An automatic cooling method for a digital energy-saving pump

Abstract

The present invention belongs to the field of energy-saving pump control, and in particular relates to an automatic cooling method for a digital energy-saving pump, comprising: obtaining the normal operating temperature range, water supply and water supply demand curve of the energy-saving pump, temperature and energy consumption changes under different working states, historical data of a cooling device, etc. and pre-processing; secondly, constructing a differential energy-saving efficiency temperature prediction curve function according to the temperature changes under different working states, and constructing a comprehensive energy consumption and a single energy consumption curve in combination with energy consumption and cooling device data; thirdly, based on a cooling control optimization model, using relevant curves and intervals to construct a temperature adjustment fitness function and constraint conditions, and obtaining the cooling time point interval and energy consumption of air cooling and water cooling devices through training; fourthly, constructing a cooling control adjustment model, inputting the above-mentioned parameters for training to obtain differential time point control instructions; finally, real-time monitoring of various parameter deviations, and feeding back to the cooling control optimization model to adjust the cooling control adjustment model, so as to realize precise cooling control of digital energy saving.

Description

Technical Field

[0001] The invention belongs to the field of energy-saving pump control, and in particular relates to an automatic cooling method for a digital energy-saving pump. Background Art

[0002] Digital energy-saving pumps are widely used in industries, water supply, HVAC and other fields. During operation, the pump body generates heat due to mechanical friction and motor operation. If the heat is not dissipated in time, it will affect the performance, life and safety. Existing cooling technology has shortcomings. Forced air cooling relies on fans to accelerate air flow and heat dissipation, but the heat dissipation capacity is limited in high temperature environments; although water cooling has high heat dissipation efficiency, it has high consumption costs and complex maintenance. Therefore, how to combine cooling methods and integrate their advantages has become an important issue in current research. For example, the cooling system with direct expansion cooling and pumped refrigerant energy-saving cooling disclosed in the Chinese patent with authorization announcement number CN107850355B can switch between pumped refrigerant energy-saving cooling and direct expansion cooling according to the external air temperature, but it is mainly aimed at specific cooling systems and does not fully consider the special working conditions of digital energy-saving pumps, such as the unique distribution and change law of heat generated by the mechanical structure of the pump body and the operation of the motor; and the system does not comprehensively weigh the cooling effect and energy-saving effect, and it is difficult to directly apply it to digital energy-saving pumps to achieve efficient, low-cost and easy-to-maintain heat dissipation needs.

[0003] The above prior art has the following problems: The prior art has significant problems in the cooling of digital energy-saving pumps. Most existing methods only focus on cooling and cooling the energy-saving pumps in isolation, but fail to effectively achieve the coordinated control of the working state, temperature, working time of the cooling system and cooling consumption of the energy-saving pumps, and cannot accurately control the cooling energy consumption. For this reason, the present invention provides an automatic cooling method and system for digital energy-saving pumps. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention proposes an automated cooling method and system for a digital energy-saving pump, including: obtaining the normal operating temperature range, water supply and water supply demand curve of the energy-saving pump, temperature and energy consumption changes under different working states, historical data of the cooling device, etc. and pre-processing; secondly, constructing a differential energy-saving efficiency temperature prediction curve function according to the temperature changes in different working states, and constructing a comprehensive energy consumption and a single energy consumption curve in combination with the energy consumption and cooling device data; thirdly, constructing a cooling control optimization model based on a genetic algorithm, and using relevant curves and intervals to construct a temperature adjustment fitness function and constraint conditions, and obtaining the cooling time point interval and energy consumption of the air cooling and water cooling devices through training; fourthly, constructing a cooling control adjustment model, inputting the above-mentioned parameters for training to obtain differential time point control instructions; finally, controlling the cooling device according to the instructions, monitoring the deviations of various parameters in real time, and feeding back to the optimization model to adjust the cooling control adjustment model, so as to realize automated and precise cooling control of the digital energy-saving pump.

[0005] To achieve the above object, the present invention provides the following technical solutions: An automatic cooling method for a digital energy-saving pump, comprising: Obtain differential energy-saving efficiency temperature prediction curve function and comprehensive energy consumption curve and single energy consumption curve function under differential energy-saving efficiency; The temperature adjustment adaptability function and constraint conditions are constructed using the comprehensive energy consumption curve and single energy consumption curve function, temperature prediction curve function, water supply change curve function, and normal operating temperature range; The temperature adjustment fitness function and constraint conditions are built into the constructed cooling control optimization model for training, and the predicted cooling time interval, single cooling energy consumption and comprehensive energy consumption of air cooling and water cooling devices are obtained; The predicted temperature drop time interval is obtained by the predicted temperature change rate of the energy-saving pump and the ideal temperature change rate per unit time of the energy-saving pump; The predicted cooling time point intervals, single cooling energy consumption and comprehensive energy consumption of the air-cooling and water-cooling devices are input into the constructed cooling control and regulation model for training, and differential time point control instructions of the cooling devices are obtained to perform differential cooling time point control of the cooling devices.

[0006] Specifically, the construction process of the comprehensive energy consumption curve includes: According to the historical temperature change data of the energy-saving pump under different working conditions, the temperature prediction curve function is obtained; According to the cooling efficiency of the air cooling or water cooling device per unit time at the corresponding temperature in the temperature prediction curve function and the cooling energy consumption per unit time under the corresponding cooling efficiency, a single energy consumption curve of the corresponding cooling device is obtained; According to the working energy consumption data of the energy-saving pump under different working conditions, the working energy consumption change curves and corresponding change functions under different working conditions are constructed.

[0007] Specifically, the construction process of the comprehensive energy consumption curve also includes: The single energy consumption curve corresponding to the air cooling and water cooling devices is aligned with the working energy consumption data under the corresponding working state in the time dimension, and the water supply energy consumption at the same time point is superimposed with the air cooling or water cooling energy consumption to obtain the comprehensive energy consumption of water supply and cooling and the comprehensive energy consumption curve of the energy-saving pump at the corresponding time point, and determine the energy consumption level at the corresponding time point.

[0008] Specifically, the working state of the energy-saving pump is the water supply flow rate of the energy-saving pump per unit time, and the construction process of the temperature adjustment fitness function and the constraint conditions includes: According to the required water supply and the working status of the energy-saving pump, the target water supply demand time interval is obtained. ,in Indicates the initial water supply time point corresponding to the demand water supply, Indicates the end water supply time point corresponding to the demand water supply; According to the target water supply demand time length and normal working temperature range, the ideal temperature change rate per unit time of the energy-saving pump is obtained. ; According to the temperature prediction curve function, the predicted temperature change rate of the energy-saving pump is obtained. .

[0009] Specifically, the process of constructing the temperature adjustment fitness function and constraint conditions also includes: According to the historical operation order of air cooling and water cooling devices, the corresponding temperature adjustment range and the corresponding energy consumption per unit time, the initial cooling device is selected for cooling; According to the predicted temperature change rate of the energy-saving pump and the ideal temperature change rate per unit time of the energy-saving pump, we can obtain First time greater than The corresponding time point , and select the initial cooling device to start cooling down, so that .

[0010] Specifically, the process of constructing the temperature adjustment fitness function and constraint conditions also includes: According to the predicted temperature change rate of the energy-saving pump, the ideal temperature change rate per unit time of the energy-saving pump, and the cooling efficiency of the initial cooling device corresponding to the rated power, the cooling efficiency of the initial cooling device at the rated power is obtained. The corresponding time point , and select the initial cooling device and the remaining cooling device to cool down the energy-saving pump at the same time; According to the cooling efficiency, cooling energy consumption, energy consumption of energy-saving pumps and the difference between supply and demand of energy-saving pumps corresponding to the initial cooling device and the remaining cooling device , construct the temperature adjustment fitness function and constraints of the initial cooling device and the remaining cooling devices, so that and Under this condition, the comprehensive energy consumption of water supply and cooling is minimal.

[0011] Specifically, the process of constructing the temperature adjustment fitness function and constraint conditions of the initial cooling device and the remaining cooling devices includes: According to the historical output power, cooling efficiency and air cooling energy consumption of the air cooling device, the air cooling energy consumption fitting function is obtained through the nonlinear fitting function. ; According to the historical water cooling device corresponding output power, cooling flow and flow rate, cooling efficiency and water cooling energy consumption, the water cooling energy consumption fitting function is obtained through nonlinear fitting function. ; According to the flow rate, speed and corresponding working energy consumption of the energy-saving pump under the corresponding working state, the energy-saving pump working energy consumption fitting function is obtained through the nonlinear fitting function. ; according to , and Constructing the temperature adjustment fitness function and the corresponding constraints, and the energy consumption value of the temperature adjustment fitness function is the minimum at the corresponding time point and Under the conditions of , the linear programming algorithm is used to solve the predicted pre-combined operation parameter set corresponding to water cooling, air cooling and energy-saving pumps; After cooling by air cooling and water cooling at the same time, the current temperature is less than or equal to When the temperature corresponding to the moment is reached, the remaining cooling devices are set to the silent state corresponding to the lowest energy consumption, and the energy-saving pump is adjusted to cool down through the previous joint operation parameter set of the cooling control optimization model, so that and .

[0012] Specifically, the pre-joint operation parameter set includes a difference adjustment factor, which is used to adjust the difference between The ratio of the output power of the air cooling device to the water cooling device corresponding to different time points is adjusted within the time interval; the step of obtaining the difference adjustment factor includes: According to the attribute data of air cooling and water cooling devices, the effective cooling efficiency of air cooling and water cooling devices at different output powers is obtained and ; according to , , current moment and The difference between and The corresponding output power of air-cooling and water-cooling devices; According to satisfaction and The corresponding air cooling and water cooling device output power and the corresponding time point and The difference is used to obtain the function of the difference adjustment factor through the support vector machine, and the function of the difference adjustment factor obtained is built into the cooling control adjustment model.

[0013] Specifically, the specific steps of building the cooling control adjustment model include: according to and , the function of the difference adjustment factor, the current temperature is less than or equal to The temperature corresponding to the moment constructs the input state of the cooling control regulation model; The execution action trigger information is constructed according to the input state of the cooling control adjustment model, specifically: When it first appeared At the corresponding time point , triggering the first action execution information, that is, calling the initial cooling device and using and , obtaining an initial cooling device operating parameter set, and controlling the initial cooling device to cool down according to the initial cooling device operating parameter set; When the cooling efficiency of the initial cooling device is still met At the corresponding time point , triggering the second action execution information, that is, calling the initial cooling device and the remaining cooling devices at the same time to cool down.

[0014] Specifically, the specific steps of constructing the cooling control adjustment model also include: The third action execution information is triggered at the same time as the second action execution information is triggered, that is, according to the temperature adjustment fitness function And the corresponding constraints, through the linear programming algorithm, obtain and The output power ratio of the initial cooling device and the remaining cooling devices is adjusted according to the function of the difference adjustment factor in the pre-joint operation parameter set corresponding to the water cooling, air cooling and energy-saving pump under the conditions; According to the output power ratio of the initial cooling device and the remaining cooling devices and the attribute data of the initial cooling device and the remaining cooling devices, the operating parameter set corresponding to the initial cooling device and the remaining cooling devices at the current moment is obtained; When the current temperature is less than or equal to When the temperature corresponding to the moment is reached, the fourth action execution information is triggered, that is, at the current time point, the remaining cooling devices are set to the silent state corresponding to the lowest energy consumption through the difference adjustment factor, and the operating parameter set corresponding to the initial cooling device is adjusted to reduce the temperature so that ; According to the execution action trigger information, construct the execution action corresponding to the trigger action execution information; When the corresponding execution action information is triggered, the air cooling, water cooling or energy-saving pump operating parameter set obtained by triggering the corresponding execution action information is input into the fuzzy control algorithm to obtain the operation control instructions of the air cooling device, water cooling device or energy-saving pump at the corresponding time point, so that the predicted temperature change rate curve of the energy-saving pump is always below the ideal temperature change rate curve.

[0015] Compared with the prior art, the present invention has the following beneficial effects: In view of the deficiencies in the prior art, the present invention constructs a differential energy-saving efficiency temperature prediction curve and a comprehensive energy consumption curve, combines temperature prediction and water supply changes, optimizes the temperature adjustment fitness function and constraint conditions of the cooling system, and accurately predicts the cooling time points and energy consumption of air-cooling and water-cooling devices. At the same time, differential adjustment factors are obtained through the temperature adjustment fitness function and constraint conditions to achieve the optimal ratio adjustment of the cooling device output power at different time points, which significantly improves the system's response speed, cooling effect and energy consumption management, prolongs equipment life, and achieves dual optimization of temperature control and energy management. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a flow chart of an automated cooling method for a digital energy-saving pump according to Embodiment 1 of the present invention; Figure 2 This is a flow chart of an automated cooling method for a digital energy-saving pump according to Example 1 of the present invention. DETAILED DESCRIPTION

[0017] Example 1

[0018] See also Figure 1 to Figure 2 The present invention provides an embodiment: an automated cooling method for a digital energy-saving pump, which is applied to an AAB digital energy-saving centrifugal pump. Furthermore, the cooling device in this embodiment is arranged on a digital integrated controller of the digital energy-saving pump to perform data collection, processing and cooling control. The specific process is as follows: S1. Obtain the normal working temperature range corresponding to the energy-saving pump, the corresponding water supply change curve and water supply demand curve, the corresponding temperature change data and energy consumption change state under different working conditions, the historical start time of the configured cooling device and the starting point of the temperature drop, and the cooling energy consumption of different cooling forms under different working conditions, and perform preprocessing; Furthermore, the cooling device in this embodiment includes an air cooling device and a water cooling device; further, the differential working state in this embodiment refers to the working state of the energy-saving pump at different output flow levels; for example, 5m 3 / h、10m 3 / h, etc.; Further, the energy-saving pump in this embodiment corresponds to three energy efficiency levels at different output flow levels. For example, the single-stage single-suction pump unit in the energy-saving pump has a flow rate of ≤300 When the single-stage single-suction pump unit is at a flow rate of ≤300, the energy efficiency level in this embodiment is represented and obtained by the efficiency value of the specified point of the energy-saving pump unit. When the corresponding energy-saving pump unit efficiency values ​​of the third, second and first energy efficiency levels are and ,in Indicates the efficiency value of the energy-saving pump unit at a specified point.

[0019] S2. Obtain a differential energy-saving efficiency temperature prediction curve function according to the corresponding temperature change data under differential working conditions. At the same time, obtain a comprehensive energy consumption curve and a single energy consumption curve corresponding to different cooling devices under differential energy-saving efficiencies according to the energy consumption prediction curves under different working conditions and the historical start time points of the cooling devices and the corresponding temperature starting points and the cooling energy consumption of different cooling forms under different working conditions. Furthermore, the construction process of the comprehensive energy consumption curve in this embodiment includes: According to the historical temperature change data of the energy-saving pump under different working conditions, the temperature prediction curve function is obtained; According to the cooling efficiency of the air cooling or water cooling device per unit time at the corresponding temperature in the temperature prediction curve function and the cooling energy consumption per unit time under the corresponding cooling efficiency, a single energy consumption curve of the corresponding cooling device is obtained; According to the working energy consumption data of energy-saving pumps under different working conditions, the working energy consumption change curve and corresponding change function under different working conditions are constructed; The single energy consumption curve corresponding to the air cooling and water cooling devices is aligned with the working energy consumption data under the corresponding working state in the time dimension, and the water supply energy consumption at the same time point is superimposed with the air cooling or water cooling energy consumption to obtain the comprehensive energy consumption of water supply and cooling and the comprehensive energy consumption curve of the energy-saving pump at the corresponding time point, and determine the energy consumption level at the corresponding time point.

[0020] This process firstly constructs a differential energy-saving efficiency temperature prediction curve function, which can accurately predict the temperature change trend of the energy-saving pump at different output flow levels, ensuring that it always maintains within the normal operating temperature range. At the same time, the construction of the comprehensive energy consumption curve and the single energy consumption curve enables the cooling system to minimize energy consumption while ensuring the efficient operation of the energy-saving pump; secondly, based on the temperature prediction curve function and the energy consumption curve, the system can predict the working state and cooling demand of the energy-saving pump in advance, select the optimal cooling method (air cooling or water cooling), and accurately control the start-up time and cooling intensity of the cooling device, avoiding the energy waste caused by overcooling or insufficient cooling in the traditional method; thirdly, by aligning and superimposing the single energy consumption curve and the comprehensive energy consumption curve of the cooling device in the time dimension, the coordinated optimization of water supply energy consumption and cooling energy consumption is achieved, unnecessary cooling operations are reduced, and energy utilization efficiency is significantly improved; finally, by constructing the working energy consumption change curve under different working conditions and the corresponding change function, the system can dynamically adjust the cooling strategy, flexibly respond to various working conditions, and ensure that the energy-saving pump can maintain an efficient and energy-saving working state at different output flow levels.

[0021] S3. Build a cooling control optimization model based on genetic algorithm, and use the comprehensive energy consumption curve and single energy consumption curve function, differential energy-saving efficiency temperature prediction curve function, water supply change curve function and water supply demand curve error, and normal working temperature range to build temperature adjustment fitness function and constraint conditions, and build the temperature adjustment fitness function and constraint conditions into the cooling control optimization model for training, and obtain the predicted cooling time point interval, single cooling energy consumption and comprehensive energy consumption of air cooling and water cooling devices; Furthermore, the process of constructing the temperature adjustment fitness function and constraint conditions in this embodiment includes: According to the required water supply and the working status of the energy-saving pump, the target water supply demand time interval is obtained. ,in Indicates the initial water supply time point corresponding to the demand water supply, Indicates the end water supply time point corresponding to the demand water supply; Furthermore, the working state of the energy-saving pump in this embodiment is the water supply flow rate per unit time of the energy-saving pump set and adjusted at the current moment. The initial water supply time point is set according to the digital integrated controller on the digital energy-saving pump, and the total water supply is set according to user needs. Assuming that the working state remains unchanged during the water supply process, the final end water supply time point is calculated.

[0022] According to the target water supply demand time length and normal working temperature range, the ideal temperature change rate per unit time of the energy-saving pump is obtained. ; Further, the normal working temperature range in this embodiment is the temperature range corresponding to the loop device in the energy-saving pump; According to the temperature prediction curve function, the predicted temperature change rate of the energy-saving pump is obtained. .

[0023] According to the historical operation order of air cooling and water cooling devices, the corresponding temperature adjustment range and the corresponding energy consumption per unit time, the initial cooling device is selected for cooling; Furthermore, in this embodiment, a cooling device with the smallest energy consumption per unit time and suitable for mechanical cooling in a low temperature state is selected. For example, in this embodiment, an air cooling device is suitable for the cooling process in a low temperature state, so an air cooling device is selected for initial cooling.

[0024] Furthermore, the specific process of selecting a cooling device in this embodiment includes: First, collect historical operating data of air-cooling and water-cooling devices, including start-up time, operating time, and temperature variation range (temperature adjustment range); Second, count the number of times each cooling device has been started in the past period of time to understand its usage frequency, record the initial and final temperatures at each start-up, determine the effective temperature adjustment range of each cooling device, calculate the total energy consumption during each operation, and divide it by the operating time to obtain the energy consumption per unit time; Third, based on the above statistical data, an analysis and evaluation of air cooling and water cooling devices shows that air cooling devices are usually more efficient at low temperatures, because air cooling relies on air flow to remove heat, and low temperature environments help improve heat dissipation, while water cooling systems perform better at high temperatures because they can handle large amounts of heat load more effectively; Fourth, set selection criteria, specifically: give priority to the cooling device with the lowest energy consumption per unit time, and secondly, consider the need for energy-saving pumps to operate at low temperatures, and select cooling devices that are more suitable for low-temperature environments; Fifth, a specific cooling device is selected based on the set selection criteria and the specific working state and temperature state of the energy-saving pump. For example, in this embodiment, the initial cooling device is an air cooling device.

[0025] According to the predicted temperature change rate of the energy-saving pump and the ideal temperature change rate per unit time of the energy-saving pump, we can obtain First time greater than The corresponding time point , and select the initial cooling device to start cooling down, so that ; Further, , which means that Satisfaction first appeared in Condition time point, further, in this embodiment f Indicates that the solution first appears to satisfy Conditional time point The corresponding function.

[0026] According to the predicted temperature change rate of the energy-saving pump, the ideal temperature change rate per unit time of the energy-saving pump, and the cooling efficiency of the initial cooling device corresponding to the rated power, the cooling efficiency of the initial cooling device at the rated power is obtained. The corresponding time point , and select the initial cooling device and the remaining cooling device to cool down the energy-saving pump at the same time; Furthermore, in this embodiment, at the rated power cooling efficiency of the initial cooling device At the corresponding time point, that is, at the maximum cooling power of the initial cooling device, it is still impossible to meet The initial cooling time point of the condition; at this moment, the initial cooling device alone can no longer meet the corresponding cooling demand, so that Condition; then call the remaining cooling device for cooling. In this embodiment, if the initial cooling device is an air cooling device, the remaining cooling device is a water cooling device.

[0027] According to the cooling efficiency, cooling energy consumption, energy consumption of energy-saving pumps and the difference between supply and demand of energy-saving pumps corresponding to the initial cooling device and the remaining cooling device , construct the temperature adjustment fitness function and constraints of the initial cooling device and the remaining cooling devices, so that and Under this condition, the comprehensive energy consumption of water supply and cooling is minimal.

[0028] Furthermore, in this embodiment, the process of constructing the temperature adjustment fitness function and constraint conditions of the initial cooling device and the remaining cooling devices includes: According to the historical output power, cooling efficiency and air cooling energy consumption of the air cooling device, the air cooling energy consumption fitting function is obtained through the nonlinear fitting function. ; By performing nonlinear fitting on the historical data of air-cooling device output power, cooling efficiency, and air-cooling energy consumption, a function that can accurately describe the relationship between factors such as air-cooling device energy consumption and output power is obtained. This allows the energy consumption of the air-cooling device under different operating parameters to be accurately predicted according to current needs and equipment status in subsequent work deployment, providing basic data support for overall energy consumption optimization. For example, when the air-cooling device is required to provide a certain cooling effect, the most energy-efficient output power setting can be quickly determined based on the fitting function.

[0029] Similarly, according to the historical water cooling device corresponding to the output power, cooling flow and flow rate, cooling efficiency and water cooling energy consumption, the water cooling energy consumption fitting function is obtained through the nonlinear fitting function. ; Furthermore, the fitting function constructed based on the historical data of the water cooling device corresponding to the output power, cooling flow and flow rate, cooling efficiency and water cooling energy consumption in this embodiment can clearly reflect the energy consumption characteristics of the water cooling device. In actual operation, the system can use this function to calculate the energy consumption under different water cooling operation parameters according to the current temperature conditions and cooling requirements, so as to select the optimal water cooling operation scheme in the temperature adjustment fitness function to achieve coordinated energy-saving operation with air cooling and energy-saving pumps.

[0030] According to the flow rate, speed and corresponding working energy consumption of the energy-saving pump under the corresponding working state, the energy-saving pump working energy consumption fitting function is obtained through the nonlinear fitting function. ; according to and Constructing the temperature adjustment fitness function and the corresponding constraints, and the energy consumption value of the temperature adjustment fitness function is the minimum at the corresponding time point and , Under this condition, the linear programming algorithm is used to solve the predicted pre-combined operation parameter set corresponding to water cooling, air cooling and energy-saving pumps; The specific expression formula of the temperature adjustment fitness function and the corresponding constraint conditions is: ; in is the weighting coefficient of the corresponding energy consumption fitting function; Indicates i Energy consumption weighting coefficient of each cooling device, Indicates that the energy-saving pump is running at j The energy efficiency level coefficient corresponding to the working state is: Indicates i Energy consumption fitting function of a cooling device, represents the weight adjustment coefficient, t Indicates the current moment, Indicates i The starting time point of the cooling device; where represents the effective cooling efficiency of the air cooling device at different output powers, where Indicates the effective cooling efficiency of the water cooling device at different output powers; Indicates i The effective cooling efficiency of the cooling device at the current moment; Indicates i The effective cooling efficiency of the cooling device at the current moment, represents the minimum value function, Indicates that the energy-saving pump is running at j The corresponding working energy consumption fitting function under the working state is: and They represent the upper limit thresholds of energy consumption per unit time corresponding to air cooling and water cooling devices respectively.

[0031] Furthermore, in this embodiment, by constructing corresponding minimum optimization functions and constraints according to the energy consumption fitting functions corresponding to the air cooling device, water cooling device and energy-saving pump respectively, the operating parameter sets of air cooling, water cooling and energy-saving pumps at the corresponding time points are searched to optimize the output energy consumption among the three as a whole. While meeting user needs and normal working temperature requirements, the operating states of the three are adjusted so that the operating states of the air cooling, water cooling and energy-saving pumps can reach the optimal state at the same time.

[0032] Furthermore, in the present embodiment, the weighted coefficients corresponding to air cooling and water cooling are used to regulate the proportional coefficient of the corresponding energy consumption through the corresponding effective cooling efficiency, the energy efficiency level of the corresponding operation of the energy-saving pump and the length of the operating time, so that in the minimum optimization function, the corresponding cooling device can adjust the overall proportion of the corresponding energy consumption according to its energy consumption within the corresponding time length. The introduction of the energy efficiency level coefficient is used to adjust the weight relationship between the cooling device and the energy-saving pump, so that the optimization function can adjust the corresponding weighted coefficient according to the different energy consumption levels, so that the overall adjustment process can be continuously adjusted and changed according to the changes in the working state of the energy-saving pump in real-time operation; for example, when the effective cooling efficiency of the air cooling device is higher within a certain period of time, its corresponding weighted coefficient will increase accordingly, so that in the work allocation, it is more inclined to use the air cooling device to achieve cooling, so as to achieve the goal of minimizing the overall energy consumption.

[0033] Furthermore, in this embodiment, the pre-joint operation parameter set includes a difference adjustment factor, which is used to The ratio of the output power of the air cooling device to the water cooling device corresponding to different time points is adjusted within the time interval; the step of obtaining the difference adjustment factor includes: According to the attribute data of air cooling and water cooling devices, the effective cooling efficiency of air cooling and water cooling devices at different output powers is obtained and ; Furthermore, the effective cooling efficiency in this embodiment is the ratio of the actual cooling value to the theoretical cooling value per unit time; according to , , current moment and The difference between and The corresponding output power of air-cooling and water-cooling devices; According to satisfaction and The corresponding air cooling and water cooling device output power and the corresponding time point and The difference is used to obtain the function of the difference adjustment factor through the support vector machine, and the function of the difference adjustment factor obtained is built into the cooling control adjustment model.

[0034] As the temperature and energy consumption of the energy-saving pump increase during operation, the cooling demand of the system also increases accordingly; however, if the working intensity of the cooling device (such as power or flow) is blindly increased, it may lead to overcooling, thus wasting energy. By reducing the weight adjustment coefficient, the excessive use of the cooling device can be suppressed and unnecessary energy consumption can be avoided.

[0035] Therefore, the weight adjustment coefficient in this embodiment decreases as energy consumption and temperature continue to increase.

[0036] Furthermore, the weight adjustment coefficient in this embodiment is obtained by fitting the correlation coefficient algorithm based on the energy consumption data and cooling temperature corresponding to the height of the cooling device at each time point.

[0037] Furthermore, in this embodiment, j The energy efficiency level coefficient corresponding to the working state is j The energy efficiency level of the flow state per unit time, where the unit time is 1 hour.

[0038] After cooling by air cooling and water cooling at the same time, the current temperature is less than or equal to When the temperature corresponding to the moment is reached, the remaining cooling devices are set to the silent state corresponding to the lowest energy consumption, and the energy-saving pump is adjusted to cool down through the previous joint operation parameter set of the cooling control optimization model, so that and .

[0039] Furthermore, in this process, the current temperature is less than or equal to When the temperature corresponding to the moment is reached, it means that the temperature has dropped to the controllable range of the initial cooling device and can be controlled by the initial cooling device. The remaining cooling devices are set to the silent state corresponding to the lowest energy consumption. This is because the switching of the cooling device consumes huge energy, and frequent switching will affect the life of the cooling device. Therefore, setting the remaining cooling devices to the silent state corresponding to the lowest energy consumption can not only reduce energy consumption, but also avoid affecting the life of the cooling device.

[0040] This process uses a cooling control optimization model constructed based on a genetic algorithm, combined with a temperature adjustment fitness function and constraints, and this embodiment achieves precise temperature control, efficient energy consumption management, and flexible cooling strategies for the energy-saving pump cooling system; specifically, the system can adaptively adjust the cooling scheme under different working conditions to ensure that the temperature is always maintained within the normal working range, significantly improving the stability and reliability of the equipment; at the same time, the genetic algorithm and linear programming algorithm are used to minimize the overall energy consumption, which greatly reduces the operating costs. The introduction of a collaborative operation adjustment factor enables the air cooling and water cooling devices to be flexibly coordinated under different temperature conditions, further optimizing the system performance and extending the equipment life. In addition, by reasonably controlling the start and stop of the cooling device, the mechanical stress and unnecessary energy consumption caused by frequent switching are reduced, thereby achieving more sophisticated energy management.

[0041] S4, constructing a cooling control adjustment model, inputting the time points, cooling energy consumption and comprehensive energy consumption corresponding to the predicted start temperature drop of different cooling forms into the cooling control adjustment model for training, and obtaining differential time point control instructions for the cooling device; Furthermore, the specific steps of constructing the cooling control adjustment model in this embodiment include: according to and , the function of the difference adjustment factor, the current temperature is less than or equal to The temperature corresponding to the moment constructs the input state of the cooling control regulation model; The execution action trigger information is constructed according to the input state of the cooling control adjustment model, specifically: When it first appeared At the corresponding time point , triggering the first action execution information, that is, calling the initial cooling device and using and , obtaining an initial cooling device operating parameter set, and controlling the initial cooling device to cool down according to the initial cooling device operating parameter set; Furthermore, assuming that the current process uses an air cooling device to arrive The cooling process of the energy-saving pump at the time point , then the process of obtaining the corresponding air cooling device operating parameter set includes: According to the predicted temperature change rate of the energy-saving pump and the ideal temperature change rate per unit time of the energy-saving pump, the difference between the predicted temperature change rate of the energy-saving pump and the ideal temperature change rate per unit time of the energy-saving pump is obtained. ; According to the cooling efficiency of the historical air cooling device, The parameters corresponding to the air-cooling equipment are fitted by support vector machine to obtain the air-cooling effect function; Based on real-time , cooling efficiency and air cooling effect function, to obtain the operating parameter set corresponding to the air cooling device at the current time point; the operating parameter set corresponding to the air cooling device includes output power, fan speed, start time and duration.

[0042] When the cooling efficiency of the initial cooling device is still met At the corresponding time point , triggering the second action execution information, that is, calling the initial cooling device and the remaining cooling devices at the same time to cool down.

[0043] The third action execution information is triggered at the same time as the second action execution information is triggered, that is, according to the temperature adjustment fitness function And the corresponding constraints, through the process of linear programming algorithm to find the minimum value, obtain the satisfaction and The output power ratio of the initial cooling device and the remaining cooling devices is adjusted according to the function of the difference adjustment factor in the pre-joint operation parameter set corresponding to the water cooling, air cooling and energy-saving pump under the conditions; According to the output power ratio of the initial cooling device and the remaining cooling devices and the attribute data of the initial cooling device and the remaining cooling devices, the operating parameter set corresponding to the initial cooling device and the remaining cooling devices at the current moment is obtained; Furthermore, the operating parameter sets corresponding to the air cooling and water cooling devices include: output power, fan speed, air cooling device start-up time and duration, water cooling device start-up time and duration, water cooling device output power, output cooling flow and flow rate, and the length of time for the coordinated operation of air cooling and water cooling.

[0044] When the current temperature is less than or equal to When the temperature corresponding to the moment is reached, the fourth action execution information is triggered, that is, at the current time point, the remaining cooling devices are set to the silent state corresponding to the lowest energy consumption through the difference adjustment factor, and the operating parameter set corresponding to the initial cooling device is adjusted to reduce the temperature so that .

[0045] According to the execution action trigger information, construct the execution action corresponding to the trigger action execution information; When the corresponding execution action information is triggered, the air cooling, water cooling or energy-saving pump operating parameter set obtained by triggering the corresponding execution action information is input into the fuzzy control algorithm to obtain the operation control instructions of the air cooling device, water cooling device or energy-saving pump at the corresponding time point, so that the predicted temperature change rate curve of the energy-saving pump is always below the ideal temperature change rate curve.

[0046] S5. Use differential time point control instructions to control the cooling device for differential cooling control, and monitor the energy-saving pump temperature, cooling energy consumption, comprehensive energy consumption and water supply in real time, obtain the corresponding cooling temperature deviation, cooling energy consumption deviation, comprehensive energy consumption deviation and water supply deviation, and feed back all the obtained deviations to the cooling control optimization model to optimize and adjust the cooling control adjustment model.

[0047] This process achieves efficient and intelligent management of the energy-saving pump cooling system by constructing a cooling control and adjustment model. Specifically, first, the system can dynamically adjust the working parameters of the cooling device (such as the output power of the air cooling device, the fan speed, etc.) according to the difference between the real-time temperature change rate and the ideal temperature change rate, ensuring that the energy-saving pump temperature is always maintained within the set ideal range, thereby improving the accuracy of temperature control. Secondly, the linear programming algorithm is used to optimize the coordinated work of the air cooling and water cooling devices, minimize the comprehensive energy consumption, and enable the system to reduce energy consumption while meeting the cooling requirements. The introduction of differential adjustment factors enables the air cooling and water cooling devices to cooperate flexibly under different temperature conditions, further optimizing the energy consumption performance. When the temperature change rate exceeds the standard for the first time, the system quickly triggers the first action execution information and calls the initial cooling device for cooling. If a single cooling device cannot meet the demand, the second and third action execution information are triggered in time, and the system calls the The air cooling and water cooling devices are used to cool down the room in a coordinated manner to ensure the continuity and reliability of the cooling effect, and the start and stop of the cooling devices are reasonably controlled to reduce mechanical stress and extend the life of the equipment. After the temperature reaches the control target, the remaining cooling devices are set to the lowest energy consumption silent state to reduce unnecessary energy consumption. Finally, the system monitors the temperature, cooling energy consumption, comprehensive energy consumption and water supply of the energy-saving pump in real time, obtains the corresponding deviation data, and feeds these deviations back to the cooling control optimization model for dynamic adjustment to achieve closed-loop control and improve the system's adaptability and robustness. The application of fuzzy control algorithm ensures that the predicted temperature change rate curve of the energy-saving pump is always below the ideal temperature change rate curve, enhancing the stability and response speed of the system. Finally, the model not only improves the response speed and accuracy of the system, but also ensures that the energy-saving pump always operates efficiently in the most energy-saving state, achieving dual optimization of temperature control and energy management.

[0048] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation modes, which are merely illustrative rather than restrictive. Under the guidance of the present invention, ordinary technicians in the field may also change, modify, replace and modify the above-mentioned embodiments without departing from the scope of protection of the purpose of the present invention and the claims, and all of these are within the protection of the present invention.

[0049] If the disclosed technical solution involves personal information, the product using the disclosed technical solution has clearly informed the personal information processing rules and obtained the individual's voluntary consent before processing the personal information. If the disclosed technical solution involves sensitive personal information, the product using the disclosed technical solution has obtained the individual's separate consent before processing the sensitive personal information, and at the same time meets the "explicit consent" requirement. For example, on personal information collection devices such as cameras, clear and prominent signs are set to inform that the personal information collection scope has been entered and personal information will be collected. If the individual voluntarily enters the collection scope, it is deemed that he or she agrees to the collection of his or her personal information; or on the device that processes personal information, when the personal information processing rules are notified by obvious signs / information, the individual's authorization is obtained through pop-up information or by asking the individual to upload his or her personal information; among them, the personal information processing rules may include information such as the personal information processor, the purpose of personal information processing, the processing method, and the type of personal information processed.

Claims

1. An automatic cooling method for a digital energy-saving pump, characterized in that: include: Obtain differential energy-saving efficiency temperature prediction curve function and comprehensive energy consumption curve and single energy consumption curve function under differential energy-saving efficiency; The temperature adjustment adaptability function and constraint conditions are constructed using the comprehensive energy consumption curve and single energy consumption curve function, temperature prediction curve function, water supply change curve function, and normal working temperature range; The temperature adjustment fitness function and constraint conditions are built into the constructed cooling control optimization model for training, and the predicted cooling time interval, single cooling energy consumption and comprehensive energy consumption of air cooling and water cooling devices are obtained; The predicted cooling time point intervals, single cooling energy consumption and comprehensive energy consumption of the air-cooling and water-cooling devices are input into the constructed cooling control and regulation model for training, and differential time point control instructions of the cooling devices are obtained to perform differential cooling time point control of the cooling devices.

2. The automatic cooling method of a digital energy-saving pump according to claim 1, characterized in that: The construction process of the comprehensive energy consumption curve includes: According to the historical temperature change data of the energy-saving pump under different working conditions, the temperature prediction curve function is obtained; According to the cooling efficiency of the air cooling or water cooling device per unit time at the corresponding temperature in the temperature prediction curve function and the cooling energy consumption per unit time under the corresponding cooling efficiency, a single energy consumption curve of the corresponding cooling device is obtained; According to the working energy consumption data of the energy-saving pump under different working conditions, the working energy consumption change curves and corresponding change functions under different working conditions are constructed.

3. The automatic cooling method of a digital energy-saving pump according to claim 2, characterized in that: The construction process of the comprehensive energy consumption curve also includes: The single energy consumption curve corresponding to the air cooling and water cooling devices is aligned with the working energy consumption data under the corresponding working state in the time dimension, and the water supply energy consumption at the same time point is superimposed with the air cooling or water cooling energy consumption to obtain the comprehensive energy consumption of water supply and cooling and the comprehensive energy consumption curve of the energy-saving pump at the corresponding time point, and determine the energy consumption level at the corresponding time point.

4. The automatic cooling method of a digital energy-saving pump according to claim 3, characterized in that: The working state of the energy-saving pump is the water supply flow rate of the energy-saving pump per unit time. The construction process of the temperature adjustment fitness function and the constraint conditions includes: According to the required water supply and the working status of the energy-saving pump, the target water supply demand time interval is obtained. ,in represents the initial water supply time point corresponding to the demand water supply, Indicates the end water supply time point corresponding to the demand water supply; According to the target water supply demand time length and normal working temperature range, the ideal temperature change rate per unit time of the energy-saving pump is obtained. ; According to the temperature prediction curve function, the predicted temperature change rate of the energy-saving pump is obtained. .

5. The automatic cooling method of a digital energy-saving pump according to claim 4, characterized in that: The process of constructing the temperature adjustment fitness function and the constraint conditions also includes: According to the historical operation order of air cooling and water cooling devices, the corresponding temperature adjustment range and the corresponding energy consumption per unit time, the initial cooling device is selected for cooling; According to the predicted temperature change rate of the energy-saving pump and the ideal temperature change rate per unit time of the energy-saving pump, we can obtain First time greater than The corresponding time point , and select the initial cooling device to start cooling down, so that .

6. The automatic cooling method of a digital energy-saving pump according to claim 5, characterized in that: The process of constructing the temperature adjustment fitness function and the constraint conditions also includes: According to the predicted temperature change rate of the energy-saving pump, the ideal temperature change rate per unit time of the energy-saving pump, and the cooling efficiency of the initial cooling device corresponding to the rated power, the cooling efficiency of the initial cooling device at the rated power is obtained. The corresponding time point , and select the initial cooling device and the remaining cooling device to cool down the energy-saving pump at the same time; According to the cooling efficiency, cooling energy consumption, energy-saving pump working energy consumption and energy-saving pump supply and demand difference of the initial cooling device and the remaining cooling device , construct the temperature adjustment fitness function and constraints of the initial cooling device and the remaining cooling devices, so that and Under this condition, the comprehensive energy consumption of water supply and cooling is minimal.

7. The automatic cooling method of a digital energy-saving pump according to claim 6, characterized in that: The process of constructing the temperature adjustment fitness function and constraint conditions of the initial cooling device and the remaining cooling devices includes: According to the historical output power, cooling efficiency and air cooling energy consumption of the air cooling device, the air cooling energy consumption fitting function is obtained through the nonlinear fitting function. ; According to the historical water cooling device corresponding output power, cooling flow and flow rate, cooling efficiency and water cooling energy consumption, the water cooling energy consumption fitting function is obtained through nonlinear fitting function. ; According to the flow rate, speed and corresponding working energy consumption of the energy-saving pump under the corresponding working state, the energy-saving pump working energy consumption fitting function is obtained through the nonlinear fitting function. ; according to , and Constructing the temperature adjustment fitness function and the corresponding constraints, and the energy consumption value of the temperature adjustment fitness function is the minimum at the corresponding time point and , Under this condition, the linear programming algorithm is used to solve the predicted pre-combined operation parameter set corresponding to water cooling, air cooling and energy-saving pumps; After cooling by air cooling and water cooling at the same time, the current temperature is less than or equal to When the temperature corresponding to the moment is reached, the remaining cooling devices are set to the silent state corresponding to the lowest energy consumption, and the energy-saving pump is adjusted to cool down through the previous joint operation parameter set of the cooling control optimization model, so that and .

8. The automatic cooling method of a digital energy-saving pump according to claim 7, characterized in that: The pre-joint operation parameter set includes a difference adjustment factor, and the difference adjustment factor is used to adjust the Adjust the output power ratio of the air cooling device to the water cooling device at different time points within the time interval; The step of obtaining the difference adjustment factor comprises: According to the attribute data of air cooling and water cooling devices, the effective cooling efficiency of air cooling and water cooling devices at different output powers is obtained and ; according to , , current moment and The difference between and The corresponding output power of air-cooling and water-cooling devices; According to satisfaction and The corresponding air cooling and water cooling device output power and the corresponding time point and The difference is obtained through support vector machine to obtain the function of the difference adjustment factor, and the obtained function of the difference adjustment factor is built into the cooling control adjustment model.

9. The automatic cooling method of a digital energy-saving pump according to claim 8, characterized in that: The specific steps of constructing the cooling control adjustment model include: according to and , the function of the difference adjustment factor, the current temperature is less than or equal to The temperature corresponding to the moment constructs the input state of the cooling control regulation model; The execution action trigger information is constructed according to the input state of the cooling control adjustment model, specifically: When it first appeared At the corresponding time point , triggering the first action execution information, that is, calling the initial cooling device and using and , obtaining an initial cooling device operating parameter set, and controlling the initial cooling device to cool down according to the initial cooling device operating parameter set; When the cooling efficiency of the initial cooling device is still met At the corresponding time point , triggering the second action execution information, that is, calling the initial cooling device and the remaining cooling devices at the same time to cool down.

10. The automatic cooling method of a digital energy-saving pump according to claim 9, characterized in that: The specific steps of constructing the cooling control adjustment model also include: The third action execution information is triggered at the same time as the second action execution information is triggered, that is, according to the temperature adjustment fitness function And the corresponding constraints, through the linear programming algorithm, obtain and The output power ratio of the initial cooling device and the remaining cooling devices is adjusted according to the function of the difference adjustment factor in the pre-joint operation parameter set corresponding to the water cooling, air cooling and energy-saving pump under the conditions; According to the output power ratio of the initial cooling device and the remaining cooling devices and the attribute data of the initial cooling device and the remaining cooling devices, the operating parameter set corresponding to the initial cooling device and the remaining cooling devices at the current moment is obtained; When the current temperature is less than or equal to When the temperature corresponding to the moment is reached, the fourth action execution information is triggered, that is, at the current time point, the remaining cooling devices are set to the silent state corresponding to the lowest energy consumption through the difference adjustment factor, and the operating parameter set corresponding to the initial cooling device is adjusted to reduce the temperature so that ; According to the execution action trigger information, construct the execution action corresponding to the trigger action execution information; When the corresponding execution action information is triggered, the air cooling, water cooling or energy-saving pump operating parameter set obtained by triggering the corresponding execution action information is input into the fuzzy control algorithm to obtain the operation control instructions of the air cooling device, water cooling device or energy-saving pump at the corresponding time point, so that the predicted temperature change rate curve of the energy-saving pump is always below the ideal temperature change rate curve.

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