A dynamic water distribution method and system for natural draft cooling towers

Abstract

The present invention discloses a method and system for dynamic water distribution of a natural draft cooling tower. The method includes the following steps: testing the natural draft cooling tower to obtain the performance parameters of the cooling tower, where the natural draft cooling tower includes a water distribution actuator of the cooling tower; constructing a CFD simulation model of the natural draft cooling tower; calculating by taking the performance parameters of the cooling tower as boundary conditions of the CFD simulation model of the natural draft cooling tower to obtain sample point response values; constructing a Kriging surrogate model and training it using the sample point response values; using the trained model to collect data of the water distribution actuator of the cooling tower and processing the data to obtain the adjusted initial circulating water flow rate of the fan-shaped area; and performing water distribution adjustment on the water distribution actuator of the cooling tower based on the adjusted initial circulating water flow rate of the fan-shaped area. The present invention realizes dynamic water distribution of the natural draft cooling tower according to environmental conditions, and reduces the influence of environmental side wind on the heat transfer performance of the natural draft cooling tower.

Description

Technical Field

[0001] The present invention relates to the technical field of medium and large natural draft cooling towers, and specifically relates to a dynamic water distribution method and system for natural draft cooling towers. Background Art

[0002] A natural draft cooling tower is the main cooling equipment in the circulating water system of a thermal power plant, and its cooling efficiency seriously affects the economy of the thermal power unit. When there is a side wind in the surrounding environment of the natural draft cooling tower, the air flow field distribution inside the tower is uneven, resulting in deteriorated heat transfer on the windward side and enhanced heat transfer on the leeward side. However, due to the consistent circulating water flow rate in each area inside the natural draft cooling tower in the prior art, the cooling potential of the leeward side is not fully utilized, leading to a weakened overall heat transfer effect inside the tower. Summary of the Invention

[0003] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a dynamic water distribution method and system for natural draft cooling towers, which solves the problems mentioned in the background art.

[0004] To achieve the above object, the present invention provides the following technical solution: A dynamic water distribution method for natural draft cooling towers, comprising the following steps:

[0005] Step S1: Conduct thermal performance and resistance performance tests on the natural draft cooling tower to obtain the performance parameters of the cooling tower. The natural draft cooling tower includes a cooling tower water distribution actuator, and process the performance parameters of the cooling tower to obtain thermal performance and resistance performance;

[0006] Step S2: Perform three-dimensional modeling on the natural draft cooling tower to obtain a three-dimensional model of the calculation domain of the natural draft cooling tower, and process the three-dimensional model of the calculation domain of the natural draft cooling tower to obtain a grid model of the calculation domain of the natural draft cooling tower;

[0007] Step S3: Build a CFD simulation model of the natural draft cooling tower based on the grid model of the calculation domain of the natural draft cooling tower, thermal performance and resistance performance. Use the performance parameters of the cooling tower as the boundary conditions of the CFD simulation model of the natural draft cooling tower for calculation to obtain the simulated value of the water temperature out of the tower of the natural draft cooling tower. Compare the simulated value of the water temperature out of the tower of the natural draft cooling tower with the performance parameters of the cooling tower to obtain a CFD simulation model of the natural draft cooling tower that meets the requirements;

[0008] Step S4: Use the CFD simulation model of the natural draft cooling tower that meets the requirements, combined with the Latin hypercube experimental design, to process the performance parameters of the cooling tower to obtain the response values of the sample points. Build a Kriging surrogate model, and use the response values of the sample points to train the Kriging surrogate model to obtain a trained Kriging surrogate model;

[0009] Step S5: Collect the average wind speed in the fan-shaped area of the cooling tower water distribution actuator through the trained Kriging surrogate model, calculate the average wind speed in the fan-shaped area, and obtain the adjusted initial circulating water flow in the fan-shaped area;

[0010] Step S6: Adjust the water distribution of the cooling tower water distribution actuator based on the adjusted initial circulating water flow in the fan-shaped area.

[0011] Furthermore, in step S1, the performance parameters of the cooling tower are divided into input performance parameters and output performance parameters. The input performance parameters include: circulating water flow , cooling tower inlet water temperature , ambient temperature , ambient relative humidity , side wind speed , air velocity at the water filling , atmospheric pressure , water filling resistance ; represents the k-th value in the circulating water flow sequence; represents the k-th value in the cooling tower inlet water temperature sequence; represents the k-th value in the ambient temperature sequence; represents the k-th value in the ambient relative humidity sequence; represents the k-th value in the side wind speed sequence; represents the k-th value in the air velocity sequence at the water filling; represents the k-th value in the atmospheric pressure sequence; represents the k-th value in the water filling resistance sequence;

[0012] The output performance parameters include: cooling tower outlet water temperature , outlet air temperature ; represents the k-th value in the cooling tower outlet water temperature sequence; represents the k-th value in the outlet air temperature sequence.

[0013] Furthermore, in step S1, the thermal performance and resistance performance, the specific process is:

[0014] Fit the performance parameters of the cooling tower through the Merkel equation to obtain the thermal performance , where , ; represents the thermal performance parameters of the cooling tower; represents the ventilation density; represents the water spray density; represents the functional relationship between two variables ga and qw; represents the air density; represents the cross-sectional area of the cooling tower packing;

[0015] Fitting the performance parameters of the cooling tower to obtain the resistance performance ; represents the functional relationship between two variables and qw.

[0016] Furthermore, in step S3, a CFD simulation model of a natural draft cooling tower is constructed. The specific process is as follows:

[0017] By calculating the thermal performance, the heat transfer coefficient per unit volume of the packing is obtained , and is used as the mass transfer model for the packing area, and is used as the heat transfer model for the packing area. The natural draft cooling tower includes a packing area. The mass transfer model and the heat transfer model are loaded into the packing area of the natural draft cooling tower in the form of user-defined functions through CFD software; c p,a is the specific heat capacity of humid air, and Le f is the Lewis factor of humid air;

[0018] By calculating the resistance performance, the viscous resistance coefficient C1 and the inertial resistance coefficient C2 of the packing area of the natural draft cooling tower are obtained. Based on the viscous resistance coefficient C1, the inertial resistance coefficient C2, and the computational domain grid model of the natural draft cooling tower, a CFD simulation model of the natural draft cooling tower is constructed.

[0019] Furthermore, the basic unit size of the grid of the three-dimensional model of the computational domain of the natural draft cooling tower is d;

[0020] The process of obtaining a satisfactory CFD simulation model of the natural draft cooling tower in step S3 is as follows:

[0021] Taking the i-th cooling tower outlet water temperature in the output performance parameters as the boundary condition of the CFD simulation model of the natural draft cooling tower for calculation to obtain the simulated value of the outlet water temperature of the natural draft cooling tower ; ;

[0022] Comparing the simulated value of the outlet water temperature of the natural draft cooling tower with the i-th cooling tower outlet water temperature in the output performance parameters When the simulated value of the outlet water temperature of the natural draft cooling tower and the i-th cooling tower outlet water temperature in the output performance parameters When the relative error Error ≥ 5%, the accuracy of the CFD simulation model of the natural draft cooling tower does not meet the requirements. Go to step S2 and adjust the basic grid cell size d to 0.9d until the relative error Error ≤ 5%. When the simulated value of the water temperature out of the natural draft cooling tower and the water temperature out of the i-th cooling tower in the output performance parameters the relative error between them is less than 5%, the accuracy of the CFD simulation model of the natural draft cooling tower meets the requirements, that is, a CFD simulation model of the natural draft cooling tower that meets the requirements is obtained.

[0023] Furthermore, the water distribution actuator of the cooling tower includes a water distribution surface, a shaft, an electric gate, branch water troughs, a first branch pipe, and a second branch pipe; the water distribution surface is composed of areas A1, A2, A3, A4, A5, A6, A7, and A8, and several first branch pipes and second branch pipes are provided on the water distribution surface; branch water troughs are provided on the shaft, and the branch water troughs are composed of a first branch water trough, a second branch water trough, a third branch water trough, and a fourth branch water trough; the first branch water trough is arranged between A1 and A2; the second branch water trough is arranged between A3 and A4; the third branch water trough is arranged between A5 and A6; the fourth branch water trough is arranged between A7 and A8; and electric gates are provided on the first branch water trough, the second branch water trough, the third branch water trough, and the fourth branch water trough.

[0024] Furthermore, the specific process of obtaining the trained Kriging surrogate model in step S4 is as follows:

[0025] Take the circulating water flow rate , the cooling tower inlet water temperature , the ambient temperature , the ambient relative humidity , the side wind speed , and the atmospheric pressure as optimization variables, and use Latin hypercube experimental design for sampling within the optimization variable range to calculate and generate sample points ; represents the n-th sample element;

[0026] Input the sample points into the CFD simulation model of the natural draft cooling tower that meets the requirements for calculation to obtain the sample point response values, that is, the average wind speed in the fan-shaped area ; represents the average wind speed in the n-th fan-shaped area;

[0027] Construct a Kriging surrogate model, expressed as: , the regression function of the Kriging surrogate model selects a quadratic function, and the covariance function of the Kriging surrogate model selects a cubic spline function; Denote the predicted output of the Kriging surrogate model; is the polynomial matrix of x; x represents the vector of input variables; is the regression coefficient; Denote the mean value of y(x); Denote the Gaussian random process with a mean of 0;

[0028] Use the mean square error to evaluate the accuracy of the Kriging surrogate model, which is expressed as: , is the predicted value of the i-th sample point; Denote the response value of the i-th sampling point obtained by calculating through the CFD simulation model of the natural draft cooling tower that meets the requirements; n represents the number of sample points; MSE represents the mean square error; when MSE ≤ 0.25, it is considered that the prediction accuracy of the Kriging surrogate model meets the requirements, and when MSE > 0.25, it is considered that the prediction accuracy of the Kriging surrogate model does not meet the requirements. Add 6 sample points, that is, n = n + 6, then calculate the response values of the added 6 sample points, and reconstruct the Kriging surrogate model. Evaluate the prediction accuracy of the Kriging surrogate model through the mean square error until the prediction accuracy of the Kriging surrogate model meets the requirements, and obtain the trained Kriging surrogate model.

[0029] Furthermore, the specific process of obtaining the adjusted initial circulating water flow rate in the sector area in step S5 is as follows:

[0030] Distribute the circulating water flow rate evenly to the areas of the cooling tower water distribution actuator. The initial circulating water flow rate in the area of the cooling tower water distribution actuator is , ; Denote the initial circulating water flow rate distributed to the area of the j-th cooling tower water distribution actuator;

[0031] Normalize the average wind speed in the sector area. The normalization formula is: , is the area-averaged wind speed in the normalized sector area; Denote the original average wind speed of the j-th sector area;

[0032] Adjust the initial circulating water flow rate in the area of the cooling tower water distribution actuator according to the proportion of the area-averaged wind speed in the normalized sector area. The obtained adjusted initial circulating water flow rate in the sector area is .

[0033] Furthermore, the specific process of water distribution regulation in step S6 is as follows:

[0034] The circulating water flow rate Enter the vertical shaft and control the opening of the electric gate to adjust the circulating water flow rate of the branch water tank according to the adjusted initial circulating water flow rate of the fan-shaped area. The circulating water flow rate Then it flows into the second branch pipe through the first branch pipe, and finally completes the water distribution adjustment of the cooling tower water distribution actuator.

[0035] Furthermore, a natural draft cooling tower dynamic water distribution system for the natural draft cooling tower dynamic water distribution method described above includes:

[0036] A data acquisition module for testing the thermal performance and resistance performance of the natural draft cooling tower to obtain the performance parameters of the cooling tower. The natural draft cooling tower includes a cooling tower water distribution actuator, and processes the performance parameters of the cooling tower to obtain the thermal performance and resistance performance;

[0037] A three-dimensional modeling and mesh processing module for performing three-dimensional modeling on the natural draft cooling tower to obtain a three-dimensional model of the natural draft cooling tower calculation domain, and processing the three-dimensional model of the natural draft cooling tower calculation domain to obtain a mesh model of the natural draft cooling tower calculation domain;

[0038] A CFD simulation model construction and correction module for constructing a CFD simulation model of the natural draft cooling tower based on the mesh model of the natural draft cooling tower calculation domain, thermal performance and resistance performance, calculating with the performance parameters of the cooling tower as the boundary conditions of the CFD simulation model of the natural draft cooling tower to obtain the simulated value of the water temperature leaving the tower of the natural draft cooling tower, and comparing the simulated value of the water temperature leaving the tower of the natural draft cooling tower with the performance parameters of the cooling tower to obtain a satisfied CFD simulation model of the natural draft cooling tower;

[0039] An offline training and surrogate model construction module for processing the performance parameters of the cooling tower by using the satisfied CFD simulation model of the natural draft cooling tower combined with the Latin hypercube experimental design to obtain the response values of the sample points, constructing a Kriging surrogate model, and training the Kriging surrogate model with the response values of the sample points to obtain a trained Kriging surrogate model;

[0040] An online calculation and flow rate dynamic distribution module for collecting the average wind speed of the fan-shaped area of the cooling tower water distribution actuator through the trained Kriging surrogate model, calculating the average wind speed of the fan-shaped area to obtain the adjusted initial circulating water flow rate of the fan-shaped area;

[0041] A water distribution adjustment execution module for performing water distribution adjustment on the cooling tower water distribution actuator based on the adjusted initial circulating water flow rate of the fan-shaped area.

[0042] Compared with the existing technologies, the present invention has the following beneficial effects:

[0043] (1) The present invention realizes dynamic water distribution for natural draft cooling towers according to environmental conditions, reduces the influence of ambient side winds on the heat transfer performance of natural draft cooling towers, effectively improves the cooling efficiency of natural draft cooling towers, and reduces the energy consumption of thermal power units.

[0044] (2) The dynamic water distribution method and system for natural draft cooling towers proposed by the present invention avoid the hysteresis of water distribution adjustment caused by online calculation of the CFD simulation model of natural draft cooling towers by using the offline training and surrogate model construction module, making the water distribution of natural draft cooling towers more real-time. Description of the Drawings

[0045] Figure 1 is a flowchart of the present invention.

[0046] Figure 2 is a schematic diagram of the fan-shaped partition structure on the lower surface of the packing of the present invention.

[0047] Figure 3 is a schematic diagram of the structure of the water distribution actuator of the cooling tower of the present invention.

[0048] Figure 4 is a system flowchart of the present invention.

[0049] Reference Numerals: 1, vertical shaft; 2, electric gate; 3, branch water tank; 4, first branch pipe; 5, second branch pipe. Detailed Embodiments

[0050] As Figure 1 shown, the present invention provides a technical solution: a dynamic water distribution method for natural draft cooling towers, including the following steps:

[0051] Step S1: Perform thermal performance and resistance performance tests on the natural draft cooling tower to obtain the performance parameters of the cooling tower. The natural draft cooling tower includes a water distribution actuator for the cooling tower. Process the performance parameters of the cooling tower to obtain thermal performance and resistance performance;

[0052] Step S2: Perform three-dimensional modeling on the natural draft cooling tower to obtain a three-dimensional model of the calculation domain of the natural draft cooling tower. Process the three-dimensional model of the calculation domain of the natural draft cooling tower to obtain a grid model of the calculation domain of the natural draft cooling tower;

[0053] Step S3: Build a CFD simulation model of the natural draft cooling tower based on the grid model of the calculation domain of the natural draft cooling tower, thermal performance and resistance performance. Use the performance parameters of the cooling tower as the boundary conditions of the CFD simulation model of the natural draft cooling tower for calculation to obtain the simulated value of the water temperature leaving the tower of the natural draft cooling tower. Compare the simulated value of the water temperature leaving the tower of the natural draft cooling tower with the performance parameters of the cooling tower to obtain a CFD simulation model of the natural draft cooling tower that meets the requirements;

[0054] Step S4: Use the CFD simulation model of the natural draft cooling tower that meets the requirements, combine it with the Latin hypercube experimental design to process the performance parameters of the cooling tower, obtain the response values of the sample points, construct a Kriging surrogate model, and use the response values of the sample points to train the Kriging surrogate model to obtain the trained Kriging surrogate model;

[0055] Step S5: Collect the average wind speed in the fan-shaped area of the cooling tower water distribution actuator through the trained Kriging surrogate model, calculate the average wind speed in the fan-shaped area, and obtain the adjusted initial circulating water flow rate in the fan-shaped area;

[0056] Step S6: Based on the adjusted initial circulating water flow rate in the fan-shaped area, adjust the water distribution of the cooling tower water distribution actuator.

[0057] Among them, the performance parameters of the cooling tower in step S1 are divided into input performance parameters and output performance parameters. The input performance parameters include: circulating water flow rate , cooling tower inlet water temperature , ambient temperature , ambient relative humidity , side wind speed , air velocity at the water filling packing , atmospheric pressure , water filling packing resistance ; represents the k-th value in the circulating water flow rate sequence; represents the k-th value in the cooling tower inlet water temperature sequence; represents the k-th value in the ambient temperature sequence; represents the k-th value in the ambient relative humidity sequence; represents the k-th value in the side wind speed sequence; represents the k-th value in the air velocity sequence at the water filling packing; represents the k-th value in the atmospheric pressure sequence; represents the k-th value in the water filling packing resistance sequence;

[0058] The output performance parameters include: cooling tower outlet water temperature , outlet air temperature ; represents the k-th value in the cooling tower outlet water temperature sequence; represents the k-th value in the outlet air temperature sequence.

[0059] Among them, the specific process of the thermal performance and resistance performance in step S1 is as follows:

[0060] Fit the performance parameters of the cooling tower through the Merkel equation to obtain the thermal performance where , ; represents the thermal performance parameters of the cooling tower; represents the ventilation density; represents the water spray density; represents the functional relationship between two variables ga and qw; represents the air density; represents the cross-sectional area of the cooling tower packing;

[0061] Fitting the performance parameters of the cooling tower to obtain the resistance performance ; represents two variables and the functional relationship of qw.

[0062] Among them, in step S3, constructing the CFD simulation model of the natural draft cooling tower, the specific process is as follows:

[0063] By calculating the thermal performance, obtaining the heat transfer coefficient per unit volume of the packing , taking as the mass transfer model of the packing area, taking as the heat transfer model of the packing area, the natural draft cooling tower includes a packing area, and loading the mass transfer model and the heat transfer model into the packing area of the natural draft cooling tower in the form of user-defined functions through CFD software; c p,a is the specific heat capacity of humid air, and Le f is the Lewis factor of humid air;

[0064] By calculating the resistance performance, obtaining the viscous resistance coefficient C1 and the inertial resistance coefficient C2 of the packing area of the natural draft cooling tower, and constructing the CFD simulation model of the natural draft cooling tower based on the viscous resistance coefficient C1, the inertial resistance coefficient C2 and the computational domain grid model of the natural draft cooling tower.

[0065] Among them, the basic unit size of the grid of the three-dimensional model of the computational domain of the natural draft cooling tower is d;

[0066] In step S3, obtaining the CFD simulation model of the natural draft cooling tower that meets the requirements, the specific process is as follows:

[0067] Taking the i-th cooling tower outlet water temperature in the output performance parameters as the boundary condition of the CFD simulation model of the natural draft cooling tower for calculation, and obtaining the simulated value of the outlet water temperature of the natural draft cooling tower ; ;

[0068] Taking the simulated value of the outlet water temperature of the natural draft cooling tower and the i-th cooling tower outlet water temperature Compare. When the simulated value of the water temperature at the outlet of the natural draft cooling tower and the water temperature at the outlet of the i-th cooling tower in the output performance parameters The relative error Error≥5%. The accuracy of the CFD simulation model of the natural draft cooling tower does not meet the requirements. Go to step S2 and adjust the basic grid cell size d to 0.9d until the relative error Error≤5%; When the simulated value of the water temperature at the outlet of the natural draft cooling tower and the water temperature at the outlet of the i-th cooling tower in the output performance parameters The relative error is less than 5%. The accuracy of the CFD simulation model of the natural draft cooling tower meets the requirements, that is, a CFD simulation model of the natural draft cooling tower that meets the requirements is obtained.

[0069] As Figures 2 - 3 shown, among them, the water distribution actuator of the cooling tower includes a water distribution surface, a shaft 1, an electric gate 2, a branch water tank 3, a first branch pipe 4 and a second branch pipe 5; the water distribution surface is composed of areas A1, A2, A3, A4, A5, A6, A7, and A8, and there are several first branch pipes 4 and second branch pipes 5 on the water distribution surface; there is a branch water tank 3 on the shaft 1, and the branch water tank 3 is composed of the first branch water tank, the second branch water tank, the third branch water tank and the fourth branch water tank; the first branch water tank is arranged between A1 and A2; the second branch water tank is arranged between A3 and A4; the third branch water tank is arranged between A5 and A6; the fourth branch water tank is arranged between A7 and A8; and there are electric gates 2 on the first branch water tank, the second branch water tank, the third branch water tank and the fourth branch water tank.

[0070] Among them, the specific process of obtaining the trained Kriging surrogate model in step S4 is as follows:

[0071] Take the circulating water flow , the inlet water temperature of the cooling tower , the ambient temperature , the ambient relative humidity , the side wind speed , the atmospheric pressure as the optimization variables, and use Latin hypercube experimental design to sample within the optimization variable interval to calculate and generate sample points ; represents the nth sample element;

[0072] Input the sample points into the CFD simulation model of the natural draft cooling tower that meets the requirements for calculation to obtain the sample point response value, that is, the average wind speed in the fan-shaped area ; represents the average wind speed in the nth fan-shaped area;

[0073] Construct a Kriging surrogate model, expressed as: For the Kriging surrogate model, the regression function is selected as the quadratic function, and the covariance function is selected as the cubic spline function; represents the predicted output of the Kriging surrogate model; is the polynomial matrix of x; x represents the vector of input variables; is the regression coefficient; represents the mean value of y(x); represents a Gaussian random process with a mean of 0;

[0074] The mean squared error is used to evaluate the accuracy of the Kriging surrogate model, which is expressed as: , is the predicted value of the i-th sample point; represents the response value of the i-th sampling point obtained by calculating through the CFD simulation model of the natural draft cooling tower that meets the requirements; n represents the number of sample points; MSE represents the mean squared error; when MSE ≤ 0.25, it is considered that the prediction accuracy of the Kriging surrogate model meets the requirements, and when MSE > 0.25, it is considered that the prediction accuracy of the Kriging surrogate model does not meet the requirements. To improve the prediction accuracy, 6 sample points are added, that is, n = n + 6, then the response values of the added 6 sample points are calculated, and the Kriging surrogate model is reconstructed. The prediction accuracy of the Kriging surrogate model is evaluated through the mean squared error until the prediction accuracy of the Kriging surrogate model meets the requirements, and the trained Kriging surrogate model is obtained.

[0075] Among them, in step S5, the adjusted initial circulating water flow rate in the fan-shaped area is obtained, and the specific process is as follows:

[0076] The circulating water flow rate is evenly distributed to the areas of the cooling tower water distribution actuator. The initial circulating water flow rate in the area of the cooling tower water distribution actuator is , ; represents the initial circulating water flow rate in the area of the j-th cooling tower water distribution actuator;

[0077] The average wind speed in the fan-shaped area is normalized to eliminate the influence of dimensions. The normalization formula is: , is the average surface wind speed in the normalized fan-shaped area; represents the original average wind speed of the j-th fan-shaped area;

[0078] According to the proportion of the average surface wind speed in the normalized fan-shaped area, the initial circulating water flow rate in the area of the cooling tower water distribution actuator is adjusted, and the adjusted initial circulating water flow rate in the fan-shaped area is .

[0079] Among them, the water distribution adjustment in step S6 is specifically as follows:

[0080] Circulating water flow Enters the vertical shaft 1, and according to the adjusted initial circulating water flow in the fan-shaped area, the opening of the electric gate 2 is controlled to adjust the circulating water flow in the branch water tank 3 , the circulating water flow Then flows into the second branch pipe 5 through the first branch pipe 4, and finally completes the water distribution adjustment of the cooling tower water distribution actuator.

[0081] As Figure 4 shown, among them, a natural ventilation cooling tower dynamic water distribution system for the above-mentioned natural ventilation cooling tower dynamic water distribution method includes:

[0082] A data acquisition module, which is used to test the thermal performance and resistance performance of the natural ventilation cooling tower to obtain the performance parameters of the cooling tower. The natural ventilation cooling tower includes a cooling tower water distribution actuator, and processes the performance parameters of the cooling tower to obtain the thermal performance and resistance performance;

[0083] A three-dimensional modeling and mesh processing module, which is used to perform three-dimensional modeling on the natural ventilation cooling tower to obtain a three-dimensional model of the natural ventilation cooling tower calculation domain, and processes the three-dimensional model of the natural ventilation cooling tower calculation domain to obtain a mesh model of the natural ventilation cooling tower calculation domain;

[0084] A CFD simulation model construction and correction module, which is used to construct a natural ventilation cooling tower CFD simulation model based on the natural ventilation cooling tower calculation domain mesh model, thermal performance and resistance performance, calculates using the performance parameters of the cooling tower as the boundary conditions of the natural ventilation cooling tower CFD simulation model to obtain the simulated value of the cooling water temperature out of the tower, and compares the simulated value of the cooling water temperature out of the tower with the performance parameters of the cooling tower to obtain a natural ventilation cooling tower CFD simulation model that meets the requirements;

[0085] An offline training and surrogate model construction module, which is used to process the performance parameters of the cooling tower by using the natural ventilation cooling tower CFD simulation model that meets the requirements combined with the Latin hypercube experimental design to obtain the response values of the sample points, constructs a Kriging surrogate model, and trains the Kriging surrogate model with the response values of the sample points to obtain a trained Kriging surrogate model;

[0086] An online calculation and flow dynamic distribution module, which is used to collect the average wind speed in the fan-shaped area of the cooling tower water distribution actuator through the trained Kriging surrogate model, calculate the average wind speed in the fan-shaped area to obtain the adjusted initial circulating water flow in the fan-shaped area;

[0087] The water distribution adjustment execution module is used to perform water distribution adjustment on the cooling tower water distribution actuator based on the adjusted initial circulating water flow rate in the fan-shaped area.

[0088] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A dynamic water distribution method for natural draft cooling towers, characterized in that, Including the following steps: Step S1: Conduct thermal performance and resistance performance tests on the natural draft cooling tower to obtain the performance parameters of the cooling tower. The natural draft cooling tower includes a cooling tower water distribution actuator. Process the performance parameters of the cooling tower to obtain the thermal performance and resistance performance; Step S2: Perform three-dimensional modeling on the natural draft cooling tower to obtain a three-dimensional model of the natural draft cooling tower calculation domain. Process the three-dimensional model of the natural draft cooling tower calculation domain to obtain a grid model of the natural draft cooling tower calculation domain; Step S3: Build a CFD simulation model of the natural draft cooling tower based on the grid model of the natural draft cooling tower calculation domain, thermal performance, and resistance performance. Use the performance parameters of the cooling tower as the boundary conditions for the CFD simulation model of the natural draft cooling tower to perform calculations, obtain the simulated value of the water temperature leaving the tower of the natural draft cooling tower, and compare the simulated value of the water temperature leaving the tower of the natural draft cooling tower with the performance parameters of the cooling tower to obtain a CFD simulation model of the natural draft cooling tower that meets the requirements; Step S4: Use the CFD simulation model of the natural draft cooling tower that meets the requirements, combined with the Latin hypercube experimental design, to process the performance parameters of the cooling tower to obtain the response values of the sample points. Build a Kriging surrogate model, and use the response values of the sample points to train the Kriging surrogate model to obtain the trained Kriging surrogate model; Step S5: Collect the average wind speed in the fan-shaped area of the cooling tower water distribution actuator through the trained Kriging surrogate model, calculate the average wind speed in the fan-shaped area, and obtain the adjusted initial circulating water flow rate in the fan-shaped area; Step S6: Adjust the water distribution of the cooling tower water distribution actuator based on the adjusted initial circulating water flow rate in the fan-shaped area.

2. The dynamic water distribution method of a natural draft cooling tower according to claim 1, characterized in that: In step S1, the performance parameters of the cooling tower are divided into input performance parameters and output performance parameters. The input performance parameters include: circulating water flow rate , the inlet water temperature of the cooling tower , the ambient temperature , the ambient relative humidity , the crosswind speed , the air velocity at the water distribution packing , the atmospheric pressure , the resistance of the water distribution packing ; represents the k-th value in the circulating water flow rate sequence; represents the k-th value in the inlet water temperature sequence of the cooling tower; represents the k-th value in the ambient temperature sequence; represents the k-th value in the ambient relative humidity sequence; represents the k-th value in the crosswind speed sequence; represents the k-th value in the air velocity sequence at the water distribution packing; represents the k-th value in the atmospheric pressure sequence; represents the k-th value in the resistance sequence of the water distribution packing; The output performance parameters include: the outlet water temperature of the cooling tower , the outlet air temperature of the tower ; represents the k-th value in the sequence of the outlet water temperature of the cooling tower; represents the k-th value in the sequence of the outlet air temperature of the tower.

3. A natural ventilation cooling tower dynamic water distribution method according to claim 2, characterized in that: For the thermal performance and resistance performance in Step S1, the specific process is as follows: Fitting the performance parameters of the cooling tower through the Merkel equation to obtain the thermal performance , where , ; represents the thermal performance parameter of the cooling tower; represents the ventilation density; represents the water spray density; represents the functional relationship between the two variables ga and qw; represents the air density; represents the cross-sectional area of the cooling tower packing Fit the performance parameters of the cooling tower to obtain the resistance performance ; represents the functional relationship between two variables and qw.

4. A dynamic water distribution method for a natural draft cooling tower according to claim 3, characterized in that: For building the CFD simulation model of the natural draft cooling tower in Step S3, the specific process is as follows: By calculating the thermal performance, the heat transfer coefficient per unit volume of the packing is obtained , take as the mass transfer model of the packing area, and take as the heat transfer model of the packing area. The natural draft cooling tower includes a packing area, and the mass transfer model and the heat transfer model are loaded into the packing area of the natural draft cooling tower through CFD software; c p,a is the specific heat capacity of moist air, and Le f is the Lewis factor of moist air; By calculating the resistance performance, obtain the viscous resistance coefficient C1 and inertial resistance coefficient C2 of the packing area of the natural draft cooling tower. Build a CFD simulation model of the natural draft cooling tower based on the viscous resistance coefficient C1, inertial resistance coefficient C2, and the grid model of the natural draft cooling tower calculation domain.

5. A dynamic water distribution method for a natural draft cooling tower according to claim 4, characterized in that: The basic unit size of the grid of the three-dimensional model of the natural draft cooling tower calculation domain is d; For obtaining the CFD simulation model of the natural draft cooling tower that meets the requirements in Step S3, the specific process is as follows: Take the i-th cooling tower outlet water temperature among the output performance parameters as the boundary condition of the CFD simulation model of the natural draft cooling tower for calculation, and obtain the simulated value of the outlet water temperature of the natural draft cooling tower ; ; The simulated outlet water temperature of the natural draft cooling tower is compared with the outlet water temperature of the i-th cooling tower in the output performance parameters . When the relative error Error between the simulated outlet water temperature of the natural draft cooling tower and the outlet water temperature of the i-th cooling tower in the output performance parameters is greater than or equal to 5%, the accuracy of the CFD simulation model of the natural draft cooling tower does not meet the requirements. Go to step S2 and adjust the basic grid cell size d to 0.9d until the relative error Error is less than or equal to 5%. When the relative error between the simulated outlet water temperature of the natural draft cooling tower and the outlet water temperature of the i-th cooling tower in the output performance parameters is less than 5%, the accuracy of the CFD simulation model of the natural draft cooling tower meets the requirements, that is, a CFD simulation model of the natural draft cooling tower that meets the requirements is obtained.

6. A dynamic water distribution method for a natural draft cooling tower according to claim 5, characterized in that: The water distribution actuator of the cooling tower includes a water distribution surface, a shaft, an electric gate, branch water troughs, a first branch pipe, and a second branch pipe; the water distribution surface is composed of areas A1, A2, A3, A4, A5, A6, A7, and A8, and several first branch pipes and second branch pipes are arranged on the water distribution surface; branch water troughs are arranged on the shaft, and the branch water troughs are composed of a first branch water trough, a second branch water trough, a third branch water trough, and a fourth branch water trough; the first branch water trough is arranged between A1 and A2; the second branch water trough is arranged between A3 and A4; the third branch water trough is arranged between A5 and A6; the fourth branch water trough is arranged between A7 and A8; and electric gates are arranged on the first branch water trough, the second branch water trough, the third branch water trough, and the fourth branch water trough.

7. A natural ventilation cooling tower dynamic water distribution method according to claim 6, characterized in that: In step S4, the trained Kriging surrogate model is obtained, and the specific process is as follows: Take the circulating water flow rate , the inlet water temperature of the cooling tower , the ambient temperature , the ambient relative humidity , the side wind speed , the atmospheric pressure as the optimization variables, and use the Latin hypercube experimental design to sample within the optimization variable range to calculate and generate sample points ; represents the nth sample element; Input the sample points into the CFD simulation model of a natural draft cooling tower that meets the requirements for calculation to obtain the response values of the sample points, i.e., the average wind speed in the fan-shaped area ; represents the average wind speed in the nth fan-shaped area; Construct a Kriging surrogate model, which means: , the regression function of the Kriging surrogate model selects a quadratic function, and the covariance function of the Kriging surrogate model selects a cubic spline function; represents the predicted output of the Kriging surrogate model; is a polynomial matrix of x; x represents a vector of input variables; is the regression coefficient; represents the mean of y(x); represents a Gaussian random process with a mean of 0; The accuracy of the Kriging surrogate model is evaluated using the mean square error, which is expressed as: , is the predicted value of the i-th sample point; represents the response value of the i-th sampling point obtained by calculating through the CFD simulation model of the natural draft cooling tower that meets the requirements; n represents the number of sample points; represents the mean square error; when MSE ≤ 0.25, it is considered that the prediction accuracy of the Kriging surrogate model meets the requirements. When MSE > 0.25, it is considered that the prediction accuracy of the Kriging surrogate model does not meet the requirements. Six sample points are added, that is, n = n + 6. Then, the response values of the six added sample points are calculated, and the Kriging surrogate model is reconstructed. The prediction accuracy of the Kriging surrogate model is evaluated through the mean square error until the prediction accuracy of the Kriging surrogate model meets the requirements, and the trained Kriging surrogate model is obtained.

8. A dynamic water distribution method for a natural draft cooling tower according to claim 7, characterized in that: In step S5, the adjusted initial circulating water flow rate of the fan-shaped area is obtained, and the specific process is as follows: The circulating water flow rate is evenly distributed to the areas of the cooling tower water distribution actuators. The initial circulating water flow rate in the areas of the cooling tower water distribution actuators is , ; represents the initial circulating water flow rate in the area of the j-th cooling tower water distribution actuator; Normalize the average wind speed in the fan-shaped area, and the normalization formula is: , is the average surface wind speed in the fan-shaped area after normalization; represents the original average wind speed in the j-th fan-shaped area; Adjust the initial circulating water flow of the regional cooling tower water distribution actuator according to the proportion of the average wind speed in the fan-shaped area after normalization, and obtain the adjusted initial circulating water flow of the fan-shaped area as .

9. A dynamic water distribution method for a natural draft cooling tower according to claim 8, characterized in that: In step S6, water distribution adjustment is carried out, and the specific process is as follows: Circulating water flow rate Enter the shaft, and according to the adjusted initial circulating water flow rate in the fan-shaped area, control the opening of the electric gate to adjust the circulating water flow rate in the branch water tank , the circulating water flow rate Then flow into the second branch pipe through the first branch pipe, and finally complete the water distribution adjustment of the cooling tower water distribution actuator.

10. A natural ventilation cooling tower dynamic water distribution system, for use in the natural ventilation cooling tower dynamic water distribution method according to any one of claims 1 to 9, characterized in that, It includes: A data acquisition module, which is used to test the thermal performance and resistance performance of a natural draft cooling tower to obtain the performance parameters of the cooling tower. The natural draft cooling tower includes a water distribution actuator of the cooling tower, and processes the performance parameters of the cooling tower to obtain the thermal performance and resistance performance; A three-dimensional modeling and mesh processing module, which is used to perform three-dimensional modeling on the natural draft cooling tower to obtain a three-dimensional model of the calculation domain of the natural draft cooling tower, and processes the three-dimensional model of the calculation domain of the natural draft cooling tower to obtain a mesh model of the calculation domain of the natural draft cooling tower; A CFD simulation model construction and correction module, which is used to construct a CFD simulation model of the natural draft cooling tower based on the mesh model of the calculation domain of the natural draft cooling tower, thermal performance, and resistance performance, calculates using the performance parameters of the cooling tower as the boundary conditions of the CFD simulation model of the natural draft cooling tower to obtain the simulated value of the water temperature leaving the tower of the natural draft cooling tower, and compares the simulated value of the water temperature leaving the tower of the natural draft cooling tower with the performance parameters of the cooling tower to obtain a CFD simulation model of the natural draft cooling tower that meets the requirements; An offline training and surrogate model construction module, which is used to process the performance parameters of the cooling tower by using the CFD simulation model of the natural draft cooling tower that meets the requirements combined with the Latin hypercube experimental design to obtain the response values of the sample points, constructs a Kriging surrogate model, and trains the Kriging surrogate model with the response values of the sample points to obtain the trained Kriging surrogate model; An online calculation and flow dynamic distribution module, which is used to collect the average wind speed of the fan-shaped area of the water distribution actuator of the cooling tower through the trained Kriging surrogate model, calculate the average wind speed of the fan-shaped area to obtain the adjusted initial circulating water flow rate of the fan-shaped area; A water distribution adjustment execution module, which is used to perform water distribution adjustment on the water distribution actuator of the cooling tower based on the adjusted initial circulating water flow rate of the fan-shaped area.

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