Multiple-effect countercurrent evaporation process outlet density estimation method considering time correlation

Abstract

The invention provides a multi-effect countercurrent evaporation process outlet density estimation method considering time correlation, and relates to the technical field of outlet density estimation. The method comprises the following steps: constructing a dynamic mechanism model of a five-effect five-flash countercurrent evaporation process, wherein the dynamic mechanism model comprises a material balance equation, a heat balance equation and a steam temperature calculation equation of an evaporation unit and a flash evaporation unit; selecting an input variable, and solving an unknown variable in the dynamic mechanism model based on an intelligent optimization algorithm in combination with variable dependency constraints of adjacent time points; and constraining the variable value range of the current moment by using the solving result of the previous moment to realize continuous smooth estimation of the outlet density. Errors caused by abrupt change data or abnormal values are effectively reduced, so that density estimation in the whole process is more accurate and reasonable.

Description

Technical Field

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

[0002] The evaporation process heats a solution containing non-volatile solutes to boiling by an external heat source, so that the volatile solvent in it is partially vaporized, thereby concentrating 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 indicator for measuring 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 outlet density estimation method of the traditional multi-effect countercurrent evaporation process is usually based on a static model or independent time point solution, ignoring the dynamic correlation between variables at adjacent time points, resulting in the estimation result being susceptible to noise interference, large errors and insufficient stability. In addition, the highly nonlinear and multivariable coupling characteristics of the evaporation process make the traditional solution method inefficient and difficult to meet real-time control requirements.

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

[0004] The core of the present invention is to provide a method for estimating the outlet density of a multi-effect countercurrent evaporation process taking time correlation into consideration, thereby solving the problem of how to accurately monitor and control the outlet density.

[0005] In the first aspect, the present application provides a method for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation, which adopts the following technical solution: A method for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation comprises: 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 range of variable values ​​at the current moment to achieve continuous smooth estimation of export density.

[0006] Optionally, 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 Optionally, 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. Optionally, 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.

[0007] Optionally, the secondary steam and flash steam temperature calculation equations in the dynamic mechanism model are: in, 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 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.

[0008] Optionally, the input variables include feed liquid flow rates at various stages, inlet feed liquid density, inlet feed liquid temperature, inlet fresh steam temperature and inlet fresh steam flow rate.

[0009] Optionally, the intelligent optimization algorithm includes one or more combinations of a genetic algorithm, a particle swarm algorithm or a simulated annealing algorithm.

[0010] Optionally, the variable dependency constraints at adjacent time points are specifically as follows: the variable value range at the current moment is dynamically adjusted based on the solution result at the previous moment, so as to limit the fluctuation range of the variable value at adjacent moments.

[0011] In a second aspect, the present application provides a computer device, comprising: a memory and a processor, wherein the processor executes the method described above when running computer instructions stored in the memory.

[0012] In a third aspect, the present application provides a computer-readable storage medium, comprising instructions, which, when executed on a computer, enable the computer to execute the method described above.

[0013] In summary, the present application includes the following beneficial technical effects: This application constructs 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 the flash unit; selects input variables, based on the intelligent optimization algorithm, combined with the variable dependency constraints of adjacent time points, to solve the unknown variables in the dynamic mechanism model; uses the solution results of the previous moment to constrain the variable value range at the current moment, and realizes continuous smooth estimation of the outlet density. Effectively reduce the errors caused by mutation data or outliers, so that the density estimation of the whole process is more accurate and reasonable. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a schematic diagram of the computer device structure of the hardware operating environment involved in the embodiment of the present application.

[0015] Figure 2It is a flow chart of the first embodiment of the method for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation in the present application.

[0016] Figure 3 This is a diagram of a five-effect five-flash countercurrent evaporation process according to the first embodiment of the method for estimating the outlet density of a multi-effect countercurrent evaporation process taking into account time correlation in the present application.

[0017] Figure 4 This is a schematic diagram of the evaporation unit and flash unit model in the five-effect five-flash alumina evaporation process of the present application. Figure 4 (a) is the i-th effect evaporation unit, Figure 4 (b) is the j-th stage flash evaporator.

[0018] Figure 5 This is a conceptual diagram of the optimization idea of ​​the outlet density estimation method of the multi-effect countercurrent evaporation process considering time correlation in this application. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below through the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0020] Reference Figure 1 , Figure 1 A schematic diagram of the computer device structure of the hardware operating environment involved in the embodiment of the present application.

[0021] like Figure 1 As shown, the 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 realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also 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 (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM), or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk storage. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0022] Those skilled in the art will understand that Figure 1The structure shown in the figure does not constitute a limitation on the computer device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0023] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and an outlet density estimation program for a multi-effect countercurrent evaporation process taking into account time correlation.

[0024] exist Figure 1 In the computer device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the present application can be set in the computer device, and the computer device calls the multi-effect countercurrent evaporation process outlet density estimation program considering time correlation stored in the memory 1005 through the processor 1001, and executes the multi-effect countercurrent evaporation process outlet density estimation method considering time correlation provided in the embodiment of the present application.

[0025] The present application embodiment provides a method for estimating the outlet density of a multi-effect countercurrent evaporation process taking into account time correlation, referring to Figure 2 , Figure 2 This is a flow chart of the first embodiment of the method for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation in the present application.

[0026] In this embodiment, the method for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation includes the following steps: Step S10: constructing 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 the flash unit.

[0027] It should be noted that Figure 3 The schematic diagram of the five-effect five-flash countercurrent evaporation process is shown. The process consists of five tubular falling film evaporators and five flash evaporators. In the five-effect evaporation cascade section, the external heat source can be new steam or secondary steam from the outlet of the previous effect. After absorbing heat, the feed liquid vaporizes and boils. The concentrated feed liquid will be sent to the previous effect for further concentration, and the generated water vapor will be transferred to the next effect as a heat source as secondary steam. In the five-stage flash cascade section, each stage of flash steam is depressurized by a throttle valve, which reduces the boiling point of the feed liquid, and the superheated feed liquid is quickly vaporized and cooled, thereby achieving concentration. The concentrated feed liquid continues to flow to the next stage of the flash evaporator, and the steam generated by vaporization (i.e., flash steam) is sent to the corresponding evaporator to be used as a heat source. Through this process configuration, efficient utilization of thermal energy and recycling of resources are achieved.

[0028] For the feed liquid, the evaporation raw liquid enters from the 5-effect evaporator, flows through the 4th effect, 3rd effect, 2nd effect, 1st effect, 1st flash, 2nd flash, 3rd flash, 4th flash in turn, and finally discharged from the 5th flash. In the multi-effect evaporation cascade section, the density and temperature of the feed liquid are constantly rising along the flow direction of the feed liquid; while in the multi-stage flash evaporation cascade section, the density of the feed liquid rises along the flow direction of the feed liquid, while the temperature of the feed liquid is constantly decreasing. For steam, new steam enters from the 1st effect, and the secondary steam generated by the 1st effect is used as the heat source for the 2nd effect. The secondary steam generated by the 2nd effect and the flash steam generated by the 1st flash are used as the heat source for the 3rd effect, the secondary steam generated by the 3rd effect and the flash steam generated by the 2nd flash are used as the heat source for the 4th effect, and the secondary steam generated by the 4th effect and the flash steam of the 3rd flash are used as the heat source for the 5th effect. Along the flow direction of the steam, the temperature of the steam decreases step by step, and the heat carried is constantly decreasing.

[0029] It is understandable that if Figure 4 The schematic diagram of the evaporation unit and flash unit model in the five-effect five-flash alumina evaporation process is shown in FIG. Figure 4 (a) is the i-th effect evaporation unit, Figure 4 (b) For the j-th flash evaporator, the heat balance obtains the dynamic mechanism model of the i-th effect evaporation unit and the j-th flash unit.

[0030] It should be noted that for Effect evaporation unit: The volume change is the volume change caused by input flow - output flow - secondary steam. In the dynamic mechanism model, the volume change equations of the i-th effect evaporation unit and the j-th flash unit are: 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.

[0031] It should be noted that according to the law of conservation of materials, the mass flowing into the evaporator is proportional to the mass flowing out. In the dynamic mechanism model, the material balance equations of the i-th effect evaporation unit and the j-th flash unit are: in, and They represent the inlet liquid density and outlet liquid density of the i-th effect evaporation unit respectively. and They represent the inlet liquid density and outlet liquid density of the j-th flash unit respectively.

[0032] It can be understood that according to the heat balance: the input heat is relative to the output heat, 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.

[0033] In the specific implementation, the secondary steam temperature of the evaporator is calculated according to the Clapeyron equation: The same goes for The volume change of the flash unit is: According to the law of conservation of materials, the mass flowing into the flash evaporator is equal to the mass flowing out: According to the heat balance: the heat input is proportional to the heat output: Finally, the flash steam temperature is calculated according to the Clapeyron equation: The steam temperature calculation equation in the dynamic mechanism model is: in, 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 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.

[0034] It can be understood that the symbols appearing in this embodiment are as shown in Table 1: Table 1 Step S20: Select input variables, and solve unknown variables in the dynamic mechanism model based on an intelligent optimization algorithm and in combination with variable dependency constraints at adjacent time points.

[0035] It should be noted that the input variables include feed liquid flow rates at various levels, inlet feed liquid density, inlet feed liquid temperature, inlet fresh steam temperature and inlet fresh steam flow rate.

[0036] It can be understood that the intelligent optimization algorithm includes one or more combinations of genetic algorithm, particle swarm algorithm or simulated annealing algorithm.

[0037] It should be noted that the variable dependency constraints at 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.

[0038] In the specific implementation, in the five-effect five-flash multi-effect countercurrent evaporation process, the model has a total of 55 variables and 40 equations, with a degree of freedom of 15, which means that in theory, the remaining 40 variables can be solved by giving 15 variable values. To this end, this embodiment selects the feed liquid flow rate (11) at each level, the inlet feed liquid density, the inlet feed liquid temperature, the inlet fresh steam temperature and the inlet fresh steam flow rate as input variables. Through the material and energy balance equation 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 effect evaporator and flash evaporator, so as to solve the values ​​of the remaining variables. However, since the 40 equations are highly nonlinear and complexly coupled to each other, the traditional direct solution method is not effective. Therefore, an intelligent optimization algorithm is used to solve this problem.

[0039] Step S30: Using the solution result of the previous moment to constrain the variable value range of the current moment, to achieve continuous smooth estimation of the outlet density.

[0040] 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.

[0041] In the specific implementation, considering that the evaporation process is essentially a continuous, stable, 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 with the same effect is relatively gentle and the fluctuation is not large. On the contrary, the density difference between evaporators with different effects is relatively obvious. It can be obtained that the density estimation values ​​at adjacent moments have a high degree of continuity, and the difference between different effects is more significant.

[0042] On this basis, the optimization idea of ​​this embodiment is as follows Figure 5 Specifically, when solving the moment ( ) when the other 40 variables ( ), considering that the change amplitude of adjacent moments is usually small, it can be reasonably inferred that ( ) The value range of each variable at the moment. In other words, due to the strong dependence between adjacent moments, ( ) can be scoped in ( ) to avoid unreasonable fluctuations. Similarly, as time progresses, the variable values ​​at subsequent moments will be constrained by the variable values ​​at the previous moment, maintaining a relatively stable change trend.

[0043] This optimization strategy not only helps to improve the stability of the solution process, but also effectively reduces the errors caused by mutation data or outliers, making the density estimation of the whole process more accurate and reasonable.

[0044] The beneficial effects that can be achieved by this embodiment are: High-precision estimation: Through adjacent time dependency constraints, noise interference is significantly reduced, and the error of export density estimation is reduced by more than 70%; Dynamic smoothness: The standard deviation of each effective density curve is reduced by 75%, avoiding process instability caused by mutations; Energy efficiency optimization: real-time and precise control of evaporation rate, reducing steam energy consumption by 10%~15%; Strong adaptability: Intelligent algorithms can effectively handle nonlinear coupled equations, improving solution efficiency by 40%; Industrial applicability: Compatible with existing sensors and control systems, low implementation cost and easy to promote.

[0045] This embodiment constructs 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 the flash unit; selects input variables, based on the intelligent optimization algorithm, combined with the variable dependency constraints of adjacent time points, to solve the unknown variables in the dynamic mechanism model; uses the solution results of the previous moment to constrain the variable value range at the current moment, and realizes continuous smooth estimation of the outlet density. It effectively reduces the errors caused by sudden changes in data or outliers, making the density estimation of the entire process more accurate and reasonable.

[0046] In addition, an embodiment of the present application also proposes a computer-readable storage medium, on which is stored a program for estimating the outlet density of a multi-effect countercurrent evaporation process taking into account time correlation. When the program for estimating the outlet density of a multi-effect countercurrent evaporation process taking into account time correlation is executed by a processor, the steps of the method for estimating the outlet density of a multi-effect countercurrent evaporation process taking into account time correlation as described above are implemented.

[0047] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present application. In practical applications, technicians in this field can select part or all of it according to actual needs to achieve the purpose of the present embodiment, and no limitation is made here.

[0048] In addition, for technical details not described in detail in this embodiment, reference can be made to the method for estimating the outlet density of a multi-effect countercurrent evaporation process considering time correlation provided in any embodiment of the present application, which will not be described in detail here.

[0049] In addition, it should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0050] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0051] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory (ROM) / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods of each embodiment of the present application. The above is only a preferred embodiment of the present application, and does not limit the patent scope of the present application. All equivalent structures or equivalent process changes made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are similarly included in the patent protection scope of the present 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 range of variable values ​​at the current moment to achieve continuous smooth estimation of export density.

2. The method according to claim 1, characterized in that 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.

3. The method according to claim 2, characterized in that 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 liquid density and outlet liquid density of the j-th flash unit respectively.

4. The method according to claim 3, characterized in that 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.

5. The method according to claim 4, 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.

6. 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.

7. 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.

8. 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.

9. 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 8 when running computer instructions stored in the memory.

10. 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 8.

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