Intelligent control system and working method of dry-wet combined cooling tower

Abstract

This invention discloses an intelligent control system and operating method for a combined wet and dry cooling tower, belonging to the field of industrial cooling technology. The compensation module compensates for the theoretical required opening degree based on the valve's flow characteristic deviation data, generating the actual valve opening degree. The dynamic rate constraint module calculates the upper limit of the dynamic change rate of the fan frequency based on the valve action lag time and water flow inertia time, and imposes rate constraints on the fan frequency change. The energy efficiency optimization module aims to minimize total energy consumption, dynamically adjusting the load distribution on the water and air sides based on the wet-bulb temperature, generating a collaborative correction coefficient to correct the valve and fan commands. The airflow distribution module calculates the target airflow distribution ratio between the wet and dry zones based on the corrected valve opening degree and fan frequency. This invention solves the collaborative control problem of nonlinear electric valves and millisecond-level frequency conversion response of fans, achieving coordinated air-water cooling and dynamic matching of wet and dry zone loads.

Description

Technical Field

[0001] This invention belongs to the field of industrial cooling technology, and in particular relates to an intelligent control system and working method for a combined dry and wet cooling tower. Background Technology

[0002] A combined dry-wet cooling tower is an energy-saving cooling device that combines dry heat dissipation with wet evaporative cooling, and is widely used in industrial circulating water cooling systems. In existing technologies, the control system of a combined dry-wet cooling tower typically adopts an independent adjustment method: the fan speed is adjusted by a frequency converter to change the air volume, the cooling water flow rate is adjusted by an electric valve to change the water volume, and coordinated control is performed based on a preset air-to-water ratio.

[0003] However, existing control schemes still have the following technical shortcomings:

[0004] As a mechanical actuator, electric valves generally have nonlinear flow characteristics. The actual flow rate and valve opening degree exhibit non-equal percentage characteristics. Existing control systems usually treat valves as linear actuators for control, resulting in poor water flow regulation accuracy and lag response.

[0005] The frequency converter of the fan has a response speed in milliseconds, while the mechanical action time of the electric valve is usually tens to hundreds of seconds. There is a serious mismatch between the two in terms of response time scale. The existing control strategy does not take into account this dynamic difference, which leads to frequent fluctuations of the fan and the valve always being in a chasing state when the load changes, causing system oscillation and air-water imbalance.

[0006] While existing technologies mention optimizing the air-to-water ratio, they fail to dynamically adjust the load distribution between dry and wet zones based on environmental parameters such as wet-bulb temperature, nor do they actively adjust the airflow entering the dry and wet zones, making it difficult to achieve optimal energy efficiency control under all operating conditions.

[0007] Therefore, there is an urgent need for an intelligent control scheme that can overcome valve nonlinearity, solve the problem of mismatch between fan and valve response speed, and realize dynamic load distribution in dry and wet zones. Summary of the Invention

[0008] To address the shortcomings of existing technologies, this invention provides an intelligent control system and operating method for a combined dry and wet cooling tower, thus solving the aforementioned problems.

[0009] To achieve the above objectives, the present invention provides the following technical solution: an intelligent control system for a combined wet and dry cooling tower, comprising:

[0010] The data acquisition module is used to collect the operating data and equipment characteristic parameters of the cooling tower;

[0011] The compensation module compensates for the theoretical required opening degree output by the controller based on the valve linearity deviation table, and generates the actual valve opening degree command.

[0012] The dynamic rate constraint module calculates the upper limit of the dynamic change rate of the fan frequency based on the action lag time of the electric valve and the inertial time of the water flow, and imposes rate constraints on the frequency change of the fan inverter, so that the change rate of the fan frequency and the change rate of the valve flow are coordinated on the time scale.

[0013] The energy efficiency optimization module is used to dynamically adjust the load distribution between the water side and the air side based on the wet-bulb temperature, with the goal of minimizing total energy consumption while meeting the outlet water temperature requirements. It generates a collaborative correction coefficient and uses the collaborative correction coefficient to correct the valve opening command and the fan frequency command, thus obtaining the corrected valve opening command and the corrected fan frequency command.

[0014] The airflow distribution module calculates the target airflow distribution ratio between dry and wet zones based on the corrected valve opening command and the corrected fan frequency command, and then adjusts the airflow ratio entering the dry radiator and the wet packing.

[0015] Based on the above technical solutions, the present invention also provides the following optional technical solutions:

[0016] Further technical solutions: The operating data and equipment characteristic parameters include inlet water temperature, outlet water temperature, wet bulb temperature, current valve opening degree, current fan frequency, flow linearity deviation table (a data set recording the flow linearity deviation coefficient of the valve at each discrete opening test point) and target outlet water temperature.

[0017] Further technical solution: The steps for the compensation module to generate the valve's actual opening command are as follows:

[0018] Obtain measured flow data of the electric valve at multiple test points with different opening degrees;

[0019] Calculate the flow linearity deviation coefficient at each test point based on the ratio of theoretical flow rate to actual flow rate at each test point.

[0020] For any opening Flow linearity deviation coefficient It is determined by linear interpolation;

[0021] The actual valve opening is calculated based on the ratio of the theoretical required opening to the flow linearity deviation coefficient.

[0022] A further technical solution: The dynamic rate constraint module constrains the wind turbine frequency in the following manner:

[0023] The water flow response time is calculated based on the total stroke time of the electric valve, the change in valve opening in the current cycle, and the water flow inertia time constant.

[0024] Based on the difference between the rated maximum frequency and the minimum allowable operating frequency of the fan, the water flow response time, and the control cycle, calculate the maximum allowable change in the fan frequency within each control cycle;

[0025] Based on the actual operating frequency of the fan in the previous control cycle, the theoretical required frequency, and the maximum change, a rate constraint is applied to the fan frequency to obtain the target frequency.

[0026] Further technical solution: The energy efficiency optimization module corrects the valve opening command and the fan frequency command in the following way:

[0027] A total energy consumption model is established that includes water-side energy consumption and wind-side energy consumption. The water-side energy consumption is related to the square of the valve opening, and the wind-side energy consumption is related to the cube of the fan frequency.

[0028] The collaborative correction coefficient is calculated based on the ratio of the current wet-bulb temperature to the reference wet-bulb temperature, and the ratio of the total energy consumption of conventional control under standard operating conditions to the current total energy consumption.

[0029] The corrected valve opening command is calculated based on the collaborative correction coefficient, the water-side load distribution weight factor, and the valve opening command; and the corrected fan frequency command is calculated based on the collaborative correction coefficient, the wind-side load distribution weight factor, and the fan frequency command.

[0030] Further technical solution: The airflow distribution module calculates the target airflow distribution ratio between dry and wet zones in the following manner:

[0031] Based on the corrected valve opening command and the corrected fan frequency command, calculate the baseline value of the dry and wet zone airflow distribution ratio under ideal conditions;

[0032] Based on the deviation between the current wet-bulb temperature and the design wet-bulb temperature, the ideal distribution ratio benchmark value is corrected to obtain the target dry area airflow distribution ratio.

[0033] Further technical solution: the water flow inertial time constant Pre-calibration is determined using the following methods:

[0034] Record the response curve of cooling water flow rate from initial value to target value under the step change condition of electric valve;

[0035] The time required for the flow response to reach the target value is defined as the inertial time constant of the water flow. The unit is seconds (s);

[0036] The water flow inertial time constant With cooling tower pipe length and pump inertia coefficient The relationship is as follows:

[0037]

[0038] in, The total length of the cooling tower water supply pipeline is expressed in meters (m). The average flow velocity of water in the pipe is expressed in meters per second (m / s). This is the pump inertia correction factor.

[0039] A method for operating a combined wet and dry cooling tower intelligent control system includes the following steps:

[0040] Step S10: Collect the operating data and equipment characteristic parameters of the cooling tower through the data acquisition module;

[0041] Step S20: The compensation module compensates for the theoretical required opening degree output by the controller based on the flow characteristic deviation data of the electric valve, and generates the actual valve opening degree command.

[0042] Step S30: The dynamic rate constraint module calculates the upper limit of the dynamic change rate of the fan frequency based on the action lag time of the electric valve and the inertial time of the water flow, and imposes rate constraints on the frequency change of the fan inverter so that the change rate of the fan frequency and the change rate of the valve flow are coordinated on the time scale.

[0043] Step S40: Under the premise of meeting the outlet water temperature requirements, the energy efficiency optimization module aims to minimize the total energy consumption by dynamically adjusting the load distribution between the water side and the air side based on the wet-bulb temperature, generating a collaborative correction coefficient, and correcting the valve opening command output in step S20 and the fan frequency command output in step S30 to obtain the corrected valve opening command and the corrected fan frequency command.

[0044] Step S50: The airflow distribution module calculates the target airflow distribution ratio between the dry and wet zones based on the corrected valve opening command and the corrected fan frequency command, and then adjusts the airflow ratio entering the dry radiator and the wet packing.

[0045] This invention provides an intelligent control system and operating method for a combined wet and dry cooling tower, which has the following advantages compared with the prior art:

[0046] 1. This invention uses a nonlinear compensation module to accurately compensate for the flow characteristic deviation of electric valves, transforming nonlinear valves into linear controllable objects, significantly improving the accuracy and response speed of water flow regulation, and avoiding control errors and system oscillations caused by valve nonlinearity.

[0047] 2. This invention uses a dynamic rate constraint module to calculate the upper limit of the dynamic change rate of the fan frequency based on the mechanical action lag time of the valve and the inertial time of the water flow, and actively constrains the frequency change of the fan inverter, so that the change rate of the fan frequency and the change rate of the valve flow rate are coordinated on the time scale, fundamentally solving the problem of "slow valve and fast fan" response speed mismatch and eliminating control system oscillation.

[0048] 3. This invention introduces a wet-bulb temperature collaborative correction coefficient through an energy efficiency optimization module to dynamically adjust the load distribution between the water side and the air side. Furthermore, through an airflow distribution adjustment module, it actively adjusts the airflow distribution ratio between the dry and wet zones based on the corrected valve opening and fan frequency, thereby achieving three-dimensional collaborative control of "water volume - total air volume - air volume distribution". This enables the optimization of overall energy consumption under different environmental conditions. Attached Figure Description

[0049] Figure 1 This is a schematic diagram of the process of the present invention. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0051] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0052] Please see Figure 1 According to one embodiment of the present invention, a smart control system for a combined wet and dry cooling tower includes:

[0053] The data acquisition module is used to collect the operating data and equipment characteristic parameters of the cooling tower. The operating data and equipment characteristic parameters include inlet water temperature, outlet water temperature, wet bulb temperature, current valve opening degree, current fan frequency, flow linearity deviation table (a data set that records the flow linearity deviation coefficient of the valve at each discrete opening test point), and target outlet water temperature.

[0054] The compensation module compensates for the theoretical required opening degree output by the controller based on the valve linearity deviation table, and generates the actual valve opening degree command.

[0055] The dynamic rate constraint module calculates the upper limit of the dynamic change rate of the fan frequency based on the action lag time of the electric valve and the inertial time of the water flow, and imposes rate constraints on the frequency change of the fan inverter, so that the change rate of the fan frequency and the change rate of the valve flow are coordinated on the time scale.

[0056] The energy efficiency optimization module is used to dynamically adjust the load distribution between the water side and the air side based on the wet-bulb temperature, with the goal of minimizing total energy consumption while meeting the outlet water temperature requirements. It generates a collaborative correction coefficient and uses the collaborative correction coefficient to correct the valve opening command and the fan frequency command, thus obtaining the corrected valve opening command and the corrected fan frequency command.

[0057] The airflow distribution module calculates the target airflow distribution ratio between dry and wet zones based on the corrected valve opening command and the corrected fan frequency command, and then adjusts the airflow ratio entering the dry radiator and the wet packing.

[0058] The following example will provide a more detailed explanation of the above technical solution:

[0059] Suppose that at location A, a combined wet and dry cooling tower is providing cooling services to user A's industrial production line. Currently, the cooling tower's outlet water temperature is slightly higher than the target outlet water temperature, and the ambient wet-bulb temperature is at a moderate level.

[0060] First, the data acquisition module collects real-time operating data and equipment characteristic parameters of the cooling tower. This includes real-time data such as inlet water temperature, outlet water temperature, wet-bulb temperature, current valve opening, and current fan frequency, as well as pre-stored flow linearity deviation tables and target outlet water temperatures. For example, the system detects that the current outlet water temperature is 35℃, while the target outlet water temperature is 32℃, resulting in a deviation of 3℃.

[0061] Next, the controller calculates a theoretical required opening degree, such as 50%, based on the outlet water temperature deviation. At this point, the compensation module intervenes. Because electric valves exhibit non-linear flow characteristics, directly sending a 50% opening command to the valve might result in a lower actual flow rate. The compensation module compensates for this 50% theoretical required opening degree based on a pre-calibrated flow linearity deviation table. For example, if the flow linearity deviation table shows that the actual flow rate would be lower at a 50% theoretical opening degree, the compensation module will correct the theoretical required opening degree to a larger value, such as 55%, as the actual opening command executed by the valve. This method ensures precise water flow regulation.

[0062] Simultaneously, the dynamic rate constraint module begins coordinating the actions of the fan and valves. Assuming it takes a considerable amount of time for the valve to change from its current opening to 55%, while the fan inverter responds extremely quickly, the dynamic rate constraint module calculates an upper limit for the dynamic rate of change of the fan frequency based on the valve's lag time (e.g., a full valve stroke time of 60 seconds) and the water flow inertia time (e.g., a water flow inertia time constant of 10 seconds). For example, the maximum frequency change per second is calculated to be 0.5 Hz. When the controller calculates, based on temperature deviation, that the fan needs to increase from its current frequency (e.g., 30 Hz) to the theoretically required frequency (e.g., 40 Hz), the dynamic rate constraint module limits the rate of change of the fan frequency, ensuring it does not exceed 0.5 Hz in each control cycle. Thus, the fan frequency gradually increases at a controlled rate, matching the valve flow rate change, avoiding drastic fluctuations in fan frequency and system oscillations, ensuring coordinated airflow and water flow.

[0063] After the valve opening command and fan frequency command are initially determined, the energy efficiency optimization module further optimizes the system's energy consumption. This module aims to minimize total energy consumption while considering the current wet-bulb temperature (e.g., 25°C). The energy efficiency optimization module dynamically adjusts the load distribution between the water and air sides, generating a collaborative correction coefficient. For example, at the current wet-bulb temperature, the system may determine that increasing the water-side load and decreasing the air-side load would result in lower energy consumption. Based on this determination, the energy efficiency optimization module generates a collaborative correction coefficient and uses this coefficient to correct the actual valve opening command (e.g., 55%) and the fan frequency command after rate constraints (e.g., 30.5 Hz). For example, the valve opening command might be corrected to 56%, and the fan frequency command might be corrected to 30 Hz, thereby further reducing total energy consumption while meeting the outlet water temperature requirements.

[0064] Finally, the airflow distribution module calculates the target airflow distribution ratio between the dry and wet zones based on the corrected valve opening command (56%) and the corrected fan frequency command (30 Hz). For example, based on these commands, the system calculates a target dry zone airflow distribution ratio of 40%, meaning that 40% of the total airflow should enter the dry radiator, with the remaining 60% entering the wet packing. The airflow distribution module adjusts the flow guides or dampers inside the cooling tower to achieve this target airflow distribution ratio. In this way, the system can flexibly adjust the cooling load in the dry and wet zones according to the current operating conditions and energy efficiency optimization goals, ensuring that the cooling tower operates efficiently under different environmental conditions.

[0065] The entire process is a closed-loop control, with each module working in concert. From data acquisition to command output and then to actual execution, it forms an intelligent and efficient control chain, effectively solving the problems of nonlinearity, dynamic mismatch and energy efficiency optimization in the operation of cooling towers.

[0066] Based on the above examples, the intelligent control system for combined wet and dry cooling towers provided in this embodiment demonstrates significant technological contributions.

[0067] In existing technologies, the nonlinear flow characteristics of electric valves are often ignored, leading to insufficient water flow regulation accuracy. For example, in the example above, if a 50% theoretical opening command is sent directly using the traditional method, the actual flow rate may not reach the expected level, thus affecting the cooling effect. This embodiment introduces a compensation module to compensate for the theoretical required opening based on a pre-calibrated flow linearity deviation table, generating a more accurate valve opening command. This compensation mechanism makes water flow regulation more precise, overcoming the problems of poor regulation accuracy and response lag caused by valve nonlinearity in traditional control schemes.

[0068] Furthermore, existing control schemes fail to effectively address the severe mismatch in response time scale between the fan and the electric valve, leading to system oscillations and air-water imbalances during load changes. In the example above, if the fan frequency increases rapidly while the valve opening changes slowly, it will result in a mismatch between airflow and water flow. The dynamic rate constraint module in this embodiment calculates and limits the upper limit of the dynamic change rate of the fan frequency based on the lag time of the electric valve and the inertia time of the water flow. By coordinating the rate of change of the fan frequency with the rate of change of the valve flow rate on the time scale, this system effectively avoids frequent fan fluctuations and valve chasing states, significantly improving system stability and coordination, and solving the air-water imbalance problem in existing technologies.

[0069] Furthermore, existing technologies, in terms of optimizing the air-to-water ratio, fail to dynamically adjust the load distribution between the wet and dry zones based on environmental parameters such as wet-bulb temperature, making it difficult to achieve optimal energy efficiency control under all operating conditions. In the example above, the energy efficiency optimization module dynamically adjusts the load distribution between the water and air sides based on the current wet-bulb temperature and generates a collaborative correction coefficient to correct valve opening commands and fan frequency commands. This dynamic and intelligent energy efficiency optimization strategy enables the system to operate with the goal of minimizing total energy consumption while meeting the outlet water temperature requirements, thus achieving optimal energy efficiency control under all operating conditions, significantly outperforming the static control method based on a preset air-to-water ratio in existing technologies.

[0070] Finally, the airflow distribution module in this embodiment calculates the target airflow distribution ratio between the dry and wet zones based on the corrected valve opening command and the corrected fan frequency command, and then adjusts the airflow ratio entering the dry radiator and the wet packing. This allows the cooling tower to flexibly adjust the ratio of dry and wet cooling modes according to actual operating needs and environmental conditions, further optimizing the cooling effect and energy efficiency.

[0071] In summary, the intelligent control system for the dry and wet combined cooling tower in this embodiment effectively solves the technical problems in the prior art, such as valve nonlinearity, fan and valve response speed mismatch, and unreasonable load distribution in the dry and wet zones, through the synergistic effect of multiple modules such as data acquisition, nonlinear compensation, dynamic rate constraint, energy efficiency optimization, and airflow distribution. It provides a more intelligent, efficient, and stable cooling tower control solution.

[0072] Preferably, the step of the compensation module generating the valve's actual opening command is as follows:

[0073] Obtain measured flow data of the electric valve at multiple test points with different opening degrees;

[0074] Calculate the flow linearity deviation coefficient at each test point based on the ratio of theoretical flow rate to actual flow rate.

[0075]

[0076] in, For the first The flow linearity deviation coefficient at each test point For test point number, For the first The theoretical flow rate at each test point when the valve exhibits ideal linear characteristics, in m³ / s. 3 / h, For the first The actual flow rate obtained from the actual measurements at each test point is expressed in m³ / s. 3 / h;

[0077] For any opening Flow linearity deviation coefficient Determined by linear interpolation:

[0078]

[0079] in, Indicates the current valve opening requirement. The flow linearity deviation coefficient under the given conditions and The first The and the first The valve opening corresponding to each test point is expressed as a percentage (%). and These are the flow linearity deviation coefficients at the corresponding test points. The current valve opening requirement is expressed as a percentage (%).

[0080] Calculate the actual valve opening based on the ratio of the theoretical required opening to the flow linearity deviation coefficient:

[0081]

[0082] in, The actual opening command sent to the electric valve is expressed as a percentage (%). This represents the theoretical required opening degree calculated by the controller based on the temperature deviation, expressed as a percentage (%). This is the flow linearity deviation coefficient for the corresponding opening degree.

[0083] The purpose of obtaining measured flow data of the electric valve at multiple test points with different opening degrees is to establish the correspondence between the actual flow rate and the opening degree of the electric valve, providing basic data for subsequent nonlinear compensation. Specifically, high-precision flow sensors can be installed upstream or downstream of the electric valve. When the electric valve is set to a series of preset discrete opening degrees (e.g., 10%, 20%, ..., 100%), the stable actual water flow data at each opening degree can be recorded and stored. Alternatively, professional flow calibration equipment can be used to conduct precise flow characteristic tests on the electric valve in a controlled experimental environment to obtain a more detailed and accurate opening-flow correspondence dataset. The flow linearity deviation coefficient at each test point is used to quantify the nonlinearity of the electric valve at different opening degrees, i.e., the degree of deviation between the actual flow rate and the ideal linear flow rate. In practice, it can be assumed that the electric valve has ideal linear flow characteristics, i.e., its theoretical flow rate is proportional to the opening degree. Then, the actual flow rate at each test point is measured... The ideal linear flow rate corresponding to this opening degree Comparison, through formula Calculate the first Flow linearity deviation coefficient at each test point These deviation coefficients reflect the degree of deviation between the actual flow rate and the ideal flow rate of the electric valve at a specific opening degree. For any opening degree... Flow linearity deviation coefficient The coefficient of linearity deviation at any intermediate opening is determined using linear interpolation. Given the limited number of actual test points, this step aims to predict the flow linearity deviation coefficient based on known discrete test point data using interpolation methods, ensuring the continuity and accuracy of compensation. Specifically, piecewise linear interpolation can be used, i.e., interpolating between two adjacent test points... and Assuming the flow linearity deviation coefficient changes linearly, for any current valve opening requirement... (in ), through formula Calculate the corresponding flow linearity deviation coefficient. Besides linear interpolation, more complex mathematical methods such as polynomial interpolation or spline interpolation can be considered to improve interpolation accuracy. Calculating the actual valve opening based on the ratio of the theoretical required opening to the flow linearity deviation coefficient is the core of achieving nonlinear compensation, aiming to adjust the theoretical required opening calculated by the controller based on temperature deviation. By comparing with the corresponding flow linearity deviation coefficient Perform ratio calculations to convert the ratios into actual opening commands that enable the electric valve to output the desired flow rate. Specifically, the controller first calculates a theoretical required opening degree based on the operating status of the cooling tower and the target outlet water temperature. Then, the aforementioned interpolation method is used to determine the... Corresponding flow linearity deviation coefficient Finally, through the formula Calculate the actual opening command sent to the electric valve. This instruction takes into account the non-linear characteristics of electric valves, ensuring that the actual water flow accurately responds to the controller's requirements.

[0084] The compensation module of this application effectively solves the problem of nonlinear flow characteristics in electric valves through a series of steps, thereby ensuring the accuracy of water-side flow control. The system establishes a true mapping relationship between valve opening and actual flow by acquiring measured flow data at multiple test points with different opening degrees. This measured data is the foundation for understanding the valve's nonlinear behavior. Based on this, for each test point, the system calculates the ratio of theoretical flow to actual flow, thus obtaining a flow linearity deviation coefficient. These deviation coefficients intuitively quantify the degree to which the valve deviates from its ideal linear characteristics at different opening degrees. To address the possibility of the controller issuing arbitrary opening commands, the system further employs linear interpolation to calculate the flow linearity deviation coefficient for any intermediate opening degree based on the known deviation coefficients of discrete test points, ensuring the continuity and comprehensiveness of the compensation. Finally, when the controller calculates the theoretical required opening degree based on the cooling tower's operational needs, the compensation module uses the flow linearity deviation coefficient corresponding to this theoretical required opening degree to correct it, generating the actual valve opening command. This actual opening command is sent to the electric valve, enabling the electric valve to output a precise water flow rate that matches the controller's theoretical requirements during actual operation. In this way, the compensation module incorporates the nonlinear characteristics of the electric valve into the control considerations, making the water-side flow control more precise. This provides a stable and reliable water flow basis for other modules in the intelligent control system of the dry-wet combined cooling tower (such as the dynamic rate constraint module, energy efficiency optimization module, and airflow distribution module), thereby improving the control accuracy and operating efficiency of the entire system.

[0085] The following is a concrete example to illustrate this. Suppose that before the intelligent control system for the combined wet and dry cooling tower was put into operation, the flow characteristics of one of the electric valves were calibrated. First, the actual flow data were obtained using a flow meter installed on the pipeline when the electric valve was at multiple discrete opening degrees, such as 20%, 40%, 60%, 80%, and 100%. For example, when the theoretical opening degree of the electric valve is 50%, the ideal flow rate should be 100 m³ / s. 3 / h, but the actual measured flow rate may only be 80 m³ / h. 3 / h. At this point, according to the formula The flow linearity deviation coefficient at this 50% opening can be calculated. = 1.25. Similarly, the deviation coefficients corresponding to all test points can be obtained and stored in the flow linearity deviation table dataset. When the cooling tower intelligent control system is running, if the controller calculates the theoretical required opening degree of the electric valve to reach 45% based on the outlet water temperature deviation... The compensation module will first use the data in the flow linearity deviation table, through a linear interpolation formula... Calculate the flow linearity deviation coefficient corresponding to a 45% opening degree. Assuming the interpolation result is 1.20, the compensation module will then calculate the result according to the formula. Calculate the actual opening command sent to the electric valve. = 37.5 The electric valve will operate according to the 37.5% opening command, so that the actual water flow can accurately reach the flow corresponding to the theoretical opening of 45% expected by the controller, effectively overcoming the nonlinear characteristics of the electric valve itself.

[0086] Through the above technical solution, this application can accurately characterize and compensate for the nonlinear flow characteristics of electric valves, ensuring that the theoretical opening degree issued by the controller can be accurately converted into the actual required flow rate. This significantly improves the accuracy and response speed of water-side flow control, eliminates flow deviation caused by valve nonlinearity, and thus makes the cooling tower outlet water temperature control more stable and accurate. This precise water-side control provides a solid foundation for the entire intelligent control system of the dry-wet combined cooling tower, enabling subsequent control strategies such as dynamic rate constraints, energy efficiency optimization, and airflow distribution to make decisions and execute based on more accurate flow information, thereby comprehensively improving the overall operating efficiency and energy-saving effect of the system and avoiding energy waste caused by inaccurate flow control.

[0087] Preferably, the dynamic rate constraint module constrains the wind turbine frequency in the following manner:

[0088] Calculate the flow response time based on the total stroke time of the electric valve, the change in valve opening during the current cycle, and the flow inertia time constant:

[0089]

[0090] in, For water flow response time, The total stroke time of the electric valve is expressed in seconds (s). The actual valve opening degree is expressed as a percentage (%). The actual valve opening degree in the previous control cycle is expressed as a percentage (%). The inertial time constant of the water flow is determined in advance by the length of the cooling tower pipes and the characteristics of the water pump, and the unit is seconds (s).

[0091] Based on the difference between the rated maximum frequency and the minimum allowable operating frequency of the fan, the water flow response time, and the control cycle, calculate the maximum allowable change in fan frequency within each control cycle:

[0092]

[0093] in, The maximum allowable change in fan frequency within each control cycle, expressed in Hertz (Hz). and These are the highest rated frequency and the lowest permissible operating frequency of the wind turbine, respectively, in Hertz (Hz). The water flow response time is expressed in seconds (s). The control period is measured in seconds (s). The maximum allowable change in fan frequency within each control cycle, in Hertz (Hz).

[0094] Based on the actual operating frequency of the wind turbine, the theoretical required frequency, and the maximum change in the previous control cycle, a rate constraint is applied to the wind turbine frequency to obtain the target frequency:

[0095]

[0096] in, The final target frequency sent to the inverter after rate constraints is expressed in Hertz (Hz). The actual operating frequency of the fan in the previous control cycle is expressed in Hertz (Hz). This is the theoretical required frequency calculated by the PID controller based on the outlet water temperature deviation, and the unit is Hertz (Hz).

[0097] Among them, the water flow response time is calculated. Aimed at quantifying the time required for changes in water-side flow to reach a steady state, this calculation comprehensively considers both the mechanical hysteresis of the electric valve's action and the inertia of the water flow itself. The total stroke time of the electric valve. This reflects the time required for the valve to go from fully closed to fully open, while the change in valve opening during the current period is also reflected. This reflects the difference between the actual valve opening command in the current control cycle and the actual opening in the previous cycle. Water flow inertia time constant. This characterizes the inherent time required for water flow to establish or change velocity in a pipe, and it is related to factors such as pipe length and pump characteristics. By combining valve actuation time with water flow inertia time, the time required for the water-side flow rate to reach a new steady state can be predicted more accurately. For example, the water flow response time can be determined by measuring the time required for the flow sensor to detect flow stabilization when the valve changes from one opening degree to another. The maximum permissible variation in fan frequency within each control cycle is calculated. Used to determine the maximum extent to which the wind turbine frequency can change within a single control cycle, ensuring that the wind-side and water-side responses remain synchronized over time. (Wind turbine rated maximum frequency) and minimum allowed operating frequency The operating range of the fan is defined. Water flow response time. As the denominator, this means that the slower the water flow response, the smaller the maximum allowable change in the fan frequency, thus limiting rapid fluctuations in the fan frequency. Control cycle This is the time interval between one control calculation and one output command by the system. A rate constraint is applied to the fan frequency to obtain the target frequency. This is the core step in actually implementing the fan frequency and rate limit; it uses the PID controller to calculate the theoretically required frequency based on the outlet water temperature deviation. The actual operating frequency of the fan in the previous control cycle A comparison is made. If the difference between the theoretical required frequency and the actual operating frequency exceeds the maximum allowable change in the fan frequency within each control cycle... The actual change in the fan frequency will then be limited to Within a certain range, and varying towards the theoretically required frequency. For example, this rate constraint algorithm can be implemented using a digital signal processor (DSP) or a microcontroller (MCU), calculating the target frequency. Send the signal to the wind turbine inverter; or, the logic can be programmed in a programmable logic controller (PLC) to control the inverter via analog output or digital communication interface.

[0098] The solution proposed in this application ensures that the dynamic responses of the water side (controlled by electric valves) and the air side (controlled by fans) are coordinated and consistent through a dynamic rate constraint module, avoiding system oscillations or control performance degradation caused by mismatch in their response speeds. This module first accurately calculates the water flow response time under the current operating conditions by comprehensively considering the mechanical action characteristics of the electric valves and the physical inertia of the water flow. Specifically, it incorporates the full stroke time of the electric valve. Change in valve opening during the current cycle This quantifies the time required for valve action and incorporates a pre-calibrated water flow inertia time constant. This yields a comprehensive index reflecting the rate of change in water flow. Based on this, the calculated water flow response time is obtained. The dynamic rate constraint module further determines the dynamic rate constraint in each control cycle. Within, the maximum allowable variation in fan frequency The calculation of this maximum variation takes into account the operating range of the wind turbine (rated maximum frequency). With minimum allowed operating frequency (the difference), and compared with the water flow response time. In connection, a longer water flow response time means slower water-side changes, thus limiting the maximum allowable change in fan frequency. This forces the fan frequency change rate to synchronize with the water flow rate change rate on the time scale. Finally, the module utilizes the calculated maximum change... The theoretical required frequency for the PID controller is calculated based on the outlet water temperature deviation. Apply rate constraints. This will apply to the theoretically required frequency. The actual operating frequency of the fan in the previous control cycle In comparison, if the variation in theoretical demand frequency exceeds... The target frequency actually sent to the inverter Will be restricted to Within a certain range. This limiting mechanism ensures that the turbine frequency does not suddenly change drastically, but rather adjusts at a smooth rate that matches the water-side response speed.

[0099] The following is a concrete example to illustrate this. The dynamic rate constraint module can be integrated into the central controller of the cooling tower, which is typically implemented using an industrial-grade programmable logic controller (PLC) or a distributed control system (DCS). At the beginning of each control cycle, the controller first obtains the current actual valve opening from the data acquisition module. The actual valve opening degree in the previous control cycle Meanwhile, the preset full stroke time of the electric valve (e.g., 30 seconds) and the inertial time constant of the water flow. (For example, 5 seconds, a value that can be pre-calibrated based on the cooling tower piping layout and water pump model) is loaded into the calculation unit. The controller uses these parameters, according to the formula... Calculate the current water flow response time For example, if 50%, If the value is 40%, then the valve opening change is 10%, and the water flow response time is... = 8 seconds. Then, the controller obtains the fan's rated maximum frequency. (e.g., 50Hz) and the minimum allowed operating frequency (e.g., 10Hz), and control cycle. (For example, 1 second). Then, according to the formula Calculate the maximum allowable change in fan frequency within each control cycle. Based on the above... For example, 8 seconds =5Hz. Finally, the controller receives the theoretically required frequency from the PID module. (For example, the current actual operating frequency of the wind turbine) For 30Hz, the PID calculates (38Hz). The controller will , and Substitute into the formula Perform calculations. Because... = |38 - 30| = 8Hz, and It is 5Hz, therefore =5Hz. =1. Therefore, =35Hz. Ultimately, the controller will use this rate-constrained target frequency. (35Hz) is sent to the wind turbine inverter instead of the unconstrained 38Hz, thus ensuring that the wind turbine frequency change matches the water-side response speed.

[0100] Through the above technical solution, the intelligent control system for combined wet and dry cooling towers can effectively solve the problem of mismatched dynamic responses between the water and air sides. By dynamically calculating the water flow response time and limiting the rate of change of the fan frequency based on this, the system can ensure that the adjustment speed of the fan frequency and the rate of change of the water flow remain synchronized on the time scale. This avoids water flow fluctuations, outlet water temperature overshoot, or oscillations caused by sudden changes in fan frequency, thereby improving the control accuracy and stability of the cooling tower outlet water temperature. At the same time, this coordinated control helps reduce unnecessary energy consumption, extend equipment lifespan, and improve the overall operating efficiency and reliability of the cooling system.

[0101] Preferably, the energy efficiency optimization module corrects the valve opening command and the fan frequency command in the following manner:

[0102] A total energy consumption model is established, including water-side energy consumption and wind-side energy consumption. The water-side energy consumption is related to the square of the valve opening, and the wind-side energy consumption is related to the cube of the fan frequency. Specifically:

[0103]

[0104] in, Total power, in kilowatts (kW). The actual valve opening degree output by the nonlinear compensation module is expressed as a percentage (%). The final target frequency sent to the frequency converter after rate constraints. The coefficients for the quadratic fitting of pump power and valve opening are expressed in kW / %. 2 , These are the cubic fitting coefficients between the wind turbine power and frequency, in kW / Hz. 3 ;

[0105] Calculate the coordination correction coefficient based on the ratio of the current wet-bulb temperature to the reference wet-bulb temperature, and the ratio of the total energy consumption of conventional control under standard operating conditions to the current total energy consumption:

[0106]

[0107] in, For the collaborative correction coefficient, This represents the current wet-bulb temperature, expressed in degrees Celsius (°C). For reference wet-bulb temperature, the unit is degrees Celsius (°C). This represents the total energy consumption under standard operating conditions and conventional control, expressed in kilowatts (kW). This represents the total energy consumption at the current moment when the linear compensation module and dynamic rate constraint module are operating, expressed in kilowatts (kW). For collaborative correction coefficients;

[0108] Based on the collaborative correction coefficient, the water-side load distribution weighting factor, and the valve opening command, the corrected valve opening command is calculated; and based on the collaborative correction coefficient, the wind-side load distribution weighting factor, and the fan frequency command, the corrected fan frequency command is calculated, specifically as follows:

[0109]

[0110]

[0111] in, This is the revised valve opening command, expressed as a percentage (%). This is the corrected wind turbine frequency command, in Hertz (Hz). Assign weighting factors to water-side loads. Assign weighting factors to wind-side loads. The actual valve opening degree output by the nonlinear compensation module is expressed as a percentage (%). This is the final target frequency sent to the frequency converter after the rate constraint.

[0112] The total energy consumption model quantifies the energy consumption during cooling tower operation. This model correlates water-side energy consumption with the square of the valve opening, reflecting the nonlinear relationship between pump power and flow rate. For example, the pump head and flow rate characteristic curves typically result in a power-to-flow-rate correlation between power and the square or higher powers of the flow rate. Simultaneously, the air-side energy consumption is correlated with the cube of the fan frequency, a common cubic relationship between fan power and speed—that is, fan power is proportional to the cube of the air volume. By establishing such a model, the system can accurately assess the total energy consumption under current operating conditions. This model can be fitted based on actual operating data of the cooling tower equipment or parameterized using performance curves provided by the equipment manufacturer. Cooperative correction coefficients are also included. It is a comprehensive indicator used to evaluate the system's energy efficiency performance under current operating conditions and the impact of environmental conditions on energy efficiency. It combines the current wet-bulb temperature. Compared with reference wet-bulb temperature The ratio is used to reflect the impact of changes in environmental heat load on cooling effect and energy consumption; at the same time, the total energy consumption of conventional control under standard operating conditions is also considered. Compared with current total energy consumption The ratio of the reference wet-bulb temperature to the baseline temperature quantifies the energy efficiency of the current control strategy relative to the baseline strategy. This coefficient allows the system to dynamically sense environmental changes and its own energy efficiency status, providing a basis for subsequent load allocation adjustments. It can be set to the design wet-bulb temperature of the cooling tower, or the average wet-bulb temperature obtained from historical operating data; the total energy consumption under standard operating conditions and conventional control. The corrected valve opening command can be obtained through offline simulation, historical data analysis, or actual measurement under specific standard operating conditions. and the revised wind turbine frequency command These are the final outputs of the energy efficiency optimization module, directly determining the actual operating load on the water and air sides of the cooling tower. This is achieved by introducing a synergistic correction coefficient. and water-side load allocation weighting factor Wind-side load allocation weighting factor The system can dynamically adjust the load distribution on the water side (via valve opening) and the wind side (via fan frequency) based on current energy efficiency assessment results. For example, when When the system indicates that there is room for improvement in current energy efficiency, it can adjust the weighting factor accordingly. and To minimize total energy consumption, the load on the water or wind side should be appropriately increased or decreased. Weighting factors γ and The cooling capacity and energy consumption of the water and air sides can be preset or dynamically adjusted based on the characteristics of the cooling tower, operating experience, or through optimization algorithms. The values ​​can be subjectively assigned based on expert experience, or determined using objective weighting methods, such as the analytic hierarchy process or entropy weighting method.

[0113] In the aforementioned intelligent control system for combined wet and dry cooling towers, the energy efficiency optimization module further enhances the system's energy-saving operation capabilities based on the compensation module and the dynamic rate constraint module. This module first establishes a total energy consumption model that includes both water-side and air-side energy consumption items. This model correlates the power consumption of the water pump with the square of the valve opening, and simultaneously correlates the power consumption of the fan with the cube of the fan frequency, thereby accurately quantifying the total energy consumption of the cooling tower under different operating conditions. Based on this, the energy efficiency optimization module dynamically calculates a collaborative correction coefficient. This coefficient takes into account the current ambient wet-bulb temperature. Compared with reference wet-bulb temperature The relative relationship, and the total energy consumption of current operation. Total energy consumption compared to conventional control under standard operating conditions The comparison allows the system to assess energy efficiency under current operating conditions and the impact of environmental conditions on energy consumption in real time. Subsequently, this collaborative correction coefficient... Used to correct the actual valve opening output by the compensation module. and the final target frequency output by the dynamic rate constraint module Specifically, by introducing a water-side load allocation weighting factor γ and a wind-side load allocation weighting factor δ, the energy efficiency optimization module can optimize the load allocation based on the following factors: The value of the variable dynamically adjusts the load distribution between the water and air sides. For example, when the ambient wet-bulb temperature is low or the current energy consumption is relatively high, the system may adjust the valve opening command accordingly. and the revised wind turbine frequency command By appropriately reducing the load on one side and increasing the load on the other, the system seeks to minimize total energy consumption while still meeting the outlet water temperature requirements. This working principle allows the system to proactively optimize energy consumption across the entire cooling tower system by intelligently adjusting the load distribution between the water and air sides, rather than simply passively responding to temperature deviations. Through coordinated correction of valve opening and fan frequency commands, the system effectively responds to changes in the external environment, avoiding local optimization rather than global optimization caused by a single control strategy. This significantly reduces operating energy consumption while maintaining cooling performance.

[0114] As a specific implementation method, the energy efficiency optimization module can be integrated into the main controller of the cooling tower intelligent control system, for example, using a high-performance industrial-grade programmable logic controller (PLC) or distributed control system (DCS). When establishing the total energy consumption model, the quadratic fitting coefficient between the pump power and the valve opening is used. The cubic fitting coefficient of the fan power versus frequency The power consumption can be determined through regression analysis of actual operating data of the cooling tower under different valve openings and fan frequencies. Alternatively, it can be determined subjectively based on expert experience, or through objective weighting methods such as the analytic hierarchy process (AHP) or entropy weighting. For example, a series of tests can be conducted on the cooling tower in the laboratory or on-site to record the pump current and voltage under different valve openings, and the fan current and voltage under different fan frequencies. Then, the power consumption can be calculated and curve fitting performed to determine the optimal power consumption. and The value can also be subjectively assigned based on expert experience, or an objective weighting method can be used, such as the analytic hierarchy process (AHP) or the entropy weighting method. In calculating the collaborative correction coefficient... At that time, refer to wet-bulb temperature It can be set to 28℃, which is the standard wet-bulb temperature in many cooling tower designs. Total energy consumption under standard operating conditions and conventional control. This can be obtained by operating the cooling tower under design conditions (e.g., inlet water temperature 37°C, outlet water temperature 32°C, wet-bulb temperature 28°C) using a traditional PID control strategy and measuring its steady-state energy consumption. Current total energy consumption The calculation is based on the instantaneous power data of the water pump and fan collected in real time by the data acquisition module. The water-side load distribution weighting factor is used when correcting valve opening commands and fan frequency commands. Wind-side load allocation weighting factor The weighting factor can be preset to 0.5, indicating that the water side and the air side have equal importance in energy efficiency optimization. Alternatively, these weighting factors can be dynamically adjusted according to the operating characteristics and energy-saving targets of the cooling tower. For example, under certain operating conditions, where water-side energy consumption accounts for a larger proportion, the weighting factor can be appropriately increased. The value. The corrected valve opening command. and the revised wind turbine frequency command It is then sent to the airflow distribution module for further adjustment of the airflow distribution ratio between the dry and wet zones.

[0115] Through the above technical solution, the intelligent control system for combined wet and dry cooling towers in this application overcomes the limitations of traditional control methods in energy consumption optimization. While meeting the cooling tower outlet water temperature requirements, the system no longer relies solely on temperature feedback for control. Instead, it proactively establishes a total energy consumption model, dynamically calculates collaborative correction coefficients, and adjusts valve opening commands and fan frequency commands accordingly, achieving intelligent load distribution between the water and air sides. This optimization mechanism allows the system to dynamically adjust its operating strategy based on real-time changes in environmental conditions such as wet-bulb temperature and its own energy consumption performance, thus avoiding the problem of high overall energy consumption caused by fixed load distribution or single-side optimization under non-design conditions. Ultimately, this solution significantly reduces the overall operating energy consumption of the cooling tower, improves the system's energy utilization efficiency, and provides users with a more economical and environmentally friendly operating experience.

[0116] Preferably, the airflow distribution module calculates the target airflow distribution ratio for the dry and wet zones in the following manner:

[0117] Based on the corrected valve opening command and the corrected fan frequency command, calculate the baseline value for the ideal dry and wet airflow distribution ratio:

[0118]

[0119] in, This is the baseline value for the ideal dry zone airflow distribution ratio, which is the proportion of airflow entering the dry radiator to the total airflow, and its value ranges from 0 to 1. This is the revised valve opening command, expressed as a percentage (%). This is the corrected wind turbine frequency command, in Hertz (Hz). , These are the highest rated frequency and the lowest permissible operating frequency of the wind turbine, respectively, in Hertz (Hz). The maximum dry area allocation ratio coefficient (characterizing the maximum theoretical value that the airflow allocation ratio in the dry area can reach). The valve sensitivity coefficient (characterizing the sensitivity of the dry zone airflow distribution ratio to changes in valve opening) is used. This is the frequency influence weighting coefficient (characterizing the weight of the influence of fan frequency changes on the airflow distribution ratio in the dry area).

[0120] Based on the deviation between the current wet-bulb temperature and the design wet-bulb temperature, the ideal distribution ratio benchmark value is corrected to obtain the target dry zone airflow distribution ratio:

[0121]

[0122] in, The airflow allocation ratio for the target dry area. This is the baseline value for the ideal airflow distribution ratio in dry areas. This is the wet-bulb temperature correction factor. The wet-bulb temperature is the temperature under design conditions, expressed in degrees Celsius (°C). The measured wet-bulb temperature is given in degrees Celsius (°C).

[0123] The airflow distribution module is a functional unit whose main function is to accurately calculate and adjust the airflow distribution ratio between the dry radiator and the wet packing according to the received control commands. This module can exist as an independent control unit, for example, composed of a dedicated microcontroller or embedded system, responsible for receiving commands from the upper-level control logic and outputting control signals to the airflow regulating actuator. Alternatively, it can be implemented as a software module or algorithm within the main controller of the entire intelligent control system, sharing hardware resources and the data bus with other control functions. (Modified valve opening command) and the revised wind turbine frequency command These are outputs from the energy efficiency optimization module, representing the water-side and wind-side load allocation strategies after multiple optimizations (including flow nonlinearity compensation, fan frequency dynamic rate constraints, and total energy consumption minimization optimization). These commands are typically transmitted as digital signals, such as percentage values ​​or frequency values, which drive the electric valves and fan inverters to perform corresponding actions. Ideal dry zone airflow distribution ratio baseline value. The theoretical allocation ratio is calculated based on these revised instructions using a pre-defined mathematical model that comprehensively considers the allocation ratio coefficient of the maximum dry area. Valve-related sensitivity coefficient and frequency influence weighting coefficient These parameters reflect the influence of valve opening and fan frequency on the airflow distribution in the dry zone under different operating conditions of the cooling tower. They can be determined through methods such as experimental data fitting, expert experience, or sensitivity analysis. Current wet-bulb temperature These are environmental parameters collected in real time, and the design wet-bulb temperature... These are reference values ​​for the cooling tower under design operating conditions. Wet-bulb temperature correction factor. This is an empirical parameter used to quantify the impact of wet-bulb temperature deviation on airflow distribution. It can be subjectively assigned based on expert experience or determined through data fitting. The final calculated airflow distribution ratio for the target dry area... It is the final control target after adjustments for environmental factors, which will guide the implementing agency to adjust the air volume in the dry and wet zones.

[0124] During actual operation, the airflow distribution module first receives the corrected valve opening command output by the energy efficiency optimization module. and the revised wind turbine frequency command These instructions have been refined to minimize total energy consumption while meeting the outlet water temperature requirements. The airflow distribution module uses a pre-established mathematical model to calculate the ideal dry zone airflow distribution ratio based on these instructions. This benchmark value reflects the theoretical proportion of the total air volume that the dry zone should occupy under the current water-side and wind-side load distribution. The calculation process considers the impact of valve opening on water-side heat dissipation capacity and the contribution of fan frequency to the total air volume, using the maximum dry zone allocation ratio coefficient. Valve-related sensitivity coefficient and frequency influence weighting coefficient These parameters ensured the rationality of the baseline values. However, since real-time changes in the external environment (especially wet-bulb temperature) significantly affect the cooling tower's cooling efficiency and optimal operating mode, relying solely on ideal baseline values ​​for airflow distribution may not achieve optimal results. Therefore, the airflow distribution module further incorporates parameters related to the current wet-bulb temperature. Real-time monitoring. By monitoring the current wet-bulb temperature. With design wet-bulb temperature Compare and incorporate wet-bulb temperature correction factors. The previously calculated ideal dry zone airflow distribution ratio benchmark value Dynamic corrections are made. This correction mechanism ensures that the final target dry area airflow distribution ratio is achieved. The system can adapt to environmental changes. For example, when the wet-bulb temperature is low, the dry zone airflow distribution ratio can be appropriately increased to utilize cooler air for dry cooling, thereby reducing evaporation losses caused by wet cooling. Conversely, when the wet-bulb temperature is high, the wet zone airflow distribution ratio may be increased to enhance the evaporative cooling effect. In this way, the airflow distribution module combines the valve opening command and fan frequency command, which have undergone multi-level optimization and constraint, with real-time environmental parameters (wet-bulb temperature) to calculate the precise target dry zone airflow distribution ratio, thereby guiding the actuator to adjust the ratio of airflow entering the dry radiator to airflow entering the wet packing.

[0125] The following is a concrete example. The airflow distribution module can be implemented by an industrial controller, such as a high-performance microprocessor or application-specific integrated circuit (ASIC). This controller receives corrected valve opening commands from the energy efficiency optimization module. (For example, a digital value from 0 to 100%) and the corrected wind turbine frequency command (For example, a digital value of 0-50Hz), and the current wet-bulb temperature from the data acquisition module. (For example, a floating-point number in degrees Celsius). The controller stores preset parameters internally, such as... , , , , , , and When the controller receives new input data, it first executes the formula. Calculate the benchmark value of the ideal dry area airflow distribution ratio. For example, if 70%, Given a frequency of 40Hz and a pre-set correlation coefficient, a value can be calculated. A value, for example, 0.55. The controller then uses the formula... Make corrections. Assume... The current temperature is 28℃. It is 25℃. If the value is 0.15, then the correction term is... =1.016. At this time, the airflow distribution ratio in the target dry area is... The value will be 0.559. Calculated... Then, the controller outputs corresponding control signals to the airflow regulating actuator inside the cooling tower, such as the driver of an electric damper or guide vane, to adjust it to the appropriate opening degree, thereby distributing the total airflow according to... The proportion is allocated to dry radiators and wet fillers.

[0126] Through the above technical solution, this application can dynamically calculate and adjust the target airflow distribution ratio between the dry and wet zones based on the modified valve opening command and fan frequency command, combined with the real-time wet-bulb temperature. This allows the cooling tower to more accurately control the load distribution between the dry and wet zones, avoiding localized overcooling or overheating that may occur when relying solely on water-side and air-side load adjustments during environmental changes. Especially when the wet-bulb temperature deviates from the design operating conditions, by correcting the ideal distribution ratio benchmark value, the system can intelligently adjust the airflow ratio between the dry and wet zones, thereby minimizing total energy consumption, reducing water consumption, and extending equipment lifespan while ensuring the outlet water temperature meets requirements. This refined airflow distribution control significantly improves the operating efficiency and economy of the combined dry and wet cooling tower under complex and variable operating conditions.

[0127] Preferably, the water flow inertial time constant Pre-calibration is determined using the following methods:

[0128] Record the response curve of cooling water flow rate from initial value to target value under the step change condition of electric valve;

[0129] The time required for the flow response to reach the target value is defined as the inertial time constant of the water flow. The unit is seconds (s);

[0130] The water flow inertial time constant With cooling tower pipe length and pump inertia coefficient The relationship is as follows:

[0131]

[0132] in, The total length of the cooling tower water supply pipeline is expressed in meters (m). The average flow velocity of water in the pipe is expressed in meters per second (m / s). The pump inertia correction factor (the pump inertia correction factor can be determined in various flexible ways. It can be obtained by statistical analysis and regression modeling of a large amount of measured data to ensure its accuracy; or when there is a lack of sufficient measured data, it can be reasonably assigned by referring to the knowledge and experience of experts in the industry to quickly establish a model).

[0133] A method for operating a combined wet and dry cooling tower intelligent control system includes the following steps:

[0134] Step S10: Collect the operating data and equipment characteristic parameters of the cooling tower through the data acquisition module;

[0135] Step S20: The compensation module compensates for the theoretical required opening degree output by the controller based on the flow characteristic deviation data of the electric valve, and generates the actual valve opening degree command.

[0136] Step S30: The dynamic rate constraint module calculates the upper limit of the dynamic change rate of the fan frequency based on the action lag time of the electric valve and the inertial time of the water flow, and imposes rate constraints on the frequency change of the fan inverter so that the change rate of the fan frequency and the change rate of the valve flow are coordinated on the time scale.

[0137] Step S40: Under the premise of meeting the outlet water temperature requirements, the energy efficiency optimization module aims to minimize the total energy consumption by dynamically adjusting the load distribution between the water side and the air side based on the wet-bulb temperature, generating a collaborative correction coefficient, and correcting the valve opening command output in step S20 and the fan frequency command output in step S30 to obtain the corrected valve opening command and the corrected fan frequency command.

[0138] Step S50: The airflow distribution module calculates the target airflow distribution ratio between the dry and wet zones based on the corrected valve opening command and the corrected fan frequency command, and then adjusts the airflow ratio entering the dry radiator and entering the wet packing.

[0139] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0140] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An intelligent control system for a combined wet and dry cooling tower, characterized in that, include: The data acquisition module is used to collect the operating data and equipment characteristic parameters of the cooling tower; The compensation module compensates for the theoretical required opening degree output by the controller based on the valve linearity deviation table, and generates the actual valve opening degree command. The dynamic rate constraint module calculates the upper limit of the dynamic change rate of the fan frequency based on the action lag time of the electric valve and the inertial time of the water flow, and imposes rate constraints on the frequency change of the fan inverter, so that the change rate of the fan frequency and the change rate of the valve flow are coordinated on the time scale. The energy efficiency optimization module is used to dynamically adjust the load distribution between the water side and the air side based on the wet-bulb temperature, with the goal of minimizing total energy consumption while meeting the outlet water temperature requirements. It generates a collaborative correction coefficient and uses the collaborative correction coefficient to correct the valve opening command and the fan frequency command, thus obtaining the corrected valve opening command and the corrected fan frequency command. The airflow distribution module calculates the target airflow distribution ratio between dry and wet zones based on the corrected valve opening command and the corrected fan frequency command, and then adjusts the airflow ratio entering the dry radiator and the wet packing.

2. The intelligent control system for combined wet and dry cooling towers according to claim 1, characterized in that, The steps by which the compensation module generates the valve's actual opening command are as follows: Obtain measured flow data of the electric valve at multiple test points with different opening degrees; Calculate the flow linearity deviation coefficient at each test point based on the ratio of theoretical flow rate to actual flow rate at each test point. For any opening Flow linearity deviation coefficient It is determined by linear interpolation; The actual valve opening is calculated based on the ratio of the theoretical required opening to the flow linearity deviation coefficient.

3. The intelligent control system for a combined wet and dry cooling tower according to claim 1, characterized in that, The dynamic rate constraint module applies rate constraints to the wind turbine frequency in the following manner: The water flow response time is calculated based on the total stroke time of the electric valve, the change in valve opening in the current cycle, and the water flow inertia time constant. Based on the difference between the rated maximum frequency and the minimum allowable operating frequency of the fan, the water flow response time, and the control cycle, calculate the maximum allowable change in the fan frequency within each control cycle; Based on the actual operating frequency of the fan in the previous control cycle, the theoretical required frequency, and the maximum change, a rate constraint is applied to the fan frequency to obtain the target frequency.

4. The intelligent control system for combined wet and dry cooling towers according to claim 1, characterized in that, The energy efficiency optimization module corrects the valve opening command and the fan frequency command in the following manner: A total energy consumption model is established that includes water-side energy consumption and wind-side energy consumption. The water-side energy consumption is related to the square of the valve opening, and the wind-side energy consumption is related to the cube of the fan frequency. The collaborative correction coefficient is calculated based on the ratio of the current wet-bulb temperature to the reference wet-bulb temperature, and the ratio of the total energy consumption of conventional control under standard operating conditions to the current total energy consumption. The corrected valve opening command is calculated based on the collaborative correction coefficient, the water-side load distribution weight factor, and the valve opening command. And calculate the corrected wind turbine frequency command based on the collaborative correction coefficient, the wind-side load allocation weighting factor, and the wind turbine frequency command.

5. The intelligent control system for a combined wet and dry cooling tower according to claim 1, characterized in that, The airflow distribution module calculates the target airflow distribution ratio for the dry and wet zones in the following manner: Based on the corrected valve opening command and the corrected fan frequency command, calculate the baseline value of the dry and wet zone airflow distribution ratio under ideal conditions; Based on the deviation between the current wet-bulb temperature and the design wet-bulb temperature, the ideal distribution ratio benchmark value is corrected to obtain the target dry area airflow distribution ratio.

6. The intelligent control system for a combined wet and dry cooling tower according to claim 1, characterized in that, The operating data and equipment characteristic parameters include inlet water temperature, outlet water temperature, wet bulb temperature, current valve opening degree, current fan frequency, flow linearity deviation table, and target outlet water temperature.

7. The intelligent control system for a combined wet and dry cooling tower according to claim 3, characterized in that, The water flow inertial time constant Pre-calibration is determined using the following methods: Record the response curve of cooling water flow rate from initial value to target value under the step change condition of electric valve; The time required for the flow response to reach the target value is defined as the inertial time constant of the water flow. The unit is seconds; The water flow inertial time constant With cooling tower pipe length and pump inertia coefficient The relationship is as follows: in, The total length of the cooling tower water supply pipeline. The average flow velocity of water inside the pipe. This is the pump inertia correction factor.

8. A method for operating a smart control system for a combined wet and dry cooling tower, characterized in that, Includes the following steps: step S10: Collects operating data and equipment characteristic parameters of the cooling tower through the data acquisition module; Step S20: The compensation module compensates for the theoretical required opening degree output by the controller based on the flow characteristic deviation data of the electric valve, and generates the actual valve opening degree command. Step S30: The dynamic rate constraint module calculates the upper limit of the dynamic change rate of the fan frequency based on the action lag time of the electric valve and the inertial time of the water flow, and imposes rate constraints on the frequency change of the fan inverter so that the change rate of the fan frequency and the change rate of the valve flow are coordinated on the time scale. Step S40: Under the premise of meeting the outlet water temperature requirements, the energy efficiency optimization module aims to minimize the total energy consumption by dynamically adjusting the load distribution between the water side and the air side based on the wet-bulb temperature, generating a collaborative correction coefficient, and correcting the valve opening command output in step S20 and the fan frequency command output in step S30 to obtain the corrected valve opening command and the corrected fan frequency command. Step S50: The airflow distribution module calculates the target airflow distribution ratio between the dry and wet zones based on the corrected valve opening command and the corrected fan frequency command, and then adjusts the airflow ratio entering the dry radiator and entering the wet packing.

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