CN108981097B - Air conditioning system and method and device for adjusting energy requirement of air conditioning system - Google Patents
Air conditioning system and method and device for adjusting energy requirement of air conditioning system Download PDFInfo
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Abstract
The invention provides an air conditioning system and a method and a device thereof capable of being adjusted, wherein the method comprises the following steps: determining a blowing air temperature prediction model; after the air conditioning system enters a mode which can be determined, acquiring the air supply temperature of the air conditioning system and state parameters related to an air supply temperature prediction model; acquiring a current preset energy demand value, and calculating and predicting the air supply temperature according to the current preset energy demand value, state parameters related to an air supply temperature prediction model and the air supply temperature prediction model; judging whether the difference value between the predicted air supply temperature and the collected air supply temperature is smaller than a preset threshold value or not; and if the difference value between the predicted air supply temperature and the collected air supply temperature is smaller than a preset threshold value, determining that the indoor unit energy of the air conditioning system needs to be a current preset energy demand value. Therefore, the internal machine needs to be self-adjusted according to the difference value between the predicted air supply temperature and the collected air supply temperature, and therefore the control reliability of the air conditioning system and the use comfort of a user are improved.
Description
Technical Field
The invention relates to the technical field of air conditioners, in particular to an air conditioning system, an energy demand adjusting method of the air conditioning system and an energy demand adjusting device of the air conditioning system.
Background
In the related art, an air conditioning system usually operates according to original energy-required control parameters set by the air conditioning system under the conditions of old engineering modification, connection of a third-party indoor unit and too long operation time of the indoor unit. However, the inventor of the present application finds that the related art has the following problems, because the fan is aged, the heat exchanger is dirty and blocked, or parameters such as the heat exchanger form, the inner volume, the fan air volume and the like of the third-party indoor unit under the same capacity are changed, so that the actual operation of the indoor unit may need to have an obvious difference from the calculation of the indoor unit, and further the original energy set by the air conditioning system needs to be controlled to be invalid or not matched with the actual working condition, so that the air conditioning system is unstable in operation or needs to reach a stable working state for a long time, and meanwhile, the problems of air outlet condensation, insufficient refrigerating capacity and the like may be caused.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, a first objective of the present invention is to provide a method for adjusting the performance of an air conditioning system, so as to achieve self-adjustment of the performance of the internal machine, and improve the control reliability and the user comfort of the air conditioning system.
A second object of the present invention is to provide an adjustable device for an air conditioning system.
A second object of the present invention is to provide an air conditioning system.
A fourth object of the invention is to propose a non-transitory computer-readable storage medium.
To achieve the above object, an adjustment method for an air conditioning system according to an embodiment of the first aspect of the present invention includes the following steps: determining a blowing air temperature prediction model; after an air conditioning system enters a mode which can be determined, acquiring the air supply temperature of the air conditioning system and state parameters related to an air supply temperature prediction model; acquiring a current preset energy demand value, and calculating and predicting the air supply temperature according to the current preset energy demand value, state parameters related to the air supply temperature prediction model and the air supply temperature prediction model; judging whether the difference value between the predicted air supply temperature and the collected air supply temperature is smaller than a preset threshold value or not; and if the difference value between the predicted air supply temperature and the collected air supply temperature is smaller than the preset threshold value, determining that the indoor unit energy of the air conditioning system needs to be the current preset energy requirement value.
According to the method for adjusting the energy requirement of the air conditioning system, an air supply temperature prediction model is determined, after the air conditioning system enters an energy requirement determination mode, the air supply temperature of the air conditioning system and state parameters related to the air supply temperature prediction model are collected, meanwhile, a current preset energy requirement value is obtained, the predicted air supply temperature is calculated according to the current preset energy requirement value, the state parameters related to the air supply temperature prediction model and the air supply temperature prediction model, whether the difference value of the predicted air supply temperature and the collected air supply temperature is smaller than a preset threshold value or not is judged, and if the difference value of the predicted air supply temperature and the collected air supply temperature is smaller than the preset threshold value, the indoor unit energy requirement of the air conditioning system is determined to be the current preset energy requirement value. Therefore, the internal machine needs to be self-adjusted according to the difference value between the predicted air supply temperature and the collected air supply temperature, and therefore the control reliability of the air conditioning system and the use comfort of a user are improved.
In addition, the method for adjusting the energy requirement of the air conditioning system according to the above embodiment of the present invention may further have the following additional technical features:
according to one embodiment of the invention, if the difference between the predicted air supply temperature and the collected air supply temperature is greater than or equal to the preset threshold, the current preset energy requirement is adjusted to obtain an adjusted preset energy requirement; after the adjusted preset energy demand value is obtained, the predicted air supply temperature is recalculated according to the adjusted preset energy demand value, the state parameters related to the air supply temperature prediction model and the air supply temperature prediction model, and whether the difference value between the recalculated predicted air supply temperature and the acquired air supply temperature is smaller than a preset threshold value or not is judged.
According to an embodiment of the invention, the state parameters related to the supply air temperature prediction model include at least one of a refrigerant inlet temperature, a refrigerant outlet temperature, a heat exchanger intermediate refrigerant temperature, a return air temperature, and a wind level.
According to an embodiment of the present invention, after the air conditioning system enters the determinable mode, the method further includes: controlling the air conditioning system to operate at a preset frequency and stably operate for a first preset time; or controlling the air conditioning system to run at a preset frequency and controlling the running time to reach a second preset time.
According to one embodiment of the present invention, the determining a supply air temperature prediction model includes: determining m experimental data samples, wherein each experimental data sample comprises air supply temperature data, state parameter data of an air conditioning system and internal machine function required data; carrying out normalization processing on the m experimental data samples; after the normalization process, extracting α% × m experimental data samples from the m experimental data samples to construct a training sample, and extracting β% × m experimental data samples from the remaining (1- α%) × m experimental data samples to construct a test sample; performing multiple regression analysis on the training samples to obtain a multiple regression model; verifying the multiple regression model according to the test sample, and obtaining the error of the multiple regression model; when the error is smaller than a preset error threshold value, determining the air supply temperature prediction model as the multiple regression model; and when the error is larger than or equal to the preset error threshold value, increasing n experimental data samples on the basis of the m experimental data samples.
In order to achieve the above object, an adjustment device of an air conditioning system according to a second aspect of the present invention includes: the model determining module is used for determining an air supply temperature prediction model; the acquisition module is used for acquiring the air supply temperature of the air conditioning system and the state parameters related to the air supply temperature prediction model after the air conditioning system enters a mode which can be determined; the calculation module is used for acquiring a current preset energy demand value and calculating and predicting the air supply temperature according to the current preset energy demand value, the state parameters related to the air supply temperature prediction model and the air supply temperature prediction model; the judging module is used for judging whether the difference value between the predicted air supply temperature and the collected air supply temperature is smaller than a preset threshold value or not; and the energy requirement determining module is used for determining that the energy requirement of the internal unit of the air conditioning system is the current preset energy requirement when the difference value between the predicted air supply temperature and the collected air supply temperature is smaller than the preset threshold value.
According to the energy-demand adjusting device of the air conditioning system, the air supply temperature prediction model is determined through the model determining module, after the air conditioning system enters the energy-demand determining mode, the air supply temperature of the air conditioning system and the state parameters related to the air supply temperature prediction model are collected through the collecting module, meanwhile, the current preset energy demand value is obtained through the calculating module, the predicted air supply temperature is calculated according to the current preset energy demand value, the state parameters related to the air supply temperature prediction model and the air supply temperature prediction model, whether the difference value of the predicted air supply temperature and the collected air supply temperature is smaller than the preset threshold value or not is judged through the judging module, and when the difference value of the predicted air supply temperature and the collected air supply temperature is smaller than the preset threshold value, the indoor unit energy of the air conditioning system is determined to be the current preset energy demand value through the energy-demand determining module. Therefore, the internal machine needs to be self-adjusted according to the difference value between the predicted air supply temperature and the collected air supply temperature, and therefore the control reliability of the air conditioning system and the use comfort of a user are improved.
In addition, the adjustment-capable device of the air conditioning system according to the above embodiment of the present invention may further have the following additional technical features:
according to an embodiment of the present invention, the energy-demand determining module is further configured to, when a difference between the predicted air supply temperature and the acquired air supply temperature is greater than or equal to the preset threshold, adjust the current preset energy demand value to obtain an adjusted preset energy demand value; the calculation module is used for recalculating the predicted air supply temperature according to the adjusted preset energy demand value, the state parameters related to the air supply temperature prediction model and the air supply temperature prediction model after the adjusted preset energy demand value is obtained, and the judgment module is used for judging whether the difference value between the recalculated predicted air supply temperature and the acquired air supply temperature is smaller than a preset threshold value.
According to an embodiment of the invention, the state parameters related to the supply air temperature prediction model include at least one of a refrigerant inlet temperature, a refrigerant outlet temperature, a heat exchanger intermediate refrigerant temperature, a return air temperature, and a wind level.
According to an embodiment of the present invention, the adjustable device of the air conditioning system further comprises: and the processing module is used for controlling the air conditioning system to operate at a preset frequency and stably operate for a first preset time or controlling the air conditioning system to operate at the preset frequency and the operating time to reach a second preset time after the air conditioning system enters the mode which can be determined.
According to one embodiment of the invention, the model determination module comprises: the system comprises a sample determining unit, a data processing unit and a data processing unit, wherein the sample determining unit is used for determining m experimental data samples, and each experimental data sample comprises air supply temperature data, state parameter data of an air conditioning system and internal machine function required data; the processing unit is used for carrying out normalization processing on the m experimental data samples; an extraction unit configured to extract α% × m experimental data samples from the m experimental data samples after normalization processing to construct a training sample, and extract β% × m experimental data samples from the remaining (1- α%) × m experimental data samples to construct an inspection sample; the analysis unit is used for carrying out multiple regression analysis on the training samples to obtain a multiple regression model; and the checking unit is used for checking the multiple regression model according to the checking sample, acquiring the error of the multiple regression model, determining the air supply temperature prediction model as the multiple regression model when the error is smaller than a preset error threshold value, and adding n experimental data samples on the basis of the m experimental data samples when the error is larger than or equal to the preset error threshold value.
In order to achieve the above object, an air conditioning system according to a third aspect of the present invention includes a memory, a processor, and a program corresponding to an adjustment capable method of the air conditioning system, where the program is stored in the memory and is executable on the processor, and when the program corresponding to the adjustment capable method of the air conditioning system is executed by the processor, the adjustment capable method of the air conditioning system is implemented.
According to the air conditioning system provided by the embodiment of the invention, the processor runs the program corresponding to the adjustment-needed method of the air conditioning system stored in the memory, and can perform self-adjustment on the internal function according to the difference value between the predicted air supply temperature and the acquired air supply temperature, so that the control reliability of the air conditioning system and the use comfort of a user are improved.
To achieve the above object, a fourth aspect of the present invention provides a non-transitory computer-readable storage medium, on which a computer program is stored, the computer program, when executed by a processor, implementing the method for adjusting the air conditioning system.
According to the non-transitory computer-readable storage medium provided by the embodiment of the invention, by executing the program stored thereon and corresponding to the method for adjusting the internal energy of the air conditioning system, the internal energy can be automatically adjusted according to the difference between the predicted air supply temperature and the collected air supply temperature, so that the control reliability of the air conditioning system and the use comfort of a user are improved.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The foregoing and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a flow chart illustrating a method for adjusting the energy demand of an air conditioning system according to an embodiment of the present invention;
FIG. 2 is a flow chart illustrating a method for adjusting the capacity of an air conditioning system according to an embodiment of the present invention;
FIG. 3 is a flow diagram illustrating a process for determining a prediction model of supply air temperature in accordance with one embodiment of the present invention;
FIG. 4 is a flow diagram of a supply air temperature prediction model according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of an exemplary supply air temperature and supply air temperature prediction value, according to an embodiment of the present invention;
FIG. 6 is a graphical illustration of a calculated error of a supply air temperature prediction model in accordance with one embodiment of the present invention;
FIG. 7 is a block diagram of an adjustable system of an air conditioning system according to one embodiment of the present invention;
FIG. 8 is a block diagram of a model determination module according to another embodiment of the present invention;
fig. 9 is a block schematic diagram of an air conditioning system according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
An air conditioning system and a method and apparatus for adjusting the air conditioning system according to an embodiment of the present invention will be described with reference to the accompanying drawings.
Fig. 1 is a flowchart illustrating a method for adjusting the energy demand of an air conditioning system according to an embodiment of the present invention.
As shown in fig. 1, the method for adjusting the energy demand of the air conditioning system includes the following steps:
s101, determining an air supply temperature prediction model.
And S102, collecting the air supply temperature of the air conditioning system and state parameters related to the air supply temperature prediction model after the air conditioning system enters the mode which can be determined.
That is, before the user starts the air conditioning system, if the user selects the mode that can be determined, the air supply temperature of the air conditioning system and the state parameters related to the air supply temperature prediction model are collected, and if the user does not select the mode that can be determined, the air conditioning system is normally started.
Further, according to an embodiment of the present invention, the state parameters related to the supply air temperature prediction model may include at least one of a refrigerant inlet temperature, a refrigerant outlet temperature, a heat exchanger intermediate refrigerant temperature, a return air temperature, and a wind gear.
It can be understood that the refrigerant inlet temperature, the refrigerant outlet temperature, and the heat exchanger intermediate refrigerant temperature respectively refer to a refrigerant inlet temperature of the indoor heat exchanger, a refrigerant outlet temperature of the indoor heat exchanger, and an intermediate refrigerant temperature of the indoor heat exchanger.
S103, acquiring a current preset energy demand value, and calculating and predicting the air supply temperature according to the current preset energy demand value, the state parameters related to the air supply temperature prediction model and the air supply temperature prediction model.
That is, the predicted supply air temperature may be calculated based on the current predetermined energy requirement, the state parameters associated with the supply air temperature prediction model, and the supply air temperature prediction model, wherein the current predetermined energy requirement may be adjusted accordingly based on a difference between the calculated predicted supply air temperature and the collected supply air temperature.
And S104, judging whether the difference value between the predicted air supply temperature and the collected air supply temperature is smaller than a preset threshold value.
For example, if the predicted air supply temperature is T, pre, and the collected air supply temperature is T, test, the difference between the air supply temperature and the collected air supply temperature is | T, test-T, pre |, where the preset threshold may be calibrated according to the maximum error allowed by the actual operation of the air conditioning system.
And S105, if the difference value between the predicted air supply temperature and the collected air supply temperature is smaller than a preset threshold value, determining that the internal machine energy of the air conditioning system needs to be a current preset energy demand value.
That is, if the difference | T, test-T, pre | between the supply air temperature and the collected supply air temperature is less than the preset threshold value, i.e., | T, test-T, pre | <, it is determined that the indoor unit energy of the air conditioning system needs to be the current preset energy requirement.
It should be noted that the indoor unit energy refers to an output capacity requirement of the air conditioning system for the indoor unit, and when it is determined that the indoor unit energy of the air conditioning system needs to be a current preset energy requirement value, the indoor unit can be considered to meet the output capacity requirement of the air conditioning system for the indoor unit.
Further, according to an embodiment of the present invention, if a difference between the predicted air supply temperature and the collected air supply temperature is greater than or equal to a preset threshold, the current preset energy requirement is adjusted to obtain an adjusted preset energy requirement, wherein after the adjusted preset energy requirement is obtained, the predicted air supply temperature is recalculated according to the adjusted preset energy requirement, the state parameter related to the air supply temperature prediction model, and it is determined whether a difference between the recalculated predicted air supply temperature and the collected air supply temperature is less than the preset threshold.
That is, if the difference | T, test-T, pre | between the predicted air supply temperature and the collected air supply temperature is greater than or equal to the preset threshold, that is, | T, test-T, pre | ≧ is, the current preset energy requirement is adjusted, wherein the predicted air supply temperature is recalculated according to the adjusted preset energy requirement, the state parameters related to the air supply temperature prediction model, and it is determined whether the difference between the recalculated predicted air supply temperature and the collected air supply temperature is less than the preset threshold until the adjusted preset energy requirement satisfies that the difference between the predicted air supply temperature and the collected air supply temperature is less than the preset threshold.
For example, a current predetermined energy requirement may be initialized to a1, a predicted supply air temperature may be calculated according to the current predetermined energy requirement a1, a state parameter associated with the supply air temperature prediction model, and the supply air temperature prediction model to obtain a predicted supply air temperature b1, and further, whether a difference between the predicted supply air temperature b1 and the collected supply air temperature is less than a predetermined threshold may be determined, if the difference between the predicted supply air temperature and the collected supply air temperature is greater than the predetermined threshold, the current predetermined energy requirement may be adjusted from a1 to a2, and the predicted supply air temperature may be recalculated according to the adjusted predetermined energy requirement a2, the state parameter associated with the supply air temperature prediction model, and the supply air temperature prediction model to obtain a predicted supply air temperature b2 again, and whether a difference between the recalculated predicted supply air temperature b2 and the collected supply air temperature is less than the predetermined threshold may be determined, if the difference between the predicted supply air temperature and the collected supply air temperature is less than the predetermined threshold, it is determined that the indoor unit capacity of the air conditioning system needs to be the current preset capacity a 2.
Further, according to an embodiment of the present invention, after the air conditioning system enters the energy-need determining mode, the method further includes: controlling the air conditioning system to operate at a preset frequency and stably operate for a first preset time; or controlling the air conditioning system to operate at a preset frequency and controlling the operation time to reach a second preset time.
It can be understood that, after the air conditioning system enters the mode capable of being determined, the air conditioning system needs to be controlled to operate at the preset frequency and stably operate for a first preset time; or controlling the air conditioning system to operate at a preset frequency and controlling the operation time to reach a second preset time so as to ensure that the air conditioning system enters a stable working normal operation state.
Specifically, as shown in fig. 2, according to an embodiment of the present invention, the method for adjusting the energy requirement of the air conditioning system includes the following steps: when the air conditioning system is started, step S201 is performed.
S201, judging whether a signal which can be confirmed is received, if so, executing the step S202; if not, execution ends.
And S202, locking the preset frequency of the air conditioning system.
And S203, controlling the air conditioning system to operate at a preset frequency for a first preset time or controlling the air conditioning system to operate at the preset frequency and the operation time to reach a second preset time.
And S204, collecting the air supply temperature of the air conditioning system and state parameters related to the air supply temperature prediction model.
S205, initializing the current preset energy demand value.
And S206, calculating and predicting the air supply temperature according to the current preset energy demand value, the state parameters related to the air supply temperature prediction model and the air supply temperature prediction model.
S207, judging whether the difference value between the predicted air supply temperature and the collected air supply temperature is smaller than a preset threshold value, if so, executing step S208, and if not, executing step S209.
And S208, determining that the internal machine energy of the air conditioning system needs to be the current preset energy requirement value.
S209, adjusting the current preset energy demand value, and executing the step S206.
Further, as shown in fig. 3, according to an embodiment of the present invention, the determining the supply air temperature prediction model includes the following steps:
s301, m experimental data samples are determined, wherein each experimental data sample comprises air supply temperature data, state parameter data of an air conditioning system and internal machine function requirement data.
As shown in table 1, the system state parameter data of the air conditioner may include a refrigerant inlet temperature X1 of the indoor heat exchanger, a refrigerant outlet temperature X2 of the indoor heat exchanger, an intermediate refrigerant temperature X3 of the indoor heat exchanger, a return air temperature X4, an indoor unit energy requirement X5, a windshield X6, a refrigerant inlet temperature X7 of the indoor heat exchanger at the previous time, a refrigerant outlet temperature X8 of the indoor heat exchanger at the previous time, an intermediate refrigerant temperature X9 of the indoor heat exchanger at the previous time, a return air temperature X10 at the previous time, a supply air temperature X11 (predicted value) at the previous time, and the like.
TABLE 1
The refrigerant inlet temperature X1 of the indoor heat exchanger, the refrigerant outlet temperature X2 of the indoor heat exchanger, the intermediate refrigerant temperature X3 of the indoor heat exchanger and the return air temperature X4 can be obtained through temperature sensors, the internal energy requirement X5, the windshield X6, the refrigerant inlet temperature X7 of the indoor heat exchanger at the last moment, the refrigerant outlet temperature X8 of the indoor heat exchanger at the last moment, the intermediate refrigerant temperature X9 of the indoor heat exchanger at the last moment and the return air temperature X10 at the last moment can be obtained through an air conditioning system controller, and the air supply temperature X11 (a predicted value) at the last moment can be obtained through calculation of an air supply temperature prediction model.
And S302, performing normalization processing on the m experimental data samples.
Specifically, before normalization processing is performed on m experimental data samples, the number m0 of m experimental data samples and the number n of samples that need to be increased need to be initialized to zero.
Further, when the number of the experimental data samples meets the number m0 of the m experimental data samples, normalization processing is performed on the m0 experimental data samples, that is, the m0 experimental data sample values are unified into the same measurement unit, so that training and verification are facilitated.
S303, after the normalization process, α% × m experimental data samples are extracted from the m experimental data samples to construct a training sample, and β% × m experimental data samples are extracted from the remaining (1- α%) × m experimental data samples to construct a test sample.
That is, the air temperature prediction model is analyzed, calculated and verified by extracting m0 experimental data samples as α% × m0 training samples and m0 × β% inspection samples, respectively.
It should be noted that α and β may be set arbitrarily, where β cannot be too small, and a sufficient number of calibration samples are ensured to perform multiple regression analysis, so as to ensure accuracy of calibration of the air supply temperature prediction model.
S304, performing multiple regression analysis on the training samples to obtain a multiple regression model.
It is understood that, by setting the temperature of the air conditioning system as a dependent variable Y and the system state parameter data and the internal energy demand data of the air conditioner as independent variables X1, X2, … and XN, a multiple regression equation Y is obtained as 0+1 · X1+2 · X2+ …. + N · XN, and coefficients 1, 2, …, N of the independent variables X1, X2, … and XN are calculated by similar matrix calculation using training samples extracted by α% × m0 in proportion. Wherein N is greater than 1.
S305, verifying the multiple regression model according to the test sample, and obtaining the error of the multiple regression model.
That is, by substituting m0 × β% of the test samples into the multiple regression equation, the error θ of the multiple regression model, that is, the difference between the actual air supply temperature and the predicted air supply temperature value is obtained.
And S306, when the error is smaller than a preset error threshold value, determining that the air supply temperature prediction model is a multiple regression model.
That is, if error θ is smaller than preset error threshold ξ, the supply air temperature prediction model is determined as a multiple regression model.
And S307, when the error is larger than or equal to the preset error threshold, increasing n experimental data samples on the basis of the m experimental data samples.
That is, if the error θ is greater than or equal to the preset error threshold ξ, the number m of experimental data samples is m0+ n, where n may be set accordingly according to the difference between the actual calculated error θ and the error threshold ξ.
For example, according to an embodiment of the present invention, the supply air temperature Y is used as a dependent variable of a multiple regression equation, and the refrigerant inlet temperature X1 of the indoor heat exchanger, the refrigerant outlet temperature X2 of the indoor heat exchanger, the intermediate refrigerant temperature X3 of the indoor heat exchanger, the return air temperature X4 and the current preset energy demand X5 are used as independent variables of the multiple regression equation, that is, the multiple regression equation is assumed to be Y ═ 0+1 · X1+2 · X2+3 · X3+4 · X4+ 5 · X5.
Specifically, the experimental sample data values are shown in table 2:
TABLE 2
From the experimental sample data shown in table 2, Y ═ 3.8841172169081-3.8841172169081X1+0.543407068248543X2+0.373026318127632X3+0.20128670841994X4+0.0103436792103981X5 was determined.
In the embodiment of the present invention, as shown in fig. 4 to 5, the error θ is ± 3 ℃ by comparing the actual supply air temperature with the supply air temperature prediction value and plotting a linear relationship.
Therefore, the air supply temperature prediction model can be determined based on the experimental data and the multiple regression analysis, and the accuracy of the air supply temperature prediction model can be improved by systematically performing the multiple regression analysis on a large amount of experimental data, so that the control accuracy of the air conditioning system is greatly improved, and the cost is reduced.
Specifically, as shown in fig. 6, according to an embodiment of the present invention, the determining of the supply air temperature prediction model implements the following steps:
s401, determining a prediction model and screening independent variables.
S402, initializing the number m0 of basic samples and increasing the number n of samples.
And S403, collecting m-m 0+ n samples, and performing normalization processing.
S404, divide the m-m 0+ n samples into α% × m random samples and β% × m training samples.
S405, performing multiple regression analysis on the alpha% × m random samples to obtain a multiple regression equation.
S406, substituting the training samples of beta percent multiplied by m into a multiple regression equation, judging whether the error theta of the multiple regression equation is smaller than the error threshold xi, and if so, executing the step S407; if not, step S408 is performed.
S407, determining and obtaining a multiple regression equation as an air supply temperature prediction model.
S408, the number of samples n is increased, and step S403 is performed.
In summary, according to the method for adjusting the energy requirement of the air conditioning system of the embodiment of the present invention, the air supply temperature prediction model is determined, after the air conditioning system enters the energy requirement determination mode, the air supply temperature of the air conditioning system and the state parameter related to the air supply temperature prediction model are collected, the current preset energy requirement is obtained, the predicted air supply temperature is calculated according to the current preset energy requirement, the state parameter related to the air supply temperature prediction model, and whether the difference between the predicted air supply temperature and the collected air supply temperature is smaller than the preset threshold value is determined, and if the difference between the predicted air supply temperature and the collected air supply temperature is smaller than the preset threshold value, it is determined that the indoor unit of the air conditioning system can be the current preset energy requirement. Therefore, the internal machine needs to be self-adjusted according to the difference value between the predicted air supply temperature and the collected air supply temperature, and therefore the control reliability of the air conditioning system and the use comfort of a user are improved.
Fig. 7 is a block diagram illustrating an adjustable device of an air conditioning system according to an embodiment of the present invention. As shown in fig. 7, the adjustable device 100 of the air conditioning system includes: the device comprises a model determining module 1, an acquisition module 2, a calculation module 3, a judgment module 4 and an energy requirement determining module 5.
The model determining module 1 is used for determining an air supply temperature prediction model; the acquisition module 2 is used for acquiring the air supply temperature of the air conditioning system and state parameters related to the air supply temperature prediction model after the air conditioning system enters a mode which can be determined; the calculation module 3 is used for acquiring a current preset energy demand value and calculating and predicting the air supply temperature according to the current preset energy demand value, state parameters related to the air supply temperature prediction model and the air supply temperature prediction model; the judgment module 4 is used for judging whether the difference value between the predicted air supply temperature and the collected air supply temperature is smaller than a preset threshold value or not; the energy requirement determining module 5 is used for determining that the internal machine energy of the air conditioning system needs to be the current preset energy requirement when the difference value between the predicted air supply temperature and the collected air supply temperature is smaller than a preset threshold value.
Specifically, as shown in fig. 8, according to one embodiment of the present invention, the model determining module 1 includes: a sample determination unit 11, a processing unit 12, an extraction unit 13, an analysis unit 14 and a verification unit 15.
The sample determining unit 11 is configured to determine m experimental data samples, where each experimental data sample includes air supply temperature data, state parameter data of an air conditioning system, and internal function requirement data; the processing unit 12 is configured to perform normalization processing on the m experimental data samples; the extraction unit 13 is configured to extract α% × m experimental data samples from the m experimental data samples after the normalization processing to construct a training sample, and extract β% × m experimental data samples from the remaining (1- α%) × m experimental data samples to construct an inspection sample; the analysis unit 14 is configured to perform multiple regression analysis on the training samples to obtain a multiple regression model; the checking unit 15 checks the multiple regression model according to the check sample, obtains an error of the multiple regression model, determines that the air supply temperature prediction model is the multiple regression model when the error is smaller than a preset error threshold, and adds n experimental data samples on the basis of the m experimental data samples when the error is larger than or equal to the preset error threshold.
For example, if the predicted air supply temperature is T, pre, and the collected air supply temperature is T, test, the difference between the air supply temperature and the collected air supply temperature is | T, test-T, pre |, where the preset threshold may be calibrated according to the maximum error allowed by the actual operation of the air conditioning system.
Further, according to an embodiment of the present invention, the energy requirement determining module 5 is further configured to adjust the current preset energy requirement to obtain an adjusted preset energy requirement when a difference between the predicted air supply temperature and the acquired air supply temperature is greater than or equal to a preset threshold, wherein the calculating module 3 further recalculates the predicted air supply temperature according to the adjusted preset energy requirement, the state parameter related to the air supply temperature prediction model, and the air supply temperature prediction model after obtaining the adjusted preset energy requirement, and the determining module further determines whether the difference between the recalculated predicted air supply temperature and the acquired air supply temperature is less than the preset threshold.
That is, if the difference | T, test-T, pre | between the predicted air supply temperature and the collected air supply temperature is greater than or equal to the preset threshold, that is, | T, test-T, pre | ≧ the determining module 5 is further configured to adjust the current preset energy requirement, wherein the calculating module 3 is further configured to recalculate the predicted air supply temperature according to the adjusted preset energy requirement, the state parameter associated with the air supply temperature prediction model, and determine whether the difference between the recalculated predicted air supply temperature and the collected air supply temperature is less than the preset threshold until the adjusted preset energy requirement satisfies that the difference between the predicted air supply temperature and the collected air supply temperature is less than the preset threshold, that is, the determining module 5 is configured to determine that the indoor unit of the air conditioning system can be the current preset energy requirement.
It should be noted that the indoor unit energy requirement refers to a requirement of a user for the output capacity of an indoor unit of the air conditioning system, and when it is determined that the indoor unit energy of the air conditioning system needs to be the current preset energy requirement, the supply air temperature of the air conditioning system can be considered to meet the temperature required by the preset energy requirement of the user.
Specifically, the state parameters related to the air supply temperature prediction model comprise at least one of a refrigerant inlet temperature, a refrigerant outlet temperature, a heat exchanger intermediate refrigerant temperature, a return air temperature and a wind gear.
It can be understood that the refrigerant inlet temperature, the refrigerant outlet temperature, and the heat exchanger intermediate refrigerant temperature respectively refer to a refrigerant inlet temperature of the indoor heat exchanger, a refrigerant outlet temperature of the indoor heat exchanger, and an intermediate refrigerant temperature of the indoor heat exchanger.
Further, according to an embodiment of the present invention, the adjustable device 100 of the air conditioning system further includes: and the processing module is used for controlling the air conditioning system to operate at a preset frequency and stably operate for a first preset time or controlling the air conditioning system to operate at the preset frequency and the operating time to reach a second preset time after the air conditioning system enters the mode which can be determined.
It can be understood that different operating frequencies of the air conditioning system have corresponding internal energy requirements, and therefore, after the air conditioning system enters the energy requirement determining mode, the air conditioning system needs to be controlled by the processing module 6 to operate at the preset frequency and stably operate for a first preset time; or controlling the air conditioning system to operate at a preset frequency and controlling the operation time to reach a second preset time so as to ensure that the air conditioning system enters a stable working normal operation state.
In summary, according to the adjustment-required device of the air conditioning system of the embodiment of the invention, the air supply temperature prediction model is determined by the model determination module, and after the air conditioning system enters the determination-required mode, the air supply temperature of the air conditioning system and the state parameters related to the air supply temperature prediction model are acquired through the acquisition module, meanwhile, the current preset energy demand value is obtained through a calculation module, the air supply temperature is calculated and predicted according to the current preset energy demand value, the state parameters related to the air supply temperature prediction model and the air supply temperature prediction model, and then judges whether the difference value between the predicted air supply temperature and the collected air supply temperature is less than a preset threshold value through the judging module, and when the difference value between the predicted air supply temperature and the collected air supply temperature is smaller than a preset threshold value, determining that the indoor unit energy of the air conditioning system needs to be a current preset energy requirement value through the energy requirement determining module. Therefore, the internal machine needs to be self-adjusted according to the difference value between the predicted air supply temperature and the collected air supply temperature, and therefore the control reliability of the air conditioning system and the use comfort of a user are improved.
Fig. 9 is a block schematic diagram of an air conditioning system according to an embodiment of the present invention.
As shown in fig. 9, the air conditioning system 1000 includes a memory 101, a processor 102, and a computer program stored in the memory 101 and executable on the processor 102, and when the processor 101 executes the computer program, the method for adjusting the air conditioning system as described above is implemented.
According to the air conditioning system provided by the embodiment of the invention, the processor runs the program corresponding to the method for adjusting the capacity of the air conditioning system stored in the memory, and the internal function can be automatically adjusted according to the difference value between the predicted air supply temperature and the collected air supply temperature, so that the control reliability of the air conditioning system and the use comfort of a user are improved.
Further, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for adjusting the air conditioning system.
The non-transitory computer readable storage medium provided by the embodiment of the invention is used for realizing the energy demand adjustment method of the air conditioning system by executing the computer program stored on the processor, and can perform self-adjustment on the internal energy demand according to the difference value between the predicted air supply temperature and the acquired air supply temperature, so that the control reliability of the air conditioning system and the use comfort of a user are improved.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (11)
1. A method for adjusting the energy demand of an air conditioning system comprises the following steps: determining a blowing air temperature prediction model; after an air conditioning system enters a mode which can be determined, acquiring the air supply temperature of the air conditioning system and state parameters related to an air supply temperature prediction model; acquiring a current preset energy demand value, and calculating and predicting the air supply temperature according to the current preset energy demand value, state parameters related to the air supply temperature prediction model and the air supply temperature prediction model; the method is characterized by further comprising the following steps:
judging whether the difference value between the predicted air supply temperature and the collected air supply temperature is smaller than a preset threshold value or not;
and if the difference value between the predicted air supply temperature and the collected air supply temperature is smaller than the preset threshold value, determining that the indoor unit energy of the air conditioning system needs to be the current preset energy requirement value.
2. The adjustable method of air conditioning system according to claim 1,
if the difference value between the predicted air supply temperature and the collected air supply temperature is larger than or equal to the preset threshold value, adjusting the current preset energy requirement value to obtain the adjusted preset energy requirement value;
after the adjusted preset energy demand value is obtained, the predicted air supply temperature is recalculated according to the adjusted preset energy demand value, the state parameters related to the air supply temperature prediction model and the air supply temperature prediction model, and whether the difference value between the recalculated predicted air supply temperature and the acquired air supply temperature is smaller than a preset threshold value or not is judged.
3. The method of claim 1, wherein the condition parameters associated with the supply air temperature prediction model comprise at least one of a refrigerant inlet temperature, a refrigerant outlet temperature, a heat exchanger intermediate refrigerant temperature, a return air temperature, and a wind level.
4. The method for adjusting the energy demand of the air conditioning system according to claim 1, further comprising, after the air conditioning system enters the energy demand determination mode:
controlling the air conditioning system to operate at a preset frequency and stably operate for a first preset time;
or controlling the air conditioning system to run at a preset frequency and controlling the running time to reach a second preset time.
5. An adjustable device for an air conditioning system, comprising:
the model determining module is used for determining an air supply temperature prediction model;
the acquisition module is used for acquiring the air supply temperature of the air conditioning system and the state parameters related to the air supply temperature prediction model after the air conditioning system enters a mode which can be determined;
the calculation module is used for acquiring a current preset energy demand value and calculating and predicting the air supply temperature according to the current preset energy demand value, the state parameters related to the air supply temperature prediction model and the air supply temperature prediction model;
the judging module is used for judging whether the difference value between the predicted air supply temperature and the collected air supply temperature is smaller than a preset threshold value or not;
and the energy requirement determining module is used for determining that the energy requirement of the internal unit of the air conditioning system is the current preset energy requirement when the difference value between the predicted air supply temperature and the collected air supply temperature is smaller than the preset threshold value.
6. Adjustable device of an air conditioning system according to claim 5,
the energy requirement determining module is further used for adjusting the current preset energy requirement value to obtain an adjusted preset energy requirement value when the difference value between the predicted air supply temperature and the acquired air supply temperature is greater than or equal to the preset threshold value;
the calculation module is used for recalculating the predicted air supply temperature according to the adjusted preset energy demand value, the state parameters related to the air supply temperature prediction model and the air supply temperature prediction model after the adjusted preset energy demand value is obtained, and the judgment module is used for judging whether the difference value between the recalculated predicted air supply temperature and the acquired air supply temperature is smaller than a preset threshold value.
7. The adjustable air conditioning system of claim 5, wherein the condition parameters associated with the supply air temperature prediction model include at least one of refrigerant inlet temperature, refrigerant outlet temperature, heat exchanger intermediate refrigerant temperature, return air temperature, and air gap.
8. The adjustable air conditioning system of claim 5, further comprising:
and the processing module is used for controlling the air conditioning system to operate at a preset frequency and stably operate for a first preset time or controlling the air conditioning system to operate at the preset frequency and the operating time to reach a second preset time after the air conditioning system enters the mode which can be determined.
9. The adjustable device of claim 5, wherein the model determining module comprises:
the system comprises a sample determining unit, a data processing unit and a data processing unit, wherein the sample determining unit is used for determining m experimental data samples, and each experimental data sample comprises air supply temperature data, state parameter data of an air conditioning system and internal machine function required data;
the processing unit is used for carrying out normalization processing on the m experimental data samples;
an extraction unit configured to extract α% × m experimental data samples from the m experimental data samples after normalization processing to construct a training sample, and extract β% × m experimental data samples from the remaining (1- α%) × m experimental data samples to construct an inspection sample;
the analysis unit is used for carrying out multiple regression analysis on the training samples to obtain a multiple regression model;
and the checking unit is used for checking the multiple regression model according to the checking sample, acquiring the error of the multiple regression model, determining the air supply temperature prediction model as the multiple regression model when the error is smaller than a preset error threshold value, and adding n experimental data samples on the basis of the m experimental data samples when the error is larger than or equal to the preset error threshold value.
10. An air conditioning system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method of any one of claims 1 to 4 when executing the program.
11. A non-transitory computer-readable storage medium, having stored thereon a computer program which, when executed by a processor, implements a method of enabling adjustment of an air conditioning system as claimed in any one of claims 1 to 4.
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| CN112052997B (en) * | 2020-09-07 | 2021-09-03 | 西安建筑科技大学 | Event trigger prediction control method for variable air volume air conditioning system |
| CN112487353B (en) * | 2020-11-30 | 2022-08-09 | 广东美的制冷设备有限公司 | Data processing method and device, dehumidifier and storage medium |
| CN112628970A (en) * | 2020-12-25 | 2021-04-09 | 珠海格力电器股份有限公司 | Control method and control device of air conditioner and air conditioning system |
| CN112728739B (en) * | 2020-12-28 | 2022-07-26 | 博锐尚格科技股份有限公司 | Method and device for determining set value of air supply temperature of air conditioning box based on algorithm prediction |
| CN112862222A (en) * | 2021-03-26 | 2021-05-28 | 中国建设银行股份有限公司 | Air conditioner return air temperature prediction method, abnormality monitoring method and related device |
| CN113254876B (en) * | 2021-04-28 | 2024-05-14 | 浙江智马达智能科技有限公司 | Air conditioner energy consumption data determining method, device, equipment and storage medium |
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