Full-weather self-adaptive energy-saving control method and system for closed cooling tower

Abstract

The application provides a closed cooling tower full-weather self-adaptive energy-saving control method and system, and relates to the technical field of energy-saving control of industrial cooling equipment. The method comprises the following steps: using steady-state data to calibrate the dry and wet working condition correlation formula coefficient; collecting parameters in real time, correcting air density and mass flow rate by using the ideal gas state equation, and obtaining real-time working conditions; identifying freezing risk according to the inlet wet bulb temperature and the outlet estimated temperature double criteria, and dividing the normal and anti-freezing working conditions; in the normal working condition, the heat dissipation is calculated by using the wet working condition coefficient and double-layer iteration, and the three-dimensional minimum total energy consumption combination is searched; in the anti-freezing working condition, the heat dissipation is calculated by using the dry working condition coefficient and double-layer iteration, the minimum energy consumption of the dry working condition is searched, and otherwise, the wet working condition is searched in the constraint; the frequency conversion instruction is converted to control the pump, and the full-weather self-adaptive energy-saving anti-freezing is realized. The problems of insufficient integration of parameter calibration-performance calculation-frequency conversion optimization, poor cooperation of multiple mechanisms and weak anti-freezing are solved.

Description

Technical Field

[0001] This invention relates to the field of energy-saving control technology for industrial cooling equipment, and more specifically, to a closed-loop cooling tower with all-weather adaptive energy-saving control method and system. Background Technology

[0002] A closed-circuit cooling tower (also known as a closed-loop cooling tower or evaporative air cooler) is a highly efficient heat dissipation device that circulates process fluids within a closed coil, achieving indirect heat exchange through the synergistic effect of sprayed water and air. Compared to open-circuit cooling towers, closed-circuit cooling towers avoid the problems of media contamination and loss caused by direct contact between the cooling medium and the outside air. Therefore, they are widely used in industrial fields such as chemical, electronics, metallurgy, and data centers. As a core heat dissipation device, its operating efficiency directly affects the stability and operating costs of the entire industrial system. With the deepening of energy conservation and emission reduction policies and the continuous improvement of the reliability requirements of industrial systems for cooling equipment, the control technology of closed-circuit cooling towers has undergone a development process from traditional start-stop control to variable frequency control, and from single-variable regulation to multi-variable synergy. In recent years, patent applications have involved energy-saving control systems for closed-circuit cooling towers. For example, some solutions use multi-dimensional sensing modules to collect target parameters and make intelligent decisions based on operating condition classification rules. Other solutions employ optimization algorithms to find the optimal combination of fan frequency, spray pump frequency, and the number of cooling towers in operation while meeting condensation load requirements. Still other technologies introduce variable frequency control instead of on / off control for spray pumps in multi-tower control systems and use differential evolution algorithms for optimization. Furthermore, regarding cooling tower performance calculations, existing solutions use energy conservation and basic heat transfer formulas for thermodynamic analysis and iterative calculations to verify the coil heat transfer coefficient. In terms of anti-freezing control, current technologies mostly employ the addition of physical anti-freezing devices or electric heating to achieve winter anti-freezing protection.

[0003] However, the aforementioned existing technologies still have the following shortcomings: First, there is a lack of collaborative optimization capabilities among multiple actuators. Most existing variable frequency control schemes only adjust the fan frequency as a single variable, or although they mention the collaboration between the fan and the spray pump, they do not provide a clear three-dimensional joint optimization logic and method; even if a few schemes involve multi-variable optimization, their optimization space does not fully cover the three dimensions of the fan, spray pump, and process pump, making it difficult to guarantee the global optimization of the total system energy consumption while meeting the heat dissipation load.

[0004] Secondly, the performance calculation model lacks dynamic correction and adaptive capabilities. Existing closed-loop cooling tower control systems typically pre-set control logic and parameter thresholds based on the ideal performance curves of the equipment at the time of manufacture. They cannot dynamically perceive and correct the heat exchange performance degradation caused by factors such as increased equipment operating years, scaling, and aging. At the same time, most existing performance calculation methods do not consider the systematic impact of air density changes on heat dissipation load calculation in high-altitude, low-pressure environments, nor do they organically integrate the three core links of parameter calibration, performance calculation, and frequency conversion control. These three are often operated as independent modules, forming data silos and control gaps.

[0005] Third, the seasonal adaptability and antifreeze control strategies are weak. Existing closed-loop cooling towers may affect system efficiency in summer due to insufficient heat exchange, and may cause pipes to freeze and crack in winter due to excessively low water temperature. Traditional antifreeze control methods either continue to run all equipment, resulting in energy waste, or rely on high-cost solutions such as adding electric heating devices or modifying physical structures. Although existing solutions propose the idea of ​​judging the switching between dry and wet conditions based on environmental parameters, they have failed to establish a complete independent thermodynamic calculation model for dry conditions and a refined optimization mechanism under antifreeze constraints.

[0006] In summary, existing technologies have not yet achieved the organic integration of the three-in-one architecture of "parameter calibration - performance calculation - frequency conversion optimization" for closed-loop cooling towers, and lack a complete technical solution from dynamic understanding of equipment characteristics to global optimization of operation strategies. Summary of the Invention

[0007] The purpose of this invention is to provide a closed-loop cooling tower all-weather adaptive energy-saving control method and system, which aims to solve the problems of insufficient integration of parameter calibration, performance calculation and frequency conversion optimization, poor coordination of multiple mechanisms and weak anti-freezing in the existing closed-loop cooling tower control technology.

[0008] This invention is achieved through the following technical solution: A closed-loop cooling tower all-weather adaptive energy-saving control method includes the following steps: A power-law correlation between the air-side enthalpy efficiency and the series correlation between the overall heat transfer coefficient and thermal resistance of a closed cooling tower is constructed. Multiple sets of steady-state operating data are imported, and after solving the initial values ​​of the coefficients through step-by-step linearization, global optimization is performed through the nonlinear least squares method to complete the calibration of the coefficients of the dry and wet operating conditions. Real-time acquisition of inlet air parameters, process fluid parameters, and real-time heat dissipation load; dynamic calculation of current air density based on ideal gas law; correction of mass flow rate and heat exchange calculation basis on the air side; and obtaining real-time operating condition calculation parameters. Based on real-time operating condition calculation parameters, the inlet air wet-bulb temperature and the estimated process fluid outlet temperature are extracted as dual criteria to determine the freezing risk, and the freezing risk results are divided into normal operating conditions and anti-freezing operating conditions. If it is determined to be a normal operating condition, the calibrated wet operating condition correlation coefficient is used as the calculation benchmark. The heat dissipation of each frequency combination is calculated by a two-layer iterative algorithm with outer layer iterative outlet air dry bulb temperature and inner layer iterative spray water film temperature. The search is carried out in the three-dimensional frequency space composed of fan frequency, spray pump frequency and process pump frequency to select the normal optimal frequency combination that meets the heat dissipation load and has the minimum total energy consumption. If the condition is determined to be antifreeze, the heat dissipation is calculated using a two-layer iterative algorithm based on the calibrated dry condition correlation coefficient and the outer layer iterative outlet air dry bulb temperature and the inner layer iterative coil outer wall temperature. The lowest energy consumption scheme under dry condition is searched. If the load is not met for several conditions, wet condition optimization is performed under the preset upper and lower limits of the spray pump frequency and fan frequency to obtain the optimal frequency combination for antifreeze. The conventional optimal frequency combination or the antifreeze optimal frequency combination is converted into variable frequency control commands to drive the operation of the fan, spray pump and process pump.

[0009] Optionally, the power-law correlation of the air-side enthalpy efficiency is shown in the following equation:

[0010] in, For air-side enthalpy efficiency; Wind speed on the windward side; This refers to the volumetric flow rate of the spray circulating water. This represents the total heat exchange area of ​​the coil. This refers to the number of coil rows; , , and All are parameters to be calibrated; The overall heat transfer coefficient and thermal resistance series correlation formula is shown below:

[0011] in, The overall heat transfer coefficient under wet conditions; The flow velocity of the process fluid inside the pipe; , , , ,and All of these are parameters to be calibrated.

[0012] Optionally, the calibration of the correlation coefficients for wet and dry operating conditions includes calibration for wet operating conditions and calibration for dry operating conditions: During wet condition calibration, the air-side enthalpy efficiency under each steady-state condition is solved point by point in reverse. With the overall heat transfer coefficient After performing a logarithmic transformation on the power-law correlation of air-side enthalpy efficiency, the parameters were regressed using the least squares method. , , and For the series correlation between the overall heat transfer coefficient and thermal resistance, first screen sample points with spray density higher than a preset threshold to regress the pipe parameters. and Then fix the internal parameters and revert to the external parameters. , and Using the obtained results as initial values, the Levenberg-Marquardt algorithm is used to perform global nonlinear least squares optimization on all samples; During dry condition calibration, the spray density and air-side enthalpy efficiency are set to zero, and the external thermal resistance term in the overall heat transfer coefficient dry condition correlation adopts a dry convection correlation coefficient independent of the wet condition. The internal parameters of the pipe are... and Maintain consistency with the calibration results under wet operating conditions.

[0013] Optionally, the specific process of dynamically calculating the current air density based on the ideal gas law and correcting the air-side mass flow rate and heat transfer calculation reference is as follows: Real-time acquisition of inlet air dry bulb temperature and atmospheric pressure The dry bulb temperature of the inlet air Converting Celsius to absolute temperature The air density under the current environment is calculated using the ideal gas law for dry air. As shown in the following formula:

[0014] in, The gas constant for air is 287.05 J / (kg·K); The calculated air density The standard air density, which replaces the preset standard air density, is used as the air density benchmark for calculating air-side parameters in the current performance calculation and optimization cycle. This benchmark is then used to calculate the corrected air mass flow rate, as shown in the following formula:

[0015] in, This is the corrected air mass flow rate; Air volume flow rate; With the corrected air mass flow rate As for the heat gain on the air side in subsequent calculations The calculation input is shown in the following formula:

[0016] in, and These are the inlet air enthalpy and the outlet air enthalpy, respectively.

[0017] Optionally, the specific process of calculating the heat dissipation of each frequency combination using the two-layer iterative algorithm of outer layer iterative outlet air dry-bulb temperature and inner layer iterative spray water film temperature is as follows: Set the outer iteration variable to the outlet air dry-bulb temperature. The inner layer iteration variable is set to the spray water film temperature. ; In the outer iteration, the moisture content of the outlet air is calculated based on the given assumed dry-bulb temperature of the outlet air. and enthalpy of outlet air ; enthalpy efficiency on the air side Definition of enthalpy of outlet air Determined by the following formula:

[0018] in, Temperature of the spray water film The corresponding enthalpy of saturated air; In the inner layer iteration, based on the given assumed value of the spray water film temperature and combined with the assumed dry-bulb temperature of the outlet air in the outer layer, the moisture content of the outlet air is calculated. The constraint is that the moisture content of the air in the mouth is less than or equal to the saturated moisture content at the spray water film temperature; Calculate the process fluid outlet temperature based on air-side energy conservation. As shown in the following formula:

[0019] in, This refers to the mass flow rate of the process fluid. The specific heat at constant pressure for process fluids; Calculate the total heat transfer of the coil using the heat transfer equation. As shown in the following formula:

[0020] in, The overall heat transfer coefficient under wet conditions; This represents the total heat exchange area of ​​the coil. It is the logarithmic mean temperature difference between the spray water film temperature and the inlet and outlet temperatures of the process fluid; Construction of wet working conditions comprehensive error As shown in the following formula:

[0021] in, For correction factors, and ; This is the theoretical water film temperature calculated based on heat balance. With the goal of minimizing the overall error under wet conditions, a two-layer iterative search strategy is adopted to traverse the possible combinations of outlet air dry-bulb temperature and spray water film temperature. When the overall error under wet conditions is less than the preset convergence tolerance, the air-side heat gain under the current combination is output. This represents the heat dissipation for this frequency combination.

[0022] Optionally, the specific process of traversing and searching within the three-dimensional frequency space comprised of the fan frequency, spray pump frequency, and process pump frequency to select the conventional optimal frequency combination that satisfies the heat dissipation load and minimizes total energy consumption is as follows: Determine the fan frequency Spray pump frequency and process pump frequency Each search range and discrete step size are used to construct a three-dimensional discrete frequency combination space; For each frequency combination in the three-dimensional frequency space, calculate the wind turbine shaft power at the current frequency according to the similarity law. Spray pump shaft power Process pump shaft power As shown in the following formula:

[0023]

[0024]

[0025] in, , and These are the rated shaft power of the fan, spray pump, and process pump, respectively. , and These are the corresponding rated frequencies; Calculate the air volume flow rate at the current frequency using the similarity law. Spray circulating water volume flow rate and process fluid volumetric flow rate As shown in the following formula:

[0026]

[0027]

[0028] in, , and These are the rated volumetric flow rates of the fan, spray pump, and process pump, respectively. Based on the calculated air volume flow rate Spray circulating water volume flow rate Calculate the heat dissipation under the current frequency combination based on the process fluid volume flow rate; Filter all frequency combinations that satisfy the condition that the heat dissipation is greater than or equal to the real-time heat dissipation load under the current frequency combination, and select the total input power from the combinations that meet the condition. The smallest group is output as the conventional optimal frequency combination, where .

[0029] Optionally, the specific process of calculating the heat dissipation using the two-layer iterative algorithm of outer layer iterative outlet air dry-bulb temperature and inner layer iterative coil outer wall temperature is as follows: Set the outer iteration variable to the outlet air dry-bulb temperature. The inner iteration variable is set to the average temperature of the outer wall of the coil. ; Under dry operating conditions, with the spray system off and no moisture exchange on the air side, the inlet moisture content is... With export moisture content Equal, enthalpy of outlet air Calculated by the following formula:

[0030] in, The specific heat of air at constant pressure; The latent heat of vaporization of water at 0℃; It is the specific heat of water vapor at constant pressure; Calculate the process fluid outlet temperature based on air-side energy conservation. As shown in the following formula:

[0031] Calculate the total heat transfer of the coil using the heat transfer equation. As shown in the following formula:

[0032] in, The overall heat transfer coefficient under dry operating conditions; This is the logarithmic mean temperature difference between the average temperature of the outer wall of the coil and the inlet and outlet temperatures of the process fluid; Comprehensive error under dry working conditions As shown in the following formula:

[0033] With the goal of minimizing the overall error under dry operating conditions, a two-layer iterative search strategy is adopted to traverse the combinations of outlet air dry-bulb temperature and coil outer wall average temperature, and physical rationality constraints are applied, as shown in the following formula:

[0034] when When the output is less than the preset convergence tolerance, output the air-side heat gain under the current combination. As heat dissipation under dry operating conditions.

[0035] Optionally, the specific process of performing wet condition optimization under preset upper and lower limits of the spray pump frequency and fan frequency to obtain the optimal frequency combination for antifreeze is as follows: Set the lower limit frequency for antifreeze spray pump frequency and the upper limit frequency for antifreeze fan frequency; wherein, the lower limit frequency for antifreeze is the minimum spray pump operating frequency that maintains continuous water film coverage on the coil surface; the upper limit frequency for antifreeze is the maximum fan operating frequency that prevents the water film from evaporating and becoming too cold; When it is determined that there is a risk of freezing and the heat dissipation under dry conditions cannot meet the real-time heat dissipation load, in the three-dimensional frequency space composed of fan frequency, spray pump frequency and process pump frequency, the search range of fan frequency is constrained to less than or equal to the upper limit frequency of antifreeze, the search range of spray pump frequency is constrained to greater than or equal to the lower limit frequency of antifreeze, and the process pump frequency is kept within its normal operating frequency range, forming a restricted three-dimensional frequency space. In the restricted three-dimensional frequency space, each frequency combination is traversed, and the fan shaft power, spray pump shaft power and process pump shaft power at the current frequency are calculated according to the similarity law. The heat dissipation at the current frequency combination is calculated by calling the calibrated wet condition correlation coefficient and the two-layer iterative algorithm. Filter all frequency combinations that satisfy the condition that the heat dissipation is greater than or equal to the real-time heat dissipation load under the current frequency combination. Among the combinations that meet the condition, select the one with the smallest total input power as the optimal frequency combination output for antifreeze.

[0036] Optionally, after real-time acquisition of inlet air parameters, and before extracting the inlet air wet-bulb temperature and the estimated process fluid outlet temperature as dual criteria, the method further includes a step of inlet air state calculation: Real-time acquisition of inlet air dry bulb temperature Relative humidity of inlet air and atmospheric pressure ; Calculate the partial pressure of saturated water vapor As shown in the following formula:

[0037] Calculate the water vapor partial pressure based on the saturated water vapor partial pressure and the relative humidity of the inlet air. As shown in the following formula:

[0038] Calculate the moisture content of the inlet air based on the partial pressure of water vapor and atmospheric pressure. As shown in the following formula:

[0039] Calculate the enthalpy of the inlet air based on its dry-bulb temperature and humidity. As shown in the following formula:

[0040] in, The specific heat of air at constant pressure; The latent heat of vaporization of water at 0℃; It is the specific heat of water vapor at constant pressure; wet-bulb temperature of inlet air As an unknown quantity, a trial-and-error iterative method is used to solve it: Set an initial guess value for the wet-bulb temperature. Calculate the moisture content and enthalpy of saturated air under this guess value, and substitute them into the wet-bulb temperature definition equation for verification. If the verification error is greater than the preset tolerance, adjust the wet-bulb temperature guess value and repeat the verification calculation until the verification error is less than the preset tolerance. Output the current guess value as the inlet air wet-bulb temperature. The wet-bulb temperature definition equation is shown below:

[0041] in, This is the enthalpy of saturated air; The moisture content of saturated air; The specific heat at constant pressure for process fluids.

[0042] Based on the same inventive concept, this invention also provides a closed-loop cooling tower all-weather adaptive energy-saving control system for implementing the aforementioned closed-loop cooling tower all-weather adaptive energy-saving control method, comprising: The data acquisition module is used to collect inlet air parameters, process fluid parameters, and equipment operating parameters in real time. The parameter calibration module, connected to the data acquisition module, is used to import multiple sets of steady-state operating condition data, construct the power law correlation of air-side enthalpy efficiency and the series correlation of total heat transfer coefficient and thermal resistance, solve the initial value of the coefficients stepwise linearization, and then perform global optimization through nonlinear least squares method to complete the calibration of the coefficients of the dry and wet operating condition correlation, and output the calibrated correlation coefficients to the performance calculation module. The performance calculation module is connected to the parameter calibration module and the data acquisition module respectively. It is used to dynamically calculate the current air density based on the ideal gas law according to the real-time collected inlet air parameters to correct the air-side mass flow rate, and call the corresponding dry or wet condition double-layer iterative algorithm to calculate the heat dissipation according to the freezing risk judgment result. The calculated heat dissipation and temperature status are output to the frequency conversion optimization module. The frequency conversion optimization module, connected to both the performance calculation module and the data acquisition module, is used to search within a three-dimensional frequency space consisting of the fan frequency, spray pump frequency, and process pump frequency, with the real-time heat dissipation load as a constraint and the minimum total input power of the fan, spray pump, and process pump as the optimization objective. It outputs the optimal frequency combination that satisfies the heat dissipation load. The frequency conversion optimization module includes a conventional optimization unit and an anti-freeze optimization unit. The conventional optimization unit outputs the conventional optimal frequency combination when there is no risk of freezing. The anti-freeze optimization unit prioritizes dry condition optimization when there is a risk of freezing. If several conditions do not meet the load, it outputs the anti-freeze optimal frequency combination under the constraint that the spray pump frequency is not lower than a preset lower limit and the fan frequency is not higher than a preset upper limit. The control output module is connected to the frequency conversion optimization module and is used to convert the optimal frequency combination into frequency conversion control commands to drive the fan, spray pump and process pump to run respectively.

[0043] The technical solution of the present invention has at least the following advantages and beneficial effects: By organically integrating correlation coefficient calibration, dynamic density correction and bi-layer iterative calculation, and three-dimensional frequency joint optimization, the shortcomings of traditional solutions, such as the separation of the three core links, the formation of data silos and control gaps, are overcome. A complete technical closed loop is constructed from equipment characteristic self-learning to global optimization of full-condition operation strategy, which improves the adaptive energy-saving control capability of closed cooling towers in all climates and throughout their entire life cycle.

[0044] By establishing a power-law correlation between air-side enthalpy efficiency and a series correlation between the overall heat transfer coefficient and thermal resistance, and by adopting a calibration method of step-by-step linearization for initial value calculation and nonlinear least squares global optimization, the heat transfer characteristic coefficients under dry and wet conditions can be dynamically obtained based on actual steady-state operating data. The heat transfer performance degradation caused by scaling, aging, etc. can be detected in real time and the model can be corrected, ensuring the accuracy of the performance calculation model and the robustness of the control system after long-term operation of the equipment.

[0045] Real-time acquisition of inlet air parameters, dynamic calculation of current air density based on the ideal gas law, and correction of air-side mass flow rate and heat transfer calculation benchmarks accordingly. This effectively eliminates systematic deviations in heat dissipation load calculation caused by air density changes in high-altitude, low-pressure environments, enabling the control method to maintain high-precision thermal calculation and optimization decision-making across all altitudes and pressure ranges.

[0046] The algorithm traverses and searches within a three-dimensional frequency space spanned by the fan frequency, spray pump frequency, and process pump frequency. It combines an outer-layer iterative algorithm with the outlet dry-bulb temperature and the inner-layer iterative spray water film temperature (wet condition) or coil outer wall temperature (dry condition) to accurately calculate the heat dissipation of each frequency combination. Finally, it selects the optimal frequency combination that meets the heat dissipation load and minimizes the total system energy consumption. This expands the actuator collaborative optimization dimension from a single variable or partially bivariate to a complete three-variable, ensuring optimal global energy consumption and reducing the operating cost of the cooling system.

[0047] Freezing risk assessment is conducted using both inlet air wet-bulb temperature and estimated process fluid outlet temperature as dual criteria, dividing the system into normal operating conditions and anti-freezing conditions. Under anti-freezing conditions, an independent dry-condition thermodynamic calculation model is established based on the calibrated dry-condition correlation to search for the lowest energy consumption scheme under dry conditions. Only when the dry conditions cannot meet the heat dissipation load is the spray system activated within constraints to optimize the wet-condition operation. This anti-freezing strategy eliminates the hidden danger of pipes freezing and cracking due to excessively low water temperatures in winter, and avoids the waste of traditional electric heating or continuous high-energy-consumption operation of equipment, achieving energy-saving operation while ensuring anti-freezing safety. Attached Figure Description

[0048] Figure 1 This is a schematic flowchart of the closed-loop cooling tower all-weather adaptive energy-saving control method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of the closed-loop cooling tower all-weather adaptive energy-saving control system according to an embodiment of the present invention. Detailed Implementation

[0049] The following is a detailed description of the embodiments, in conjunction with the accompanying drawings.

[0050] Reference Figure 1 A closed-loop cooling tower all-weather adaptive energy-saving control method includes the following steps: Step 1: Construct the power-law correlation between the air-side enthalpy efficiency and the series correlation between the overall heat transfer coefficient and thermal resistance of the closed cooling tower. Import multiple sets of steady-state operating data, solve the initial values ​​of the coefficients step by step through linearization, and then perform global optimization through the nonlinear least squares method to complete the calibration of the coefficients of the dry and wet operating conditions.

[0051] In some embodiments, the power-law correlation of the air-side enthalpy efficiency is shown in the following equation:

[0052] in, For air-side enthalpy efficiency; Wind speed on the windward side; This refers to the volumetric flow rate of the spray circulating water. This represents the total heat exchange area of ​​the coil. This refers to the number of coil rows; , , and All are parameters to be calibrated; The overall heat transfer coefficient and thermal resistance series correlation formula is shown below:

[0053] in, The overall heat transfer coefficient under wet conditions; The flow velocity of the process fluid inside the pipe; , , , ,and All of these are parameters to be calibrated.

[0054] In some embodiments, the calibration of the wet-dry condition correlation coefficient includes wet condition calibration and dry condition calibration: During wet condition calibration, the air-side enthalpy efficiency under each steady-state condition is solved point by point in reverse. With the overall heat transfer coefficient After performing a logarithmic transformation on the power-law correlation of air-side enthalpy efficiency, the parameters were regressed using the least squares method. , , and For the series correlation between the overall heat transfer coefficient and thermal resistance, first screen sample points with spray density higher than a preset threshold to regress the pipe parameters. and Then fix the internal parameters and revert to the external parameters. , and Using the obtained results as initial values, the Levenberg-Marquardt algorithm is used to perform global nonlinear least squares optimization on all samples; During dry condition calibration, the spray density and air-side enthalpy efficiency are set to zero, and the external thermal resistance term in the overall heat transfer coefficient dry condition correlation adopts a dry convection correlation coefficient independent of the wet condition. The internal parameters of the pipe are... and Maintain consistency with the calibration results under wet operating conditions.

[0055] Step 2: Collect inlet air parameters, process fluid parameters, and real-time heat dissipation load in real time. Calculate the current air density dynamically based on the ideal gas law, correct the mass flow rate and heat transfer calculation benchmark on the air side, and obtain the real-time operating condition calculation parameters.

[0056] In some embodiments, the specific process of dynamically calculating the current air density based on the ideal gas law and correcting the air-side mass flow rate and heat transfer calculation reference is as follows: Real-time acquisition of inlet air dry bulb temperature and atmospheric pressure The dry bulb temperature of the inlet air Converting Celsius to absolute temperature The air density under the current environment is calculated using the ideal gas law for dry air. As shown in the following formula:

[0057] in, The gas constant for air is 287.05 J / (kg·K); The calculated air density The standard air density, which replaces the preset standard air density, is used as the air density benchmark for calculating air-side parameters in the current performance calculation and optimization cycle. This benchmark is then used to calculate the corrected air mass flow rate, as shown in the following formula:

[0058] in, This is the corrected air mass flow rate; Air volume flow rate; With the corrected air mass flow rate As for the heat gain on the air side in subsequent calculations The calculation input is shown in the following formula:

[0059] in, and These are the inlet air enthalpy and the outlet air enthalpy, respectively.

[0060] Step 3: Based on real-time operating condition calculation parameters, extract the inlet air wet-bulb temperature and the estimated process fluid outlet temperature as dual criteria to determine the freezing risk, and classify the operating conditions into normal operating conditions and anti-freezing operating conditions according to the freezing risk results.

[0061] In some embodiments, after completing the inlet air state calculation (including humidity, enthalpy, wet-bulb temperature, etc.) in step two, key parameters under the current operating conditions can be extracted in real time. These key parameters include at least: inlet air wet-bulb temperature. Process fluid outlet temperature under the current frequency combination Among them, the process fluid outlet temperature It can be obtained directly from the real-time measurement value of the temperature sensor or deduced from the approximation between the real-time heat dissipation load and the set outlet water temperature.

[0062] Preferably, before calling the performance calculation module to perform any heat dissipation calculations, the current atmospheric pressure is first considered. With the dry bulb temperature of the inlet air The air density under the current environment is dynamically updated using the ideal gas law. The real-time air density is used instead of the preset standard air density as the benchmark for all subsequent mass flow and heat exchange calculations. This correction ensures the accuracy of air mass flow calculations under high altitude, low air pressure, or extreme temperature conditions, avoiding misjudgments of freezing risk due to inaccurate density.

[0063] A preset first safety threshold is used to determine the risk of freezing. Second security threshold Among them, the first safety threshold This is the lower limit of the inlet air wet-bulb temperature, used to determine whether the ambient air has the potential to cause supercooling of the spray water film evaporation; the second safety threshold. This is the lower limit of the process fluid outlet temperature, used to determine whether the medium inside the coil has caused the overall temperature of the outer wall of the coil to drop to the freezing point due to excessively low load or excessive cooling.

[0064] In some embodiments, the first security threshold The value range is 0℃~2℃, and the second safety threshold The value range is 3℃ to 5℃. The above thresholds can be manually calibrated or adaptively adjusted according to the type of antifreeze used in the closed cooling tower (e.g., water or ethylene glycol aqueous solution) and local meteorological conditions.

[0065] The obtained inlet air wet-bulb temperature With the first safety threshold Compare the process fluid outlet temperatures at the same time. With the second safety threshold A comparison is made, and the current operating condition is determined to be a normal operating condition without freezing risk if and only if both of the following conditions are met simultaneously: This means that the ambient wet-bulb temperature is not lower than the safe lower limit, and the air is insufficient to cause the water film to evaporate excessively due to supercooling. This means that the outlet temperature of the process fluid is not lower than the lower safety limit, and the temperature of the coil itself is still within the safe range.

[0066] If either of the above two conditions is not met, i.e. or If the current condition indicates a risk of freezing, the current operating condition will be classified as an anti-freezing condition.

[0067] Based on the judgment result, the system generates a working condition identifier bit. When determined to be a normal operating condition, The control flow then shifts to step four (conventional three-dimensional variable frequency drive linkage optimization branch); when the condition is determined to be anti-freeze, The control flow then shifts to step five (anti-freeze priority control branch).

[0068] Preferably, when the system is determined to be in a normal operating condition, the lower limit of the spray pump frequency and the upper limit of the fan frequency are not restricted by the anti-freeze constraint, and the system performs energy consumption optimization within the complete three-dimensional frequency space (fan, spray pump, process pump); when the system is determined to be in an anti-freeze operating condition, the anti-freeze logic is immediately activated, and the dry operation mode of the spray pump is preferentially attempted to be shut down. If the heat dissipation load cannot be met under certain operating conditions, the anti-freeze wet operation optimization is performed within the constrained frequency space.

[0069] To prevent frequent switching of operating modes due to fluctuations in ambient temperature around the first and second safety thresholds, hysteresis control logic is introduced. When switching from normal to anti-freeze mode, the system must continuously monitor whether either of the two criteria is below its corresponding threshold for a duration greater than a preset time delay (e.g., 30-60 seconds) before switching. When returning from anti-freeze mode to normal mode, the system must continuously monitor whether both criteria are above their corresponding thresholds for a duration greater than a preset recovery delay before exiting anti-freeze mode. This hysteresis logic effectively avoids control oscillations caused by sensor noise or short-term environmental disturbances, improving the system's operational stability.

[0070] Step 4: If the condition is determined to be a normal operating condition, the calibrated wet operating condition correlation coefficient is used as the calculation benchmark. A two-layer iterative algorithm is used to calculate the heat dissipation of each frequency combination based on the outer layer iterative outlet air dry bulb temperature and the inner layer iterative spray water film temperature. The algorithm traverses and searches within the three-dimensional frequency space composed of the fan frequency, spray pump frequency and process pump frequency to select the normal optimal frequency combination that meets the heat dissipation load and minimizes the total energy consumption.

[0071] In some embodiments, the specific process of calculating the heat dissipation of each frequency combination using a two-layer iterative algorithm that employs the outer layer iterative outlet air dry-bulb temperature and the inner layer iterative spray water film temperature is as follows: Set the outer iteration variable to the outlet air dry-bulb temperature. The inner layer iteration variable is set to the spray water film temperature. ; In the outer iteration, the moisture content of the outlet air is calculated based on the given assumed dry-bulb temperature of the outlet air. and enthalpy of outlet air ; enthalpy efficiency on the air side Definition of enthalpy of outlet air Determined by the following formula:

[0072] in, Temperature of the spray water film The corresponding enthalpy of saturated air; In the inner layer iteration, based on the given assumed value of the spray water film temperature and combined with the assumed dry-bulb temperature of the outlet air in the outer layer, the moisture content of the outlet air is calculated. The constraint is that the moisture content of the air in the mouth is less than or equal to the saturated moisture content at the spray water film temperature; Calculate the process fluid outlet temperature based on air-side energy conservation. As shown in the following formula:

[0073] in, This refers to the mass flow rate of the process fluid. The specific heat at constant pressure for process fluids; Calculate the total heat transfer of the coil using the heat transfer equation. As shown in the following formula:

[0074] in, The overall heat transfer coefficient under wet conditions; This represents the total heat exchange area of ​​the coil. It is the logarithmic mean temperature difference between the spray water film temperature and the inlet and outlet temperatures of the process fluid; Construction of wet working conditions comprehensive error As shown in the following formula:

[0075] in, For correction factors, and ; This is the theoretical water film temperature calculated based on heat balance. With the goal of minimizing the overall error under wet conditions, a two-layer iterative search strategy is adopted to traverse the possible combinations of outlet air dry-bulb temperature and spray water film temperature. When the overall error under wet conditions is less than the preset convergence tolerance (which can be preset to 1×10⁻⁶), the search continues. -4 Up to 1×10 - When ³), output the air-side heat gain under the current combination. This represents the heat dissipation for this frequency combination.

[0076] Furthermore, in the absence of direct measurement of the outlet state, the outlet state of air and process fluid is mathematically uniquely determined by assuming the temperature of the key intermediate interface and combining the self-consistency of energy balance and heat transfer equations. Under wet conditions, the spray water forms a flowing water film on the outer surface of the coil, and the heat transfer path is: process fluid - pipe wall - water film - air. The temperature of the spray water film is the core interface temperature connecting the heat and mass exchange on both sides, but it cannot be directly measured. Therefore, it is necessary to uniquely determine the system state by assuming the dry-bulb temperature of the outlet air and the temperature of the spray water film, under the premise of satisfying three self-consistency conditions: (1) the heat and mass exchange equation on the air side is consistent with the energy conservation equation on the process fluid side; (2) the heat conducted through the pipe wall is equal to the heat transfer through convection on both sides; (3) the temperature of the spray water film is consistent with the heat transfer results on both sides. It is impossible to solve the problem by relying solely on the inlet parameters, so it is necessary to continuously combine and iterate. The assumed values ​​for the outlet air dry-bulb temperature and the spray water film temperature are both obtained using a traversal search strategy in the two-layer iterative solution. Within their respective physically reasonable ranges, the system iterates through all possible temperature combinations according to a set discrete step size (outer layer traversing the outlet air dry-bulb temperature, inner layer traversing the spray water film temperature). For each combination of assumed values, the comprehensive error is calculated. Finally, the option that minimizes the error and satisfies physical constraints (such as...) is selected. , The combination of (representing the saturated air humidity at the spray water film temperature) is used as the iterative convergence result.

[0077] In some embodiments, the specific process of traversing and searching within a three-dimensional frequency space comprised of the fan frequency, spray pump frequency, and process pump frequency to select the conventional optimal frequency combination that satisfies the heat dissipation load and minimizes total energy consumption is as follows: Determine the fan frequency Spray pump frequency and process pump frequency Each search range and discrete step size are used to construct a three-dimensional discrete frequency combination space; For each frequency combination in the three-dimensional frequency space, calculate the wind turbine shaft power at the current frequency according to the similarity law. Spray pump shaft power Process pump shaft power As shown in the following formula:

[0078]

[0079]

[0080] in, , and These are the rated shaft power of the fan, spray pump, and process pump, respectively. , and These are the corresponding rated frequencies; Calculate the air volume flow rate at the current frequency using the similarity law. Spray circulating water volume flow rate and process fluid volumetric flow rate As shown in the following formula:

[0081]

[0082]

[0083] in, , and These are the rated volumetric flow rates of the fan, spray pump, and process pump, respectively. Based on the calculated air volume flow rate Spray circulating water volume flow rate Calculate the heat dissipation under the current frequency combination based on the process fluid volume flow rate; Filter all frequency combinations that satisfy the condition that the heat dissipation is greater than or equal to the real-time heat dissipation load under the current frequency combination, and select the total input power from the combinations that meet the condition. The smallest group is output as the conventional optimal frequency combination, where .

[0084] Step 5: If the condition is determined to be antifreeze, the heat dissipation is calculated using a two-layer iterative algorithm based on the calibrated dry condition correlation coefficient and the outer layer iterative outlet air dry bulb temperature and the inner layer iterative coil outer wall temperature. The lowest energy consumption scheme under dry condition is searched. If the load is not met for some conditions, wet condition optimization is performed under the preset upper and lower limits of the spray pump frequency and fan frequency to obtain the optimal frequency combination for antifreeze.

[0085] In some embodiments, the specific process of calculating heat dissipation using a two-layer iterative algorithm that combines the outer layer iterative outlet air dry-bulb temperature and the inner layer iterative coil outer wall temperature is as follows: Set the outer iteration variable to the outlet air dry-bulb temperature. The inner iteration variable is set to the average temperature of the outer wall of the coil. ; Under dry operating conditions, with the spray system off and no moisture exchange on the air side, the inlet moisture content is... With export moisture content Equal, enthalpy of outlet air Calculated by the following formula:

[0086] in, The specific heat of air at constant pressure; The latent heat of vaporization of water at 0℃; It is the specific heat of water vapor at constant pressure; Calculate the process fluid outlet temperature based on air-side energy conservation. As shown in the following formula:

[0087] Calculate the total heat transfer of the coil using the heat transfer equation. As shown in the following formula:

[0088] in, The overall heat transfer coefficient under dry operating conditions; This is the logarithmic mean temperature difference between the average temperature of the outer wall of the coil and the inlet and outlet temperatures of the process fluid; Comprehensive error under dry working conditions As shown in the following formula:

[0089] With the goal of minimizing the overall error under dry operating conditions, a two-layer iterative search strategy is adopted to traverse the combinations of outlet air dry-bulb temperature and coil outer wall average temperature, and physical rationality constraints are applied, as shown in the following formula:

[0090] when Less than the preset convergence tolerance (which can be preset to 1×10) -5 Up to 1×10 -4 When outputting the air-side heat gain under the current combination, As heat dissipation under dry operating conditions.

[0091] In some embodiments, the specific process of performing wet condition optimization under preset upper and lower limits of the spray pump frequency and fan frequency to obtain the optimal frequency combination for antifreeze is as follows: Set the lower limit frequency for antifreeze spray pump frequency and the upper limit frequency for antifreeze fan frequency; wherein, the lower limit frequency for antifreeze is the minimum spray pump operating frequency that maintains continuous water film coverage on the coil surface; the upper limit frequency for antifreeze is the maximum fan operating frequency that prevents the water film from evaporating and becoming too cold; When it is determined that there is a risk of freezing and the heat dissipation under dry conditions cannot meet the real-time heat dissipation load, in the three-dimensional frequency space composed of fan frequency, spray pump frequency and process pump frequency, the search range of fan frequency is constrained to less than or equal to the upper limit frequency of antifreeze, the search range of spray pump frequency is constrained to greater than or equal to the lower limit frequency of antifreeze, and the process pump frequency is kept within its normal operating frequency range, forming a restricted three-dimensional frequency space. In the restricted three-dimensional frequency space, each frequency combination is traversed, and the fan shaft power, spray pump shaft power and process pump shaft power at the current frequency are calculated according to the similarity law. The heat dissipation at the current frequency combination is calculated by calling the calibrated wet condition correlation coefficient and the two-layer iterative algorithm. Filter all frequency combinations that satisfy the condition that the heat dissipation is greater than or equal to the real-time heat dissipation load under the current frequency combination. Among the combinations that meet the condition, select the one with the smallest total input power as the optimal frequency combination output for antifreeze.

[0092] In some embodiments, after the real-time acquisition of inlet air parameters, and before extracting the inlet air wet-bulb temperature and the estimated process fluid outlet temperature as dual criteria, the method further includes an inlet air state calculation step: Real-time acquisition of inlet air dry bulb temperature Relative humidity of inlet air and atmospheric pressure ; Calculate the partial pressure of saturated water vapor As shown in the following formula:

[0093] Calculate the water vapor partial pressure based on the saturated water vapor partial pressure and the relative humidity of the inlet air. As shown in the following formula:

[0094] Calculate the moisture content of the inlet air based on the partial pressure of water vapor and atmospheric pressure. As shown in the following formula:

[0095] Calculate the enthalpy of the inlet air based on its dry-bulb temperature and humidity. As shown in the following formula:

[0096] in, The specific heat of air at constant pressure; The latent heat of vaporization of water at 0℃; It is the specific heat of water vapor at constant pressure; wet-bulb temperature of inlet air As an unknown quantity, a trial-and-error iterative method is used to solve it: Set an initial guess value for the wet-bulb temperature. Calculate the moisture content and enthalpy of saturated air under this guess value, and substitute them into the wet-bulb temperature definition equation for verification. If the verification error is greater than the preset tolerance (which can be preset to 1×10⁻⁶), the error will be verified. - ³ to 1×10 -If the wet-bulb temperature guess is less than the preset tolerance, then adjust the wet-bulb temperature guess and repeat the verification calculation until the verification error is less than the preset tolerance. Output the current guess value as the inlet air wet-bulb temperature. The wet-bulb temperature definition equation is as follows:

[0097] in, This is the enthalpy of saturated air; The moisture content of saturated air; The specific heat at constant pressure for process fluids.

[0098] Step 6: Convert the conventional optimal frequency combination or the antifreeze optimal frequency combination into variable frequency control commands to drive the fan, spray pump and process pump.

[0099] In some embodiments, the system converts the optimal frequency combination obtained in step four or five (including three target values: fan frequency, spray pump frequency, and process pump frequency) into analog or digital control commands corresponding to the frequency converters, and sends them to the frequency converter drivers of the fan, spray pump, and process pump via industrial communication protocols (such as Modbus, Profibus, or BACnet). Each frequency converter driver adjusts its output current frequency according to the received frequency commands, driving the motor to run at the target speed in real time, thereby synchronously changing the fan airflow, spray water flow, and process water flow, so that the closed cooling tower meets the heat dissipation requirements with the lowest total energy consumption under the current environmental and load conditions. After the command is output, the system continuously monitors the feedback frequency of each frequency converter and the actual operating frequency. If any device fails to track the target frequency due to inverter failure, communication interruption, or mechanical jamming, or if key parameters such as process fluid outlet temperature and spray water film temperature exceed the preset safe operating range, a protective response is immediately triggered. The execution of the current optimization command is suspended, and the system switches to the preset safe frequency or shuts down depending on the fault type. An alarm signal is also issued to notify the maintenance personnel. Under normal operating conditions, when the next control cycle (usually 5 to 30 minutes, with the specific cycle adaptively adjusted according to the rate of change of process load and the degree of fluctuation of environmental parameters) is reached, the system re-executes steps two to five, dynamically updating the optimal frequency combination. This cycle repeats continuously to achieve continuous adaptive energy-saving control of the closed cooling tower under all weather conditions.

[0100] Based on the same inventive concept, and corresponding to any of the above embodiments, refer to... Figure 2 This invention provides a closed-loop cooling tower all-weather adaptive energy-saving control system for implementing the aforementioned closed-loop cooling tower all-weather adaptive energy-saving control method, comprising: The data acquisition module is used to collect inlet air parameters, process fluid parameters, and equipment operating parameters in real time. The parameter calibration module, connected to the data acquisition module, is used to import multiple sets of steady-state operating condition data, construct the power law correlation of air-side enthalpy efficiency and the series correlation of total heat transfer coefficient and thermal resistance, solve the initial value of the coefficients stepwise linearization, and then perform global optimization through nonlinear least squares method to complete the calibration of the coefficients of the dry and wet operating condition correlation, and output the calibrated correlation coefficients to the performance calculation module. The performance calculation module is connected to the parameter calibration module and the data acquisition module respectively. It is used to dynamically calculate the current air density based on the ideal gas law according to the real-time collected inlet air parameters to correct the air-side mass flow rate, and call the corresponding dry or wet condition double-layer iterative algorithm to calculate the heat dissipation according to the freezing risk judgment result. The calculated heat dissipation and temperature status are output to the frequency conversion optimization module. The frequency conversion optimization module, connected to both the performance calculation module and the data acquisition module, is used to search within a three-dimensional frequency space consisting of the fan frequency, spray pump frequency, and process pump frequency, with the real-time heat dissipation load as a constraint and the minimum total input power of the fan, spray pump, and process pump as the optimization objective. It outputs the optimal frequency combination that satisfies the heat dissipation load. The frequency conversion optimization module includes a conventional optimization unit and an anti-freeze optimization unit. The conventional optimization unit outputs the conventional optimal frequency combination when there is no risk of freezing. The anti-freeze optimization unit prioritizes dry condition optimization when there is a risk of freezing. If several conditions do not meet the load, it outputs the anti-freeze optimal frequency combination under the constraint that the spray pump frequency is not lower than a preset lower limit and the fan frequency is not higher than a preset upper limit. The control output module is connected to the frequency conversion optimization module and is used to convert the optimal frequency combination into frequency conversion control commands to drive the fan, spray pump and process pump to run respectively.

[0101] Based on the same inventive concept, corresponding to any of the above embodiments, the present invention provides an electronic device, including a memory and a processor. The memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the closed-loop cooling tower all-weather adaptive energy-saving control method of the embodiment.

[0102] Alternatively, the aforementioned electronic device may be a server.

[0103] In addition, this embodiment also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the closed-loop cooling tower all-weather adaptive energy-saving control method of the embodiment.

[0104] It is understood that the processor in the embodiments of the present invention may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. The general-purpose processor may be a microprocessor or any conventional processor.

[0105] The method steps in the embodiments of the present invention can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, portable hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can reside in an ASIC.

[0106] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a storage medium or transmitted through a storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive (SSD)).

Claims

1. A closed-loop cooling tower all-weather adaptive energy-saving control method, characterized in that, Includes the following steps: A power-law correlation between the air-side enthalpy efficiency and the series correlation between the overall heat transfer coefficient and thermal resistance of a closed cooling tower is constructed. Multiple sets of steady-state operating data are imported, and after solving the initial values ​​of the coefficients through step-by-step linearization, global optimization is performed through the nonlinear least squares method to complete the calibration of the coefficients of the dry and wet operating conditions. Real-time acquisition of inlet air parameters, process fluid parameters, and real-time heat dissipation load; dynamic calculation of current air density based on ideal gas law; correction of mass flow rate and heat exchange calculation basis on the air side; and obtaining real-time operating condition calculation parameters. Based on real-time operating condition calculation parameters, the inlet air wet-bulb temperature and the estimated process fluid outlet temperature are extracted as dual criteria to determine the freezing risk, and the freezing risk results are divided into normal operating conditions and anti-freezing operating conditions. If it is determined to be a normal operating condition, the calibrated wet operating condition correlation coefficient is used as the calculation benchmark. The heat dissipation of each frequency combination is calculated by a two-layer iterative algorithm with outer layer iterative outlet air dry bulb temperature and inner layer iterative spray water film temperature. The search is carried out in the three-dimensional frequency space composed of fan frequency, spray pump frequency and process pump frequency to select the normal optimal frequency combination that meets the heat dissipation load and has the minimum total energy consumption. If the condition is determined to be antifreeze, the heat dissipation is calculated using a two-layer iterative algorithm based on the calibrated dry condition correlation coefficient and the outer layer iterative outlet air dry bulb temperature and the inner layer iterative coil outer wall temperature. The lowest energy consumption scheme under dry condition is searched. If the load is not met for several conditions, wet condition optimization is performed under the preset upper and lower limits of the spray pump frequency and fan frequency to obtain the optimal frequency combination for antifreeze. The conventional optimal frequency combination or the antifreeze optimal frequency combination is converted into variable frequency control commands to drive the operation of the fan, spray pump and process pump.

2. The closed-loop cooling tower all-weather adaptive energy-saving control method as described in claim 1, characterized in that, The power-law correlation of the air-side enthalpy efficiency is shown in the following equation: in, For air-side enthalpy efficiency; Wind speed on the windward side; This refers to the volumetric flow rate of the spray circulating water. This represents the total heat exchange area of ​​the coil. This refers to the number of coil rows; , , and All are parameters to be calibrated; The overall heat transfer coefficient and thermal resistance series correlation formula is shown below: in, The overall heat transfer coefficient under wet conditions; The flow velocity of the process fluid inside the pipe; , , , ,and All of these are parameters to be calibrated.

3. The closed-loop cooling tower all-weather adaptive energy-saving control method as described in claim 2, characterized in that, The calibration of the correlation coefficients for wet and dry operating conditions includes calibration for wet operating conditions and calibration for dry operating conditions: During wet condition calibration, the air-side enthalpy efficiency under each steady-state condition is solved point by point in reverse. With the overall heat transfer coefficient After performing a logarithmic transformation on the power-law correlation of air-side enthalpy efficiency, the parameters were regressed using the least squares method. , , and For the series correlation between the overall heat transfer coefficient and thermal resistance, first screen sample points with spray density higher than a preset threshold to regress the pipe parameters. and Then fix the internal parameters and revert to the external parameters. , and Using the obtained results as initial values, the Levenberg-Marquardt algorithm is used to perform global nonlinear least squares optimization on all samples; During dry condition calibration, the spray density and air-side enthalpy efficiency are set to zero, and the external thermal resistance term in the overall heat transfer coefficient dry condition correlation adopts a dry convection correlation coefficient independent of the wet condition. The internal parameters of the pipe are... and Maintain consistency with the calibration results under wet operating conditions.

4. The closed-loop cooling tower all-weather adaptive energy-saving control method as described in claim 1, characterized in that, The specific process of dynamically calculating the current air density based on the ideal gas law and correcting the air-side mass flow rate and heat transfer calculation reference is as follows: Real-time collection of inlet air dry bulb temperature and atmospheric pressure The dry bulb temperature of the inlet air Converting Celsius to absolute temperature The air density under the current environment is calculated using the ideal gas law for dry air. As shown in the following formula: in, The gas constant for air is 287.05 J / (kg·K); The calculated air density The standard air density, which replaces the preset standard air density, is used as the air density benchmark for calculating air-side parameters in the current performance calculation and optimization cycle. This benchmark is then used to calculate the corrected air mass flow rate, as shown in the following formula: in, This is the corrected air mass flow rate; Air volume flow rate; With the corrected air mass flow rate As for the heat gain on the air side in subsequent calculations The calculation input is shown in the following formula: in, and These are the inlet air enthalpy and the outlet air enthalpy, respectively.

5. The closed-loop cooling tower all-weather adaptive energy-saving control method as described in claim 4, characterized in that, The specific process of calculating the heat dissipation of each frequency combination using the two-layer iterative algorithm of outer layer iterative outlet air dry bulb temperature and inner layer iterative spray water film temperature is as follows: Set the outer iteration variable to the dry-bulb temperature of the outlet air. The inner layer iteration variable is set to the spray water film temperature. ; In the outer iteration, the moisture content of the outlet air is calculated based on the given assumed dry-bulb temperature of the outlet air. and enthalpy of outlet air ; enthalpy efficiency on the air side Definition of enthalpy of outlet air Determined by the following formula: in, Temperature of the spray water film The corresponding enthalpy of saturated air; In the inner layer iteration, the moisture content of the outlet air is calculated based on the given assumed value of the spray water film temperature and the assumed dry-bulb temperature of the outlet air in the outer layer. The constraint is that the moisture content of the air in the mouth is less than or equal to the saturated moisture content at the spray water film temperature; Calculate the process fluid outlet temperature based on air-side energy conservation. As shown in the following formula: in, This refers to the mass flow rate of the process fluid. The specific heat at constant pressure for process fluids; Calculate the total heat transfer of the coil using the heat transfer equation. As shown in the following formula: in, The overall heat transfer coefficient under wet conditions; This represents the total heat exchange area of ​​the coil. It is the logarithmic mean temperature difference between the spray water film temperature and the inlet and outlet temperatures of the process fluid; Construction wet working condition comprehensive error As shown in the following formula: in, For correction coefficients, and ; This is the theoretical water film temperature calculated based on heat balance. With the goal of minimizing the overall error under wet conditions, a two-layer iterative search strategy is adopted to traverse the possible combinations of outlet air dry-bulb temperature and spray water film temperature. When the overall error under wet conditions is less than the preset convergence tolerance, the air-side heat gain under the current combination is output. This represents the heat dissipation for this frequency combination.

6. The closed-loop cooling tower all-weather adaptive energy-saving control method as described in claim 5, characterized in that, The specific process of traversing and searching within the three-dimensional frequency space comprised of the fan frequency, spray pump frequency, and process pump frequency to select the conventional optimal frequency combination that satisfies the heat dissipation load and minimizes total energy consumption is as follows: Determine the fan frequency Spray pump frequency and process pump frequency Each search range and discrete step size are used to construct a three-dimensional discrete frequency combination space; For each frequency combination in the three-dimensional frequency space, calculate the wind turbine shaft power at the current frequency according to the similarity law. Spray pump shaft power Process pump shaft power As shown in the following formula: in, , and These are the rated shaft power of the fan, spray pump, and process pump, respectively. , and These are the corresponding rated frequencies; Calculate the air volume flow rate at the current frequency using the similarity law. Spray circulating water volume flow rate and process fluid volumetric flow rate As shown in the following formula: in, , and These are the rated volumetric flow rates of the fan, spray pump, and process pump, respectively. Based on the calculated air volume flow rate Spray circulating water volume flow rate Calculate the heat dissipation under the current frequency combination based on the process fluid volume flow rate; Filter all frequency combinations that satisfy the condition that the heat dissipation is greater than or equal to the real-time heat dissipation load under the current frequency combination, and select the total input power from the combinations that meet the condition. The smallest group is output as the conventional optimal frequency combination, where .

7. The closed-loop cooling tower all-weather adaptive energy-saving control method as described in claim 4, characterized in that, The specific process of calculating heat dissipation using the two-layer iterative algorithm, which employs the outer layer iterative outlet air dry-bulb temperature and the inner layer iterative coil outer wall temperature, is as follows: Set the outer iteration variable to the dry-bulb temperature of the outlet air. The inner layer iteration variable is set to the average temperature of the outer wall of the coil. ; Under dry operating conditions, with the spray system off and no moisture exchange on the air side, the inlet moisture content is... With export moisture content Equal, enthalpy of outlet air Calculated by the following formula: in, The specific heat of air at constant pressure; The latent heat of vaporization of water at 0℃; It is the specific heat of water vapor at constant pressure; Calculate the process fluid outlet temperature based on air-side energy conservation. As shown in the following formula: Calculate the total heat transfer of the coil using the heat transfer equation. As shown in the following formula: in, The overall heat transfer coefficient under dry operating conditions; This is the logarithmic mean temperature difference between the average temperature of the outer wall of the coil and the inlet and outlet temperatures of the process fluid; Comprehensive error under dry working conditions As shown in the following formula: With the goal of minimizing the overall error under dry operating conditions, a two-layer iterative search strategy is adopted to traverse the combinations of outlet air dry-bulb temperature and coil outer wall average temperature, and physical rationality constraints are applied, as shown in the following formula: when When the output is less than the preset convergence tolerance, output the air-side heat gain under the current combination. As heat dissipation under dry operating conditions.

8. The closed-loop cooling tower all-weather adaptive energy-saving control method as described in claim 6, characterized in that, The specific process of performing wet condition optimization under preset upper and lower limits of spray pump frequency and fan frequency to obtain the optimal frequency combination for antifreeze is as follows: Set the lower limit frequency for antifreeze spray pump frequency and the upper limit frequency for antifreeze fan frequency; wherein, the lower limit frequency for antifreeze is the minimum spray pump operating frequency that maintains continuous water film coverage on the coil surface; the upper limit frequency for antifreeze is the maximum fan operating frequency that prevents the water film from evaporating and becoming too cold; When it is determined that there is a risk of freezing and the heat dissipation under dry conditions cannot meet the real-time heat dissipation load, in the three-dimensional frequency space composed of fan frequency, spray pump frequency and process pump frequency, the search range of fan frequency is constrained to less than or equal to the upper limit frequency of antifreeze, the search range of spray pump frequency is constrained to greater than or equal to the lower limit frequency of antifreeze, and the process pump frequency is kept within its normal operating frequency range, forming a restricted three-dimensional frequency space. In the restricted three-dimensional frequency space, each frequency combination is traversed, and the fan shaft power, spray pump shaft power and process pump shaft power at the current frequency are calculated according to the similarity law. The heat dissipation at the current frequency combination is calculated by calling the calibrated wet condition correlation coefficient and the two-layer iterative algorithm. Filter all frequency combinations that satisfy the condition that the heat dissipation is greater than or equal to the real-time heat dissipation load under the current frequency combination. Among the combinations that meet the condition, select the one with the smallest total input power as the optimal frequency combination output for antifreeze.

9. The closed-loop cooling tower all-weather adaptive energy-saving control method as described in claim 4, characterized in that, After real-time acquisition of inlet air parameters, and before extracting the inlet air wet-bulb temperature and the estimated process fluid outlet temperature as dual criteria, the process also includes a step of inlet air state calculation: Real-time collection of inlet air dry bulb temperature Relative humidity of inlet air and atmospheric pressure ; Calculate the partial pressure of saturated water vapor As shown in the following formula: Calculate the water vapor partial pressure based on the saturated water vapor partial pressure and the relative humidity of the inlet air. As shown in the following formula: Calculate the moisture content of the inlet air based on the partial pressure of water vapor and atmospheric pressure. As shown in the following formula: Calculate the enthalpy of the inlet air based on its dry-bulb temperature and humidity. As shown in the following formula: in, The specific heat of air at constant pressure; The latent heat of vaporization of water at 0℃; It is the specific heat of water vapor at constant pressure; wet-bulb temperature of inlet air As an unknown quantity, a trial-and-error iterative method is used to solve it: Set an initial guess value for the wet-bulb temperature. Calculate the moisture content and enthalpy of saturated air under this guess value, and substitute them into the wet-bulb temperature definition equation for verification. If the verification error is greater than the preset tolerance, adjust the wet-bulb temperature guess value and repeat the verification calculation until the verification error is less than the preset tolerance. Output the current guess value as the inlet air wet-bulb temperature. The wet-bulb temperature definition equation is shown below: in, This is the enthalpy of saturated air; The moisture content of saturated air; The specific heat at constant pressure for process fluids.

10. A closed-loop cooling tower all-weather adaptive energy-saving control system, used to implement the closed-loop cooling tower all-weather adaptive energy-saving control method according to any one of claims 1-9, characterized in that, include: The data acquisition module is used to collect inlet air parameters, process fluid parameters, and equipment operating parameters in real time. The parameter calibration module, connected to the data acquisition module, is used to import multiple sets of steady-state operating condition data, construct the power law correlation of air-side enthalpy efficiency and the series correlation of total heat transfer coefficient and thermal resistance, solve the initial value of the coefficients stepwise linearization, and then perform global optimization through nonlinear least squares method to complete the calibration of the coefficients of the dry and wet operating condition correlation, and output the calibrated correlation coefficients to the performance calculation module. The performance calculation module is connected to the parameter calibration module and the data acquisition module respectively. It is used to dynamically calculate the current air density based on the ideal gas law according to the real-time collected inlet air parameters to correct the air-side mass flow rate, and call the corresponding dry or wet condition double-layer iterative algorithm to calculate the heat dissipation according to the freezing risk judgment result. The calculated heat dissipation and temperature status are output to the frequency conversion optimization module. The frequency conversion optimization module, connected to both the performance calculation module and the data acquisition module, is used to search within a three-dimensional frequency space consisting of the fan frequency, spray pump frequency, and process pump frequency, with the real-time heat dissipation load as a constraint and the minimum total input power of the fan, spray pump, and process pump as the optimization objective. It outputs the optimal frequency combination that satisfies the heat dissipation load. The frequency conversion optimization module includes a conventional optimization unit and an anti-freeze optimization unit. The conventional optimization unit outputs the conventional optimal frequency combination when there is no risk of freezing. The anti-freeze optimization unit prioritizes dry condition optimization when there is a risk of freezing. If several conditions do not meet the load, it outputs the anti-freeze optimal frequency combination under the constraint that the spray pump frequency is not lower than a preset lower limit and the fan frequency is not higher than a preset upper limit. The control output module is connected to the frequency conversion optimization module and is used to convert the optimal frequency combination into frequency conversion control commands to drive the fan, spray pump and process pump to run respectively.

Images