distillation conditions, resulting in substandard product purity and yield; excessive cooling capacity leads to energy waste and may even cause deterioration of the distillation column's operating conditions. Traditional control methods struggle to identify surplus or shortage of cooling capacity in a timely manner and lack proactive means to adjust the cooling capacity balance, resulting in high energy consumption per unit of nitrogen production. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a multivariable coupled control method and system for cryogenic air separation nitrogen production. It has the advantages of achieving coordinated regulation of distillation and refrigeration systems by constructing a multivariable coupled state-space model and rolling optimization predictive control, thereby improving purity while reducing unit nitrogen production energy consumption and solving the aforementioned technical problems.

[0006] To achieve the above objectives, the present invention provides the following technical solution: S1: The operating parameters of the nitrogen generator are collected in real time through the DCS control system and instruments installed on the process pipeline; S2: Construct a multidimensional state vector based on the operating parameters. ; S3: Based on the multi-dimensional state vector, the current operating condition type is obtained by identifying the operating condition. The operating condition type includes low load condition, normal operating condition, high load condition, and abnormal operating condition. S4: Determine the set of dominant control variables based on the current operating condition. With the set of auxiliary control variables Establish a multivariable coupled control model; S5: The multivariable coupled control model is solved by rolling optimization using the model predictive control algorithm, and the optimal adjustment of each control variable is output. S6: Perform multivariate linkage adjustment based on the optimal adjustment amount.

[0007] As a preferred technical solution of the present invention, the operating parameters of S1 include inlet flow rate, inlet temperature, inlet pressure, lower tower pressure, upper tower pressure, reflux liquid flow rate, nitrogen product purity, nitrogen product flow rate, expander speed, air compressor power, hot end temperature difference of main heat exchanger, and cold end temperature difference of main heat exchanger.

[0008] As a preferred technical solution of the present invention, the S2 multidimensional state vector The expression is as follows: ; in, Represents a multidimensional state vector; Indicates the intake airflow; Indicates intake pressure; Indicates the intake air temperature; Indicates the pressure at the bottom of the tower; Indicates the pressure at the top of the tower; Indicates the reflux fluid flow rate; Indicates the purity of nitrogen products; Indicates the flow rate of nitrogen products; Indicates the expander speed; Indicates the air compressor power; This indicates the temperature difference at the hot end of the main heat exchanger; This indicates the temperature difference at the cold end of the main heat exchanger; This indicates transpose.

[0009] As a preferred embodiment of the present invention, the S3 step of identifying operating conditions includes the following steps: S3.1: Based on multidimensional state vectors Calculated load characteristic parameters ; S3.2: Based on load characteristic parameters The current operating condition type is obtained, specifically: when <Low load threshold When this is the case, it is determined to be a low-load operating condition. ≤ ≤High load threshold When this time, it is determined that the condition is normal. > At this time, the operating condition is determined to be a high-load condition, and the purity of the nitrogen product is... Minimum Permissible Purity When this condition is determined, it is considered an abnormal operating condition.

[0010] As a preferred technical solution of the present invention, the load characteristic parameters in step S3.1 The expression is as follows: ; in, Indicates load characteristic parameters; Indicates the flow rate of nitrogen products; Indicates the reflux fluid flow rate; Indicates the intake air temperature; Standard operating temperature; Indicates standard pressure; This indicates the intake pressure.

[0011] As a preferred technical solution of the present invention, the S4 dominant control variable set The S4 auxiliary control variable set includes the reflux valve opening, the upper tower pressure setpoint, and the expander speed setpoint. This includes the opening degree of the air compressor inlet guide vanes and the opening degree of the product valve.

[0012] As a preferred embodiment of the present invention, the expression of the S4 multivariable coupled control model is as follows: ; in, Represents the rate of change of state; Represents the state variables in a coupled control model; Indicates the dominant control variable; Indicates auxiliary control variables; , and These are the state matrix, control matrix, and coupling matrix, respectively. The expressions for the state variables in the coupled control model are as follows: ; in, Indicates the purity of the filtered nitrogen product; This indicates the pressure at the bottom of the tower after filtering. This indicates the pressure at the top of the tower after filtering. This indicates the temperature in the middle of the distillation column; Indicates the liquid level at the top of the column; This indicates transpose.

[0013] As a preferred technical solution of the present invention, the rolling optimization solution of the S5 multivariable coupled control model specifically involves: at the current moment... In the current state As initial conditions, in the prediction time domain Minimize the following objective function: ; in, Represents the objective function value; To predict the length of the time domain; To control the length of the time domain; To output the weight matrix; To control the incremental weight matrix; Indicates the current moment Based on the information, predictions are obtained through a multivariable coupled control model. Output value at time; Indicates in The ideal target value that we always hope to achieve; This represents the square of the weighted Euclidean norm; This represents the square of the weighted Euclidean norm; This represents the summation operation; This indicates a summation operation.

[0014] As a preferred technical solution of the present invention, the S6 multi-variable linkage regulation specifically includes: when a decrease in nitrogen purity is predicted, a combination of regulation actions is performed simultaneously, including increasing the opening of the reflux valve, decreasing the pressure in the upper tower, and increasing the speed of the expander; when a cooling imbalance is detected, a combination of regulation actions is performed simultaneously, including adjusting the opening of the air compressor inlet guide vane, adjusting the operating conditions of the expander, and adjusting the opening of the product valve.

[0015] This invention provides a multivariable coupled control system for cryogenic air separation and nitrogen production, comprising: Data acquisition unit: used to collect operating parameters of the cryogenic air separation nitrogen generator in real time; State identification unit: used to construct a multi-dimensional state vector based on the operating parameters and identify the current operating condition; Coupled modeling unit: used to establish a multivariable coupled control model based on the current operating condition type; Rolling optimization unit: used to perform rolling optimization on the multivariable coupled control model using model predictive control algorithm, and output the optimal adjustment of each control variable; Linkage execution unit: used to synchronously output multiple control commands according to the optimal adjustment amount, and to perform linkage adjustment on each actuator.

[0016] Compared with the prior art, the present invention provides a multivariable coupled control method and system for nitrogen production from cryogenic air separation, which has the following beneficial effects: 1. This invention constructs a multivariable coupled state-space model, incorporating actuators such as reflux valves, expanders, air compressor guide vanes, and product valves into a unified optimization framework. By using a coupling matrix to explicitly quantify the impact of auxiliary variable changes on the distillation state, the controller can comprehensively consider the interactions between various variables when making decisions. This fundamentally overcomes the shortcomings of traditional single-loop PID control, which ignores coupling relationships and causes mutual interference between loops and frequent system oscillations, thus significantly improving the stability of nitrogen product purity.

[0017] 2. This invention achieves fully automated closed-loop control of the entire process from parameter acquisition, working condition identification, model updating, optimization solution to linkage execution through the coordinated cooperation of data acquisition unit, state identification unit, coupled modeling unit, rolling optimization unit and linkage execution unit. This significantly reduces the workload of operators, reduces the risk of human error, and improves the automation level and operational safety of the device. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the process of the present invention; Figure 2 This is a schematic diagram of the system framework of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Please see Figure 1 A multivariable coupled control method for nitrogen production from cryogenic air separation includes the following steps: S1: The operating parameters of the nitrogen generator are collected in real time through the DCS control system and field instruments such as temperature sensors, pressure transmitters, flow meters, purity analyzers and speed sensors installed on the process pipeline; Operating parameters include inlet flow rate, inlet temperature, inlet pressure, lower tower pressure, upper tower pressure, reflux liquid flow rate, nitrogen product purity, nitrogen product flow rate, expander speed, air compressor power, hot end temperature difference of the main heat exchanger, and cold end temperature difference of the main heat exchanger. S2: Construct a multidimensional state vector based on operating parameters Its expression is as follows: ; in, Represents a multidimensional state vector; Indicates the intake airflow; Indicates intake pressure; Indicates the intake air temperature; Indicates the pressure at the bottom of the tower; Indicates the pressure at the top of the tower; Indicates the reflux fluid flow rate; Indicates the purity of nitrogen products; Indicates the flow rate of nitrogen products; Indicates the expander speed; Indicates the air compressor power; This indicates the temperature difference at the hot end of the main heat exchanger; This indicates the temperature difference at the cold end of the main heat exchanger; Indicates transpose; S3: Based on multi-dimensional state vectors, identify the current operating condition type to obtain the operating condition type, which includes low load condition, normal condition, high load condition, and abnormal condition. This includes the following steps: S3.1: Based on multidimensional state vectors Calculated load characteristic parameters Its expression is as follows: ; in, Indicates load characteristic parameters; Indicates the flow rate of nitrogen products; Indicates the reflux fluid flow rate; Indicates the intake air temperature; Standard operating temperature; Indicates standard pressure; Indicates intake pressure; This formula uses the ideal gas law as its theoretical basis, according to the law of state. Under the premise of constant mass flow rate, gas volumetric flow rate is directly proportional to thermodynamic temperature and inversely proportional to absolute pressure; based on this principle of physical properties, this invention introduces temperature correction factors. and stress correction factor The nitrogen product flow rate measured under actual operating conditions With reflux flow rate The ratio is converted to a unified standard state for comparison, thereby eliminating the interference of ambient temperature fluctuations and intake pressure changes on load judgment, and ensuring that the actual operating load level of the unit can be accurately identified under different seasons, different altitudes and different compression conditions. S3.2: Based on load characteristic parameters The current operating condition type is obtained, specifically: when <Low load threshold When this is the case, it is determined to be a low-load operating condition. ≤ ≤High load threshold When this time, it is determined that the condition is normal. > At this time, the operating condition is determined to be a high-load condition, and the purity of the nitrogen product is... Minimum Permissible Purity When this condition is determined, it is considered an abnormal operating condition. S4: Determine the set of dominant control variables based on the current operating condition. With the set of auxiliary control variables Establish a multivariable coupled control model and dominate the set of control variables. This includes the reflux valve opening, the upper tower pressure setpoint, and the expander speed setpoint; the S4 auxiliary control variable setpoint. The expression for the multivariable coupled control model, including the air compressor inlet guide vane opening and the product valve opening, is as follows: ; in, Represents the rate of change of state; Represents the state variables in a coupled control model; Indicates the dominant control variable; Indicates auxiliary control variables; , and These are the state matrix, control matrix, and coupling matrix, respectively. State variable matrix Used to characterize the thermal inertia and dynamic response characteristics of core equipment such as distillation columns and heat exchangers, reflecting the natural evolution of the system state without external control; control matrix Used to quantitatively characterize the impact of direct operational measures such as reflux valves, tower pressure regulation, and expander speed control on the system state; coupling matrix It is specifically used to quantify the disturbance transmission coefficient of the distillation operation when the auxiliary adjustment variables such as air compressor guide vanes and product valves change. Through the above model structure, the coupling effect of auxiliary variables is explicitly incorporated into the unified description framework of the system, so that the controller can consider the mutual influence of all variables at the same time when making optimization decisions, thereby realizing multi-variable collaborative control in essence, and fundamentally overcoming the technical problem of control failure caused by model mismatch in traditional decoupling schemes. The expressions for the state variables in the coupled control model are as follows: ; in, Indicates the purity of the filtered nitrogen product; This indicates the pressure at the bottom of the tower after filtering. This indicates the pressure at the top of the tower after filtering. This indicates the temperature in the middle of the distillation column; Indicates the liquid level at the top of the column; Indicates transpose; S5: The model predictive control algorithm is used to perform rolling optimization to solve the multivariable coupled control model and output the optimal adjustment of each control variable; The specific steps for solving the rolling optimization problem of a multivariable coupled control model are as follows: at the current time... In the current state As initial conditions, in the prediction time domain Minimize the following objective function: ; in, Represents the objective function value; To predict the length of the time domain; To control the length of the time domain; To output the weight matrix; To control the incremental weight matrix; Indicates the current moment Based on the information, predictions are obtained through a multivariable coupled control model. Output value at time; Indicates in The ideal target value that we always hope to achieve; This represents the square of the weighted Euclidean norm; This represents the square of the weighted Euclidean norm; This represents the summation operation; This represents the summation operation; The first term of the objective function Used to quantify the deviation between the predicted output and the ideal target over a future time domain, driving the controller to bring key indicators such as nitrogen purity and tower pressure as close as possible to the set values; the second item This is used to constrain the range of change in control actions, preventing system oscillations or damage to actuators due to over-adjustment; by adjusting the weight matrix. and The relative size can be flexibly balanced between high-precision tracking and smooth operation, achieving the optimal compromise under different working conditions; S6: Perform multi-variable linkage regulation based on the optimal adjustment amount. Specifically, when a decrease in nitrogen purity is predicted, simultaneously execute a combination of regulation actions such as increasing the opening of the reflux valve, decreasing the pressure in the upper tower, and increasing the speed of the expander; when an imbalance in cooling capacity is detected, simultaneously execute a combination of regulation actions such as adjusting the opening of the air compressor inlet guide vane, adjusting the operating conditions of the expander, and adjusting the opening of the product valve.

[0021] Please see Figure 2 The present invention also provides a multivariable coupled control system for cryogenic air separation nitrogen production, comprising: Data acquisition unit: used to collect operating parameters of the cryogenic air separation nitrogen generator in real time; State identification unit: used to construct a multi-dimensional state vector based on the operating parameters and identify the current operating condition; Coupled modeling unit: used to establish a multivariable coupled control model based on the current operating condition type; Rolling optimization unit: used to perform rolling optimization on the multivariable coupled control model using model predictive control algorithm, and output the optimal adjustment of each control variable; Linkage execution unit: used to synchronously output multiple control commands according to the optimal adjustment amount, and to perform linkage adjustment on each actuator.

[0022] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A multivariable coupled control method for nitrogen production from cryogenic air separation, characterized in that: Includes the following steps: S1: Real-time acquisition of nitrogen generator operating parameters through DCS control system and instruments installed on process pipelines; S2: Construct a multidimensional state vector based on the operating parameters. ; S3: Based on the multi-dimensional state vector, the current operating condition type is obtained by identifying the operating condition. The operating condition type includes low load condition, normal operating condition, high load condition, and abnormal operating condition. S4: Determine the set of dominant control variables based on the current operating condition. With the set of auxiliary control variables Establish a multivariable coupled control model; S5: The multivariable coupled control model is solved by rolling optimization using the model predictive control algorithm, and the optimal adjustment of each control variable is output. S6: Perform multivariate linkage adjustment based on the optimal adjustment amount.

2. The multivariable coupling control method for nitrogen production from cryogenic air separation according to claim 1, characterized in that: The S1 operating parameters include inlet flow rate, inlet temperature, inlet pressure, lower tower pressure, upper tower pressure, reflux liquid flow rate, nitrogen product purity, nitrogen product flow rate, expander speed, air compressor power, hot end temperature difference of the main heat exchanger, and cold end temperature difference of the main heat exchanger.

3. The multivariable coupling control method for nitrogen production from cryogenic air separation according to claim 2, characterized in that: The S2 multidimensional state vector The expression is as follows: ； in, Represents a multidimensional state vector; Indicates the intake airflow; Indicates intake pressure; Indicates the intake air temperature; Indicates the pressure at the bottom of the tower; Indicates the pressure at the top of the tower; Indicates the reflux fluid flow rate; Indicates the purity of nitrogen products; Indicates the flow rate of nitrogen products; Indicates the expander speed; Indicates the air compressor power; This indicates the temperature difference at the hot end of the main heat exchanger; This indicates the temperature difference at the cold end of the main heat exchanger; This indicates transpose.

4. The multivariable coupling control method for nitrogen production from cryogenic air separation according to claim 3, characterized in that: The S3 performs operational condition identification, including the following steps: S3.1: Based on multidimensional state vectors Calculated load characteristic parameters ; S3.2: Based on load characteristic parameters The current operating condition type is obtained, specifically: when <Low load threshold When this is the case, it is determined to be a low-load operating condition. ≤ ≤High load threshold When this time, it is determined that the condition is normal. > At this time, the operating condition is determined to be a high-load condition, and the purity of the nitrogen product is... Minimum Permissible Purity When this condition is determined, it is considered an abnormal operating condition.

5. The multivariable coupling control method for nitrogen production from cryogenic air separation according to claim 4, characterized in that: The load characteristic parameters in step S3.1 The expression is as follows: ； in, Indicates load characteristic parameters; Indicates the flow rate of nitrogen products; Indicates the reflux fluid flow rate; Indicates the intake air temperature; Standard operating temperature; Indicates standard pressure; This indicates the intake pressure.

6. The multivariable coupling control method for cryogenic air separation nitrogen production according to claim 3, characterized in that: The S4 dominant control variable set The S4 auxiliary control variable set includes the reflux valve opening, the upper tower pressure setpoint, and the expander speed setpoint. This includes the opening degree of the air compressor inlet guide vanes and the opening degree of the product valve.

7. The multivariable coupling control method for cryogenic air separation nitrogen production according to claim 6, characterized in that: The expression for the S4 multivariable coupled control model is as follows: ； in, Represents the rate of change of state; Represents the state variables in a coupled control model; Indicates the dominant control variable; Indicates auxiliary control variables; , and These are the state matrix, control matrix, and coupling matrix, respectively. The expressions for the state variables in the coupled control model are as follows: ； in, Indicates the purity of the filtered nitrogen product; This indicates the pressure at the bottom of the tower after filtering. This indicates the pressure at the top of the tower after filtering; This indicates the temperature in the middle of the distillation column; Indicates the liquid level at the top of the column; This indicates transpose.

8. The multivariable coupling control method for nitrogen production from cryogenic air separation according to claim 7, characterized in that: The rolling optimization solution of the S5 multivariable coupled control model is specifically as follows: at the current time... In the current state As initial conditions, in the prediction time domain Minimize the following objective function: ； in, Represents the objective function value; To predict the length of the time domain; To control the length of the time domain; To output the weight matrix; To control the incremental weight matrix; Indicates the current moment Based on the information, predictions are obtained through a multivariable coupled control model. Output value at time; Indicates in The ideal target value that we always hope to achieve; This represents the square of the weighted Euclidean norm; This represents the square of the weighted Euclidean norm; This represents the summation operation; This indicates a summation operation.

9. The multivariable coupling control method for nitrogen production from cryogenic air separation according to claim 8, characterized in that: The S6 multivariable linkage regulation specifically refers to the following: when a decrease in nitrogen purity is predicted, a combination of regulation actions is performed simultaneously, including increasing the opening of the reflux valve, decreasing the pressure in the upper tower, and increasing the speed of the expander; when a cooling imbalance is detected, a combination of regulation actions is performed simultaneously, including adjusting the opening of the air compressor inlet guide vane, adjusting the operating conditions of the expander, and adjusting the opening of the product valve.

10. A multivariable coupled control system for cryogenic air separation nitrogen production, comprising: Data acquisition unit: used to collect operating parameters of the cryogenic air separation nitrogen generator in real time; State identification unit: used to construct a multi-dimensional state vector based on the operating parameters and identify the current operating condition; Coupled modeling unit: used to establish a multivariable coupled control model based on the current operating condition type; Rolling optimization unit: used to perform rolling optimization on the multivariable coupled control model using model predictive control algorithm, and output the optimal adjustment of each control variable; Linkage execution unit: used to synchronously output multiple control commands according to the optimal adjustment amount to perform linkage adjustment on each actuator.

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