Seawater desalination integrated process system based on mathematical model analysis

Abstract

The present invention discloses an integrated seawater desalination process system based on mathematical model analysis, relating to the technical field of seawater desalination. By defining the input variables, output variables, and performance parameters of an evaporator, obtaining data from the evaporator's historical operation process and performing fitting processing, the functional relationship between the input and output variables associated with the performance parameters is determined based on the data fitting results. A limited range of input and output variables is set for any evaporator. Using the limited range as a constraint and minimizing the difference in performance parameters between any two evaporators as the objective function, an optimization control model is constructed. The optimization control model is used to obtain the optimal values ​​of the input and output variables when the performance parameters of the i-th effect evaporator are at their optimal values. The operating state of the evaporator is controlled based on the obtained optimal values, adjusting the current input and output variables of the evaporator to their optimal values. This achieves optimized control of the overall system performance.

Description

Technical Field

[0001] The present invention relates to the technical field of seawater desalination, and in particular to a seawater desalination integrated process system based on mathematical model analysis. Background Art

[0002] Low-temperature, multi-effect seawater desalination technology refers to a desalination process in which the maximum evaporation temperature of brine is below 70°C. It involves connecting a series of evaporators in series, injecting a fixed amount of steam and seawater, and then producing distilled water many times the steam volume through repeated evaporation and condensation. Depending on the relative travel direction of the feed water and steam, the feed can be divided into three types: cocurrent, countercurrent, and advection. Advection feed, in which feed water enters all evaporators simultaneously, eliminates the need for additional inter-effect pumps and is currently the mainstream feed method for low-temperature, multi-effect distillation desalination systems. Low thermal efficiency can be compensated by using steam ejectors.

[0003] The existing industrial control methods for seawater desalination systems, such as the PID control algorithm, form a control quantity by passing the error through proportional, integral and differential links, and feed it back to the controlled object. Because of its simple principle and easy implementation, it is widely used in industrial seawater desalination control. The low-temperature multi-effect distillation seawater desalination system is a complex nonlinear time-varying system. During the operation of the system, lag links are prevalent and are often affected by various factors, such as feed seawater temperature and flow, motive steam mass flow, final brine flow, noise and load changes. This makes it difficult for the existing PID control method to meet the control requirements of maximizing the water production ratio. For this reason, related research has proposed a seawater desalination system control method based on model prediction. For example, in the patent document with application number: 202410381473.4, by establishing a nonlinear MPC algorithm equation, the NMPC module is based on the motive steam flow W ms and feed seawater flow rate W sw Two major types of control inputs are used to achieve automatic control to maximize the water production ratio.

[0004] The aforementioned model-based predictive control method controls the desalination system as a whole, optimizing system performance (such as the water production ratio, ejection ratio, steam temperature in the first-effect evaporator, and desalted water level in the last-effect evaporator) by considering overall system inputs. However, it does not consider the impact of inter-effect variability. Ideally, performance indicators of different evaporators should be kept equal or similar; otherwise, system performance will be negatively impacted. For example, significant differences in the water production ratios of different evaporators can lead to a decrease in the overall system water production ratio. Differences in heat transfer efficiency and effective heat transfer temperature differences can also affect the thermal energy utilization efficiency of each evaporator. If some evaporators have low heat transfer efficiencies and small effective heat transfer temperature differences, this can reduce the overall system thermal energy utilization efficiency and increase energy consumption. Therefore, how to account for these differences in evaporators and achieve optimal control of overall system performance while maintaining optimal performance in each evaporator is a pressing technical challenge. To this end, a seawater desalination process system based on mathematical model analysis is proposed. Summary of the Invention

[0005] The main purpose of the present invention is to provide an integrated seawater desalination process system based on mathematical model analysis, which can effectively solve the problems in the background technology.

[0006] To achieve the above object, the technical solution adopted by the present invention is:

[0007] Based on the mathematical model analysis of the integrated desalination process system, the system control process includes the following steps:

[0008] Definition The input variables of the 1 / 2 effect evaporator are , the output variable is And the performance parameters are , obtain the data of the evaporator during historical operation and perform fitting processing, and determine the functional relationship between the input variables and output variables associated with the performance parameters based on the data fitting results = , where input variables and output variables are variables that affect performance parameters, 、 and Input variables and output variables respectively and the number of performance parameters;

[0009] Set the input variables for any evaporator With output variables With the limited range as the constraint condition and minimizing the difference in performance parameters between any two evaporators as the objective function, an optimization control model is constructed, and the optimization control model is used to obtain the The performance parameters of the high-efficiency evaporator are the optimal values When inputting variables Optimal value With output variables The optimal value of ;

[0010] According to the input variables obtained Optimal value With output variables The optimal value of For the first The operating state of the high-efficiency evaporator is controlled in steps of Adjustment Current input variables of the 1 / 2 effect evaporator To the optimal value , with a step length Adjustment Current output variable of the 1 / 2 effect evaporator To the optimal value .

[0011] The integrated desalination process system based on mathematical model analysis includes:

[0012] Data acquisition module, used to obtain data on the evaporator during historical operation, including input variables , output variables And performance parameters ;

[0013] The data fitting module is used to fit the data acquired during the historical operation of the evaporator, and determine the functional relationship between the input variables and output variables associated with the performance parameters based on the data fitting results. = ;

[0014] Variable setting module, used to set the input variables for any evaporator With output variables limited scope;

[0015] An optimization model building module is used to build an optimization control model with a limited range as a constraint condition and minimizing the difference in performance parameters between any two evaporators as the objective function;

[0016] Variable optimization module, used to obtain the current The performance parameters of the high-efficiency evaporator are the optimal values When inputting variables Optimal value With output variables The optimal value of ;

[0017] Variable adjustment module, used to adjust the input variables according to the obtained Optimal value With output variables The optimal value of For the first The operating status of the high-efficiency evaporator is controlled. The specific control strategies include:

[0018] By step length Adjustment Current input variables of the 1 / 2 effect evaporator To the optimal value ;

[0019] By step length Adjustment Current output variable of the 1 / 2 effect evaporator To the optimal value .

[0020] It also includes a memory, a processor, and an electronic program stored in the memory and capable of running on the processor.

[0021] Furthermore, the input variables include one or more combinations of heating steam temperature, heating steam pressure, seawater flow rate, seawater temperature, seawater salinity, seawater pH value, seawater spray density and operating pressure;

[0022] The output variables include one or more combinations of fresh water production, fresh water temperature, fresh water salinity, secondary steam flow rate, secondary steam temperature, brine flow rate, brine temperature, and brine salinity;

[0023] The performance parameters include one or more combinations of water production ratio, heat transfer efficiency, effective heat transfer temperature difference, specific heat transfer area, specific cooling water volume, concentration ratio, scaling rate and corrosion rate.

[0024] Furthermore, the process of determining the input variables and output variables associated with the performance parameters includes the following steps:

[0025] Step S01: Calculate performance parameters based on the acquired historical data With input variables and output variables Correlation coefficient ,in, Performance parameters With the The correlation coefficient between the variables, = Where, For the The first variable data values; Performance parameters No. data values; is the total amount of sampled data; is the resolution coefficient, which is taken as 0.5; is the minimum difference between the two levels of data; is the maximum difference between the two levels of data;

[0026] = ;

[0027] = ;

[0028] Indicates first take =1,2,..., hour, The minimum value of all calculation results is taken =1,2,..., When , the minimum value among all minimum values ​​in the calculation results is obtained;

[0029] Indicates first take =1,2,..., hour, The maximum value among all the calculated results is taken. =1,2,..., When , the maximum value among all the maximum values ​​in the calculation results is obtained; is the type of variable;

[0030] Step S02: Correlation coefficient Perform normalization processing to obtain the normalized correlation coefficient ,in, = ;

[0031] Step S03: normalize the correlation coefficient Arrange in descending order, select the The correlation coefficient of the sum of the values ​​is not less than 0.9 The corresponding variable, as the variable type associated with the performance parameter.

[0032] Furthermore, the differences in performance parameters are described using Euclidean distance, specifically: = Where, Expressed as The first effect evaporator and ≠ ; For the Performance parameters of high-efficiency evaporator.

[0033] Furthermore, in step size Adjustment Current input variables of the 1 / 2 effect evaporator To the optimal value During the process, the step length The first gradient of the input variable is determined according to the objective function, specifically: = ;in, is the first gradient of the objective function with respect to the input variable; is a positive constant; F is the objective function.

[0034] Furthermore, the step length Adjustment Current output variable of the 1 / 2 effect evaporator To the optimal value During the process, the step length The second gradient of the output variable is determined according to the objective function, specifically: = ;in, is the second gradient of the objective function with respect to the output variable; is a positive constant; F is the objective function.

[0035] The present invention has the following beneficial effects:

[0036] Compared with the existing technology, this solution defines the input variables, output variables and performance parameters of the evaporator, obtains the data of the evaporator in the historical operation process for fitting processing, determines the functional relationship between the input variables and output variables associated with the performance parameters based on the data fitting results, sets the limited range of the input variables and output variables for any evaporator, uses the limited range as the constraint condition, and takes minimizing the difference in performance parameters between any two evaporators as the objective function to construct an optimization control model, and uses the optimization control model to obtain the current When the performance parameters of the single-effect evaporator are at optimal values, the optimal values ​​of the input variables and the optimal values ​​of the output variables are obtained. The operating state of the evaporator is controlled according to the obtained optimal values, and the current input variables and the current output variables of the evaporator are adjusted to the optimal values. The influence of the differences between evaporators of different effects can be considered. Under the premise that the performance of a single-effect evaporator is optimal, the overall performance of the system can be optimized and controlled, thereby improving the overall performance of the desalination system. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a schematic diagram of the control flow of the integrated seawater desalination process system based on mathematical model analysis of the present invention;

[0038] Figure 2 It is a structural diagram of the parallel feed seawater desalination system;

[0039] Figure 3 Schematic diagram of the evaporator inlet and outlet structure of the parallel feed seawater desalination system. DETAILED DESCRIPTION

[0040] The present invention will be further described below in conjunction with specific embodiments. The accompanying drawings are for illustrative purposes only and represent only schematic diagrams rather than actual drawings. They should not be understood as limiting the present invention. In order to better illustrate the specific embodiments of the present invention, some parts of the drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product.

[0041] The specific implementation process of the technical solution of the present invention includes the following steps:

[0042] Step 1: Define the The input variables of the 1 / 2 effect evaporator are , the output variable is And the performance parameters are .

[0043] Low temperature multi-effect seawater desalination technology connects a series of horizontal tube falling film evaporators or vertical tube evaporators in series to form multiple effect groups. In this embodiment, Figure 2 Take the desalination system shown in the figure as an example. The system has 7 evaporators. The input and output of each evaporator are as follows: Figure 3 As shown, the input variables include:

[0044] Heating steam temperature: The temperature of heating steam directly affects the heat transfer efficiency and water production ratio of the evaporator;

[0045] Heating Steam Pressure: Steam pressure affects the temperature and available latent heat of steam;

[0046] Seawater flow rate: The flow rate of seawater affects the heat transfer efficiency and scaling;

[0047] Seawater temperature: The initial temperature of seawater affects the energy required for preheating and the heat transfer efficiency;

[0048] Seawater salinity: The salinity of seawater affects the risk of scaling and corrosion;

[0049] Seawater pH: The pH of seawater affects the corrosion rate and scale formation;

[0050] Seawater spray density: Spray density affects heat transfer efficiency and scaling;

[0051] Operating pressure: Operating pressure affects evaporation temperature and heat transfer efficiency.

[0052] Output variables include:

[0053] Freshwater production: the freshwater flow rate produced by each evaporator;

[0054] Freshwater temperature: the temperature of the freshwater produced;

[0055] Freshwater salinity: The salinity of the freshwater produced should usually be below a certain standard;

[0056] Secondary steam flow rate: the secondary steam flow rate generated from the evaporator, used for the next-effect evaporator;

[0057] Secondary steam temperature: the temperature of secondary steam;

[0058] Brine flow rate: the flow rate of concentrated brine;

[0059] Brine temperature: the temperature of the brine after concentration;

[0060] Brine salinity: the salinity of brine after concentration.

[0061] Performance parameters include:

[0062] Fresh water production ratio: the amount of fresh water produced per unit of heating steam;

[0063] Heat transfer efficiency: the ratio of actual heat transfer to theoretical heat transfer;

[0064] Effective heat transfer temperature difference: the actual temperature difference between the heating steam and the heated liquid;

[0065] Specific heat transfer area: the ratio of heat transfer area to fresh water production;

[0066] Specific cooling water volume: ratio of cooling water volume to fresh water production;

[0067] Concentration ratio: the ratio of the salinity of the concentrated brine to the salinity of the feed seawater;

[0068] Fouling rate: the fouling rate on the evaporator surface;

[0069] Corrosion rate: The corrosion rate of the evaporator material.

[0070] Step 2: Obtain the data of the evaporator during historical operation and perform fitting processing. According to the data fitting results, determine the functional relationship between the input variables and output variables associated with the performance parameters. = , where input variables and output variables are variables that affect performance parameters, 、 and Input variables and output variables respectively And the performance parameter number.

[0071] The process of determining the input variables and output variables associated with the performance parameters includes the following steps:

[0072] Step S01: Calculate performance parameters based on the acquired historical data With input variables and output variables Correlation coefficient ,in, Performance parameters With the The correlation coefficient between the variables, = Where, For the The first variable data values; Performance parameters No. data values; is the total amount of sampled data; is the resolution coefficient, which is taken as 0.5; is the minimum difference between the two levels of data; is the maximum difference between the two levels of data;

[0073] = ;

[0074] = ;

[0075] Indicates first take =1,2,..., hour, The minimum value of all calculation results is taken =1,2,..., When , the minimum value among all minimum values ​​in the calculation results is obtained;

[0076] Indicates first take =1,2,..., hour, The maximum value among all the calculated results is taken. =1,2,..., When , the maximum value among all the maximum values ​​in the calculation results is obtained; is the type of variable;

[0077] Step S02: Correlation coefficient Perform normalization processing to obtain the normalized correlation coefficient ,in, = ;

[0078] Step S03: normalize the correlation coefficient Arrange in descending order, select the The correlation coefficient of the sum of the values ​​is not less than 0.9 The corresponding variable, as the variable type associated with the performance parameter.

[0079] Step 3: Set the input variables for any evaporator With output variables The optimization control model is constructed with the limited range as the constraint condition and minimizing the difference in performance parameters between any two evaporators as the objective function.

[0080] The difference in performance parameters is described using Euclidean distance, specifically: = Where, Expressed as The first effect evaporator and ≠ ; For the Performance parameters of high-efficiency evaporator.

[0081] In a possible embodiment, the water production ratio is used as a performance parameter for illustration. First, the types of input variables and output variables related to the evaporator water production ratio can be determined in step 2. Then, the expression of the objective function F can be written as:

[0082] F= ;

[0083] The constraints for the optimization control model include the following:

[0084] 1. The water production ratio of each evaporator needs to be optimal;

[0085] Then we have: = ;in, 、 are the input and output variables associated with the water production ratio respectively;

[0086] 2. All input variables associated with any water production ratio must be within the specified limits;

[0087] Then we have: ∈ ;in, 、 are the upper limit and lower limit of the value range of the input variable associated with the water production ratio respectively;

[0088] 3. The output variables associated with any water production ratio must be within the set limit range;

[0089] Then we have: ∈ ;in, 、 are the upper limit and lower limit of the value range of the output variable associated with the water production ratio respectively;

[0090] Then the expression of the constructed optimization control model is:

[0091] F= ;

[0092] St.

[0093] = ;

[0094] ∈ ;

[0095] ∈ ;

[0096] Among them, St. is the constraint condition of the optimization control model.

[0097] Step 4: Use the optimization control model to obtain the current The performance parameters of the high-efficiency evaporator are the optimal values When inputting variables Optimal value With output variables The optimal value of ;

[0098] According to the input variables obtained Optimal value With output variables The optimal value of For the first The operating state of the high-efficiency evaporator is controlled in steps of Adjustment Current input variables of the 1 / 2 effect evaporator To the optimal value , with a step length Adjustment Current output variable of the 1 / 2 effect evaporator To the optimal value .

[0099] Among them, the step length The first gradient of the input variable is determined according to the objective function, specifically: = ;in, is the first gradient of the objective function with respect to the input variable; is a positive constant; F is the objective function;

[0100] step length The second gradient of the output variable is determined according to the objective function, specifically: = ;in, is the second gradient of the objective function with respect to the output variable; is a positive constant; F is the objective function.

[0101] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. The integrated seawater desalination process system based on mathematical model analysis is characterized by: The control process of the system includes the following steps: Definition The input variables of the 1 / 2 effect evaporator are , the output variable is And the performance parameters are , obtaining the data of the evaporator during the historical operation process for fitting processing, and determining the functional relationship between the input variable and the output variable associated with the performance parameter based on the data fitting result = , wherein the input variables and the output variables are variables that affect the performance parameters, 、 and The input variables are , the output variable And the performance parameters Number; Set the input variables for any of the evaporators With the output variable The limited range is used as a constraint condition, and the objective function is to minimize the difference in the performance parameters between any two evaporators. An optimization control model is constructed, and the optimization control model is used to obtain the The performance parameters of the high-efficiency evaporator are the optimal values When the input variable Optimal value With the output variable The optimal value of ; According to the input variables obtained Optimal value With the output variable The optimal value of For the first The operating state of the high-efficiency evaporator is controlled in steps of Adjustment Current input variables of the 1 / 2 effect evaporator To the optimal value , with a step length Adjustment Current output variable of the 1 / 2 effect evaporator To the optimal value .

2. The integrated seawater desalination process system based on mathematical model analysis according to claim 1, characterized in that: The input variables include one or more combinations of heating steam temperature, heating steam pressure, seawater flow rate, seawater temperature, seawater salinity, seawater pH value, seawater spray density and operating pressure; The output variables include one or more combinations of fresh water production, fresh water temperature, fresh water salinity, secondary steam flow, secondary steam temperature, brine flow, brine temperature and brine salinity; The performance parameters include one or more combinations of water production ratio, heat transfer efficiency, effective heat transfer temperature difference, specific heat transfer area, specific cooling water volume, concentration ratio, scaling rate and corrosion rate.

3. The integrated seawater desalination process system based on mathematical model analysis according to claim 1, characterized in that: The process of determining the input variables and the output variables associated with the performance parameters comprises the following steps: Step S01: Calculate the performance parameters based on the acquired historical data With the input variables and the output variable Correlation coefficient ,in, For the performance parameters With the The correlation coefficient between the variables, = Where, For the The first variable data values; Performance parameters No. data values; is the total amount of sampled data; is the resolution coefficient, which is taken as 0.5; is the minimum difference between the two levels of data; is the maximum difference between the two levels of data; = ； = ； Indicates first take =1,2,..., hour, The minimum value of all calculation results is taken =1,2,..., When , the minimum value among all minimum values ​​in the calculation results is obtained; Indicates first take =1,2,..., hour, The maximum value among all the calculated results is taken. =1,2,..., When , the maximum value among all the maximum values ​​in the calculation results is obtained; is the type of variable; Step S02: The correlation coefficient Perform normalization processing to obtain the normalized correlation coefficient ,in, = , For the performance parameters With the Correlation coefficients between item variables; Step S03: normalize the correlation coefficient Arrange in descending order, select the The correlation coefficient of the sum of the values ​​is not less than 0.9 The corresponding variable is used as the variable type associated with the performance parameter.

4. The integrated seawater desalination process system based on mathematical model analysis according to claim 1, characterized in that: The differences in the performance parameters are described using Euclidean distance, specifically: = Where, Expressed as The first effect evaporator and ≠ ; For the Performance parameters of high-efficiency evaporator.

5. The integrated seawater desalination process system based on mathematical model analysis according to claim 1, characterized in that: In step length Adjustment Current input variables of the 1 / 2 effect evaporator To the optimal value During the process, the step length The first gradient of the input variable is determined according to the objective function, specifically: = ;in, is the first gradient of the objective function with respect to the input variable; is a positive constant; F is the objective function.

6. The integrated seawater desalination process system based on mathematical model analysis according to claim 1, characterized in that: By step length Adjustment Current output variable of the 1 / 2 effect evaporator To the optimal value During the process, the step length The second gradient of the output variable is determined according to the objective function, specifically: = ;in, is a second gradient of the objective function with respect to the output variable; is a positive constant; F is the objective function.

7. The integrated seawater desalination process system based on mathematical model analysis according to claim 1, characterized in that: include: Data acquisition module, used to obtain data on the evaporator during historical operation, including input variables , output variables And performance parameters ; A data fitting module is used to fit the data acquired during the historical operation of the evaporator, and determine the functional relationship between the input variables and the output variables associated with the performance parameters based on the data fitting results. = ; A variable setting module for setting the input variables for any of the evaporators With the output variable limited scope; an optimization model construction module, configured to construct an optimization control model with the limited range as a constraint condition and minimizing the difference in the performance parameters between any two evaporators as an objective function; Variable optimization module, used to obtain the current The performance parameters of the high-efficiency evaporator are the optimal values When the input variable Optimal value With the output variable The optimal value of ; A variable adjustment module is used to adjust the input variables according to the obtained Optimal value With the output variable The optimal value of For the first The operating status of the high-efficiency evaporator is controlled. The specific control strategies include: By step length Adjustment Current input variables of the 1 / 2 effect evaporator To the optimal value ; By step length Adjustment Current output variable of the 1 / 2 effect evaporator To the optimal value .

8. The integrated seawater desalination process system based on mathematical model analysis according to claim 7, characterized in that: It also includes a memory, a processor, and an electronic program stored in the memory and capable of running on the processor, wherein the processor can implement the steps of the control flow described in claim 1 when running the electronic program.

Images