A method for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation

Abstract

The present invention provides a method for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation, which relates to the technical field of outlet density estimation. By constructing a dynamic mechanism model of a five-effect and five-flash countercurrent evaporation process, including material balance equations, heat balance equations and steam temperature calculation equations for evaporation units and flash units; selecting input variables, based on an intelligent optimization algorithm, and combining the variable dependence constraints of adjacent time points, solving the unknown variables in the dynamic mechanism model; using the solution results of the previous moment to constrain the value range of variables at the current moment, realizing continuous and smooth estimation of the outlet density. It effectively reduces the errors caused by mutation data or outliers, thereby making the density estimation of the whole process more accurate and reasonable.

Description

Technical Field

[0001] The present application relates to the technical field of outlet density estimation, and particularly to a method for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation. Background Art

[0002] In the evaporation process, a solution containing non-volatile solutes is heated to boiling by an external heat source, so that a part of the volatile solvent is vaporized, thereby realizing the concentration of the solution. This process is widely used in many industrial fields such as non-ferrous metallurgy, chemical industry, papermaking, food processing, and environmental protection. As an important index to measure the quality of the evaporation process, the outlet density directly reflects the degree of solution concentration and the evaporation effect. Real-time estimation of the outlet density is the core of evaporation process control and optimization, which can provide key support for accurately adjusting the evaporation rate, improving energy efficiency, and ensuring the quality of the final product. The traditional methods for estimating the outlet density of a multi-effect countercurrent evaporation process usually solve based on static models or independent time points, ignoring the dynamic correlation between variables at adjacent time points, resulting in the estimation results being easily affected by noise, with large errors and insufficient stability. In addition, the highly non-linear and multi-variable coupling characteristics of the evaporation process make the traditional solution methods inefficient and difficult to meet the requirements of real-time control.

[0003] Therefore, how to accurately monitor and control the outlet density has become a technical problem to be solved urgently. Summary of the Invention

[0004] The core of the present invention lies in providing a method for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation, which solves the problem of how to accurately monitor and control the outlet density.

[0005] In a first aspect, a method for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation provided by the present application adopts the following technical solutions:

[0006] A method for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation includes:

[0007] Construct a dynamic mechanism model of a five-effect five-flash countercurrent evaporation process, including material balance equations, heat balance equations, and steam temperature calculation equations for evaporation units and flash units;

[0008] Select input variables, and based on an intelligent optimization algorithm, combined with the variable dependence constraints at adjacent time points, solve the unknown variables in the dynamic mechanism model;

[0009] Use the solution results of the previous moment to constrain the value range of variables at the current moment to achieve continuous and smooth estimation of the outlet density.

[0010] Optionally, in the dynamic mechanism model, the volume change equations of the i-th effect evaporation unit and the j-th stage flash unit are respectively:

[0011]

[0012] Among them, represents the change in the liquid volume in the i-th effect evaporation unit; represents the change in the liquid volume in the j-th stage flash evaporation unit; and respectively represent the inlet feed flow rate and the outlet feed flow rate of the i-th effect evaporation unit; and respectively represent the inlet feed flow rate and the outlet feed flow rate of the j-th stage flash evaporation unit; represents the outlet secondary steam flow rate of the i-th effect evaporation unit; represents the outlet secondary steam flow rate of the j-th stage flash evaporation unit; is the density of water

[0013] Optionally, in the dynamic mechanism model, the material balance equations of the i-th effect evaporation unit and the j-th stage flash evaporation unit are respectively:

[0014]

[0015] Among them, and respectively represent the inlet feed density and the outlet feed density of the i-th effect evaporation unit, and respectively represent the inlet feed density and the outlet feed density of the j-th stage flash evaporation unit

[0016] Optionally, in the dynamic mechanism model, the heat balance equations of the i-th effect evaporation unit and the j-th stage flash evaporation unit are respectively:

[0017]

[0018] Among them, and respectively represent the inlet feed temperature and the outlet feed temperature of the i-th effect evaporation unit; and respectively represent the inlet feed temperature and the outlet feed temperature of the j-th stage flash evaporation unit; is the temperature of the condensed water; is the inlet secondary steam flow rate of the i-th effect evaporation unit; and respectively represent the latent heat of the inlet secondary steam of the i-th effect evaporation unit and the latent heat of the j-th stage flash steam; and respectively represent the specific heat of the inlet feed and the outlet feed of the i-th effect evaporation unit; and respectively represent the specific heat of the feed liquid input and the output liquid of the j-th stage evaporation unit; is the specific heat of water.

[0019] Optionally, the calculation equations for the temperature of secondary steam and flash steam in the dynamic mechanism model are:

[0020]

[0021] where represents the latent heat of vaporization of water, and R represents the gas constant; and are respectively the temperatures of the secondary steam at the inlet and outlet of the i-th effect evaporation unit; and are respectively the temperatures of the flash steam at the (j - 1)-th stage and the j-th stage; and are respectively the pressures of the secondary steam at the inlet and outlet of the i-th effect evaporation unit; and are respectively the pressures of the flash steam at the (j - 1)-th stage and the j-th stage.

[0022] Optionally, the input variables include the feed liquid flow rates at all levels, the inlet feed liquid density, the inlet feed liquid temperature, the inlet fresh steam temperature, and the inlet fresh steam flow rate.

[0023] Optionally, the intelligent optimization algorithm includes one or a combination of genetic algorithm, particle swarm algorithm, or simulated annealing algorithm.

[0024] Optionally, the variable dependence constraint at adjacent time points is specifically: the value range of the variable at the current moment is dynamically adjusted based on the solution result at the previous moment, restricting the fluctuation amplitude of the variable values at adjacent moments.

[0025] In a second aspect, the present application provides a computer device, which includes: a memory, a processor, and when the processor runs the computer instructions stored in the memory, it executes the method as described above.

[0026] In a third aspect, the present application provides a computer-readable storage medium, including instructions, and when the instructions run on a computer, it causes the computer to execute the method as described above.

[0027] In summary, the present application includes the following beneficial technical effects:

[0028] In this application, a dynamic mechanism model of a five-effect and five-flash countercurrent evaporation process is constructed, including material balance equations, heat balance equations, and steam temperature calculation equations for the evaporation unit and the flash evaporation unit; input variables are selected, and based on an intelligent optimization algorithm, combined with variable dependence constraints at adjacent time points, the unknown variables in the dynamic mechanism model are solved; the solution results at the previous moment are used to constrain the value range of variables at the current moment, so as to achieve continuous and smooth estimation of the outlet density. The error caused by mutation data or outliers is effectively reduced, making the density estimation of the entire process more accurate and reasonable. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 is a schematic structural diagram of a computer device in the hardware operating environment related to the solution of the embodiment of this application.

[0030] Figure 2 is a schematic flowchart of the first embodiment of the method for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation in this application.

[0031] Figure 3 is a diagram of a five-effect and five-flash countercurrent evaporation process in the first embodiment of the method for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation in this application.

[0032] Figure 4 is a schematic diagram of the evaporation unit and the flash evaporation unit models in the five-effect and five-flash alumina evaporation process of this application, Figure 4 (a) is the i-th effect evaporation unit, Figure 4 (b) is the j-th stage flash evaporator.

[0033] Figure 5 is a conceptual diagram of the optimization idea of the method for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation in this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0034] In order to make the purpose, technical solutions, and advantages of this application clearer, the following further details this application through the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not used to limit this application.

[0035] Refer to Figure 1 , Figure 1 is a schematic structural diagram of a computer device in the hardware operating environment related to the solution of the embodiment of this application.

[0036] Such as Figure 1As shown in the figure, a computer device may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to implement connection communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard). Optionally, the user interface 1003 may further include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a Wireless-Fidelity (Wi-Fi) interface). The memory 1005 may be a high-speed Random Access Memory (RAM), or a stable Non-Volatile Memory (NVM), such as a disk memory. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0037] Those skilled in the art can understand that Figure 1 the structure shown in does not constitute a limitation on the computer device, and it may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0038] As Figure 1 shown, in the memory 1005 as a storage medium, there may be included an operating system, a network communication module, a user interface module, and a multi-effect countercurrent evaporation process outlet density estimation program considering time correlation.

[0039] In Figure 1 the computer device shown, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; in the present application, the processor 1001 and the memory 1005 may be disposed in the computer device. The computer device calls the multi-effect countercurrent evaporation process outlet density estimation program stored in the memory 1005 through the processor 1001, and executes the multi-effect countercurrent evaporation process outlet density estimation method provided in the embodiments of the present application.

[0040] The embodiments of the present application provide a multi-effect countercurrent evaporation process outlet density estimation method considering time correlation. Referring to Figure 2 , Figure 2 is a schematic flowchart of the first embodiment of the multi-effect countercurrent evaporation process outlet density estimation method considering time correlation in the present application.

[0041] In this embodiment, the method for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation includes the following steps:

[0042] Step S10: Construct a dynamic mechanism model of a five-effect and five-flash countercurrent evaporation process, including material balance equations, heat balance equations, and steam temperature calculation equations for the evaporation unit and the flash evaporation unit.

[0043] It should be noted that Figure 3 shows a schematic diagram of a five-effect and five-flash countercurrent evaporation process, which consists of 5 tubular falling film evaporators and 5 flash evaporators. In the five-effect evaporation cascade section, the external heat source can be fresh steam or secondary steam from the outlet of the previous effect. After absorbing heat, the feed liquid vaporizes and boils, and the concentrated feed liquid is sent to the previous effect for further concentration. The generated water vapor, as secondary steam, is passed to the next effect as a heat source. In the five-stage flash evaporation cascade section, the flash steam at each stage is depressurized through a throttle valve, reducing the boiling point of the feed liquid. The superheated feed liquid quickly vaporizes and cools down, thus achieving concentration. The concentrated feed liquid continues to flow to the next-stage flash evaporator, and the vaporized steam (i.e., flash steam) is sent to the corresponding evaporator as a heat source. Through this process configuration, efficient utilization of thermal energy and recycling of resources are achieved.

[0044] For the feed liquid, the original evaporation liquid enters from the 5-effect evaporator and flows through the 4-effect, 3-effect, 2-effect, 1-effect, 1-flash, 2-flash, 3-flash, 4-flash in sequence, and finally discharges from the 5-flash. In the multi-effect evaporation cascade section, both the density and temperature of the feed liquid continuously increase along the flow direction of the feed liquid; while in the multi-stage flash evaporation cascade section, the density of the feed liquid increases along the flow direction of the feed liquid, and the temperature of the feed liquid continuously decreases. For the steam, the fresh steam enters from the 1-effect, and the secondary steam generated by the 1-effect serves as the heat source for the 2-effect. The secondary steam generated by the 2-effect and the flash steam generated by the 1-flash serve as the heat source for the 3-effect. The secondary steam generated by the 3-effect and the flash steam generated by the 2-flash serve as the heat source for the 4-effect. The secondary steam generated by the 4-effect and the flash steam generated by the 3-flash serve as the heat source for the 5-effect. Along the flow direction of the steam, the temperature of the steam gradually decreases, and the heat carried continuously decreases.

[0045] It can be understood that, as Figure 4 shown in the schematic diagram of the evaporation unit and flash evaporation unit models in the five-effect and five-flash alumina evaporation process, where Figure 4 (a) is the i-th effect evaporation unit, Figure 4 (b) is the j-th stage flash evaporator, and the dynamic mechanism models of the i-th effect evaporation unit and the j-th stage flash evaporation unit are obtained through heat balance.

[0046] It should be noted that for the th effect evaporation unit: the volume change is the input flow rate - output flow rate - volume change brought by the secondary steam. In the dynamic mechanism model, the volume change equations of the i-th effect evaporation unit and the j-th stage flash evaporation unit are respectively:

[0047]

[0048] Among them, represents the change in the liquid volume in the i-th effect evaporation unit; represents the change in the liquid volume in the j-th stage flash evaporation unit; and respectively represent the inlet feed flow rate and the outlet feed flow rate of the i-th effect evaporation unit; and respectively represent the inlet feed flow rate and the outlet feed flow rate of the j-th stage flash evaporation unit; represents the secondary steam flow rate at the outlet of the i-th effect evaporation unit; represents the secondary steam flow rate at the outlet of the j-th stage flash evaporation unit; is the density of water.

[0049] It should be noted that according to the material conservation, for the mass flowing into the evaporator and the mass flowing out, in the dynamic mechanism model, the material balance equations of the i-th effect evaporation unit and the j-th stage flash evaporation unit are respectively:

[0050]

[0051] Among them, and respectively represent the inlet feed density and the outlet feed density of the i-th effect evaporation unit. and respectively represent the inlet feed density and the outlet feed density of the j-th stage flash evaporation unit.

[0052] It can be understood that according to the heat balance: for the heat input and the heat output, in the dynamic mechanism model, the heat balance equations of the i-th effect evaporation unit and the j-th stage flash evaporation unit are respectively:

[0053]

[0054] Among them, and respectively represent the inlet feed temperature and the outlet feed temperature of the i-th effect evaporation unit; and respectively represent the inlet feed temperature and the outlet feed temperature of the j-th stage flash evaporation unit; is the temperature of the condensed water; is the secondary steam flow rate at the inlet of the i-th effect evaporation unit; and respectively represent the latent heat of the secondary steam at the inlet of the i-th effect evaporation unit and the latent heat of the flash steam of the j-th stage; and respectively represent the specific heat of the inlet feed and the outlet feed of the i-th effect evaporation unit; and respectively represent the specific heat of the feed liquid input and the output liquid of the j-th stage evaporation unit; is the specific heat of water.

[0055] In a specific implementation, the secondary steam temperature of the evaporator is calculated according to the Clapeyron equation:

[0056]

[0057] Similarly, for the stage flash unit, the volume change is:

[0058] According to the material balance, the mass flowing into the flash evaporator is equal to the mass flowing out:

[0059] According to the heat balance: the heat input is equal to the heat output:

[0060] Finally, the flash steam temperature is calculated according to the Clapeyron equation:

[0061] The steam temperature calculation equation in the dynamic mechanism model is:

[0062]

[0063] Wherein, represents the heat of vaporization of water, and R represents the gas constant; and are the secondary steam temperatures at the inlet and outlet of the i-th effect evaporation unit respectively; and are the flash steam temperatures of the (j - 1)-th stage and the j-th stage respectively; and are the secondary steam pressures at the inlet and outlet of the i-th effect evaporation unit respectively; and are the flash steam pressures of the (j - 1)-th stage and the j-th stage respectively.

[0064] It can be understood that the symbols appearing in this embodiment are shown in Table 1:

[0065] Table 1

[0066]

[0067] Step S20: Select input variables, and based on the intelligent optimization algorithm, combined with the variable dependence constraints of adjacent time points, solve the unknown variables in the dynamic mechanism model.

[0068] It should be noted that the input variables include the feed liquid flow rates at all levels, the inlet feed liquid density, the inlet feed liquid temperature, the inlet fresh steam temperature, and the inlet fresh steam flow rate.

[0069] It is understandable that the intelligent optimization algorithm includes one or a combination of genetic algorithm, particle swarm algorithm, or simulated annealing algorithm.

[0070] It should be noted that the variable dependence constraint at adjacent time points is specifically: the value range of the variable at the current moment is dynamically adjusted based on the solution result at the previous moment, restricting the fluctuation amplitude of the variable values at adjacent moments.

[0071] In a specific implementation, in the five-effect and five-flash multi-effect countercurrent evaporation process, the model has a total of 55 variables and 40 equations, with 15 degrees of freedom, meaning that theoretically, the remaining 40 variables can be solved by specifying the values of 15 variables. For this reason, in this embodiment, the feed liquid flow rates at each stage (11), the inlet feed liquid density, the inlet feed liquid temperature, the inlet fresh steam temperature, and the inlet fresh steam flow rate are selected as input variables. Through the material and energy balance equations and the heat exchange model, these input variables can be used to calculate the feed liquid flow rate, density, temperature, and steam flow rate in each evaporator and flash evaporator, so as to solve the values of the remaining variables. However, due to the highly nonlinear and complex coupling of the 40 equations, the traditional direct solution method has poor effects. Therefore, an intelligent optimization algorithm is used to solve this problem.

[0072] Step S30: Use the solution result at the previous moment to constrain the value range of the variable at the current moment to achieve continuous and smooth estimation of the outlet density.

[0073] The variable dependence constraint at adjacent time points is specifically: the value range of the variable at the current moment is dynamically adjusted based on the solution result at the previous moment, restricting the fluctuation amplitude of the variable values at adjacent moments.

[0074] In a specific implementation, considering that the evaporation process is essentially a continuous, stable, and slow time-varying process, there is a strong dependence between the data at adjacent moments. The density change of the evaporator or flash evaporator at adjacent moments is usually small, which means that at adjacent time points, the density change trend of the evaporator or flash evaporator of the same effect is relatively gentle and the fluctuation is small. On the contrary, the density difference between different-effect evaporators is relatively obvious. It can be obtained that the density estimation values at adjacent moments have high continuity, while the difference between different effects is more significant.

[0075] On this basis, the optimization idea of this embodiment is as Figure 5 shown. Specifically, after solving the other 40 variables ( ) at time ( ), considering that the change amplitude at adjacent moments is usually small, the value range of each variable at time ( ) can be reasonably inferred. That is to say, due to the strong dependence between adjacent moments, ( ) The variable range can be restricted based on ( ) to avoid unreasonable fluctuations. And so on. As time progresses, the variable values at subsequent times will be restricted by the variable values at the previous time, maintaining a relatively stable changing trend.

[0076] This optimization strategy not only helps to improve the stability of the solution process, but also can effectively reduce the errors caused by mutant data or outliers, thus making the density estimation of the whole process more accurate and reasonable.

[0077] The beneficial effects that can be achieved in this embodiment are as follows:

[0078] High-precision estimation: By means of adjacent time-dependence constraints, the noise interference is significantly reduced, and the outlet density estimation error is reduced by more than 70%;

[0079] Dynamic smoothness: The standard deviation of the density curves of each effect is reduced by 75%, avoiding process instability caused by mutations;

[0080] Energy efficiency optimization: The evaporation rate is accurately controlled in real time, and the steam energy consumption is reduced by 10% - 15%;

[0081] Strong adaptability: The intelligent algorithm effectively processes non-linear coupling equations, and the solution efficiency is increased by 40%;

[0082] Industrial practicability: Compatible with existing sensors and control systems, with low implementation cost and easy to promote.

[0083] In this embodiment, a dynamic mechanism model of a five-effect and five-flash countercurrent evaporation process is constructed, including material balance equations, heat balance equations and steam temperature calculation equations of the evaporation unit and the flash evaporation unit; input variables are selected, and based on an intelligent optimization algorithm, combined with the variable dependence constraints of adjacent time points, the unknown variables in the dynamic mechanism model are solved; the variable value range at the current time is restricted by the solution result at the previous time to achieve continuous and smooth estimation of the outlet density. The errors caused by mutant data or outliers are effectively reduced, thus making the density estimation of the whole process more accurate and reasonable.

[0084] In addition, the embodiment of the present application also proposes a computer-readable storage medium, on which a program for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation is stored. When the program for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation is executed by a processor, the steps of the method for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation as described above are implemented.

[0085] It should be noted that the above-described work process is only illustrative and does not limit the protection scope of this application. In actual applications, those skilled in the art can select some or all of them according to actual needs to achieve the purpose of the solution of this embodiment, and no limitation is made here.

[0086] In addition, for the technical details not described in detail in this embodiment, reference can be made to the method for estimating the outlet density of the multi-effect countercurrent evaporation process considering time correlation provided in any embodiment of this application, which will not be elaborated here.

[0087] In addition, it should be noted that in this article, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such a process, method, article or system. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the process, method, article or system including that element.

[0088] The serial numbers of the embodiments of the present application above are only for description and do not represent the superiority or inferiority of the embodiments.

[0089] Through the description of the above embodiments, those skilled in the art can clearly understand that the above embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of this application, 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 is stored in a storage medium (such as Read-Only Memory (ROM) / RAM, magnetic disk, optical disc), and includes several instructions for causing a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application. The above is only the preferred embodiment of this application, and does not limit the patent scope of this application accordingly. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of this application, or directly or indirectly applied to other related technical fields, is equally included in the patent protection scope of this application.

Claims

1. A method for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation, characterized in that: include: Construct a dynamic mechanism model of the five-effect five-flash countercurrent evaporation process, including the material balance equation, heat balance equation and steam temperature calculation equation of the evaporation unit and flash unit; Select input variables, and solve unknown variables in the dynamic mechanism model based on an intelligent optimization algorithm and combined with variable dependency constraints at adjacent time points; The solution result of the previous moment is used to constrain the variable value range of the current moment, so as to achieve continuous smooth estimation of the export density; In the dynamic mechanism model, the volume change equations of the i-th effect evaporation unit and the j-th flash unit are respectively: in, It represents the change of liquid volume in the i-th effect evaporation unit; represents the change in liquid volume in the j-th flash unit; and They represent the inlet and outlet feed liquid flow rates of the i-th effect evaporation unit respectively; and They represent the inlet and outlet feed liquid flow rates of the j-th flash unit respectively; represents the secondary steam flow at the outlet of the i-th effect evaporation unit; represents the secondary steam flow at the outlet of the j-th flash unit; is the density of water; In the dynamic mechanism model, the material balance equations of the i-th effect evaporation unit and the j-th flash unit are respectively: in, and They represent the inlet and outlet liquid densities of the i-th effect evaporation unit, respectively. and They represent the inlet and outlet liquid densities of the j-th flash unit, respectively; In the dynamic mechanism model, the heat balance equations of the i-th effect evaporation unit and the j-th flash unit are respectively: in, and Respectively represent the input liquid and output liquid temperatures of the i-th effect evaporation unit; and They represent the input and output liquid temperatures of the j-th flash unit respectively; is the temperature of condensed water; is the secondary steam flow at the inlet of the i-effect evaporation unit; and They represent the latent heat of secondary steam at the inlet of the i-th effect evaporation unit and the latent heat of flash steam at the j-th stage respectively; and They represent the specific heats of the input liquid and output liquid of the i-th effect evaporation unit respectively; and They represent the specific heat of the input liquid and output liquid of the j-th evaporation unit respectively; is the specific heat of water.

2. The method according to claim 1, characterized in that The calculation equations for the secondary steam and flash steam temperatures in the dynamic mechanism model are: in, represents the heat of vaporization of water, and R represents the gas constant; and are the inlet and outlet secondary steam temperatures of the i-th effect evaporation unit, respectively; and are the j-1th stage flash steam and jth stage flash steam temperatures respectively; and are the secondary steam pressures at the inlet and outlet of the i-th effect evaporation unit, respectively; and are the j-1th stage flash steam pressure and the jth stage flash steam pressure respectively.

3. The method according to claim 1, characterized in that The input variables include feed liquid flow rates at each level, inlet feed liquid density, inlet feed liquid temperature, inlet fresh steam temperature and inlet fresh steam flow rate.

4. The method according to claim 1, characterized in that: The intelligent optimization algorithm includes one or more combinations of a genetic algorithm, a particle swarm algorithm or a simulated annealing algorithm.

5. The method according to claim 1, characterized in that The variable dependency constraints of adjacent time points are specifically: the variable value range at the current moment is dynamically adjusted based on the solution result at the previous moment to limit the fluctuation range of the variable value at adjacent moments.

6. A computer device, characterized in that: The device comprises: a memory and a processor, wherein the processor executes the method according to any one of claims 1 to 5 when running computer instructions stored in the memory.

7. A computer-readable storage medium, characterized in that: The method comprises instructions, which, when executed on a computer, cause the computer to execute the method according to any one of claims 1 to 5.

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