Optimization control system and method for recycling latent heat of steam condensate through injection phase change

Abstract

The invention provides an optimal control system and method for recovering latent heat of steam condensate through injection phase change, and relates to the technical field of optimal control, and the system comprises a raw material parameter association module which is used for analyzing processing raw material data to obtain process dynamic parameters, and building an association relationship with steam condensate parameter data in combination with the heating demand of an evapo-separated machine. And the collaborative data integration module is used for integrating according to the injection pump control parameters and the corresponding relation between the pressure and the liquid level of the flash tank to obtain collaborative control data. And the steam quantity calculation module is used for analyzing the influence of the aging degree of the parts on the steam condensate parameter data to obtain a wear influence coefficient, and calculating the steam suction quantity in combination with the steam condensate parameter data. And the optimization scheme generation module is used for generating a control scheme according to the Wild-gull optimization algorithm in combination with the cooperative control data, the association relationship and the steam suction amount. According to the invention, the recovery efficiency and the utilization efficiency of steam condensate water are improved, and the energy consumption and the operation cost are reduced.

Description

Technical Field

[0001] This invention relates to the field of optimization control technology, and in particular to an optimized control system and method for recovering the latent heat of steam condensate by ejector phase change. Background Technology

[0002] In the recovery and utilization of latent heat from high-calorific-value steam condensate, traditional technologies such as indirect heat exchange and natural flash evaporation, despite continuous improvement and innovation in practice, still suffer from problems such as low thermal energy utilization and incomplete heat recovery.

[0003] High-calorific-value saturated condensate generated in indirect steam heating processes such as descaling, mixed oil evaporation, and mineral oil recovery is discharged into an atmospheric pressure condensate recovery tank, either directly or after simple subcooling heat exchange. This condensate may also contain some fresh steam mixed in by a failed steam trap, resulting in secondary flash evaporation in the condensate recovery tank. The flash steam carries a large amount of heat and escapes from the condensate recovery tank, causing a significant waste of thermal energy.

[0004] Core components in the system (such as jet pump nozzles, flash tank inner walls, steam traps, and throttle valves) will age during long-term operation due to media erosion, scaling, and seal wear. However, the existing system does not establish a logical correlation between the degree of component aging and steam condensate parameters, nor does it quantify the impact of aging on the calculation of the extracted steam volume. As the equipment's service life increases, the calculation deviation of the extracted steam volume gradually widens, leading to a disconnect between the control parameters of the jet pump and flash tank and actual needs. This results in problems such as insufficient energy supply or overpressure operation of heat-using equipment, seriously affecting the system's energy-saving effect and operational safety.

[0005] The operation of the ejector phase change recovery system involves the linkage of multi-dimensional data and multi-equipment parameters. From the perspective of raw materials, the moisture fluctuation of the raw materials will directly affect the heating requirements of the descaling machine, thereby changing the consumption of secondary steam. From the perspective of equipment, the pressure, flow rate, and temperature parameters of the ejector pump are strongly coupled with the pressure and liquid level parameters of the flash tank.

[0006] In summary, there is an urgent need for an optimized control system and method for recovering the latent heat of steam condensate by ejector phase change, in order to solve the above-mentioned technical defects and improve the system's latent heat recovery efficiency, operational stability and adaptability. Summary of the Invention

[0007] This invention provides an optimized control system and method for recovering the latent heat of steam condensate by ejector phase change, which solves the defects of the prior art that ignore the impact of component aging on the system and the lack of data integration and coordination.

[0008] On one hand, the present invention provides an optimized control system for recovering the latent heat of steam condensate by ejector phase change, comprising:

[0009] The raw material parameter association module is used to collect processing raw material data and steam condensate parameter data, analyze the processing raw material data to obtain process dynamic parameters, and establish a correlation between the heating requirements of the desiccant and the steam condensate parameter data.

[0010] The collaborative data integration module is used to obtain the jet pump control parameters by controlling the temperature based on the jet pump pressure and flow rate, and to integrate the collaborative control data by combining the corresponding relationship between the flash tank pressure and liquid level.

[0011] The steam volume calculation module is used to analyze the impact of component aging on steam condensate parameter data to obtain the wear influence coefficient, and calculate the amount of steam extracted in combination with the steam condensate parameter data.

[0012] The optimization scheme generation module is used to generate control schemes based on the tern optimization algorithm and in combination with collaborative control data, correlation relationships and the amount of extracted steam.

[0013] This invention provides an optimized control system for recovering the latent heat of steam condensate via ejector phase change. The steps of obtaining process dynamic parameters by the raw material parameter correlation module include:

[0014] Missing values ​​are filled in and noise is filtered from the raw material data, and the time granularity is unified to obtain preprocessed raw material data.

[0015] Real-time flow values ​​at preset time intervals are extracted from preprocessed raw material data to form continuous raw material flow data. Using a preset time as a sliding window, fluctuation amplitude, fluctuation efficiency, and load fluctuation coefficient are calculated as flow fluctuation characteristics.

[0016] By combining real-time monitoring values ​​from online sensors with offline detection calibration values, material solvent residue data at preset time intervals are obtained. Based on the total vapor pressure and vapor component analysis of the processing equipment, solvent vapor partial pressure and water vapor partial pressure are generated to form vapor phase partial pressure data.

[0017] This invention provides an optimized control system for recovering the latent heat of steam condensate via ejector phase change. The steps for establishing correlation relationships in the raw material parameter correlation module include:

[0018] Using process dynamic parameters as a reference, the rate of change of gas consumption between the steam degasser and the degasser is calculated under different dynamic fluctuation deviations of each batch of processed raw materials, thus forming a correspondence between dynamic parameters and gas consumption.

[0019] The effects of condensate production, pressure, and enthalpy on indirect gas consumption were correlated, and the influence of gas phase partial pressure and steam trap leakage on the condensate calorific value were combined to obtain the condensate heating effect.

[0020] Based on the dynamic parameter-gas consumption correspondence and the impact of condensate heating, a three-level progressive logic is decomposed to construct the correlation matrix of time-dynamic parameter-gas consumption-condensate parameter.

[0021] The correlation matrix is ​​corrected based on the residence time of the processed raw materials and the lag in steam pressure transmission to obtain the correlation relationship.

[0022] This invention provides an optimized control system for recovering the latent heat of steam condensate via ejector phase change, and the steps for obtaining ejector pump control parameters through a collaborative data integration module include:

[0023] The operating target of the jet pump is determined based on the target requirements, thereby clarifying the control target, and monitoring parameters of different ports are collected in real time.

[0024] Based on the current mixed steam pressure and the control target, determine the direction of pressure and flow regulation, and adjust the nozzle opening step by step to obtain the pressure and flow rate parameters that meet the requirements.

[0025] The actual superheat and deviation are calculated based on the pressure and flow rate compliance parameters and the thermal properties of steam, and the temperature compliance parameters are obtained by adjusting the desuperheating water flow rate to control the output temperature.

[0026] Based on the pressure, flow rate and temperature compliance parameters, the control parameters of the jet pump are determined to achieve the control target under different load fluctuations.

[0027] This invention provides an optimized control system for recovering the latent heat of steam condensate via ejector phase change. The steps of the collaborative data integration module to obtain collaborative control data include:

[0028] Real-time data from the jet pump and flash tank are collected synchronously, and parameter correspondence logic is established based on the initial data collection baseline.

[0029] Based on the influence of the jet pump control parameters on the flash tank pressure, the trend of flash tank pressure change is analyzed, and the pressure balance range is determined in combination with the pressure target.

[0030] By adjusting the drain valve of the flash tank to change the liquid level, the influence on the phase change efficiency of condensate and the amount of flash steam drawn into the jet pump is analyzed, and the feedback logic of the liquid level on the control parameters of the jet pump is obtained.

[0031] The safe liquid level range is determined based on the feedback logic and the stability requirements of the jet pump control parameters.

[0032] The valve correction state of the flash tank is determined based on the pressure balance range and the liquid level safety range, and the control target is monitored by monitoring whether the change in the injection pump input reaches the control target. If so, the coordinated control data is obtained.

[0033] This invention provides an optimized control system for recovering the latent heat of steam condensate via ejector phase change. The steps for the steam quantity calculation module to obtain the wear influence coefficient include:

[0034] By combining operating principles and on-site fault records, key aging components were screened, and the corresponding steam condensate parameter data were identified to construct the original dataset.

[0035] Quantitative indicators were set for the aging characteristics of different key aging components. Based on the original dataset, the corresponding parameter change rate was selected for each key aging component.

[0036] Based on the parameter change rate and quantitative indicators, the aging effect pattern is judged. Based on the significance of the impact of each key aging component on the steam condensate parameter data, the component weights are determined by the analytic hierarchy process.

[0037] Based on the aging effect law and combined with the component weights, the wear effect coefficients of each key aging component are obtained by fitting.

[0038] This invention provides an optimized control system for recovering the latent heat of steam condensate by ejector phase change. The steam quantity calculation module calculates the amount of extracted steam in the following steps:

[0039] The pressure correction, flash steam production correction, and suction efficiency correction are obtained from the wear effect coefficient.

[0040] The amount of steam extracted is calculated based on the pressure correction, flash steam production correction, and extraction efficiency correction, combined with steam condensate parameter data. The formula is as follows:

[0041] ;

[0042] In the formula, It refers to the amount of steam drawn in. It is the suction efficiency correction amount. This is the saturated hydrothermal value of the steam source after adjustment for pressure correction. This is the saturated hydrothermal value after adjustment for pressure correction. It is the latent heat of saturated steam. It indirectly uses the instantaneous flow rate of steam. This is a correction for flash steam production. This is the initial flash steam production.

[0043] This invention provides an optimized control system for recovering the latent heat of steam condensate via ejector phase change, wherein the optimization scheme generation module includes:

[0044] The constraint and population generation unit is used to determine the constraints from three aspects: hardware, security and response speed. It integrates the cooperative control data, correlation and the amount of extracted steam into a decision variable vector, and combines the Tent chaotic mapping to generate the initial population of black terns.

[0045] The Black Terns position update unit is used to perform collision avoidance and approach the current optimal individual position of the Black Terns, and combines spiral hunting to update the position to obtain multiple updated positions of the Black Terns.

[0046] The fitness value calculation unit is used to transform the decision variable vector into fitness values ​​in combination with the cooperative control objective, and to calculate the fitness value of each tern's updated position, and to take the individual with the smallest fitness value as the global optimal solution.

[0047] The control scheme selection unit is used to select the decision variable vector with the smallest fitness value from the global optimal solution generated in each iteration after the maximum number of iterations has been reached.

[0048] This invention provides an optimized control system for recovering the latent heat of steam condensate via ejector phase change. The steps for the tern position update unit to obtain multiple updated tern positions include:

[0049] Based on the current location of individual terns, avoid collisions between individual terns to generate new individual locations.

[0050] Calculate the relative distance between the current position of the black tern and the current optimal position, and guide the current black tern to move in the optimal direction.

[0051] The total displacement of the individual tern was calculated based on the relative spacing and the individual's new position.

[0052] The spiral flight simulation of the tern's attack on prey is used to generate a spiral update position based on the total displacement and the current best individual position.

[0053] The current individual position of the black tern is updated based on the total displacement and spiral update position to obtain multiple updated positions for the black tern.

[0054] On the other hand, the present invention provides an optimized control method for recovering the latent heat of steam condensate by ejector phase change, comprising:

[0055] Collect data on raw materials and steam condensate parameters, analyze the raw material data to obtain dynamic process parameters, and establish a correlation between the heating requirements of the desiccant and the steam condensate parameters.

[0056] The jet pump control parameters are obtained by controlling the temperature based on the jet pump pressure and flow rate, and then integrated with the correspondence between the flash tank pressure and liquid level to obtain coordinated control data.

[0057] The wear influence coefficient was obtained by analyzing the impact of component aging on steam condensate parameters, and the amount of steam extracted was calculated by combining the steam condensate parameters.

[0058] A control scheme is generated based on the tern optimization algorithm and combined with collaborative control data, correlation relationships, and the amount of extracted steam.

[0059] This invention provides an optimized control system and method for recovering the latent heat of steam condensate using an ejector phase change process. It effectively integrates multi-source data, including processing raw material data and steam condensate parameter data, and establishes collaborative control data, improving the system's collaborative control capabilities and enabling it to better handle complex industrial processes. By optimizing the collaborative control data, correlations, and steam extraction volume using the U-Tern optimization algorithm, a better control scheme is generated, improving the system's control accuracy and stability, and achieving better control performance under different operating conditions. By analyzing the aging degree of components and calculating the wear influence coefficient, the impact of component aging on the system is more accurately considered, allowing for timely maintenance measures and extending equipment lifespan. This improves the recovery and utilization efficiency of steam condensate, reduces energy consumption and operating costs, and enhances the overall operating efficiency and economy of the system. Attached Figure Description

[0060] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0061] Figure 1 This is one of the flowcharts of an optimized control system for recovering the latent heat of steam condensate by ejector phase change according to an embodiment of the present invention;

[0062] Figure 2 This is the second schematic diagram of an optimized control system for recovering the latent heat of steam condensate by ejector phase change according to an embodiment of the present invention.

[0063] Figure 3 This is the third flowchart of an optimized control system for recovering the latent heat of steam condensate from ejector phase change provided in this embodiment of the invention.

[0064] Figure 4 This is a schematic flowchart of an optimized control method for recovering the latent heat of steam condensate by ejector phase change according to an embodiment of the present invention. Detailed Implementation

[0065] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0066] The following is combined Figures 1-4 This invention describes an optimized control system and method for recovering the latent heat of steam condensate using an ejector phase change reactor.

[0067] like Figure 1 As shown in the figure, an optimized control system for recovering the latent heat of steam condensate by ejector phase change provided in this embodiment of the invention includes:

[0068] The raw material parameter association module is used to collect processing raw material data and steam condensate parameter data, analyze the processing raw material data to obtain process dynamic parameters, and establish a correlation between the heating requirements of the desiccant and the steam condensate parameter data.

[0069] Steam condensate parameters may include: condensate output (kg / h, corresponding to the output of indirect steam consumption), condensate calorific value (KJ / kg, reflecting the heat content), condensate pressure (MPa, affecting phase change flash evaporation efficiency), steam leakage from steam trap (%, a key factor in correcting calorific value), etc.

[0070] The steps by which the raw material parameter association module obtains process dynamic parameters include:

[0071] Raw material data can include basic attribute data of the raw materials: raw material batch, initial moisture content, density, and composition.

[0072] Real-time processing data: raw material conveying flow rate, operating parameters of processing equipment.

[0073] Material state data: Solvent residue detection values ​​of processed materials, pressure and composition of the gas phase space, etc.

[0074] Missing values ​​are filled in and noise is filtered from the raw material data, and the time granularity is unified to obtain preprocessed raw material data.

[0075] Real-time flow values ​​at preset time intervals are extracted from preprocessed raw material data to form continuous raw material flow data. Using a preset time as a sliding window, fluctuation amplitude, fluctuation efficiency, and load fluctuation coefficient are calculated as flow fluctuation characteristics.

[0076] By combining real-time monitoring values ​​from online sensors with offline detection calibration values, material solvent residue data at preset time intervals are obtained. Based on the total vapor pressure and vapor component analysis of the processing equipment, solvent vapor partial pressure and water vapor partial pressure are generated to form vapor phase partial pressure data.

[0077] The steps for establishing relationships in the raw material parameter association module include:

[0078] Using process dynamic parameters as a reference, the rate of change of gas consumption between the steam degasser and the degasser is calculated under different dynamic fluctuation deviations of each batch of processed raw materials, thus forming a correspondence between dynamic parameters and gas consumption.

[0079] The effects of condensate production, pressure, and enthalpy on indirect gas consumption were correlated, and the influence of gas phase partial pressure and steam trap leakage on the condensate calorific value were combined to obtain the condensate heating effect.

[0080] Based on the dynamic parameter-gas consumption correspondence and the impact of condensate heating, a three-level progressive logic is decomposed to construct the correlation matrix of time-dynamic parameter-gas consumption-condensate parameter.

[0081] First-level mapping (multi-process factors → heating demand): Calculate the real-time indirect steam consumption (the core indicator of heating demand) based on the fluctuation deviation of raw material moisture content.

[0082] Secondary mapping (heating demand → condensate production / pressure): Input real-time indirect steam consumption, output condensate production and condensate pressure.

[0083] Three-level mapping (heating demand → condensate calorific value): Input real-time indirect steam consumption, output condensate calorific value.

[0084] The correlation matrix is ​​corrected based on the residence time of the processed raw materials and the lag in steam pressure transmission to obtain the correlation relationship.

[0085] The collaborative data integration module is used to obtain the jet pump control parameters by controlling the temperature based on the jet pump pressure and flow rate, and to integrate the collaborative control data by combining the corresponding relationship between the flash tank pressure and liquid level.

[0086] like Figure 2 As shown, the steps by which the collaborative data integration module obtains the control parameters of the jet pump include:

[0087] The operating target of the jet pump is determined based on the target requirements, thereby clarifying the control target, and monitoring parameters of different ports are collected in real time.

[0088] Control objectives may include: the output steam superheat should be kept stable at 5~50℃ (to prevent the material in the desiccant from clumping due to the moisture content of the steam).

[0089] The output steam pressure needs to match the direct steam demand of the degasser, which is usually 0.3~0.8MPa.

[0090] The output steam flow rate needs to be matched with the real-time steam load of the steam dehydrogenator (e.g., a 4000TPD production line needs to maintain 12000~16000kg / h, and the basic load can be estimated by the feed rate of the steam dehydrogenator and the moisture content of the material).

[0091] Real-time monitoring parameters may include: Input: driving steam pressure (high-pressure steam pressure entering the jet pump), driving steam flow rate.

[0092] Intermediate end: Flash steam intake flow rate (the amount of flash steam entering the jet pump from the flash tank).

[0093] Output: Mixed steam pressure (jet pump outlet pressure), mixed steam temperature (outlet temperature), mixed steam flow rate.

[0094] Adjustment end: Laval nozzle opening of jet pump (adjusted by electric actuator), desuperheating water flow rate (adjusted by desuperheating water pipeline valve).

[0095] Based on the current mixed steam pressure and the control target, determine the direction of pressure and flow regulation, and adjust the nozzle opening step by step to obtain the pressure and flow rate parameters that meet the requirements.

[0096] The actual superheat and deviation are calculated based on the pressure and flow rate compliance parameters and the thermal properties of steam, and the temperature compliance parameters are obtained by adjusting the desuperheating water flow rate to control the output temperature.

[0097] Based on the pressure, flow rate and temperature compliance parameters, the control parameters of the jet pump are determined to achieve the control target under different load fluctuations.

[0098] The steps by which the collaborative data integration module obtains collaborative control data include:

[0099] Real-time data from the jet pump and flash tank are collected synchronously, and parameter correspondence logic is established based on the initial data collection baseline.

[0100] Real-time data for the flash tank: tank pressure (e.g., 0.015 MPa), tank level (e.g., 50% tank capacity), condensate inlet flow rate (e.g., 14500 kg / h, consistent with the steam consumption between the jet pump and the throttle valve), and throttle valve opening (e.g., 30%). The corresponding logic for these parameters may include: when the jet pump nozzle opening is 53.5% (flash steam intake flow rate 9800 kg / h), the flash tank pressure stabilizes at 0.015 MPa, and the level stabilizes at 50%. At this point, the condensate phase change is complete (flash rate 13.39%), with no flash steam escaping or insufficient suction.

[0101] Record the corresponding group of "ejector pump parameters - flash tank parameters" in this state as a benchmark template for subsequent integration.

[0102] Based on the influence of the jet pump control parameters on the flash tank pressure, the trend of flash tank pressure change is analyzed, and the pressure balance range is determined in combination with the pressure target.

[0103] By adjusting the drain valve of the flash tank to change the liquid level, the influence on the phase change efficiency of condensate and the amount of flash steam drawn into the jet pump is analyzed, and the feedback logic of the liquid level on the control parameters of the jet pump is obtained.

[0104] When the liquid level rises from 50% to 65% (drain valve partially closed): the residence time of condensate in the flash tank is extended, the phase change is more complete, the flash steam output increases from 9800 kg / h to 10000 kg / h, and the jet pump outlet flow rate increases from 14500 kg / h to 14700 kg / h (the desuperheating water flow rate needs to be finely adjusted to 2850 kg / h to maintain the temperature at 136℃).

[0105] When the liquid level drops from 50% to 35% (drain valve opens wider): the residence time of condensate in the flash tank is shortened, the phase change is insufficient, the flash steam output drops from 9800 kg / h to 9600 kg / h, and the jet pump outlet flow rate drops from 14500 kg / h to 14300 kg / h (the desuperheating water flow rate needs to be finely adjusted to 2750 kg / h to maintain the temperature at 136℃).

[0106] Summary of feedback patterns: For every 10% change in liquid level, the flash steam production changes by approximately 200 kg / h, corresponding to a change of 200 kg / h in the jet pump outlet flow rate. It is necessary to simultaneously fine-tune the desuperheating water flow rate by ±50 kg / h to maintain temperature stability.

[0107] Based on the stability requirements of the jet pump parameters, determine the safe range of the flash tank liquid level:

[0108] Liquid level ≤30%: Insufficient flash steam production, jet pump outlet flow fluctuation exceeding ±300 kg / h, affecting the stability of steam supply to the desiccant.

[0109] Liquid level ≥70%: Condensate is easily carried into the jet pump by flash steam, resulting in water carryover in the outlet steam (sudden temperature drop).

[0110] Determine the safe liquid level range: 30%~70%. Within this range, the flash steam production is stable, and the jet pump parameters can be finely adjusted to maintain compliance.

[0111] The safe liquid level range is determined based on the feedback logic and the stability requirements of the jet pump control parameters.

[0112] The valve correction state of the flash tank is determined based on the pressure balance range and the liquid level safety range, and the control target is monitored by monitoring whether the change in the injection pump input reaches the control target. If so, the coordinated control data is obtained.

[0113] The steam volume calculation module is used to analyze the impact of component aging on steam condensate parameter data to obtain the wear influence coefficient, and calculate the amount of steam extracted in combination with the steam condensate parameter data.

[0114] The steps for the steam quantity calculation module to obtain the wear influence coefficient include:

[0115] By combining operating principles and on-site fault records, key aging components were screened, and the corresponding steam condensate parameter data were identified to construct the original dataset.

[0116] Key aging components may include water valves: responsible for draining condensate and preventing fresh steam from leaking out. After aging, valve core wear and sealing failure are likely to occur, leading to increased steam leakage.

[0117] Laval nozzle for jet pump: controls the driving steam flow rate and flash steam suction volume. After aging, wear on the inner wall of the nozzle leads to an increase in the flow area and a decrease in suction efficiency.

[0118] The inner wall of the flash tank is prone to scaling due to long-term contact with condensate containing impurities. As it ages, the scale layer thickens, affecting the phase change efficiency of the condensate.

[0119] Throttling valve: Regulates the pressure of the flash tank. After aging, the valve seat wears down, causing internal leakage in the valve and reducing the accuracy of pressure control.

[0120] Steam trap → calorific value of condensate, condensate production (increased steam leakage will increase the calorific value of condensate, and may also cause condensate to carry steam, resulting in a slight increase in production).

[0121] Jet pump nozzle → flash steam production, condensate pressure (decreased suction efficiency leads to flash steam residue, resulting in increased condensate pressure).

[0122] Flash tank inner wall → condensate phase change rate (scale layer hinders heat transfer, reduces phase change rate, and reduces flash steam production).

[0123] Throttling valve → condensate pressure (internal leakage of the valve causes the flash tank pressure to run out of control, indirectly affecting the condensate discharge pressure).

[0124] Quantitative indicators are set for the aging characteristics of different key aging components. Based on the original dataset, the corresponding parameter change rate is selected for each key aging component, and the formula is expressed as follows:

[0125] ;

[0126] In the formula, It is the rate of change of the parameter. These are parameter values ​​after aging. These are the baseline parameter values.

[0127] Based on the parameter change rate and quantitative indicators, the aging effect pattern is judged. Based on the significance of the impact of each key aging component on the steam condensate parameter data, the component weights are determined by the analytic hierarchy process.

[0128] The effects of aging can include: Steam trap aging: For every 1% increase in steam leakage rate (20% increase in aging degree), the calorific value of condensate increases by about 0.64%, showing a linear positive correlation (increased steam leakage means fresh steam mixes into the condensate, increasing the calorific value).

[0129] Nozzle aging: For every 1% increase in flow area deviation rate (10% increase in aging degree), flash steam production decreases by approximately 0.625%, showing a linear negative correlation (increased flow area leads to reduced suction negative pressure and residual flash steam).

[0130] Flash tank aging: For every 0.1 mm increase in scale thickness (5% increase in aging degree), the phase change rate decreases by about 0.08%, showing a linear negative correlation (scale hinders heat transfer, resulting in insufficient phase change).

[0131] Throttling valve aging: For every 1% increase in internal leakage rate (33% increase in aging degree), the condensate pressure increases by about 0.01 MPa (pressure change rate 1.25%), showing a linear positive correlation (internal leakage leads to an increase in flash tank pressure, and the condensate discharge pressure increases synchronously).

[0132] Based on the aging effect law and combined with the component weights, the wear effect coefficients of each key aging component are obtained by fitting.

[0133] The influence coefficient of steam trap on the calorific value of condensate: Based on single-factor data, as the steam leakage rate increases from 1% (20% aging) to 5% (100% aging), the calorific value change rate increases from 0% to 2.56%. Therefore, K1 = 2.56% / (100% - 20%) = 0.032% / %; meaning: for every 1% increase in the aging degree of the steam trap, the calorific value of the condensate increases by 0.032%.

[0134] The influence coefficient K3 of the flash tank on the phase change rate: When the scale thickness increases from 0 mm (0% aging) to 1.5 mm (75% aging), the phase change rate decreases from 0% to -6.65% ((12.5-13.39) / 13.39×100%≈-6.65%), then K3=-6.65% / 75%≈-0.0887% / %; meaning: for every 1% increase in the aging degree of the flash tank, the phase change rate decreases by 0.0887%.

[0135] The influence coefficient K4 of the throttle valve on the condensate pressure: When the internal leakage rate increases from 1% (33% aging) to 3% (100% aging), and the pressure change rate increases from 0% to 6.25%, then K4 = 6.25% / (100% - 33%) ≈ 0.0933% / %; meaning: for every 1% increase in the aging degree of the throttle valve, the condensate pressure increases by 0.0933%.

[0136] The steam quantity calculation module calculates the amount of steam extracted.

[0137] The pressure correction, flash steam production correction, and suction efficiency correction are obtained from the wear effect coefficient.

[0138] The amount of steam extracted is calculated based on the pressure correction, flash steam production correction, and extraction efficiency correction, combined with steam condensate parameter data. The formula is as follows:

[0139] ;

[0140] In the formula, It refers to the amount of steam drawn in. It is the suction efficiency correction amount. This is the saturated hydrothermal value of the steam source after adjustment for pressure correction. This is the saturated hydrothermal value after adjustment for pressure correction. It is the latent heat of saturated steam. It indirectly uses the instantaneous flow rate of steam. This is a correction for flash steam production. This is the initial flash steam production.

[0141] The optimization scheme generation module is used to generate control schemes based on the tern optimization algorithm and in combination with collaborative control data, correlation relationships and the amount of extracted steam.

[0142] like Figure 3 As shown, the optimization scheme generation module includes:

[0143] The constraint and population generation unit is used to determine constraints from three aspects: hardware, security, and response speed. It integrates cooperative control data, correlations, and extracted steam volume into a decision variable vector, and combines it with Tent chaotic mapping to generate the initial population of black terns. The formula is expressed as:

[0144] ;

[0145] In the formula, It is a random number. It is the first The first individual tern The initial position of the dimension. It is an adjustable control parameter.

[0146] The Black Terns position update unit is used to perform collision avoidance and approach the current optimal individual position of the Black Terns, and combines spiral hunting to update the position to obtain multiple updated positions of the Black Terns.

[0147] The steps for the Black-eared Tern location update unit to obtain multiple updated locations of Black-eared Tern include:

[0148] Based on the current location of individual terns, a new location is generated to avoid collisions between individual terns. The formula is expressed as follows:

[0149] ;

[0150] ;

[0151] In the formula, It is a new position for the individual. This indicates the current location of an individual Black Terrier. It is a collision avoidance vector. It is a constant parameter. It is time. It represents the number of collision iterations.

[0152] Calculate the relative distance between the current position of the Black-eared Tern and the current optimal position, and guide the current Black-eared Tern to move in the optimal direction. The formula is expressed as:

[0153] ;

[0154] In the formula, It is a relative spacing. It is the clustering coefficient. It is the current optimal individual position.

[0155] The total displacement of an individual tern is calculated based on the relative spacing and the individual's new position, expressed by the following formula:

[0156] ;

[0157] In the formula, It is the total displacement.

[0158] The spiral flight simulation of the Black-winged Tern's attack on prey is used to generate a spiral update position based on the total displacement and the current best individual position. The formula is expressed as follows:

[0159] ;

[0160] In the formula, It is a spiral update position. It is a spiral coordinate system.

[0161] The formula for calculating the helical coordinates is expressed as follows:

[0162] ;

[0163] ;

[0164] ;

[0165] In the formula, It is the helix radius. It is the helix angle.

[0166] The current individual position of the black tern is updated based on the total displacement and spiral update position to obtain multiple updated positions for the black tern.

[0167] The fitness value calculation unit is used to transform the decision variable vector into fitness values ​​in combination with the cooperative control objective, and to calculate the fitness value of each tern's updated position, and to take the individual with the smallest fitness value as the global optimal solution.

[0168] The steps for transforming the decision variable vector into fitness values ​​by combining the cooperative control objective and constructing the fitness function may include: When dealing with a steam system, the fitness function is expressed as follows:

[0169] ;

[0170] In the formula, , , These are weighting coefficients. It's energy consumption. It is response time. It's a fluctuation in steam flow. It is the fitness value.

[0171] The control scheme selection unit is used to select the decision variable vector with the smallest fitness value from the global optimal solution generated in each iteration after the maximum number of iterations has been reached.

[0172] like Figure 3 As shown, based on the same general inventive concept, this invention also protects an optimized control method for recovering the latent heat of steam condensate by ejector phase change, the optimized control method comprising:

[0173] Collect data on raw materials and steam condensate parameters, analyze the raw material data to obtain dynamic process parameters, and establish a correlation between the heating requirements of the desiccant and the steam condensate parameters.

[0174] The jet pump control parameters are obtained by controlling the temperature based on the jet pump pressure and flow rate, and then integrated with the correspondence between the flash tank pressure and liquid level to obtain coordinated control data.

[0175] The wear influence coefficient was obtained by analyzing the impact of component aging on steam condensate parameters, and the amount of steam extracted was calculated by combining the steam condensate parameters.

[0176] A control scheme is generated based on the tern optimization algorithm and combined with collaborative control data, correlation relationships, and the amount of extracted steam.

[0177] This embodiment provides an optimized control system and method for recovering the latent heat of steam condensate from ejector phase change reactors. By constructing an association matrix through a raw material parameter association module, it achieves real-time matching between dynamic process parameters and system operation, improving heat recovery efficiency and avoiding heat waste caused by changes in raw material characteristics. Furthermore, by clearly defining the pressure balance range and liquid level safety range of the ejector pump and flash tank, it stabilizes the fluctuation range of equipment operating parameters, ensuring stable equipment operation. The wear influence coefficient is used to correct the amount of steam extracted, reducing control failures caused by aging and lowering maintenance costs. Combined with the initial population generation mechanism of the Tent chaotic mapping, the convergence speed of the ternary algorithm is improved, and the generated control scheme meets hardware, safety, and response speed constraints. This achieves energy saving and consumption reduction, and improves the adaptability of the equipment.

[0178] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0179] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An optimized control system for recovering the latent heat of steam condensate via ejector phase change, characterized in that, include: The raw material parameter association module is used to collect processing raw material data and steam condensate parameter data, analyze the processing raw material data to obtain process dynamic parameters, and establish an association relationship between the steam condensate parameter data and the heating requirements of the desiccant. The collaborative data integration module is used to obtain the jet pump control parameters by controlling the temperature based on the jet pump pressure and flow rate, and to integrate the collaborative control data by combining the corresponding relationship between the flash tank pressure and liquid level. The steam volume calculation module is used to analyze the impact of component aging on the steam condensate parameter data to obtain the wear influence coefficient, and calculate the amount of steam extracted in combination with the steam condensate parameter data; The optimization scheme generation module is used to generate a control scheme based on the tern optimization algorithm and in combination with the collaborative control data, the correlation relationship and the amount of extracted steam.

2. The optimized control system for recovering the latent heat of steam condensate by ejector phase change according to claim 1, characterized in that, The steps by which the raw material parameter association module obtains the process dynamic parameters include: The raw material data is filled with missing values, filtered for noise, and the time granularity is unified to obtain preprocessed raw material data. Real-time flow values ​​at preset time intervals are extracted from the preprocessed raw material data to form continuous raw material flow data. Using the preset time as a sliding window, the fluctuation amplitude, fluctuation efficiency, and load fluctuation coefficient are calculated as flow fluctuation characteristics. The material solvent residue data at the preset time interval is obtained by combining the real-time monitoring value of the online sensor with the offline detection calibration value. Based on the total gas phase pressure and gas phase component analysis of the processing equipment, the partial pressure of solvent vapor and water vapor are formed to generate gas phase partial pressure data.

3. The optimized control system for recovering the latent heat of steam condensate by ejector phase change according to claim 2, characterized in that, The steps for establishing the association relationship in the raw material parameter association module include: Using the process dynamic parameters as a reference, the rate of change of gas consumption between the steam degasser and the degasser is calculated under different dynamic fluctuation deviations of each batch of processed raw materials, thus forming a dynamic parameter-gas consumption correspondence. The effects of condensate production, pressure, and enthalpy on indirect gas consumption were correlated, and the influence of gas phase partial pressure and steam trap leakage on the calorific value of condensate were combined to obtain the effect of condensate heating. Based on the dynamic parameter-gas consumption correspondence and the impact of condensate heating, which are decomposed into a three-level progressive logic, a correlation matrix of time-dynamic parameter-gas consumption-condensate parameter is constructed. The correlation relationship is obtained by correcting the correlation matrix based on the residence time of the processed raw materials and the lag in steam pressure transmission.

4. The optimized control system for recovering the latent heat of steam condensate by ejector phase change according to claim 1, characterized in that, The steps by which the collaborative data integration module obtains the jet pump control parameters include: The operating target of the jet pump is determined based on the target requirements, thereby clarifying the control target, and monitoring parameters of different ports are collected in real time; Based on the current mixed steam pressure and the control target, determine the direction of pressure and flow rate adjustment, and adjust the nozzle opening step by step to obtain the pressure and flow rate target parameters; The actual superheat and deviation are calculated based on the pressure and flow rate compliance parameters and the thermal properties of steam, and the temperature compliance parameters are obtained by adjusting the desuperheating water flow rate to control the output temperature. Based on the pressure and flow rate compliance parameters and the temperature compliance parameters, the jet pump control parameters are determined to achieve the control target under different load fluctuations through debugging.

5. An optimized control system for recovering the latent heat of steam condensate by ejector phase change according to claim 4, characterized in that, The steps by which the collaborative data integration module obtains the collaborative control data include: Real-time data from the jet pump and flash tank are collected synchronously, and parameter correspondence logic is established based on the initial data collection baseline. Based on the influence of the jet pump control parameters on the flash tank pressure, the trend of flash tank pressure change is analyzed, and the pressure balance range is determined in combination with the pressure target. By adjusting the drain valve of the flash tank to change the liquid level, the influence on the phase change efficiency of condensate and the amount of flash vapor drawn into the jet pump is analyzed, and the feedback logic of the liquid level on the control parameters of the jet pump is obtained. The safe liquid level range is determined based on the feedback logic and the stability requirements of the jet pump control parameters; The corrected state of the flash tank valve is determined based on the pressure balance range and the liquid level safety range, and the change in the injection pump input is monitored to see if the control target is achieved. If so, the coordinated control data is obtained.

6. The optimized control system for recovering the latent heat of steam condensate by ejector phase change according to claim 1, characterized in that, The steps for the steam quantity calculation module to obtain the wear influence coefficient include: By combining operating principles and on-site fault records, key aging components were screened, and the corresponding steam condensate parameter data were identified to construct the original dataset; Quantitative indicators are set for the aging characteristics of different key aging components. Based on the original dataset, the corresponding parameter change rate is selected for each key aging component. Based on the parameter change rate and the quantitative index, the aging effect law is judged. Based on the significance of the influence of each key aging component on the steam condensate parameter data, the component weight is determined by the analytic hierarchy process. Based on the aging effect law and combined with the component weights, the wear effect coefficients of each key aging component are fitted.

7. An optimized control system for recovering the latent heat of steam condensate by ejector phase change according to claim 1, characterized in that, The steps for the steam quantity calculation module to calculate the extracted steam quantity include: The pressure correction, flash vapor production correction, and suction efficiency correction are obtained from the wear effect coefficient. The amount of steam extracted is calculated based on the pressure correction, the flash steam production correction, and the extraction efficiency correction, combined with the steam condensate parameter data. The formula is as follows: ； In the formula, It refers to the amount of steam drawn in. It is the suction efficiency correction amount. This is the saturated hydrothermal value of the steam source after adjustment for pressure correction. This is the saturated hydrothermal value after adjustment for pressure correction. It is the latent heat of saturated steam. It indirectly uses the instantaneous flow rate of steam. This is a correction for flash steam production. This is the initial flash steam production.

8. An optimized control system for recovering the latent heat of steam condensate by ejector phase change according to claim 1, characterized in that, The optimization scheme generation module includes: The constraint and population generation unit is used to determine the constraints from three aspects: hardware, security and response speed. It integrates the cooperative control data, the correlation relationship and the amount of extracted steam into a decision variable vector, and combines the Tent chaotic mapping to generate the initial population of black terns. The Black Terns position update unit is used to perform collision avoidance and approach the current optimal individual position of the Black Terns, and combines spiral hunting to update the position to obtain multiple updated positions of the Black Terns. The fitness value calculation unit is used to combine the cooperative control objective to transform the decision variable vector into fitness values, calculate the fitness value of each tern's updated position, and take the individual with the smallest fitness value as the global optimal solution. The control scheme selection unit is used to select the decision variable vector with the smallest fitness value from the global optimal solution generated in each iteration after the maximum number of iterations has been reached as the control scheme.

9. An optimized control system for recovering the latent heat of steam condensate by ejector phase change according to claim 8, characterized in that, The steps for the black tern location update unit to obtain multiple updated black tern locations include: Based on the current location of individual terns, avoid collisions between individual terns to generate new individual locations; Calculate the relative distance between the current position of the black tern and the current optimal position, and guide the current black tern to move in the optimal direction; Calculate the total displacement of the individual tern based on the relative spacing and the individual's new position; The spiral flight simulation of the tern's attack on prey is used to generate a spiral update position based on the total displacement and the current optimal individual position. Multiple updated positions of the terns are obtained by updating the current individual position of the tern based on the total displacement and the spiral update position.

10. An optimized control method for recovering the latent heat of steam condensate using an ejector phase change reactor, comprising an optimized control system for recovering the latent heat of steam condensate as described in any one of claims 1 to 9, characterized in that, The optimized control method includes: Collect raw material data and steam condensate parameter data, analyze the raw material data to obtain process dynamic parameters, and establish a correlation between the heating requirements of the desiccant and the steam condensate parameter data; The jet pump control parameters are obtained by controlling the temperature based on the jet pump pressure and flow rate, and then integrated with the correspondence between the flash tank pressure and liquid level to obtain coordinated control data. The wear influence coefficient is obtained by analyzing the impact of component aging on steam condensate parameters, and the amount of steam extracted is calculated by combining the steam condensate parameters. The optimization algorithm for black terns is combined with the collaborative control data, the correlation relationship, and the control scheme for the generation of extracted steam.

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