A Cooling Tower Operation Control Method and Device Based on a White-Box Model

Abstract

The present invention discloses a method and device for controlling the operation of a cooling tower based on a white-box model. The method includes: establishing a white-box model, where the white-box model includes a first sub-model, a second sub-model, and a third sub-model. The input parameter of the first sub-model is the fan frequency, and the output parameter is the single-tower power of the cooling tower. The input parameter of the second sub-model is the water-air ratio, and the output parameter is the approximation degree. The input parameters of the third sub-model are the single-unit load, the chilled water supply temperature, and the cooling tower outlet temperature, and the output parameter is the single-unit power of the chiller; obtaining the cooling tower frequency and the number of operating cooling towers when the sum of the total power of the cooling tower and the total power of the chiller is the smallest according to the white-box model; controlling the cooling tower according to the cooling tower frequency and the number of operating cooling towers. It can be seen that the present invention establishes a white-box model for the optimal strategy of the cooling tower by using the theory of heating, ventilation, and heat transfer and some experimental data.

Description

Technical Field

[0001] The present invention relates to the field of processing, and particularly to a method, device, electronic device, and computer-readable storage medium for controlling the operation of a cooling tower based on a white-box model. Background Art

[0002] As a general device for discharging waste heat in a thermal system, during the actual operation and maintenance of a heating, ventilation, and air conditioning (HVAC) system, the control of the cooling tower is often overlooked. Based on the investigation of the cooling towers in 140 commercial plazas, in most plazas, the cooling towers have the situations of non-frequency conversion and constant number of cooling tower units, full-frequency full-open operation, or excessive amplitude of frequency conversion and tower number change of the cooling tower. However, the cooling performance of the cooling tower is crucial for the operation performance of the refrigeration unit. The performance test and prediction model of the cooling tower are the focus of many studies. Different scholars have conducted a series of studies based on different models. There is the ε-NTU method (effectiveness-number of transfer units method), but this method requires many physical parameters (such as mass transfer coefficient) that are difficult to measure. With the continuous accumulation of sub-metering of public buildings, the cooling tower performance model based on the black box has gradually become a research hotspot. However, unlike the empirical model of the chiller, there is no relatively consistent consensus on the input parameters of the model and the selection of the model: the multiple polynomial regression models used by simulation software such as EnergyPlus and Modelica, and other different scholars have used Support Vector Machine (SVM), Random Forest, etc. Different projects fit the cooling tower model based on the actual collected data. Due to the lack of strong generality, it is still necessary to select the fitting model and design the input parameters based on the actual data situation.

[0003] Some plazas manage the operation of the cooling tower in the way of combined frequency conversion (approach temperature of 3 - 5 °C), lacking a detailed introduction of the corresponding detailed control parameters when the specific working conditions change, resulting in energy waste caused by unreasonable operation in some working conditions.

[0004] The water distribution uniformity, packing aging degree, air flow organization of the cooling tower, and the operation of the cooling pump will all affect the heat transfer of the cooling tower. The accuracy of establishing a physical model may be insufficient, and with frequent feedback control of the outlet water temperature, the cooling tower is in a non-steady state for a long time. The laws learned from historical data cannot be applied to the steady state. When the actual operation mode is relatively single, the operation laws in other modes cannot be obtained from the data, so the optimal strategies in all modes cannot be obtained. Summary of the Invention

[0005] In view of the above problems, the present invention is proposed to provide a method, device, electronic device, and computer-readable storage medium for controlling the operation of a cooling tower based on a white-box model that overcomes the above problems or at least partially solves the above problems.

[0006] An embodiment of the present invention provides a cooling tower operation control method based on a white-box model, and the method includes:

[0007] Establish a white-box model, where the white-box model includes a first sub-model, a second sub-model, and a third sub-model. The input parameter of the first sub-model is the fan frequency, and the output parameter is the single-tower power of the cooling tower. The input parameter of the second sub-model is the water-air ratio, and the output parameter is the approximation degree. The input parameters of the third sub-model are the single-unit load, the chilled water supply temperature, and the cooling tower outlet temperature, and the output parameter is the single-unit power of the chiller;

[0008] Obtain the cooling tower frequency and the number of operating cooling towers when the sum of the total power of the cooling tower and the total power of the chiller is the smallest according to the white-box model, where the total power of the cooling tower is the product of the single-tower power of the cooling tower and the number of operating cooling towers, and the total power of the chiller is the product of the single-unit power of the chiller and the number of operating chillers;

[0009] Control the cooling tower according to the cooling tower frequency and the number of operating cooling towers.

[0010] Optionally, the calculation formula of the first sub-model is:

[0011] Single-tower power of the cooling tower = (rated power of the fan * η 风机 ) * (a * (fan frequency / 50)^3 + b)

[0012] where η 风机 is the rated power correction factor of the fan, and a and b are fan characteristic parameters.

[0013] Optionally, the calculation formula of the second sub-model is:

[0014] Approximation degree = design approximation degree * water-air ratio^(-c)

[0015] where c is a constant obtained by measuring actual on-site data.

[0016] Optionally, the calculation formula of the third sub-model is:

[0017] P 冷机 = P 查表 * η 冷冻水温度

[0018] where P 冷机 is the single-unit power of the chiller, P 查表 is the single-unit power of the chiller obtained by looking up a table under the specified cooling tower outlet temperature and single-unit load, and η 冷冻水温度 is the chilled water supply temperature correction factor.

[0019] Another embodiment of the present invention provides a cooling tower operation control device based on a white-box model, including:

[0020] A white-box model building unit for building a white-box model, the white-box model including a first sub-model, a second sub-model, and a third sub-model, wherein the input parameter of the first sub-model is the fan frequency, and the output parameter is the single-tower power of the cooling tower; the input parameter of the second sub-model is the water-air ratio, and the output parameter is the approximation degree; the input parameters of the third sub-model are the single-unit load, the chilled water supply temperature, and the cooling tower outlet temperature, and the output parameter is the single-unit power of the chiller.

[0021] A cooling tower control parameter obtaining unit for obtaining the cooling tower frequency and the number of operating cooling towers when the sum of the total power of the cooling tower and the total power of the chiller is minimized according to the white-box model, wherein the total power of the cooling tower is the product of the single-tower power of the cooling tower and the number of operating cooling towers, and the total power of the chiller is the product of the single-unit power of the chiller and the number of operating chillers.

[0022] A control unit for controlling the cooling tower according to the cooling tower frequency and the number of operating cooling towers.

[0023] Optionally, the calculation formula of the first sub-model is:

[0024] Single-tower power of the cooling tower = (rated power of the fan * η 风机 ) * (a * (fan frequency / 50)^3 + b)

[0025] where η 风机 is the rated power correction factor of the fan, and a and b are fan characteristic parameters.

[0026] Optionally, the calculation formula of the second sub-model is:

[0027] Approximation degree = design approximation degree * (water-air ratio)^(-c)

[0028] where c is a constant obtained by measuring actual on-site data.

[0029] Optionally, the calculation formula of the third sub-model is:

[0030] P 冷机 = P 查表 * η 冷冻水温度

[0031] where P 冷机 is the single-unit power of the chiller, P 查表 is the single-unit power of the chiller obtained by looking up a table at the specified cooling tower outlet temperature and single-unit load, and η 冷冻水温度 is the chilled water supply temperature correction factor.

[0032] Another embodiment of the present invention provides an electronic device, wherein the electronic device includes:

[0033] A processor; and,

[0034] A memory arranged to store computer-executable instructions that, when executed, cause the processor to perform the above-described method.

[0035] Another embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores one or more programs that, when executed by a processor, implement the above-described method.

[0036] The beneficial effect of the present invention is that, by using the theory of heating, ventilation, and air-conditioning heat transfer and some experimental data, a white-box model of the optimal strategy of the cooling tower is established. A model foundation and model verification rules are established for obtaining higher accuracy through on-site measured data and related algorithm corrections in the later stage. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a schematic flowchart of a cooling tower operation control method based on a white-box model according to an embodiment of the present invention;

[0038] Figure 2 It is a schematic diagram of the principle of a water-cooling system according to an embodiment of the present invention;

[0039] Figure 3 It is a relationship curve diagram of the water-air ratio and the approach temperature according to an embodiment of the present invention;

[0040] Figure 4 It is a schematic flowchart of a cooling tower operation control method based on a white-box model according to another embodiment of the present invention;

[0041] Figure 5 It is a schematic structural diagram of a cooling tower operation control device based on a white-box model according to an embodiment of the present invention;

[0042] Figure 6 It shows a schematic structural diagram of an electronic device according to an embodiment of the present invention;

[0043] Figure 7 It shows a schematic structural diagram of a computer-readable storage medium according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0045] The present invention assumes that the cooling water pump is controlled in a constant temperature difference mode, and the cooling tower return water temperature - the cooling tower outlet water temperature = Δt. Usually, the target temperature difference is set to 5 - 7°C. Taking 5°C as an example, that is, when Δt > 5, the water pump motor increases the frequency, and when Δt < 5, the water pump motor decreases the frequency.

[0046] Figure 1Schematic diagram of the cooling tower operation control method based on the white-box model according to an embodiment of the present invention. As Figure 1 shown, the method includes:

[0047] S11: Establish a white-box model, the white-box model includes a first sub-model, a second sub-model and a third sub-model, wherein the input parameter of the first sub-model is the fan frequency, and the output parameter is the single-tower power of the cooling tower; the input parameter of the second sub-model is the water-air ratio, and the output parameter is the approximation degree; the input parameters of the third sub-model are the single-unit load, the chilled water supply temperature, and the cooling tower outlet temperature, and the output parameter is the single-unit power of the chiller;

[0048] S12: Obtain the cooling tower frequency and the number of operating cooling towers when the sum of the total power of the cooling tower and the total power of the chiller is the smallest according to the white-box model, wherein the total power of the cooling tower is the product of the single-tower power of the cooling tower and the number of operating cooling towers, and the total power of the chiller is the product of the single-unit power of the chiller and the number of operating chillers;

[0049] S13: Control the cooling tower according to the cooling tower frequency and the number of operating cooling towers.

[0050] The cooling tower operation control method based on the white-box model according to the embodiment of the present invention uses the theory of heating, ventilation and heat transfer and partial experimental data to establish a white-box model for the optimal strategy of the cooling tower. To obtain higher accuracy through on-site measured data and related algorithm correction in the later stage, a model foundation and model verification rules are established.

[0051] Figure 2 Schematic diagram of the water-cooled system according to an embodiment of the present invention. As Figure 2 shown, the composition structure and water circuit of the water-cooled system are given, and the cooling tower outlet temperature, the cooling tower return water temperature, the cooling water outlet temperature, the cooling water return water temperature, the chilled water supply temperature, the chilled water return water temperature, the evaporation temperature, and the condensation temperature are marked. Among them, the cooling tower outlet temperature and the cooling water return water temperature are assumed to be the same by ignoring the deviation, and are uniformly represented by the cooling tower outlet temperature in the invention.

[0052] It should be noted that according to the heating, ventilation theory and empirical formula, the fan frequency f has a first-power relationship with the rotational speed n, the rotational speed n has a first-power relationship with the air volume Q, and the rotational speed n has a third-power relationship with the power, that is: f1 / f2 = n1 / n2 = Q1 / Q2, P1 / P2 = n1 3 / n2 3 .

[0053] However, due to the influence brought by the fan efficiency and static pressure change, a correction coefficient affected by actual data should be added in practical applications. In addition, there is also a correction coefficient between the actual power and the rated power of the fan at 50 hz.

[0054] Therefore, in an alternative embodiment of the embodiment of the present invention, the calculation formula of the first sub-model is as follows:

[0055] Cooling tower single tower power = (rated fan power * η 风机 ) * (a * (fan frequency / 50)^3 + b)

[0056] where η 风机 is the rated fan power correction factor, and a and b are fan characteristic parameters.

[0057] It should be noted that the value calculated by (rated fan power * η 风机 ) * (a * (fan frequency / 50)^3 + b) is the fan power, and in the present invention, the fan power is equivalent to the cooling tower power.

[0058] Furthermore, the calculation formula of the second sub-model is as follows:

[0059] Approximation degree = design approximation degree * water-air ratio^(-c)

[0060] where c is a constant obtained by measuring actual on-site data.

[0061] It should be noted that the design approximation degree refers to the design parameter used when designing the model and quantity of the cooling tower in the project. For example: The design heat dissipation of a certain square is 1500 RT, the design condition is the wet bulb temperature of 29 °C, the design cooling water inlet and outlet temperature difference is 5 °C. According to the project requirements, the design personnel stipulate the design approximation degree of the cooling tower. From approximation degree = cooling tower outlet water temperature - wet bulb temperature, for example, if the design approximation degree is 4 °C, then the condition and requirements reported to the cooling tower manufacturer are the wet bulb temperature of 29 °C, the cooling tower inlet water temperature of 38 °C, the cooling tower outlet water temperature of 33 °C, and the heat dissipation of 1650 RT (10% margin).

[0062] Taking the water-air ratio of 1A for the cooling tower designed with a design approximation degree of 4 °C for constant load estimation, the following data is obtained:

[0063] NO. Gas-liquid ratio Approximation degree 1 0.60 9.0 2 0.62 8.5 3 0.64 8.0 4 0.66 7.5 5 0.68 7.0 6 0.72 6.5 7 0.76 6.0 8 0.81 5.5 9 0.86 5.0 10 0.93 4.5 11 1 4.0 12 1.1 3.6 13 1.2 3.2 14 1.3 2.9 15 1.4 2.6 16 1.5 2.4 17 1.6 2.1 18 1.7 1.9 19 1.8 1.8 20 1.9 1.7 21 2 1.6

[0064] Figure 3 This is the relationship curve graph of the water-air ratio and the approximation degree of an embodiment of the present invention. By fitting the curve through software, it can be obtained that the relationship between the water-air ratio and the approximation degree is a power function relationship, that is, the calculation formula of the second sub-model as described above is obtained.

[0065] Furthermore, the calculation formula of the third sub-model is as follows:

[0066] P 冷机 = P 查表 * η 冷冻水温度

[0067] Among them, P 冷机 is the single-unit power of the chiller, and P 查表 is the single-unit power of the chiller obtained by looking up the table at the specified cooling tower outlet water temperature and single-unit load. η 冷冻水温度 is the correction coefficient of the chilled water supply temperature.

[0068] P 查表 can be obtained from the data in the selection table provided by the chiller manufacturer. However, in the research, the equipment selection table of a certain manufacturer is used as the constant water flow data. Under the on-site cooling pump constant temperature difference control mode, the data needs to be corrected. The constant temperature difference method of assuming the cooling tower outlet water temperature and the condensation temperature can be used to calculate the change of the condensation temperature, and then according to the inverse Carnot cycle, the coefficient of performance: ICOP = te / (tc - te) formula, the power is corrected. Among them, te is the evaporation temperature and tc is the condensation temperature.

[0069] Assume that the chilled water supply temperature is a fixed value, such as 7°C. A corresponding table with a temperature difference of 1°C and a load of 10% per scale can be obtained. Then, using an algorithm or simple linear difference calculation, a table with an accuracy of 0.1°C and 1% load can be obtained, as follows (a part of the table):

[0070] Cooling tower outlet water temperature 10％ 11％ 12％ 13％ 14％ 15％ 16％ 17％ 18％ 19％ 20％ 21％ 22％ 23％ 24％ 25％ 26％ 27％ 28％ 29％ 30％ 33 333.4 330.4 327.4 324.4 321.4 318.4 315.4 312.4 309.4 306.4 303.4 305.6 307.8 309.9 312.1 314.3 316.4 318.6 320.7 322.9 325.1 32.9 331.5 328.6 325.7 322.7 319.8 316.9 314.0 311.1 308.2 305.2 302.3 304.5 306.6 308.8 310.9 313.1 315.2 317.4 319.5 321.6 323.8 32.8 329.7 326.8 324.0 321.1 318.3 315.4 312.6 309.7 306.9 304.0 301.2 303.3 305.5 307.6 309.7 311.9 314.0 316.1 318.3 320.4 322.5 32.7 327.8 325.0 322.3 319.5 316.7 313.9 311.2 308.4 305.6 302.8 300.1 302.2 304.3 306.4 308.5 310.7 312.8 314.9 317.0 319.1 321.3 32.6 325.9 323.2 320.5 317.8 315.1 312.4 309.7 307.0 304.3 301.6 298.9 301.0 303.1 305.2 307.3 309.5 311.6 313.7 315.8 317.9 320.0 32.5 324.1 321.5 318.8 316.2 313.6 310.9 308.3 305.7 303.1 300.4 297.8 299.9 302.0 304.1 306.2 308.3 310.3 312.4 314.5 316.6 318.7 32.4 322.2 319.7 317.1 314.6 312.0 309.5 306.9 304.3 301.8 299.2 296.7 298.7 300.8 302.9 305.0 307.1 309.1 311.2 313.3 315.4 317.4 32.3 320.4 317.9 315.4 312.9 310.4 308.0 305.5 303.0 300.5 298.0 295.5 297.6 299.7 301.7 303.8 305.9 307.9 310.0 312.0 314.1 316.2 32.2 318.5 316.1 313.7 311.3 308.9 306.5 304.1 301.6 299.2 296.8 294.4 296.4 298.5 300.5 302.6 304.7 306.7 308.8 310.8 312.9 314.9 32.1 316.7 314.3 312.0 309.7 307.3 305.0 302.6 300.3 297.9 295.6 293.3 295.3 297.3 299.4 301.4 303.5 305.5 307.5 309.6 311.6 313.6 32 314.8 312.6 310.3 308.0 305.8 303.5 301.2 298.9 296.7 294.4 292.1 294.2 296.2 298.2 300.2 302.2 304.3 306.3 308.3 310.31 3012.4

[0071] This accuracy table can meet the on-site use conditions and no further linear fitting is required.

[0072] Finally, when calculating the single-unit power of the chiller, the correction coefficient η 冷冻水温度 of the chilled water supply temperature needs to be obtained.

[0073] η 冷冻水温度 = (1 + 0.03)^(7 - chilled water supply temperature)

[0074] In practical applications, η 冷冻水温度 can also be estimated using a common estimation coefficient. When the evaporation temperature increases by 1°C, ICOP increases by 3%.

[0075] Figure 4 is the flow schematic diagram of the cooling tower operation control method based on the white box model in another embodiment of the present invention. The following combines Figure 4 to illustrate the flow of the control method of the embodiment of the present invention. This flow assumes that the types of each cooling tower and chiller are the same:

[0076] Similar to Figure 1 , first establish a white box model, which will not be elaborated here.

[0077] Set the total number of on-site cooling towers as num, f as the average frequency, and n as the number of operating cooling towers. According to HVAC theory and common sense, the cooling tower control strategy can be simply divided into two modes: adding or subtracting cooling towers at low frequency and increasing or decreasing the frequency with all cooling towers operating. That is, f = 30, n = (1 to num); n = num, f = (31 to 50). Substitute these situations into the white box model for calculation respectively, and the minimum value of the sum of the obtained powers is the optimal n, f control strategy. Specifically:

[0078] (1) Substitute the fan frequency into Model 1 to calculate the single-tower power of the cooling tower, then the total power of the cooling tower = single-tower power * number of operating cooling towers.

[0079] (2) Calculate the water-air ratio: m is the number of operating cooling towers for the design approach temperature. Since the water-air ratio is inversely proportional to the load, the water-air ratio = (n * f) / (m * 50) / (actual refrigeration capacity / rated refrigeration capacity per unit).

[0080] Among them, the rated refrigeration capacity per unit is the static parameter of the chiller selected in Model 3.

[0081] Substitute the water-air ratio into Model 2 to obtain the approach temperature.

[0082] (3) Obtain the outlet water temperature of the cooling tower from the approach temperature and the wet bulb temperature.

[0083] Substitute the outlet water temperature of the cooling tower and other input parameters into Model 3 to obtain the single-chiller power. The total chiller power is the product of the single-chiller power and the number of operating chillers.

[0084] The sum of powers = total power of the cooling tower + total chiller power.

[0085] In practical applications, when there are significant differences in the selection of on-site cooling towers and chillers, it is necessary to number the cooling towers and chillers, and perform strategy optimization and output according to the combination method and algorithm optimization.

[0086] Figure 5 It is a schematic structural diagram of a cooling tower operation control device based on a white box model according to an embodiment of the present invention. As Figure 5 shown, the device includes:

[0087] A white box model establishment unit 51, which is used to establish a white box model. The white box model includes a first sub-model, a second sub-model, and a third sub-model. Among them, the input parameter of the first sub-model is the fan frequency, and the output parameter is the single-tower power of the cooling tower; the input parameter of the second sub-model is the water-air ratio, and the output parameter is the approach temperature; the input parameters of the third sub-model are the single-unit load, the supply temperature of the chilled water, and the outlet water temperature of the cooling tower, and the output parameter is the single-chiller power;

[0088] A cooling tower control parameter acquisition unit 52, configured to obtain the cooling tower frequency and the number of operating cooling towers when the sum of the total power of the cooling tower and the total power of the chiller is minimized according to the white box model, where the total power of the cooling tower is the product of the single-tower power of the cooling tower and the number of operating cooling towers, and the total power of the chiller is the product of the single-unit power of the chiller and the number of operating chillers;

[0089] A control unit 53, configured to control the cooling tower according to the cooling tower frequency and the number of operating cooling towers.

[0090] The cooling tower operation control device based on the white box model according to the embodiment of the present invention uses the theory of heating, ventilation and heat transfer and partial experimental data to establish a white box model for the optimal strategy of the cooling tower. In order to obtain higher accuracy through on-site measured data and related algorithm correction in the later stage, a model foundation and model verification rules are established.

[0091] In an optional implementation manner of the embodiment of the present invention, the calculation formula of the first sub-model is:

[0092] Single-tower power of the cooling tower = (rated power of the fan * η 风机 ) * (a * (fan frequency / 50)^3 + b)

[0093] where η 风机 is the rated power correction coefficient of the fan, and a and b are fan characteristic parameters.

[0094] Further, the calculation formula of the second sub-model is:

[0095] Approximation degree = design approximation degree * (water-air ratio)^(-c)

[0096] where c is a constant obtained by measuring on-site actual data.

[0097] Further, the calculation formula of the third sub-model is:

[0098] P 冷机 = P 查表 * ηchilled water temperature

[0099] where P 冷机 is the single-unit power of the chiller, P 查表 is the single-unit power of the chiller obtained by looking up the table under the specified cooling tower outlet water temperature and single-unit load, and η 冷冻水温度 is the chilled water supply temperature correction coefficient.

[0100] It should be noted that the cooling tower operation control device based on the white box model in the above embodiments can be respectively used to execute the methods in the foregoing embodiments, so specific descriptions will not be repeated one by one.

[0101] In summary, the present invention utilizes the theory of heating ventilation and heat transfer and partial experimental data to establish a white box model for the optimal strategy of cooling towers. To obtain higher accuracy through on-site measured data and relevant algorithm corrections in the later stage, a model foundation and model verification rules are established.

[0102] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0103] It should be noted that:

[0104] The algorithms and displays provided herein are not inherently related to any particular computer, virtual device, or other equipment. Various general-purpose devices can also be used in conjunction with the teachings herein. Based on the above description, the structures required to construct such devices are obvious. In addition, the present invention is not directed to any particular programming language. It should be understood that the content of the present invention described herein can be implemented using various programming languages, and the description of the specific language above is to disclose the best mode of the present invention.

[0105] In the specification provided herein, a large number of specific details are set forth. However, it can be understood that the embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures, and technologies have not been shown in detail so as not to obscure the understanding of this specification.

[0106] Similarly, it should be understood that, in order to streamline the present invention and assist in understanding one or more of the various inventive aspects, in the above description of the exemplary embodiments of the present invention, the various features of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, the disclosed method should not be construed as reflecting the intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the following claims, the inventive aspects lie in less than all the features of the single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into the detailed description, with each claim standing on its own as a separate embodiment of the present invention.

[0107] Those skilled in the art can understand that the modules in the devices in the embodiments can be adaptively changed and set in one or more devices different from the embodiments. The modules or units or components in the embodiments can be combined into one module or unit or component, and in addition, they can be divided into multiple sub-modules or sub-units or sub-components. Except that at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all the features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all the processes or units of any method or device so disclosed. Unless otherwise explicitly stated, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) can be replaced by an alternative feature that provides the same, equivalent, or similar purpose.

[0108] In addition, those skilled in the art can understand that although some of the embodiments described herein include certain features included in other embodiments rather than other features, the combination of features of different embodiments means that it is within the scope of the present invention and forms different embodiments. For example, in the following claims, any one of the claimed embodiments can be used in any combination.

[0109] Each component embodiment of the present invention can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art should understand that a microprocessor or a digital signal processor (DSP) can be used in practice to implement some or all of the functions of some or all of the components of the device for detecting the wearing state of an electronic device according to the embodiments of the present invention. The present invention can also be implemented as a device or device program (for example, a computer program and a computer program product) for executing part or all of the methods described herein. Such a program implementing the present invention can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0110] For example, Figure 6 The structural schematic diagram of an electronic device according to an embodiment of the present invention is shown. The electronic device traditionally includes a processor 61 and a memory 62 arranged to store computer-executable instructions (program code). The memory 62 can be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read-only memory), an EPROM, a hard disk, or a ROM. The memory 62 has a storage for executing Figure 1The storage space 63 for the program code 64 shown and of any method steps in the embodiments. For example, the storage space 63 for storing the program code may include respective program codes 64 for implementing the various steps in the above method. These program codes may be read from or written into one or more computer program products. These computer program products include program code carriers such as hard disks, compact discs (CDs), memory cards, or floppy disks. Such computer program products are typically, for example Figure 7 the computer-readable storage medium described. The computer-readable storage medium may have storage segments, storage spaces, etc. arranged similarly to the memory 62 in the Figure 6 electronic device. The program code may be compressed in a suitable form, for example. Generally, the storage space stores program code 71 for executing the method steps according to the present invention, that is, there may be program code readable by a processor 61, and when these program codes are run by the electronic device, the electronic device is caused to execute the respective steps in the method described above.

[0111] As described above, the above are only specific embodiments of the present invention. Under the above teachings of the present invention, those skilled in the art may make other improvements or deformations based on the above embodiments. Those skilled in the art should understand that the above specific description is only a better explanation of the purpose of the present invention, and the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A cooling tower operation control method based on a white box model, characterized in that Including: Establish a white-box model, which includes a first sub-model, a second sub-model and a third sub-model. The input parameter of the first sub-model is the fan frequency, and the output parameter is the single-tower power of the cooling tower. The input parameter of the second sub-model is the water-air ratio, and the output parameter is the approximation degree. The input parameters of the third sub-model are the single-unit load, the supply temperature of the chilled water, and the outlet temperature of the cooling tower, and the output parameter is the single-unit power of the chiller; Obtain the cooling tower frequency and the number of operating cooling towers when the sum of the total power of the cooling tower and the total power of the chiller is minimized according to the white-box model, where the total power of the cooling tower is the product of the single-tower power of the cooling tower and the number of operating cooling towers, and the total power of the chiller is the product of the single-unit power of the chiller and the number of operating chillers; Control the cooling tower according to the cooling tower frequency and the number of operating cooling towers.

2. The method according to claim 1, wherein The calculation formula of the first sub-model is: Cooling tower single tower power = (rated power of the fan * η 风机 ) * (a * (fan frequency / 50)^3 + b) where, η 风机 is the correction coefficient of the rated power of the fan, and a and b are the characteristic parameters of the fan.

3. The method according to claim 1, characterized in that, The calculation formula of the second sub-model is: Approximation degree = Design approximation degree * (water-air ratio)^(-c) Where c is a constant obtained by measuring actual on-site data.

4. The method according to claim 1, wherein The calculation formula of the third sub-model is: P 冷机 = P 查表 * η Chilled water temperature Among them, P 冷机 is the single chiller power, P 查表 is the single chiller power obtained by looking up the table at the specified cooling tower outlet water temperature and single unit load, and η 冷冻水温度 is the chilled water supply temperature correction factor.

5. A cooling tower operation control device based on a white box model, characterized in that Including: A white-box model establishment unit for establishing a white-box model, which includes a first sub-model, a second sub-model and a third sub-model. The input parameter of the first sub-model is the fan frequency, and the output parameter is the single-tower power of the cooling tower. The input parameter of the second sub-model is the water-air ratio, and the output parameter is the approximation degree. The input parameters of the third sub-model are the single-unit load, the supply temperature of the chilled water, and the outlet temperature of the cooling tower, and the output parameter is the single-unit power of the chiller; A cooling tower control parameter obtaining unit for obtaining the cooling tower frequency and the number of operating cooling towers when the sum of the total power of the cooling tower and the total power of the chiller is minimized according to the white-box model, where the total power of the cooling tower is the product of the single-tower power of the cooling tower and the number of operating cooling towers, and the total power of the chiller is the product of the single-unit power of the chiller and the number of operating chillers; A control unit for controlling the cooling tower according to the cooling tower frequency and the number of operating cooling towers.

6. The device according to claim 5, characterized in that The calculation formula of the first sub-model is: Cooling tower single tower power = (rated power of fan * η 风机 ) * (a * (fan frequency / 50)^3 + b) where, η 风机 is the correction coefficient of the rated power of the fan, and a and b are the characteristic parameters of the fan.

7. The device according to claim 5, characterized in that, The calculation formula of the second sub-model is: Approximation degree = Design approximation degree * (water-air ratio)^(-c) Where c is a constant obtained by measuring actual on-site data.

8. The device according to claim 5, characterized in that, The calculation formula of the third sub-model is: P 冷机 = P 查表 * η chilled water temperature Among them, P 冷机 is the single-unit power of the chiller, and P 查表 is the single-unit power of the chiller obtained by looking up the table at the specified cooling tower outlet water temperature and single-unit load. η 冷冻水温度 is the correction coefficient of the chilled water supply temperature.

9. An electronic device, characterized in that, The electronic device includes: A processor; and, A memory arranged to store computer-executable instructions, which when executed cause the processor to execute the method according to any one of claims 1-4.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores one or more programs, which when executed by the processor, implement the method according to any one of claims 1-4.

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