CN114329979A - Cooling tower operation control method and device based on white box model - Google Patents
Cooling tower operation control method and device based on white box model Download PDFInfo
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Abstract
The invention discloses a cooling tower operation control method and device based on a white box model. The method comprises the following steps: establishing a white box model, wherein the white box model comprises a first sub model, a second sub model and a third sub model, the input parameter of the first sub model is fan frequency, the output parameter is single-tower power of a cooling tower, the input parameter of the second sub model is air-water ratio, the output parameter is approximation degree, the input parameter of the third sub model is single-machine load, chilled water supply temperature and cooling tower outlet water temperature, and the output parameter is single-machine power of a cooling machine; obtaining the frequency and the open tower number of the cooling tower when the sum of the total power of the cooling tower and the total power of the cold machine is minimum according to the white box model; and controlling the cooling tower according to the frequency of the cooling tower and the tower opening number of the cooling tower. Therefore, the invention establishes the white box model of the cooling tower optimal strategy by using the heating ventilation heat transfer theory and partial experimental data.
Description
Technical Field
The invention relates to the field of processing, in particular to a cooling tower operation control method and device based on a white box model, electronic equipment and a computer readable storage medium.
Background
The cooling tower is used as general equipment for a thermodynamic system to discharge waste heat, the control of the cooling tower is often ignored in the operation and maintenance process of an actual heating, ventilation and air conditioning system, the cooling tower of 140 commercial squares researched and researched is taken as a basis, the number of the cooling towers in most squares is unchanged and unchanged, and the situations that the full frequency is fully opened or the amplitude of the variable frequency variable tower of the cooling tower is overlarge exist. But the cooling performance of the cooling tower is important to the operational performance of the refrigeration unit. The performance test and prediction model of the cooling tower is the key point of a plurality of researches, different scholars make a series of researches on the performance test and prediction model based on different models, such as an epsilon-NTU method (efficiency-heat transfer unit number method), but the method needs more physical parameters (mass transfer coefficient and the like) which are difficult to measure; with the continuous accumulation of the public building subentry measurement, the black box-based cooling tower performance model gradually becomes a research hotspot, but the black box-based cooling tower model is not like a cold machine experience model, and the input parameters of the model and the selection of the model are not consistent: the multivariate polynomial used by simulation software such as EnergyPlus and Modelica is a regression model, and other different students adopt Support Vector Machines (SVM), Random Forest (RANDOM Forest) and the like. Different projects are based on actually acquired data to fit a cooling tower model, are not strong in universality, and currently, a fitting model and design input parameters still need to be selected based on actual data conditions.
The operation of the cooling tower is managed in a combined frequency conversion (approach degree of 3-5 ℃) mode in part of squares, and when specific working condition changes are lacked in detail, corresponding detailed and specific control parameters cause energy waste caused by unreasonable operation of part of working conditions.
The water distribution uniformity, the filler aging degree and the air flow organization of the cooling tower, the operation of a cooling pump can influence the heat exchange of the cooling tower, the water outlet temperature feedback control is frequently established when the accuracy of a physical model is possibly insufficient, a large amount of time of the cooling tower is in an unstable state, the rules learned from historical data cannot be applied to the stable state, and the operation rules in other modes cannot be obtained by data under the condition that the actual operation mode is single, so that the optimal strategy in all modes cannot be obtained.
Disclosure of Invention
In view of the above, the present invention has been made to provide a white box model-based cooling tower operation control method, apparatus, electronic device, computer-readable storage medium that overcomes or at least partially solves the above-mentioned problems.
One embodiment of the invention provides a cooling tower operation control method based on a white box model, which comprises the following steps:
establishing a white box model, wherein the white box model comprises a first sub model, a second sub model and a third sub model, the input parameter of the first sub model is fan frequency, the output parameter is single-tower power of a cooling tower, the input parameter of the second sub model is air-water ratio, the output parameter is approximation degree, the input parameter of the third sub model is single-machine load, chilled water supply temperature and cooling tower outlet water temperature, and the output parameter is single-machine power of a cooling machine;
obtaining the frequency and the number of the opened towers of the cooling tower when the sum of the total power of the cooling tower and the total power of the cold machine is minimum 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 the opened towers of the cooling tower, and the total power of the cold machine is the product of the single-machine power of the cold machine and the number of the opened towers of the cold machine;
and controlling the cooling tower according to the frequency of the cooling tower and the tower opening number of the cooling tower.
Optionally, the calculation formula of the first sub-model is:
single tower power of cooling tower (rated power of fan) · ηFan blower) (a is (fan frequency/50) ^3+ b)
Wherein eta isFan blowerAnd a and b are fan characteristic parameters.
Optionally, the calculation formula of the second submodel is:
the approach degree is the design approach degree, wind-water ratio (-c)
Where c is a constant obtained from field actual data measurements.
Optionally, the calculation formula of the third submodel is:
Pcooling machine＝PLook-up table*ηTemperature of refrigerating water
Wherein, PCooling machineFor the power of a single machine of the refrigerator, PLook-up tableThe single-machine power, eta of the cold machine obtained by looking up the table under the specified outlet water temperature of the cold tower and the single-machine loadTemperature of refrigerating waterIs a chilled water temperature correction coefficient.
Another embodiment of the present invention provides a cooling tower operation control apparatus based on a white box model, including:
the white box model establishing unit is used for establishing a white box model, the white box model comprises a first sub model, a second sub model and a third sub model, wherein the input parameter of the first sub model is fan frequency, the output parameter is single tower power of a cooling tower, the input parameter of the second sub model is air-water ratio, the output parameter is approximation degree, the input parameter of the third sub model is single machine load, chilled water supply temperature and cooling tower outlet water temperature, and the output parameter is single machine power of a cooling machine;
the cooling tower control parameter obtaining unit is used for obtaining the frequency and the open tower number of the cooling tower when the sum of the total power of the cooling tower and the total power of the cold machine is minimum 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 open tower number of the cooling tower, and the total power of the cold machine is the product of the single-machine power of the cold machine and the open machine number of the cold machine;
and the control unit is used for controlling the cooling tower according to the cooling tower frequency and the tower opening number of the cooling tower.
Optionally, the calculation formula of the first sub-model is:
single tower power of cooling tower (rated power of fan) · ηFan blower) (a is (fan frequency/50) ^3+ b)
Wherein eta isFan blowerAnd a and b are fan characteristic parameters.
Optionally, the calculation formula of the second submodel is:
the approach degree is the design approach degree, wind-water ratio (-c)
Where c is a constant obtained from field actual data measurements.
Optionally, the calculation formula of the third submodel is:
Pcooling machine＝PLook-up table*ηTemperature of refrigerating water
Wherein, PCooling machineFor the power of a single machine of the refrigerator, PLook-up tableThe single-machine power, eta of the cold machine obtained by looking up the table under the specified outlet water temperature of the cold tower and the single-machine loadTemperature of refrigerating waterIs a chilled water temperature correction coefficient.
Another embodiment of the present invention provides an electronic device, wherein the electronic device includes:
a processor; and the number of the first and second groups,
a memory arranged to store computer executable instructions that, when executed, cause the processor to perform the method described above.
Another embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores one or more programs which, when executed by a processor, implement the above-described method.
The invention has the beneficial effect that a white box model of the optimal strategy of the cooling tower is established by utilizing the heating, ventilating and heat transfer theory and partial experimental data. And establishing a model foundation and a model verification rule for obtaining higher accuracy through field measured data and related algorithm correction in the later period.
Drawings
FIG. 1 is a schematic flow chart of a cooling tower operation control method based on a white box model according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a water cooling system according to an embodiment of the present invention;
FIG. 3 is a graph of wind-water ratio versus approximation according to an embodiment of the present invention;
FIG. 4 is a schematic flow chart of a cooling tower operation control method based on a white box model according to another embodiment of the present invention;
FIG. 5 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;
FIG. 6 shows a schematic structural diagram of an electronic device according to one embodiment of the invention;
fig. 7 shows a schematic structural diagram of a computer-readable storage medium according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
The invention assumes that a cooling water pump is in a constant temperature difference control mode, the return water temperature of a cooling tower and the outlet water temperature of the cooling tower are delta t, the target temperature difference is generally set to be 5-7 ℃, for example, 5 ℃, namely when delta t is greater than 5, the motor of the water pump is increased in frequency, and when delta t is less than 5, the motor of the water pump is decreased in frequency.
Fig. 1 is a schematic flow chart of a cooling tower operation control method based on a white box model according to an embodiment of the present invention. As shown in fig. 1, the method includes:
s11: establishing a white box model, wherein the white box model comprises a first sub model, a second sub model and a third sub model, the input parameter of the first sub model is fan frequency, the output parameter is single-tower power of a cooling tower, the input parameter of the second sub model is air-water ratio, the output parameter is approximation degree, the input parameter of the third sub model is single-machine load, chilled water supply temperature and cooling tower outlet water temperature, and the output parameter is single-machine power of a cooling machine;
s12: obtaining the frequency and the number of the opened towers of the cooling tower when the sum of the total power of the cooling tower and the total power of the cold machine is minimum 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 the opened towers of the cooling tower, and the total power of the cold machine is the product of the single-machine power of the cold machine and the number of the opened towers of the cold machine;
s13: and controlling the cooling tower according to the frequency of the cooling tower and the tower opening number of the cooling tower.
According to the cooling tower operation control method based on the white box model, the white box model of the cooling tower optimal strategy is established by using the heating, ventilation and heat transfer theory and partial experimental data. And establishing a model foundation and a model verification rule for obtaining higher accuracy through field measured data and related algorithm correction in the later period.
Fig. 2 is a schematic diagram of a water cooling system according to an embodiment of the present invention. As shown in fig. 2, the composition structure and the water path of the water cooling system are given, and the outlet water temperature, the return water temperature, the supply water temperature, the return water temperature, the evaporation temperature and the condensation temperature of the chilled water are marked. The water outlet temperature of the cooling tower and the return water temperature of the cooling water are assumed to be the same by neglecting deviation, and are uniformly expressed by the water outlet temperature of the cooling tower in the invention.
It should be noted that, according to the heating and ventilation theory and empirical formula, the fan frequency f and the rotation speed n are in a 1-power relationship, the rotation speed n and the air quantity Q are in a 1-power relationship, and the rotation speed n and the power are in a 3-power relationship, that is: f1/f2 ═ n1/n2 ═ Q1/Q2, and P1/P2 ═ n13/n 23.
However, due to the influence of the fan efficiency and the static pressure change, a correction coefficient influenced by actual data should be added in practical application, and in addition, the actual power and the rated power of the fan under 50hz also have a correction coefficient.
Thus, in an optional implementation manner of the embodiment of the present invention, the calculation formula of the first sub-model is:
single tower power of cooling tower (rated power of fan) · ηFan blower) (a is (fan frequency/50) ^3+ b)
Wherein eta isFan blowerAnd a and b are fan characteristic parameters.
It should be noted that (rated power of fan [. eta. ]) [. eta. ]Fan blower) The calculation of a is the fan power, while in the present invention, the fan power is equivalent to the cooling tower power.
Further, the calculation formula of the second submodel is as follows:
the approach degree is the design approach degree, wind-water ratio (-c)
Where c is a constant obtained from field actual data measurements.
It should be noted that the design proximity refers to design parameters used in designing the model and number of the cooling tower. For example: the design heat dissipation capacity of a certain square is 1500RT, the design working condition is wet bulb temperature 29 ℃, the design cooling water inlet and outlet water temperature difference is 5 ℃, a designer specifies the approach degree design of the cooling tower according to the requirement of a project, the approach degree is equal to the cooling tower outlet water temperature-wet bulb temperature, for example, the design approach degree is 4 ℃, the working condition and the requirement reported to a cooling tower manufacturer are 29 ℃ of wet bulb temperature, 38 ℃ of cooling tower inlet water temperature, 33 ℃ of cooling tower outlet water temperature, and the heat dissipation capacity is 1650RT (10% of allowance).
And (3) carrying out constant load estimation by taking the wind-water ratio of the design of the cooling tower with the design approach degree of 4 ℃ as 1A to obtain the following data:
fig. 3 is a graph showing a relationship between the ratio of wind to water and the degree of approximation according to an embodiment of the present invention, and the relationship between the ratio of wind to water and the degree of approximation as a power function can be obtained by fitting the curve with software, i.e., the calculation formula of the second submodel is obtained.
Further, the calculation formula of the third submodel is as follows:
table lookup of refrigerating water temp. for P refrigerator
The P cold machine is the power of a single machine of the cold machine, the P cold table is the power of the single machine of the cold machine obtained by looking up a table under the specified water outlet temperature of the cold tower and the single machine load, and the eta chilled water temperature is a chilled water temperature correction coefficient.
The P-table can be obtained from the data of the model selection table provided by the refrigerator manufacturer. However, in the investigation, the equipment model selection table of a certain manufacturer is taken as constant water flow data, the data needs to be corrected under the control mode that the field cooling pump is in a constant temperature difference mode, the change of the condensation temperature can be calculated by adopting a method of assuming that the outlet water temperature and the condensation temperature of the cooling tower are in the constant temperature difference mode, and then the inverse Carnot cycle and the refrigeration coefficient are carried out: the power is corrected by the equation ICOP te/(tc-te). Where te is the evaporation temperature and tc is the condensation temperature.
Assuming that the chilled water supply water temperature is a fixed value, for example 7 ℃, a corresponding table with a temperature difference of 1 ℃ and a load per 10% is obtained, and then using an algorithm or a simple linear difference calculation, a table with an accuracy of 0.1 ℃ and a load of 1% is obtained, as follows (part of the table):
| water temperature of cooling tower Degree of rotation | 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. 3 | 312. 4 |
The precision table can meet the field use condition and does not need to be subjected to linear fitting.
Finally, when the power of the single machine of the cold machine is calculated, the temperature correction coefficient eta of the chilled water needs to be obtainedTemperature of refrigerating water。
ηTemperature of refrigerating water═ 1+0.03 ^ (7-chilled water supply temperature)
In practical application, etaTemperature of refrigerating waterThe evaluation can also be carried out using the usual evaluation coefficients, with an increase in evaporation temperature of 1 ℃ and an increase in ICOP of 3%.
Fig. 4 is a schematic flow chart of a cooling tower operation control method based on a white box model according to another embodiment of the present invention. The flow of the control method of the embodiment of the present invention is described below with reference to fig. 4, assuming that the respective cooling towers and the chiller selection are identical:
similar to fig. 1, a white box model is first established, and will not be described herein again.
Setting the total number of the on-site cooling towers to num, f is the average frequency, and n is the number of opened towers. By the heating and ventilation theory and the empirical common knowledge, the control strategy of the cooling tower can be simply divided into two modes of low-frequency tower increasing and decreasing and full-open tower frequency increasing and decreasing. I.e., f is 30, n is (1 to num); and n is num, f is (31-50), the situations are respectively taken into a white box model for calculation, and the minimum sum of the obtained power is the optimal n and f control strategy. Specifically, the method comprises the following steps:
(1) and substituting the fan frequency into the model 1 to calculate the single tower power of the cooling tower, wherein the total power of the cooling tower is the single tower power and the number of opened towers.
(2) Calculating the wind-water ratio: m is the number of open towers with design approach degree, and the air-water ratio is obtained by the inverse relation of the air-water ratio and the load, namely (n f)/(m 50)/(actual refrigerating capacity/single machine rated refrigerating capacity)
The rated refrigerating capacity of the single machine is the static parameter of the refrigerator selected by the model III.
And substituting the wind-water ratio into the model 2 to obtain the approximation degree.
(3) And obtaining the water outlet temperature of the cooling tower according to the approximation degree and the wet bulb temperature.
And substituting the outlet water temperature of the cooling tower and other input parameters into the model 3 to obtain the single machine power of the cold machine. Total power of the refrigerator is the product of single power of the refrigerator and the number of the refrigerators
The sum of the power is the total power of the cooling tower and the total power of the cooling machine.
In practical application, when the difference between the on-site cooling tower and the cold machine selection is large, the cooling tower and the cold machine need to be numbered, and strategy optimization output is carried out according to a combination mode and algorithm optimization.
Fig. 5 is a schematic structural diagram of a cooling tower operation control device based on a white box model according to an embodiment of the invention. As shown in fig. 5, the apparatus includes:
the white box model establishing unit 51 is used for establishing a white box model, the white box model comprises a first sub model, a second sub model and a third sub model, wherein the input parameter of the first sub model is fan frequency, the output parameter is single tower power of a cooling tower, the input parameter of the second sub model is air-water ratio, the output parameter is approximation degree, the input parameter of the third sub model is single machine load, chilled water supply temperature and water outlet temperature of the cooling tower, and the output parameter is single machine power of a cooling machine;
a cooling tower control parameter obtaining unit 52, configured to obtain, according to the white box model, a cooling tower frequency and a cooling tower open number when a sum of a total power of a cooling tower and a total power of a chiller is minimum, where the total power of the cooling tower is a product of a single-tower power of the cooling tower and the open number of the cooling tower, and the total power of the chiller is a product of a single-machine power of the chiller and the open number of the chiller;
and the control unit 53 is used for controlling the cooling tower according to the cooling tower frequency and the tower opening number of the cooling tower.
The cooling tower operation control device based on the white box model provided by the embodiment of the invention establishes the white box model of the cooling tower optimal strategy by using a heating, ventilating and heat transfer theory and partial experimental data. And establishing a model foundation and a model verification rule for obtaining higher accuracy through field measured data and related algorithm correction in the later period.
In an optional implementation manner of the embodiment of the present invention, a calculation formula of the first sub-model is:
single tower power of cooling tower (rated power of fan) · ηFan blower) (a is (fan frequency/50) ^3+ b)
Wherein eta isFan blowerAnd a and b are fan characteristic parameters.
Further, the calculation formula of the second submodel is as follows:
the approach degree is the design approach degree, wind-water ratio (-c)
Where c is a constant obtained from field actual data measurements.
Further, the calculation formula of the third submodel is as follows:
Pcooling machine＝PLook-up table*ηTemperature of refrigerating water
Wherein, PCooling machineFor the power of a single machine of the refrigerator, PLook-up tableThe single-machine power, eta of the cold machine obtained by looking up the table under the specified outlet water temperature of the cold tower and the single-machine loadTemperature of refrigerating waterIs a chilled water temperature correction coefficient.
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 for executing the methods in the foregoing embodiments, and therefore, detailed description thereof is omitted.
In conclusion, the invention establishes the white box model of the optimal strategy of the cooling tower by using the heating ventilation heat transfer theory and partial experimental data. And establishing a model foundation and a model verification rule for obtaining higher accuracy through field measured data and related algorithm correction in the later period.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
It should be noted that:
the algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose devices may be used with the teachings herein. The required structure for constructing such a device will be apparent from the description above. Moreover, the present invention is not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose the best mode of the invention.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the invention and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It will be appreciated by those skilled in the art that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components of the apparatus for detecting a wearing state of an electronic device according to embodiments of the present invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
For example, fig. 6 shows a schematic structural diagram of an electronic device according to an embodiment of the invention. The electronic device conventionally comprises a processor 61 and a memory 62 arranged to store computer executable instructions (program code). The memory 62 may 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 space 63 storing program code 64 for performing the steps of the method shown in fig. 1 and in any of the embodiments. For example, the storage space 63 for storing the program code may comprise respective program codes 64 for implementing the various steps in the above method, respectively. The program code can be read from or written to one or more computer program products. These computer program products comprise a program code carrier such as a hard disk, a Compact Disc (CD), a memory card or a floppy disk. Such a computer program product is typically a computer readable storage medium such as described in fig. 7. The computer readable storage medium may have memory segments, memory spaces, etc. arranged similarly to the memory 62 in the electronic device of fig. 6. The program code may be compressed, for example, in a suitable form. In general, the memory space stores program code 71 for performing the steps of the method according to the invention, i.e. there may be program code, such as read by the processor 61, which, when run by the electronic device, causes the electronic device to perform the steps of the method described above.
While the foregoing is directed to embodiments of the present invention, other modifications and variations of the present invention may be devised by those skilled in the art in light of the above teachings. It should be understood by those skilled in the art that the foregoing detailed description is for the purpose of better explaining the present invention, and the scope of the present invention should be determined by the scope of the appended claims.
Claims (10)
1. A cooling tower operation control method based on a white box model is characterized by comprising the following steps:
establishing a white box model, wherein the white box model comprises a first sub model, a second sub model and a third sub model, the input parameter of the first sub model is fan frequency, the output parameter is single-tower power of a cooling tower, the input parameter of the second sub model is air-water ratio, the output parameter is approximation degree, the input parameter of the third sub model is single-machine load, chilled water supply temperature and cooling tower outlet water temperature, and the output parameter is single-machine power of a cooling machine;
obtaining the frequency and the number of the opened towers of the cooling tower when the sum of the total power of the cooling tower and the total power of the cold machine is minimum 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 the opened towers of the cooling tower, and the total power of the cold machine is the product of the single-machine power of the cold machine and the number of the opened towers of the cold machine;
and controlling the cooling tower according to the frequency of the cooling tower and the tower opening number of the cooling tower.
2. The method of claim 1, wherein the first submodel is calculated by:
single tower power of cooling tower (rated power of fan) · ηFan blower) (a is (fan frequency/50) ^3+ b)
Wherein eta isFan blowerAnd a and b are fan characteristic parameters.
3. The method of claim 1, wherein the second submodel is calculated by:
the approach degree is the design approach degree, wind-water ratio (-c)
Where c is a constant obtained from field actual data measurements.
4. The method of claim 1, wherein the third submodel is calculated by:
Pcooling machine＝PLook-up table*ηTemperature of refrigerating water
Wherein, PCooling machineFor the power of a single machine of the refrigerator, PLook-up tableThe single-machine power, eta of the cold machine obtained by looking up the table under the specified outlet water temperature of the cold tower and the single-machine loadTemperature of refrigerating waterIs a chilled water temperature correction coefficient.
5. A cooling tower operation control device based on a white box model is characterized by comprising:
the white box model establishing unit is used for establishing a white box model, the white box model comprises a first sub model, a second sub model and a third sub model, wherein the input parameter of the first sub model is fan frequency, the output parameter is single tower power of a cooling tower, the input parameter of the second sub model is air-water ratio, the output parameter is approximation degree, the input parameter of the third sub model is single machine load, chilled water supply temperature and cooling tower outlet water temperature, and the output parameter is single machine power of a cooling machine;
the cooling tower control parameter obtaining unit is used for obtaining the frequency and the open tower number of the cooling tower when the sum of the total power of the cooling tower and the total power of the cold machine is minimum 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 open tower number of the cooling tower, and the total power of the cold machine is the product of the single-machine power of the cold machine and the open machine number of the cold machine;
and the control unit is used for controlling the cooling tower according to the cooling tower frequency and the tower opening number of the cooling tower.
6. The apparatus of claim 5, wherein the first submodel is calculated by:
single tower power of cooling tower (rated power of fan) · ηFan blower) (a is (fan frequency/50) ^3+ b)
Wherein eta isFan blowerAnd a and b are fan characteristic parameters.
7. The apparatus of claim 5, wherein the second submodel is calculated by:
the approach degree is the design approach degree, wind-water ratio (-c)
Where c is a constant obtained from field actual data measurements.
8. The apparatus of claim 5, wherein the third submodel is calculated by:
Pcooling machine＝PLook-up table*ηTemperature of refrigerating water
Wherein, PCooling machineFor the power of a single machine of the refrigerator, PLook-up tableThe single-machine power, eta of the cold machine obtained by looking up the table under the specified outlet water temperature of the cold tower and the single-machine loadChilled waterTemperature ofIs a chilled water temperature correction coefficient.
9. An electronic device, comprising:
a processor; and the number of the first and second groups,
a memory arranged to store computer executable instructions that, when executed, cause the processor to perform the method of 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 a processor, implement the method of any of claims 1-4.
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| CN114974480A (en) * | 2022-08-01 | 2022-08-30 | 浙江大学 | Modelica rectifying tower model-based model design parameter calculation method and device |
| CN114974480B (en) * | 2022-08-01 | 2022-10-11 | 浙江大学 | Modelica rectifying tower model-based model design parameter calculation method and device |
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