CN117109141A - Intelligent energy consumption adjusting method and device for central air conditioner and terminal equipment - Google Patents
Intelligent energy consumption adjusting method and device for central air conditioner and terminal equipment Download PDFInfo
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- CN117109141A CN117109141A CN202311378331.4A CN202311378331A CN117109141A CN 117109141 A CN117109141 A CN 117109141A CN 202311378331 A CN202311378331 A CN 202311378331A CN 117109141 A CN117109141 A CN 117109141A
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- 238000005265 energy consumption Methods 0.000 title claims abstract description 60
- 238000000034 method Methods 0.000 title claims abstract description 37
- 238000005057 refrigeration Methods 0.000 claims abstract description 230
- 230000006870 function Effects 0.000 claims description 53
- 230000004043 responsiveness Effects 0.000 claims description 29
- 238000001816 cooling Methods 0.000 claims description 12
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 12
- 238000004378 air conditioning Methods 0.000 description 8
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- 238000010586 diagram Methods 0.000 description 5
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- 238000012795 verification Methods 0.000 description 1
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
- F24F11/46—Improving electric energy efficiency or saving
- F24F11/47—Responding to energy costs
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/89—Arrangement or mounting of control or safety devices
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Abstract
The invention discloses an intelligent energy consumption adjusting method and device for a central air conditioner and terminal equipment, wherein the method comprises the following steps: collecting original data of a plurality of parameters in a period of time, and storing the original data into an information database, wherein the plurality of parameters comprise outdoor temperature, indoor temperature and refrigerating output; constructing a refrigeration demand model according to the outdoor temperature and the original data of the refrigeration output quantity, and calculating the original refrigeration demand of a central air conditioner host based on the refrigeration demand model; and analyzing the responsivity of the indoor temperature in the information database to the original refrigeration requirement, establishing a calibration function according to the responsivity, and adjusting the original refrigeration requirement of the central air conditioner host through the calibration function. According to the invention, the actual refrigeration requirement is prejudged in advance by establishing the calibration function so as to adjust the original refrigeration requirement of the central air conditioner host, so that the timely feedback of the central air conditioner system on the actual refrigeration requirement is realized, and the waste of refrigeration energy consumption is reduced.
Description
Technical Field
The present invention relates to the field of refrigeration systems, and in particular, to an intelligent energy consumption adjustment method and apparatus for a central air conditioner, and a terminal device.
Background
In the prior art, there are two ways of adjusting load by a central air conditioning system host: one is to adjust the load according to the chilled water temperature, for example, the outlet water temperature is set to 8 ℃, and the central air conditioner control system only performs load shedding when the chilled water temperature reaches or approaches 8 ℃ so as to reduce the load of the host. The other is to adjust the load according to the indoor temperature, and the central air conditioning system host starts to adjust the load when the indoor temperature is used as a feedback signal, for example, the indoor temperature is higher than 28 ℃.
However, because the central air conditioning system is a huge system, although the system has huge chilled water storage, the chilled water generally flows through the whole pipeline and then flows back to the host, and the whole process needs 20-40 minutes, which also causes that the control system of the central air conditioning system is a hysteresis system and cannot give timely feedback to actual refrigeration demands.
Accordingly, there is a need for improvement and advancement in the art.
Disclosure of Invention
The invention aims to solve the technical problems that aiming at the defects in the prior art, an intelligent energy consumption adjusting method, an intelligent energy consumption adjusting device and terminal equipment of a central air conditioner are provided, and the invention aims to solve the problems that a control system of a central air conditioner system is a hysteresis system and timely feedback cannot be given to actual refrigeration demands in the prior art.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
in a first aspect, the present invention provides an intelligent energy consumption adjustment method for a central air conditioner, where the method includes:
collecting original data of a plurality of parameters in a period of time, and storing the original data into an information database, wherein the plurality of parameters comprise outdoor temperature, indoor temperature and refrigerating output;
constructing a refrigeration demand model according to the outdoor temperature and the original data of the refrigeration output quantity, and calculating the original refrigeration demand of a central air conditioner host based on the refrigeration demand model;
and analyzing the responsivity of the indoor temperature in the information database to the original refrigeration requirement, establishing a calibration function according to the responsivity, and adjusting the original refrigeration requirement of the central air conditioner host through the calibration function.
In one implementation, the collecting raw data of a plurality of parameters over a period of time, storing the raw data in an information database, the plurality of parameters including outdoor temperature, indoor temperature, and cooling output, includes:
through a mode of wireless communication, raw data of a plurality of parameters including outdoor temperature, indoor temperature and refrigerating output are acquired within a period of time, wherein the outdoor temperature comprises a first outdoor temperature and a second outdoor temperature, and the indoor temperature comprises a first indoor temperature and a second indoor temperature.
In one implementation, the collecting the raw data of the parameters over a period of time, storing the raw data in an information database includes:
collecting the original data of each parameter in a period of time, and analyzing the actual numerical value of each parameter in a period of time;
and establishing a learning library of each parameter based on the actual numerical value, wherein the learning library of each parameter is stored in an information database.
In one implementation, the collecting the raw data of the parameters in a period of time, and after storing the raw data in the information database, further includes:
and monitoring the original data collected in each time in real time, and updating the original data of the information database in real time.
In one implementation manner, the constructing a refrigeration requirement model according to the outdoor temperature and the original data of the refrigeration output quantity, and calculating the original refrigeration requirement of the central air conditioner host based on the refrigeration requirement model includes:
reading original data of outdoor temperature and refrigerating output in the information database, and constructing a refrigerating demand model Fq (T0, T1, Q) based on the original data of the outdoor temperature and the refrigerating output, wherein T0 is the first outdoor temperature, T1 is the second outdoor temperature and Q is the refrigerating output;
and calculating the original refrigeration demand of the central air conditioner host based on the refrigeration demand model, wherein the original refrigeration demand comprises original refrigeration power and original refrigeration time.
In one implementation, the analyzing the responsiveness of the indoor temperature in the information database to the original refrigeration demand, and establishing a calibration function according to the responsiveness includes:
obtaining the responsivity of the indoor temperature in the information database to the refrigeration requirement in a preset time period, wherein the responsivity is the energy consumption difference between the actual refrigeration requirement and the original refrigeration requirement;
and establishing a calibration function Fz (T, T0, T1, T3 and T4) according to the responsivity, wherein T is the preset time, T0 is the first outdoor temperature, T1 is the second outdoor temperature, T3 is the first indoor temperature and T4 is the second indoor temperature.
In one implementation, the adjusting the original refrigeration requirement of the central air conditioner host by the calibration function includes:
calculating the actual refrigeration requirement of the central air conditioner host based on the calibration function, wherein the actual refrigeration requirement is used for judging the deviation condition between the actual refrigeration temperature and the original refrigeration temperature;
and adjusting the original refrigeration requirement of the central air conditioner host in real time through the actual refrigeration requirement.
In a second aspect, an embodiment of the present invention further provides an intelligent energy consumption adjusting device for a central air conditioner, where the device includes:
the system comprises an original data acquisition module, a data storage module and a data storage module, wherein the original data acquisition module is used for acquiring original data of a plurality of parameters in a period of time, and storing the original data into an information database, wherein the plurality of parameters comprise outdoor temperature, indoor temperature and refrigerating output;
the refrigeration demand calculation module is used for constructing a refrigeration demand model according to the original data of the outdoor temperature and the refrigeration output quantity, and calculating the original refrigeration demand of the central air conditioner host based on the refrigeration demand model;
and the refrigeration demand adjusting module is used for analyzing the responsiveness of the indoor temperature in the information database to the original refrigeration demand, establishing a calibration function according to the responsiveness, and adjusting the original refrigeration demand of the central air conditioner host through the calibration function.
In a third aspect, an embodiment of the present invention further provides a terminal device, where the terminal device includes a memory, a processor, and an intelligent energy consumption adjustment program of a central air conditioner stored in the memory and capable of running on the processor, and when the processor executes the intelligent energy consumption adjustment program of the central air conditioner, the processor implements the steps of the intelligent energy consumption adjustment method of the central air conditioner in any one of the above schemes.
In a fourth aspect, an embodiment of the present invention further provides a computer readable storage medium, where the computer readable storage medium stores an intelligent energy consumption adjustment program of a central air conditioner, where the intelligent energy consumption adjustment program of the central air conditioner, when executed by a processor, implements the steps of the intelligent energy consumption adjustment method of the central air conditioner according to any one of the above schemes.
The beneficial effects are that: compared with the prior art, the invention discloses an intelligent energy consumption adjusting method, an intelligent energy consumption adjusting device and terminal equipment of a central air conditioner. And then, constructing a refrigeration demand model according to the original data of the outdoor temperature and the refrigeration output quantity, and calculating the original refrigeration demand of the central air conditioner host based on the refrigeration demand model. And finally, analyzing the responsiveness of the indoor temperature in the information database to the original refrigeration requirement, establishing a calibration function according to the responsiveness, and adjusting the original refrigeration requirement of the central air conditioner host through the calibration function. According to the invention, the actual refrigeration requirement is prejudged in advance by establishing the calibration function so as to adjust the original refrigeration requirement of the central air conditioner host, so that the central air conditioner system can timely feed back the actual refrigeration requirement, and the waste of refrigeration energy consumption is reduced.
Drawings
Fig. 1 is a flowchart of a specific implementation of an intelligent energy consumption adjusting method of a central air conditioner according to an embodiment of the present invention.
Fig. 2 is a flow chart of steps of an intelligent energy consumption adjusting method of a central air conditioner according to an embodiment of the present invention.
Fig. 3 is a graph comparing the power consumption of the central air conditioner when the outdoor temperature rises.
Fig. 4 is a graph comparing the power consumption of the central air conditioner for cooling when the outdoor temperature is reduced.
Fig. 5 is a functional schematic diagram of an intelligent energy consumption adjusting device of a central air conditioner according to an embodiment of the present invention.
Fig. 6 is a schematic block diagram of a terminal device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and effects of the present invention clearer and more specific, the present invention will be described in further detail below with reference to the accompanying drawings and examples. It will be appreciated by persons skilled in the art that the specific embodiments described herein are for purposes of illustration only and are not intended to be limiting. As used herein, the singular forms "a," "an," "the" and "the" are intended to include the plural forms as well, and the word "comprising" when used in the specification of the present invention means that there are one or more of the stated features, integers, steps, operations, elements, and/or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The embodiment provides an intelligent energy consumption adjusting method of a central air conditioner, and in the implementation, firstly, raw data of a plurality of parameters including outdoor temperature, indoor temperature and refrigerating output are collected within a period of time, and the raw data are stored in an information database. And then, constructing a refrigeration demand model according to the original data of the outdoor temperature and the refrigeration output quantity, and calculating the original refrigeration demand of the central air conditioner host based on the refrigeration demand model. And finally, analyzing the responsiveness of the indoor temperature in the information database to the original refrigeration requirement, establishing a calibration function according to the responsiveness, and adjusting the original refrigeration requirement of the central air conditioner host through the calibration function. According to the embodiment, the actual refrigeration requirement is prejudged in advance by establishing the calibration function so as to adjust the original refrigeration requirement of the central air conditioner host, so that the timely feedback of the central air conditioner system on the actual refrigeration requirement is realized, and the waste of refrigeration energy consumption is reduced.
For example, in this embodiment, the influence of parameters such as outdoor temperature, indoor temperature and refrigeration output on the original refrigeration requirement of the central air conditioner host is comprehensively considered, and first, according to the original data of the outdoor temperature and the refrigeration output, a refrigeration requirement model is constructed and used for calculating the original refrigeration requirement of the central air conditioner host. And then, comprehensively considering the responsiveness of the indoor temperature to the original refrigeration requirement, and establishing a calibration function for adjusting the original refrigeration requirement of the central air conditioner host. Therefore, when the central air conditioner calculates the refrigeration requirement jointly by using the refrigeration requirement model and the calibration function constructed in the implementation, the effect of pre-judging the actual refrigeration requirement in advance and adjusting the original refrigeration requirement of the central air conditioner host can be achieved, the timely feedback of the central air conditioner system to the actual refrigeration requirement is realized, and the waste of refrigeration energy consumption is reduced.
Exemplary method
The intelligent energy consumption adjusting method of the central air conditioner can be applied to terminal equipment, wherein the terminal equipment can be a mobile terminal preset by a mobile phone, a tablet, a computer and the like, and can also be intelligent equipment such as the central air conditioner. As shown in fig. 1, the intelligent energy consumption adjusting method of the central air conditioner of the embodiment includes the following steps:
step S100, collecting original data of a plurality of parameters in a period of time, and storing the original data into an information database, wherein the plurality of parameters comprise outdoor temperature, indoor temperature and refrigerating output.
In this embodiment, the energy consumption of the central air conditioner is analyzed by the data of the outdoor temperature, the indoor temperature and the refrigerating output, so that the embodiment firstly collects the original data of the parameters of the outdoor temperature, the indoor temperature and the refrigerating output in a period of time, and stores the series of original data into the information database, and then when the embodiment needs to analyze the energy consumption of the central air conditioner, the required parameter data can be obtained only by the pre-built information database. It can be seen that the information database can provide raw data for several parameters.
In one implementation, step S100 of the present embodiment includes the following steps:
step S101, acquiring original data of a plurality of parameters in a period of time through a wireless communication mode, wherein the plurality of parameters comprise outdoor temperature, indoor temperature and refrigerating output, the outdoor temperature comprises first outdoor temperature and second outdoor temperature, and the indoor temperature comprises first indoor temperature and second indoor temperature.
The central air conditioning system is a huge system, has huge chilled water storage, and has the following operation flow: the central air conditioning host outputs chilled water to each floor, which typically flows back to the host after passing through the entire floor tunnel. Therefore, the position space of the central air conditioning system is relatively large, and in order to improve the acquired effective data of the central air conditioning system during operation, in this embodiment, data acquisition is performed through a wireless communication mode, and when a wireless module is connected, temperature and equipment operation information can be sensed remotely. Of course, the communication mode in this embodiment may also adopt a wired communication mode, which is not specifically limited in this embodiment.
Specifically, in this embodiment, the energy consumption of the central air conditioner is analyzed by analyzing data of three parameters, namely, an outdoor temperature, an indoor temperature and a refrigerating output, and further, the outdoor temperature in this embodiment includes a first outdoor temperature and a second outdoor temperature, wherein the first outdoor temperature is a temperature with shielding outdoors and no heat radiation. The second outdoor temperature is a temperature at which heat is radiated outdoors. The radiation intensity can be reflected by a difference between the first outdoor temperature and the second outdoor temperature. The indoor temperature in this embodiment includes a first indoor temperature and a second indoor temperature, where the first indoor temperature is an indoor temperature that is closer to the host, and the load of the host is quickly perceived to increase. The second indoor temperature is the indoor temperature farther from the host, and the change in cooling is perceived slowest. Because the cooling speed of the pipelines of the whole floor is different, the reaction time of the specific pipeline to the chilled water can be obtained through the temperature change of the first indoor temperature and the second indoor temperature in the embodiment.
In one implementation, when collecting raw data of a plurality of parameters in a period of time and storing the raw data in an information database, the embodiment includes:
step S102, collecting original data of each parameter in a period of time, and analyzing actual values of each parameter in a period of time;
step S103, based on the actual values, establishing a learning library of each parameter, wherein the learning library of each parameter is stored in an information database.
As shown in fig. 2, fig. 2 is a step flowchart of an intelligent energy consumption adjusting method of a central air conditioner according to the present embodiment. Specifically, the information database in this embodiment can provide raw data of several parameters, and then according to actual values of each parameter in a period of time, a learning library of 5 parameters is established, which are respectively: f1 (T, T0), F2 (T, T1), F3 (T, T3), F4 (T, T4), and F5 (T, Q). Wherein T0 is a first outdoor temperature, T1 is a second outdoor temperature, T3 is a first indoor temperature, and T4 is a second indoor temperature. F1 (T, T0) including a temperature value of the first outdoor temperature over time, F2 (T, T1) including a temperature value of the second outdoor temperature over time, F3 (T, T3) including a temperature value of the first indoor temperature over time, F4 (T, T4) including a temperature value of the second indoor temperature over time, and F5 (T, Q) including a cooling output amount over time. Therefore, 5 parameter learning libraries of F1 (T, T0), F2 (T, T1), F3 (T, T3), F4 (T, T4), and F5 (T, Q) are stored in the information database of the present embodiment. In addition, the average temperatures of T0, T1, T3, and T4 are calculated in this embodiment to obtain an average temperature change reference value of T2, where T2 is used as a temperature reference value of an average position, and is more commonly used in practical applications.
In one implementation, the method further includes, after collecting original data of a plurality of parameters over a period of time and storing the original data in an information database:
step S104, original data collected in each time are monitored in real time, and the original data of the information database are updated in real time.
Specifically, in order to ensure that the original data provided by the information database is accurate and reliable, the original data in the information database of the present embodiment is updated in real time. For example, when the season is in summer, the original data of each parameter in a certain time in summer is collected, and the actual value of each parameter in a certain time in summer is analyzed, and the temperatures of T0, T1, T3 and T4 are relatively high. When the season changes from summer to autumn, the outdoor temperatures (T0, T1) and the indoor temperatures (T3 and T4) are correspondingly reduced, and if the information database collected and constructed in summer is still used in autumn and winter, the accuracy of the calculated original refrigeration requirement of the central air conditioner host cannot be ensured. Therefore, the embodiment can monitor the original data collected in each time in real time and update the original data of the information database in real time.
And step 200, constructing a refrigeration demand model according to the outdoor temperature and the original data of the refrigeration output quantity, and calculating the original refrigeration demand of the central air conditioner host based on the refrigeration demand model.
In one implementation, step S200 of the present embodiment includes the following steps:
step S201, original data of outdoor temperature and refrigerating output in the information database are read, and a refrigerating demand model Fq (T0, T1, Q) is constructed based on the original data of the outdoor temperature and the refrigerating output, wherein T0 is the first outdoor temperature, T1 is the second outdoor temperature and Q is the refrigerating output;
step S202, calculating the original refrigeration requirement of the central air conditioner host based on the refrigeration requirement model, wherein the original refrigeration requirement comprises original refrigeration power and original refrigeration time.
First, in the present embodiment, considering the influence of the outdoor heat radiation, a refrigeration requirement model Fq (T0, T1, Q) is constructed by a relationship between an outdoor temperature and a refrigeration output, where T0 is the first outdoor temperature, T1 is the second outdoor temperature, and Q is the refrigeration output. Specifically, when the refrigeration demand model is constructed, the embodiment calculates the functional relation between the external temperature of the internal chamber and the refrigeration output in a period of time by adopting a polynomial approximation mode, and because an error function is also established in the subsequent step of the embodiment, the error range and the precision requirement in the step are not high, the 5-order function is selected for calculation, and when T0 corresponds to an x variable and T1 corresponds to a y variable, the function Fq=a5x is approximated to the 5-order function 5 +a4x 4 +a3x 3 +a2x 2 +a1x 1 +b5y 5 +b4y 4 +b3y 3 +b2y 2 +b1y 1 And +K, obtaining a refrigeration demand model Fq (T0, T1, Q) of approximate data, wherein a, b and K are constants, and a and b can be response values of a first outdoor temperature T0 and a second outdoor temperature T1 to refrigeration output in the conventional data acquisition process. As shown in fig. 2, the present embodiment also eliminates unexpected data during the construction of the refrigeration demand model Fq to ensure the accuracy of the construction model. Finally, the embodiment calculates the original refrigeration requirement of the central air conditioner host through the constructed refrigeration requirement model.
And step 300, analyzing the responsiveness of the indoor temperature in the information database to the original refrigeration requirement, establishing a calibration function according to the responsiveness, and adjusting the original refrigeration requirement of the central air conditioner host through the calibration function.
Generally, the refrigeration requirement of the central air conditioner host is not only affected by outdoor temperature, but also affected by other factors, in this embodiment, the influence of indoor temperature on the refrigeration requirement of the central air conditioner host is also considered, and according to the responsiveness of indoor temperature to the original refrigeration requirement, a calibration function is established, and the original refrigeration requirement of the central air conditioner host is regulated through the calibration function, so that the central air conditioner host can more accurately learn the actual temperature deviation, and regulate the load of the host, so that the actual refrigeration output just meets the refrigeration requirement, the effect of optimizing the actual output refrigeration capacity is achieved, and unnecessary waste is reduced.
In one implementation, the method of analyzing the responsiveness of the indoor temperature in the information database to the original refrigeration requirement and establishing the calibration function according to the responsiveness includes the following steps:
step 301, obtaining the responsivity of the indoor temperature in the information database to the refrigeration requirement in a preset time period, wherein the responsivity is the energy consumption difference between the actual refrigeration requirement and the original refrigeration requirement;
step S302, a calibration function Fz (T, T0, T1, T3, T4) is established according to the responsiveness, wherein T is the preset time, T0 is the first outdoor temperature, T1 is the second outdoor temperature, T3 is the first indoor temperature, and T4 is the second indoor temperature.
In specific implementation, the embodiment analyzes the energy consumption of the central air conditioner by analyzing the data of three parameters, namely the outdoor temperature, the indoor temperature and the refrigerating output. On the basis of constructing a refrigeration demand model Fq (T0, T1, Q) by considering the influence of outdoor heat radiation through the relationship between the outdoor temperature and the refrigeration output, the embodiment also establishes a calibration function Fz (T, T0, T1, T3, T4) according to the responsiveness of the indoor temperature in the information database to the refrigeration demand in a preset time period, where T is the preset time, T0 is the first outdoor temperature, T1 is the second outdoor temperature, T3 is the first indoor temperature, and T4 is the second indoor temperature. The preset time period may be a time period set by the user, for example, when the preset time period is 30 minutes in the future, the calibration function Fz (T, T0, T1, T3, T4) predicts the refrigeration requirement after 30 minutes (i.e. the responsiveness of the indoor temperature to the refrigeration requirement after 30 minutes), and the prediction result is: the current temperature is 30 ℃ and the time is 12:00, then within 30 minutes, the probability of a 5% increase in temperature is 10%, the probability of a 15% increase in temperature is 20%, the probability of a 25% increase in temperature is 23%, and the probability of a 7% decrease in temperature. The predicted result (responsiveness) is the energy consumption difference between the actual refrigeration demand and the original refrigeration demand. Meanwhile, the data predicted by the calibration functions Fz (T, T0, T1, T3, T4) in this embodiment are scattered points, and the error range is determined according to the prediction period and the actual temperature condition, which belongs to a verification database.
In one implementation, when the original refrigeration requirement of the central air conditioner host is adjusted through the calibration function, the embodiment includes the following steps:
step S303, calculating the actual refrigeration requirement of the central air conditioner host based on the calibration function, wherein the actual refrigeration requirement is used for judging the deviation condition between the actual refrigeration temperature and the original refrigeration temperature;
and step S304, the original refrigeration requirement of the central air conditioner host is regulated in real time according to the actual refrigeration requirement.
Specifically, after the actual refrigeration requirement of the central air conditioner host is predicted in advance by the calibration function, the actual temperature deviation can be more accurately known by the central air conditioner host, and the load of the host is adjusted so that the actual refrigeration output just meets the refrigeration requirement, the effect of optimizing the actual output refrigeration capacity is achieved, and unnecessary waste is reduced.
In this embodiment, after the original refrigeration requirement of the central air conditioner host is adjusted in real time according to the actual refrigeration requirement, the energy consumption of the central air conditioner is obviously optimized. Further, the present embodiment will present some data comparison records of "before optimization" and "after optimization", mainly in two cases, one is when the outdoor temperature increases, and the other is when the outdoor temperature decreases, as shown in fig. 3 and 4. Before the original refrigeration requirement is regulated by using the calibration functions Fz (T, T0, T1, T3 and T4), the system takes manually set data as a reference, for example, the water outlet temperature is set to be 8 ℃, and the central air conditioner control system is only used for load shedding when the chilled water temperature reaches or approaches 8 ℃, and the output refrigeration capacity exceeds the actual requirement due to lag in return water temperature feedback. Along with the gradual decrease of the water temperature and the hysteresis, when the refrigeration is lower than the demand, the loading can not be immediately reacted, and the loading is also carried out after a period of time, at the moment, the refrigeration power can be suddenly increased due to insufficient refrigeration, so that the excessive refrigeration demand brings waste.
Further, as can be seen from the values in fig. 3, the total "cooling" requirement of the central air conditioner is: 3+3.1+3.2+3.3+3.3+3.3+3.4+3.5+3.6+3.7+3.8+3.9+3.9+4=49 (1000 KW), the total refrigeration of the central air conditioner "before optimization" is: 4.2+4.2+4.2+4.1+4.1+4+3.9+3.8+3.7+3.6+3.5+4.2+4.3=55.8 (1000 KW), the central air conditioner "after optimization" total refrigeration is: 3.4+3.4+3.5+3.5+3.5+3.5+3.5+3.5+3.5+3.5+3.5+3.5+3.6+4.1+4.1=50.1 (1000 KW). Therefore, the cooling capacity is saved after the optimization compared with the cooling capacity before the optimization: 55.8-50.1=5.7 (1000 KW), the optimization efficiency is: (55.8-50.1)/(55.8=10.215%. Similarly, the optimization efficiency in fig. 4 is calculated as: (58.6-52.6)/(58.6=10.239%). Therefore, after the original refrigeration requirement of the central air conditioner host is regulated in real time through the actual refrigeration requirement, the refrigeration consumption of the central air conditioner is obviously optimized.
In summary, when the embodiment is implemented, first, the embodiment collects original data of a plurality of parameters in a period of time, and stores the original data in an information database, where the plurality of parameters include outdoor temperature, indoor temperature and refrigerating output. And then, constructing a refrigeration demand model according to the original data of the outdoor temperature and the refrigeration output quantity, and calculating the original refrigeration demand of the central air conditioner host based on the refrigeration demand model. And finally, analyzing the responsiveness of the indoor temperature in the information database to the original refrigeration requirement, establishing a calibration function according to the responsiveness, and adjusting the original refrigeration requirement of the central air conditioner host through the calibration function. According to the embodiment, the actual refrigeration requirement is prejudged in advance by establishing the calibration function so as to adjust the original refrigeration requirement of the central air conditioner host, so that the timely feedback of the central air conditioner system on the actual refrigeration requirement is realized, and the waste of refrigeration energy consumption is reduced.
Exemplary apparatus
Based on the above embodiment, the present invention further provides an intelligent energy consumption adjusting device of a central air conditioner, as shown in fig. 5, where the intelligent energy consumption adjusting device of a central air conditioner includes: the system comprises a raw data acquisition module 10, a refrigeration requirement calculation module 20 and a refrigeration requirement adjustment module 30. Specifically, the raw data acquisition module 10 is configured to acquire raw data of a plurality of parameters over a period of time, and store the raw data in an information database, where the plurality of parameters include outdoor temperature, indoor temperature, and cooling output. The refrigeration requirement calculation module 20 is configured to construct a refrigeration requirement model according to the outdoor temperature and the original data of the refrigeration output, and calculate an original refrigeration requirement of the central air conditioner host based on the refrigeration requirement model. The refrigeration requirement adjusting module 30 is configured to analyze the responsiveness of the indoor temperature in the information database to the original refrigeration requirement, establish a calibration function according to the responsiveness, and adjust the original refrigeration requirement of the central air conditioner host according to the calibration function.
In one implementation, the raw data acquisition module 10 includes:
the system comprises an original data acquisition unit, a control unit and a control unit, wherein the original data acquisition unit is used for acquiring original data of a plurality of parameters in a period of time through a wireless communication mode, the plurality of parameters comprise outdoor temperature, indoor temperature and refrigerating output, the outdoor temperature comprises a first outdoor temperature and a second outdoor temperature, and the indoor temperature comprises a first indoor temperature and a second indoor temperature.
The actual numerical analysis unit is used for collecting the original data of each parameter in a period of time and analyzing the actual numerical value of each parameter in a period of time;
and the learning library establishing unit is used for establishing a learning library of each parameter based on the actual numerical value, wherein the learning library of each parameter is stored in the information database.
And the information database updating unit is used for monitoring the original data acquired in each time in real time and updating the original data of the information database in real time.
In one implementation, the refrigeration demand calculation module 20 includes:
the refrigeration demand model construction unit is used for reading the original data of the outdoor temperature and the refrigeration output quantity in the information database, and constructing a refrigeration demand model Fq (T0, T1, Q) based on the original data of the outdoor temperature and the refrigeration output quantity, wherein T0 is the first outdoor temperature, T1 is the second outdoor temperature and Q is the refrigeration output quantity;
and the original refrigeration demand calculation unit is used for calculating the original refrigeration demand of the central air conditioner host based on the refrigeration demand model, wherein the original refrigeration demand comprises original refrigeration power and original refrigeration time.
In one implementation, the refrigeration demand conditioning module 30 includes:
the responsiveness acquisition unit is used for acquiring responsiveness of the indoor temperature in the information database to the refrigeration requirement in a preset time period, wherein the responsiveness is an energy consumption difference between an actual refrigeration requirement and the original refrigeration requirement;
and the calibration function establishing unit is used for establishing a calibration function Fz (T, T0, T1, T3 and T4) according to the responsivity, wherein T is the preset time, T0 is the first outdoor temperature, T1 is the second outdoor temperature, T3 is the first indoor temperature and T4 is the second indoor temperature.
The actual refrigeration demand calculation unit is used for calculating the actual refrigeration demand of the central air conditioner host based on the calibration function, wherein the actual refrigeration demand is used for judging the deviation condition between the actual refrigeration temperature and the original refrigeration temperature;
and the refrigeration demand adjusting unit is used for adjusting the original refrigeration demand of the central air conditioner host in real time according to the actual refrigeration demand.
The working principle of each module in the intelligent energy consumption adjusting device of the central air conditioner in this embodiment is the same as that of each step in the above method embodiment, and will not be described here again.
Based on the above embodiment, the present invention also provides a terminal device, and a schematic block diagram of the terminal device may be shown in fig. 6. The terminal device may comprise one or more processors 100 (only one shown in fig. 6), a memory 101 and a computer program 102 stored in the memory 101 and executable on the one or more processors 100, for example an intelligent regulation program of the energy consumption of a central air conditioner. The one or more processors 100, when executing the computer program 102, may implement the steps of an embodiment of a method for intelligently adjusting energy consumption of a central air conditioner. Alternatively, the one or more processors 100, when executing the computer program 102, may implement the functions of the modules/units in the embodiment of the intelligent energy consumption device for a central air conditioner, which is not limited herein.
In one embodiment, the processor 100 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
In one embodiment, the memory 101 may be an internal storage unit of the electronic device, such as a hard disk or a memory of the electronic device. The memory 101 may also be an external storage device of the electronic device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash card (flash card) or the like, which are provided on the electronic device. Further, the memory 101 may also include both an internal storage unit and an external storage device of the electronic device. The memory 101 is used to store computer programs and other programs and data required by the terminal device. The memory 101 may also be used to temporarily store data that has been output or is to be output.
It will be appreciated by those skilled in the art that the functional block diagram shown in fig. 6 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the terminal device to which the present inventive arrangements are applied, and that a particular terminal device may include more or less components than those shown, or may combine some of the components, or may have a different arrangement of components.
Those skilled in the art will appreciate that implementing all or part of the above-described methods may be accomplished by way of a computer program, which may be stored on a non-transitory computer readable storage medium, that when executed may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, operational database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual operation data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
In summary, the invention discloses an intelligent energy consumption adjusting method and device for a central air conditioner and terminal equipment, wherein the method comprises the following steps: collecting original data of a plurality of parameters in a period of time, and storing the original data into an information database, wherein the plurality of parameters comprise outdoor temperature, indoor temperature and refrigerating output; constructing a refrigeration demand model according to the original data of the outdoor temperature and the refrigeration output quantity, and calculating the original refrigeration demand of a central air conditioner host based on the refrigeration demand model; and analyzing the responsivity of the indoor temperature in the information database to the original refrigeration requirement, establishing a calibration function according to the responsivity, and adjusting the original refrigeration requirement of the central air conditioner host through the calibration function. According to the invention, the actual refrigeration requirement is prejudged in advance by establishing the calibration function so as to adjust the original refrigeration requirement of the central air conditioner host, so that the timely feedback of the central air conditioner system on the actual refrigeration requirement is realized, and the waste of refrigeration energy consumption is reduced.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. An intelligent energy consumption adjusting method of a central air conditioner is characterized by comprising the following steps:
collecting original data of a plurality of parameters in a period of time, and storing the original data into an information database, wherein the plurality of parameters comprise outdoor temperature, indoor temperature and refrigerating output;
constructing a refrigeration demand model according to the outdoor temperature and the original data of the refrigeration output quantity, and calculating the original refrigeration demand of a central air conditioner host based on the refrigeration demand model;
and analyzing the responsivity of the indoor temperature in the information database to the original refrigeration requirement, establishing a calibration function according to the responsivity, and adjusting the original refrigeration requirement of the central air conditioner host through the calibration function.
2. The intelligent energy consumption regulating method of a central air conditioner according to claim 1, wherein the collecting raw data of a plurality of parameters including outdoor temperature, indoor temperature and cooling output for a period of time, storing the raw data in an information database, comprises:
through a mode of wireless communication, raw data of a plurality of parameters including outdoor temperature, indoor temperature and refrigerating output are acquired within a period of time, wherein the outdoor temperature comprises a first outdoor temperature and a second outdoor temperature, and the indoor temperature comprises a first indoor temperature and a second indoor temperature.
3. The intelligent energy consumption regulating method of a central air conditioner according to claim 2, wherein the collecting raw data of a plurality of parameters in a period of time, storing the raw data in an information database, comprises:
collecting the original data of each parameter in a period of time, and analyzing the actual numerical value of each parameter in a period of time;
and establishing a learning library of each parameter based on the actual numerical value, wherein the learning library of each parameter is stored in an information database.
4. The intelligent energy consumption adjusting method of a central air conditioner according to claim 1 or 3, wherein the collecting raw data of a plurality of parameters in a period of time, and storing the raw data in an information database, further comprises:
and monitoring the original data collected in each time in real time, and updating the original data of the information database in real time.
5. The intelligent energy consumption adjusting method of a central air conditioner according to claim 2, wherein the constructing a refrigeration demand model according to the outdoor temperature and the original data of the refrigeration output, and calculating the original refrigeration demand of the central air conditioner host based on the refrigeration demand model, comprises:
reading original data of outdoor temperature and refrigerating output in the information database, and constructing a refrigerating demand model Fq (T0, T1, Q) based on the original data of the outdoor temperature and the refrigerating output, wherein T0 is the first outdoor temperature, T1 is the second outdoor temperature and Q is the refrigerating output;
and calculating the original refrigeration demand of the central air conditioner host based on the refrigeration demand model, wherein the original refrigeration demand comprises original refrigeration power and original refrigeration time.
6. The intelligent energy consumption regulating method of a central air conditioner according to claim 2, wherein said analyzing the responsiveness of the indoor temperature in the information database to the original cooling demand, and establishing a calibration function according to the responsiveness, comprises:
obtaining the responsivity of the indoor temperature in the information database to the refrigeration requirement in a preset time period, wherein the responsivity is the energy consumption difference between the actual refrigeration requirement and the original refrigeration requirement;
and establishing a calibration function Fz (T, T0, T1, T3 and T4) according to the responsivity, wherein T is the preset time, T0 is the first outdoor temperature, T1 is the second outdoor temperature, T3 is the first indoor temperature and T4 is the second indoor temperature.
7. The intelligent energy consumption regulating method of a central air conditioner according to claim 1, wherein said regulating the original cooling demand of the central air conditioner host by the calibration function comprises:
calculating the actual refrigeration requirement of the central air conditioner host based on the calibration function, wherein the actual refrigeration requirement is used for judging the deviation condition between the actual refrigeration temperature and the original refrigeration temperature;
and adjusting the original refrigeration requirement of the central air conditioner host in real time through the actual refrigeration requirement.
8. An intelligent energy consumption adjusting device of a central air conditioner, which is characterized by comprising:
the system comprises an original data acquisition module, a data storage module and a data storage module, wherein the original data acquisition module is used for acquiring original data of a plurality of parameters in a period of time, and storing the original data into an information database, wherein the plurality of parameters comprise outdoor temperature, indoor temperature and refrigerating output;
the refrigeration demand calculation module is used for constructing a refrigeration demand model according to the original data of the outdoor temperature and the refrigeration output quantity, and calculating the original refrigeration demand of the central air conditioner host based on the refrigeration demand model;
and the refrigeration demand adjusting module is used for analyzing the responsiveness of the indoor temperature in the information database to the original refrigeration demand, establishing a calibration function according to the responsiveness, and adjusting the original refrigeration demand of the central air conditioner host through the calibration function.
9. A terminal device, characterized in that the terminal device comprises a memory, a processor and an intelligent regulation program of the energy consumption of a central air conditioner stored in the memory and running on the processor, the processor implementing the steps of the intelligent regulation method of the energy consumption of the central air conditioner according to any one of claims 1-7 when executing the intelligent regulation program of the energy consumption of the central air conditioner.
10. A computer readable storage medium, wherein the computer readable storage medium stores an intelligent energy consumption adjustment program of a central air conditioner, and when the intelligent energy consumption adjustment program of the central air conditioner is executed by a processor, the steps of the intelligent energy consumption adjustment method of the central air conditioner according to any one of claims 1 to 7 are implemented.
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| CN119901064A (en) * | 2025-02-27 | 2025-04-29 | 江森自控日立万宝空调(广州)有限公司 | Refrigeration equipment control method, device, electronic equipment and storage medium |
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| WO2022126950A1 (en) * | 2020-12-14 | 2022-06-23 | 山东建筑大学 | Method and system for controlling demand response of building central air conditioning |
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| CN105371420A (en) * | 2014-09-01 | 2016-03-02 | 阿里巴巴集团控股有限公司 | Refrigeration control method, device and system |
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| WO2022126950A1 (en) * | 2020-12-14 | 2022-06-23 | 山东建筑大学 | Method and system for controlling demand response of building central air conditioning |
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