CN117109158A

CN117109158A - Energy efficiency optimization method and device for air conditioning system

Info

Publication number: CN117109158A
Application number: CN202310982106.5A
Authority: CN
Inventors: 王宝龙; 孟涛; 梁辰吉昱; 林炎顷; 李先庭; 王翠灵; 王文涛; 程俊
Original assignee: Tsinghua University; GD Midea Heating and Ventilating Equipment Co Ltd
Current assignee: Tsinghua University; GD Midea Heating and Ventilating Equipment Co Ltd
Priority date: 2023-08-04
Filing date: 2023-08-04
Publication date: 2023-11-24

Abstract

The application discloses an energy efficiency optimization method and device for an air conditioning system, and belongs to the technical field of air conditioning optimization. The energy efficiency optimization method of the air conditioning system comprises the following steps: acquiring the equipment operation characteristics of an air conditioning system to be optimized and the actual power of each equipment under the target load condition and the target external weather condition; based on the equipment operation characteristics and the actual power, determining an energy efficiency model of the air conditioning system before and after the target equipment is replaced, wherein the energy efficiency model is used for representing the relation between the operation mode of the air conditioning system and the energy efficiency of the system; based on the energy efficiency model, determining the maximum energy efficiency and the corresponding operation mode of the air conditioning system before and after the replacement of the target equipment; and determining an optimization scheme of the air conditioning system based on the maximum energy efficiency of the air conditioning system before and after the target equipment is replaced and the corresponding operation mode. According to the method, at least two optimization schemes with different costs are determined according to the external weather conditions of the air conditioning system, so that the accuracy is higher, and the actual use effect is better.

Description

Energy efficiency optimization method and device for air conditioning system

Technical Field

The application belongs to the technical field of air conditioner optimization, and particularly relates to an energy efficiency optimization method and device of an air conditioner system.

Background

Energy conservation and emission reduction are common knowledge of the current society, the carbon emission of building operation is large, and the air conditioner energy consumption has the largest proportion in the building operation energy consumption, so that energy efficiency optimization of an air conditioner system can effectively realize energy conservation and emission reduction of building operation. The method for optimizing the energy efficiency of the air conditioning system generally provides evaluation indexes under typical working conditions and accumulated working conditions, is only a general optimizing mode, and has limited energy efficiency optimizing and improving effects on specific air conditioning systems.

Disclosure of Invention

The present application aims to solve at least one of the technical problems existing in the prior art. Therefore, the application provides the energy efficiency optimization method and the device for the air conditioning system, which have good energy efficiency optimization effect.

In a first aspect, the present application provides a method for optimizing energy efficiency of an air conditioning system, the method comprising:

acquiring the equipment operation characteristics of an air conditioning system to be optimized and the actual power of each equipment under the target load condition and the target external weather condition, wherein the equipment operation characteristics of the target equipment to be replaced in the air conditioning system comprise the first equipment operation characteristics before replacement and the second equipment operation characteristics after replacement;

Based on the equipment operation characteristics and the actual power, determining an energy efficiency model of the air conditioning system before and after the target equipment is replaced, wherein the energy efficiency model is used for representing the relation between the operation mode of the air conditioning system and the system energy efficiency;

based on the energy efficiency model, determining the maximum energy efficiency and the corresponding operation mode of the air conditioning system before and after replacing target equipment;

and determining an optimization scheme of the air conditioning system based on the maximum energy efficiency of the air conditioning system before and after the target equipment is replaced and the corresponding operation mode.

According to the energy efficiency optimization method of the air conditioning system, at least two optimization schemes with different costs are determined according to the external weather conditions of the place where the air conditioning system is located, so that the accuracy is higher, and the actual use effect is better.

According to one embodiment of the present application, the determining an energy efficiency model of the air conditioning system before and after replacing a target device based on the device operation characteristics and the actual power includes:

determining a sub-model corresponding to each device of the air conditioning system based on the device operation characteristics and the actual power;

and adjusting the value of the target setting parameter based on the matching relation between the target output of the sub-model corresponding to each device of the air conditioning system and the target setting parameter, and determining the energy efficiency model of the air conditioning system.

According to one embodiment of the present application, the air conditioning system includes: a surface cooler, a chiller, a freeze pump connected between the surface cooler and the chiller, a cooling tower, and a cooling pump connected between the chiller and the cooling tower; the target load condition comprises a target air inlet parameter and a target air supply temperature;

the method for determining the energy efficiency model of the air conditioning system based on the matching relation between the target output of the sub-model corresponding to each device of the air conditioning system and the target setting parameter adjusts the value of the target setting parameter comprises the following steps:

inputting the target load condition and the target external meteorological condition into a first sub-model to obtain the chilled water flow m output by the first sub-model _w,chilled Cooling water flow m _w,cool Power W of freeze pump _pump,chilled And cooling pump power W _pump,cool The method comprises the steps of carrying out a first treatment on the surface of the The first sub-model is used for representing the characteristics of a pipe network and a pump in the air conditioning system;

setting the target air inlet parameter and the set return water temperature t of the cooling water _cool,in And cooling water flow m output by the first submodel _w,cool Inputting into a second sub-model to obtain the cooling water supply temperature t output by the second sub-model _cool,out And cooling tower power W _tower The method comprises the steps of carrying out a first treatment on the surface of the Wherein the second sub-model is used to characterize the cooling tower;

The target air inlet parameter and the set chilled water supply temperature t _chilled,in And the flow rate m of the frozen water output by the first submodel _w,chilled Inputting the temperature t of the returned chilled water to a third sub-model to obtain the temperature t of the returned chilled water output by the third sub-model _chilled,out And supply air temperature t _a,out' The method comprises the steps of carrying out a first treatment on the surface of the Wherein the third sub-model is used to characterize the characteristics of the surface cooler; the set chilled water supply temperature t _chilled,in The air supply temperature t output by the third sub-model _a,out' Matching with the target air supply temperature;

the air supply temperature t output by the third sub-model _a,out' When the water supply temperature matches the target air supply temperature, the set chilled water supply temperature t _chilled,in The flow m of the frozen water output by the first submodel _w,chilled And cooling water flow rate m _w,cool The cooling water supply temperature t output by the second sub-model _cool,out And the return water temperature t of the chilled water output by the third sub-model _chilled,out Inputting the temperature t of the cooling water returned by the fourth sub-model into the fourth sub-model to obtain the temperature t of the cooling water returned by the fourth sub-model _cool,in' Power W of cooler _chilled And an evaporation load Q _e The method comprises the steps of carrying out a first treatment on the surface of the Wherein,the fourth sub-model is used for representing the characteristics of the chiller; the set backwater temperature t of the cooling water _cool,in The return water temperature t of the cooling water output by the fourth sub-model _cool,in' And the set return water temperature t of the cooling water _cool,in Matching condition adjustment of (2);

the return water temperature t of the cooling water output by the fourth sub-model _cool,in' And the set return water temperature t of the cooling water _cool,in Under the condition of matching, determining the air conditioning system energy efficiency model; wherein the first submodel outputs the refrigerating pump power W _pump,chilled And cooling pump power W _pump,cool Cooling tower power W output by second sub-model _tower The cold machine power W output by the fourth sub-model _chilled And an evaporation load Q _e For determining an energy efficiency of the air conditioning system.

According to one embodiment of the application, the chilled water supply temperature t is set _chilled,in The flow m of the frozen water output by the first submodel _w,chilled And cooling water flow rate m _w,cool The cooling water supply temperature t output by the second sub-model _cool,out And the return water temperature t of the chilled water output by the third sub-model _chilled,out Inputting the temperature t of the cooling water returned by the fourth sub-model into the fourth sub-model to obtain the temperature t of the cooling water returned by the fourth sub-model _cool,in' Power W of cooler _chilled And an evaporation load Q _e Comprising:

the set chilled water supply temperature t _chilled,in The flow rate m of the refrigerating water output by the first submodel _w,chilled And the return water temperature t of the chilled water output by the third sub-model _chilled,out Inputting the temperature of the vapor to an evaporator model to obtain the evaporation temperature t output by the evaporator model _e Condensation temperature t _c And an evaporation load Q _e ；

The evaporation temperature t output by the evaporator model _e And condensation temperature t _c Inputting the power W into a compressor model to obtain the cold machine power W output by the compressor model _chilled And condensing load Q _c ；

Flow of cooling water m _w,cool The cooling water supply temperature t output by the second sub-model _cool,out And the condensing load Q output by the evaporator model _c Inputting the temperature t of the returned cooling water into a condenser model to obtain the temperature t of the returned cooling water output by the condenser model _cool,in '。

According to an embodiment of the present application, the energy efficiency optimization method of an air conditioning system further includes:

updating the system form of the air conditioning system to be optimized;

acquiring the equipment operation characteristics of the updated air conditioning system;

determining an energy efficiency model of the updated air conditioning system based on the updated equipment operating characteristics of the air conditioning system;

and determining the maximum energy efficiency and the corresponding operation mode of the updated air conditioning system based on the energy efficiency model of the updated air conditioning system, wherein the maximum energy efficiency and the corresponding operation mode of the updated air conditioning system are used for determining an optimization scheme of the air conditioning system.

According to one embodiment of the present application, the determining, based on the energy efficiency model, a maximum energy efficiency and a corresponding operation mode of the air conditioning system before and after the replacement of the target device includes:

Determining the energy efficiency of the air conditioning system in each operation mode before the target equipment is replaced based on the energy efficiency model of the air conditioning system before the target equipment is replaced;

based on the energy efficiency in each operation mode, obtaining the maximum energy efficiency of the air conditioning system before replacing the target equipment and the corresponding operation mode;

determining the energy efficiency of the air conditioning system in each operation mode after the target equipment is replaced based on the energy efficiency model of the air conditioning system after the target equipment is replaced;

and obtaining the maximum energy efficiency of the air conditioning system after the target equipment is replaced and the corresponding operation mode based on the energy efficiency in each operation mode.

In a second aspect, the present application provides an energy efficiency optimizing apparatus for an air conditioning system, the apparatus comprising:

the device comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for acquiring the device operation characteristics of an air conditioning system to be optimized and the actual power of each device under the target load condition and the target external weather condition, and the device operation characteristics of the target device to be replaced in the air conditioning system comprise a first device operation characteristic before replacement and a second device operation characteristic after replacement;

the first processing module is used for determining an energy efficiency model of the air conditioning system before and after replacing target equipment based on the equipment operation characteristics and the actual power, wherein the energy efficiency model is used for representing the relation between an operation mode of the air conditioning system and system energy efficiency;

The second processing module is used for determining the maximum energy efficiency and the corresponding operation mode of the air conditioning system before and after the replacement of the target equipment based on the energy efficiency model;

and the third processing module is used for determining an optimization scheme of the air conditioning system based on the maximum energy efficiency of the air conditioning system before and after the target equipment is replaced and the corresponding operation mode.

According to the energy efficiency optimizing device of the air conditioning system, at least two optimizing schemes with different costs are determined according to the external weather conditions of the place where the air conditioning system is located, so that the accuracy is higher, and the actual using effect is better.

In a third aspect, the present application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the energy efficiency optimization method of the air conditioning system according to the first aspect when executing the computer program.

In a fourth aspect, the present application provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the energy efficiency optimization method of an air conditioning system according to the first aspect described above.

In a fifth aspect, the present application provides a chip, the chip including a processor and a communication interface, the communication interface and the processor being coupled, the processor being configured to execute a program or instructions to implement the energy efficiency optimization method of the air conditioning system according to the first aspect.

In a sixth aspect, the present application provides a computer program product comprising a computer program which, when executed by a processor, implements a method for optimizing the energy efficiency of an air conditioning system according to the first aspect described above.

Additional aspects and advantages of the application 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 application.

Drawings

The foregoing and/or additional aspects and advantages of the application will become apparent and may be better understood from the following description of embodiments taken in conjunction with the accompanying drawings in which:

FIG. 1 is a schematic flow chart of an energy efficiency optimization method for an air conditioning system according to an embodiment of the present application;

FIG. 2 is a second flow chart of an energy efficiency optimization method for an air conditioning system according to an embodiment of the present application;

FIG. 3 is a third flow chart of an energy efficiency optimization method for an air conditioning system according to an embodiment of the present application;

FIG. 4 is a flow chart of an energy efficiency optimization method for an air conditioning system according to an embodiment of the present application;

FIG. 5 is a flowchart of an energy efficiency optimization method for an air conditioning system according to an embodiment of the present application;

FIG. 6 is a schematic diagram of an air conditioning system according to an embodiment of the present application;

FIG. 7 is a second schematic diagram of an air conditioning system according to an embodiment of the present application;

FIG. 8 is a schematic diagram showing the comparison of the optimizing effect of the energy efficiency optimizing method of the air conditioning system according to the embodiment of the present application;

fig. 9 is a schematic structural diagram of an energy efficiency optimizing device of an air conditioning system according to an embodiment of the present application;

fig. 10 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

The technical solutions of the embodiments of the present application will be clearly described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which are obtained by a person skilled in the art based on the embodiments of the present application, fall within the scope of protection of the present application.

The terms first, second and the like in the description and in the claims, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged, as appropriate, such that embodiments of the present application may be implemented in sequences other than those illustrated or described herein, and that the objects identified by "first," "second," etc. are generally of a type, and are not limited to the number of objects, such as the first object may be one or more. Furthermore, in the description and claims, "and/or" means at least one of the connected objects, and the character "/", generally means that the associated object is an "or" relationship.

In the related art, there are two ways to optimize the energy efficiency of the air conditioning system:

firstly, digitally modeling is carried out aiming at the characteristics of an air conditioning system, then the energy efficiency level of the optimized system control strategy under the given working condition is predicted, and a suggestion is given to the system control method. However, this approach has limited energy efficiency improvement space for optimizing only the control method;

secondly, according to the performance of the equipment used in the actual measurement data evaluation system, the equipment is subjected to model selection optimization, so that the performance of the equipment is improved, and the operation energy efficiency of the system is improved. However, this approach only considers the device's own performance, not from the global perspective of the air conditioning system, and it is difficult to evaluate the actual extraction effect.

In addition, the two modes are not combined with local weather conditions of the building and heat and wet load characteristics of the building, so that the energy efficiency optimization and lifting effect is limited.

The energy efficiency optimization method of the air conditioning system, the energy efficiency optimization device of the air conditioning system, the electronic equipment and the readable storage medium provided by the embodiment of the application are described in detail below through specific embodiments and application scenes thereof with reference to the accompanying drawings.

The execution main body of the energy efficiency optimization method of the air conditioning system provided by the embodiment of the application can be electronic equipment or a functional module or a functional entity in the electronic equipment, wherein the electronic equipment comprises, but is not limited to, a mobile phone, a tablet personal computer, a camera, a wearable device and the like.

As shown in fig. 1, the energy efficiency optimization method of the air conditioning system includes: step 110, step 120 and step 130.

Step 110, acquiring the equipment operation characteristics of an air conditioning system to be optimized and the actual power of each equipment under the target load condition and the target external weather condition;

the equipment operation characteristics of the target equipment to be replaced in the air conditioning system comprise a first equipment operation characteristic before replacement and a second equipment operation characteristic after replacement;

an air conditioning system includes a plurality of devices whose device operating characteristics affect the operating energy efficiency of the overall air conditioning system.

In the embodiment shown in fig. 6, the air conditioning system includes: the surface cooler 610, the blower 620, the first freezing pump 631, the second freezing pump 632, the first cooler 641, the second cooler 642, the first cooling pump 651, the second cooling pump 652, the first cooling tower 661, and the second cooling tower 662.

The return air and the fresh air are converged to an air supply pipe, the surface cooler 610 is arranged in the air supply pipe, and an air feeder 620 is also arranged in the air supply pipe.

The surface cooler 610 is connected to the evaporators of the first cooler 641 and the second cooler 642 through a pipe, the first freezing pump 631 and the second freezing pump 632 are connected in parallel, the evaporators of the first cooler 641 and the second cooler 642 are connected in parallel, the condensers of the first cooler 641 and the second cooler 642 are connected to the first cooling tower 661 and the second cooling tower 662 which are connected in parallel through a pipe, and the first cooling pump 651 and the second cooling pump 652 are connected in parallel.

The equipment operation characteristics are used for representing the characteristics related to heat exchange of the equipment, such as the chilled water supply temperature and chilled water flow rate of the surface cooler, the cooling backwater temperature of the cooling tower and the cooling water flow rate; pump head and flow; differential pressure and resistance of the pipe network; chilled water supply temperature, chilled water return temperature, cooling water supply temperature, cooling water return temperature and the like of the water chiller.

The target external weather conditions comprise outdoor environment parameters including outdoor dry bulb temperature and outdoor wet bulb temperature, the target load conditions of the air conditioning system comprise air inlet parameters and air supply parameters, and the air inlet parameters can comprise air inlet temperature and air inlet humidity; the air supply parameters may include air supply temperature and air supply humidity.

In this step, the obtained actual power of each device under the target load condition and the target external weather condition is used to verify the accuracy of the model determined in the subsequent step.

Step 120, determining an energy efficiency model of the air conditioning system before and after replacing the target equipment based on the equipment operation characteristics and the actual power, wherein the energy efficiency model is used for representing the relation between the operation mode of the air conditioning system and the energy efficiency of the system;

the operation mode includes the operation states of the respective devices, and by way of example of the embodiment shown in fig. 6, the flow rate of the refrigerating fluid can be adjusted by adjusting the on-off states of the first and second refrigerating pumps 631 and 632, the temperature of the refrigerating fluid can be adjusted by adjusting the on-off states of the first and second refrigerating machines 641 and 642, the temperature of the cooling fluid can be adjusted by adjusting the on-off states of the first and second cooling pumps 651 and 652, and the temperature of the cooling fluid can be adjusted by adjusting the on-off states of the first and second cooling towers 661 and 662.

For different operation modes of the air conditioning system, the on-off states of the equipment are different, and therefore different system energy efficiency is achieved.

In the step, an energy efficiency model of the air conditioning system before the target equipment is replaced can be determined, and the operation mode information of the air conditioning system is input into the energy efficiency model, so that the system energy efficiency output by the energy efficiency model can be obtained;

in the step, an energy efficiency model of the air conditioning system after the target equipment is replaced can be determined, and the operation mode information of the air conditioning system is input into the energy efficiency model, so that the system energy efficiency output by the energy efficiency model can be obtained. The target device can be relatively poor-performance device in the air conditioning system, or the cost of the device is considered, and the target device can be comprehensively determined to be the target device which can be replaced and optimized.

Because the actual power is used for detecting the accuracy of the model and adjusting the model in the step, the accuracy of the energy efficiency model is higher in consideration of the local meteorological conditions of the building in the resume process of the model.

In actual execution, a mathematical model can be constructed on the basis of the equipment operating characteristics in the heat exchange principle; or training an energy efficiency model through a deep neural network, wherein a training sample is an operation mode of the air conditioning system, and a sample label is actual power.

Step 130, determining the maximum energy efficiency and the corresponding operation mode of the air conditioning system before and after replacing the target equipment based on the energy efficiency model;

using the energy efficiency model determined in step 130 before the target device is replaced, a maximum energy efficiency and a corresponding operation mode can be obtained, and the maximum energy efficiency is compared with the initial energy efficiency, so that the energy efficiency improvement potential caused by the operation mode optimization can be determined.

Using the energy efficiency model determined in step 130 after the target device is replaced, a maximum energy efficiency and a corresponding operation mode can be obtained, and comparing the maximum energy efficiency with the initial energy efficiency, thereby determining the energy efficiency improvement potential caused by the device optimization and the operation mode optimization.

And 140, determining an optimization scheme of the air conditioning system based on the maximum energy efficiency of the air conditioning system before and after the replacement of the target equipment and the corresponding operation mode.

After determining the maximum energy efficiency and the corresponding operation mode before replacing the target device, the energy efficiency improvement potential brought by the operation mode optimization can be obtained, and the energy efficiency improvement potential is used for representing the improvement condition of the maximum energy efficiency and the initial energy efficiency, for example:

operation mode optimization energy efficiency boost potential = maximum energy efficiency/initial energy efficiency before replacement of target device-1.

After determining the maximum energy efficiency and the corresponding operation mode after replacing the target device, the energy efficiency improvement potential brought by the device optimization can be obtained, for example:

device optimization energy efficiency boost potential = maximum energy efficiency after target device replacement/maximum energy efficiency before target device replacement-1.

Based on the potential, the optimization cost is comprehensively considered, and then the optimization scheme can be determined.

For example, the maximum energy efficiency after the target equipment is replaced is greater than the cost of the target equipment before the target equipment is replaced, so that the optimal scheme of the air conditioning system can be determined to be the target equipment, and the operation mode of the air conditioning system is determined to be the operation mode corresponding to the maximum energy efficiency.

In other words, the energy efficiency optimization method of the air conditioning system gives at least two levels of optimization modes: the cost of operation mode optimization is low, and the operation mode optimization can be realized without more transformation cost; the cost of equipment optimization is relatively high, a certain degree of equipment acquisition cost and construction transformation cost are required to be input, and corresponding energy efficiency is improved. And the optimization modes are determined according to the external weather conditions of the place where the air conditioning system is located, so that the method is more in line with the actual situation of the air conditioning system.

These two optimization schemes can be used as alternatives for the user to choose according to the economical situation or other factors.

According to the energy efficiency optimization method of the air conditioning system, provided by the embodiment of the application, at least two optimization schemes with different costs are determined according to the external weather conditions of the place where the air conditioning system is located, so that the accuracy is higher, and the actual use effect is better.

In some embodiments, step 120, determining an energy efficiency model of the air conditioning system before and after the replacement of the target device based on the device operating characteristics and the actual power, includes:

determining a sub-model corresponding to each device of the air conditioning system based on the device operating characteristics and the actual power;

It should be noted that, the manner of determining the corresponding energy efficiency model before and after the replacement of the target device in the air conditioning system may be the same, and only the sub-model corresponding to the target device needs to be adjusted.

The equipment related to heat exchange medium circulation of the air conditioning system can affect the energy efficiency of the air conditioning system, and based on the heat exchange principle or the fluid circulation principle, a sub-model of each equipment is built based on the operation characteristics of the equipment, and the actual power is used for adjusting the parameters of the sub-model.

And associating the sub-models to represent the actual connection relation of the devices in the air conditioning system.

The output of some of the sub-models between the sub-models is used as the input of other sub-models, and when the values of the target setting parameters need to be set, the set values are also used as the input of some of the sub-models, but the other sub-models also output the values, and the set values of certain parameters are compared with the output values, so that the energy efficiency model can be iterated.

The target setting parameters may be a cooling water return temperature and a chilled water supply temperature.

For example, the cooling tower needs to cool the input cooling water, the submodel corresponding to the cooling tower can input the set cooling water backwater temperature, the cooling water output by the condenser of the cooling machine is input to the cooling tower, the submodel corresponding to the cooling machine can output the cooling water backwater temperature to be compared with the set cooling water backwater temperature, and whether the correction of the energy efficiency model reaches the standard can be determined.

By setting the submodel and comparing the output value of the submodel with the set value according to the target setting parameters, the energy efficiency model can be quickly and accurately obtained, and the dependent calculation force of the whole process is small.

In some embodiments, as shown in fig. 6, the surface cooler 610, the chiller, the cryopump connected between the surface cooler 610 and the chiller, the cooling tower, and the cooling pump connected between the chiller and the cooling tower, wherein the chiller is two, including a first chiller 641 and a second chiller 642; the two freezing pumps comprise a first freezing pump 631 and a second freezing pump 632; the number of the cooling towers is two, and the two cooling towers comprise a first cooling tower 661 and a second cooling tower 662; the cooling pumps are two, including a first cooling pump 651 and a second cooling pump 652.

The target load condition comprises a target air inlet parameter and a target air supply parameter, the target air inlet parameter comprises a target air inlet temperature and a target air inlet humidity, and the target air supply parameter comprises a target air supply temperature and a target air supply humidity.

The following models are built under the target load conditions, so that the energy efficiency optimization method meets the actual operation requirements of the air conditioning system.

Adjusting the value of a target setting parameter based on the matching relation between the target output of the sub-model corresponding to each device of the air conditioning system and the target setting parameter, and determining an energy efficiency model of the air conditioning system, wherein the method comprises the following steps:

inputting the target load condition and the target external weather condition into a first sub-model to obtain the chilled water flow m output by the first sub-model _w,chilled Cooling water flow m _w,cool Power W of freeze pump _pump,chilled And cooling pump power W _pump,cool The method comprises the steps of carrying out a first treatment on the surface of the The first sub-model is used for representing the characteristics of a pipe network and a pump in the air conditioning system;

the target air inlet parameter and the set backwater temperature t of the cooling water _cool,in And cooling water flow m output by the first submodel _w,cool Inputting the cooling water into the second sub-model to obtain the cooling water supply temperature t output by the second sub-model _cool,out And cooling tower power W _tower The method comprises the steps of carrying out a first treatment on the surface of the Wherein the second sub-model is used to characterize the cooling tower;

the target air inlet parameter and the set chilled water supply temperature t _chilled,in And the flow rate m of the frozen water output by the first submodel _w,chilled Inputting the temperature t of the returned chilled water output by the third sub-model into the third sub-model _chilled,out And feedingWind temperature t _a,out' The method comprises the steps of carrying out a first treatment on the surface of the Wherein the third sub-model is used for characterizing the characteristics of the surface cooler; set chilled water supply temperature t _chilled,in Air supply temperature t output through third sub-model _a,out' And the target air supply temperature t _a,out Matching condition adjustment of (2);

the air supply temperature t output by the third sub-model _a,out' When the water supply temperature matches the target air supply temperature, the set chilled water supply temperature t _chilled,in The flow m of the frozen water output by the first submodel _w,chilled And cooling water flow rate m _w,cool The cooling water supply temperature t output by the second sub-model _cool,out And the return water temperature t of the chilled water output by the third sub-model _chilled,out Inputting the temperature t of the cooling water returned by the fourth sub-model into the fourth sub-model to obtain the temperature t of the cooling water returned by the fourth sub-model _cool,in' Power W of cooler _chilled And an evaporation load Q _e The method comprises the steps of carrying out a first treatment on the surface of the The fourth sub-model is used for representing the characteristics of the cooling machine; the set backwater temperature t of the cooling water _cool,in The return water temperature t of the cooling water output by the fourth sub-model _cool,in' And the set backwater temperature t of the cooling water _cool,in Matching condition adjustment of (2);

the return water temperature t of the cooling water output by the fourth sub-model _cool,in' And the set backwater temperature t of the cooling water _cool,in Under the condition of matching, determining an energy efficiency model of the air conditioning system; wherein the freezing pump power W output by the first submodel _pump,chilled And cooling pump power W _pump,cool Cooling tower power W output by second sub-model _tower Cold machine power W output by fourth sub-model _chilled And an evaporation load Q _e For determining the energy efficiency of the air conditioning system.

It will be appreciated that based on the structure of the air conditioning system, the energy efficiency model is divided into a plurality of sub-models, the first sub-model being used to characterize the characteristics of the pipe network and the pump in the air conditioning system, the second sub-model being used to characterize the characteristics of the cooling tower, the third sub-model being used to characterize the characteristics of the surface air cooler, and the fourth sub-model being used to characterize the characteristics of the chiller.

The air supply temperature t output by the third sub-model _a,out' With the target air supply temperatureDegree t _a,out In case of mismatch, readjusting the set chilled water supply temperature t _chilled,in Up to the air supply temperature t output by the third sub-model _a,out' And the target air supply temperature t _a,out And matching, so that the accuracy of the energy efficiency model is higher.

Judging the air supply temperature t output by the third sub-model _a,out' And the target air supply temperature t _a,out There are several ways to match the degree of (c): for example, using subtraction, at |t _a,out' -t _a,out Under the condition that the temperature is less than or equal to a, determining the air supply temperature t output by the third sub-model _a,out' And the target air supply temperature t _a,out Matching at |t _a,out' -t _a,out In the case of < a >, the air supply temperature t output by the third sub-model is determined _a,out' And the target air supply temperature t _a,out Mismatch, a is a threshold; or by division |t _a,out' /t _a,out Determining the air supply temperature t output by the third sub-model under the condition that the temperature is less than or equal to 1 ℃ and less than or equal to b _a,out' And the target air supply temperature t _a,out Matching at |t _a,out' /t _a,out -determining the supply air temperature t output by the third sub-model in the case of-1| > b _a,out' And the target air supply temperature t _a,out Mismatch, b is the threshold.

The return water temperature t of the cooling water output by the fourth sub-model _cool,in' And the set backwater temperature t of the cooling water _cool,in Under the condition of mismatch, readjusting the set backwater temperature t of the cooling water _cool,in Until the return water temperature t of the cooling water output by the fourth sub-model _cool,in' And the set backwater temperature t of the cooling water _cool,in And matching, so that the accuracy of the energy efficiency model is higher.

Judging the return water temperature t of cooling water output by the fourth sub-model _cool,in' And the set backwater temperature t of the cooling water _cool,in There are several ways to match the degree of (c): for example, using subtraction, at |t _cool,in' -t _cool,in Under the condition that the temperature is less than or equal to c, determining the return water temperature t of the cooling water output by the fourth sub-model _cool,in' And the set backwater temperature t of the cooling water _cool,in Matching at |t _cool,in' -t _cool,in |＞c, determining the return water temperature t of the cooling water output by the fourth sub-model _cool,in' And the set backwater temperature t of the cooling water _cool,in Mismatch, c is a threshold; or by division |t _cool,in' /t _cool,in Determining the return water temperature t of the cooling water output by the fourth sub-model under the condition that d is less than or equal to 1% _cool,in' And the set backwater temperature t of the cooling water _cool,in Matching at |t _cool,in' /t _cool,in Under the condition that-1| > d, determining the return water temperature t of the cooling water output by the fourth sub-model _cool,in' And the set backwater temperature t of the cooling water _cool,in Mismatch, d is the threshold.

The construction method of the model is simple in iterative calculation and high in accuracy, so that the finally determined optimization scheme is more in line with the actual situation.

In some embodiments, the above steps, the chilled water supply temperature t will be set _chilled,in The flow m of the frozen water output by the first submodel _w,chilled And cooling water flow rate m _w,cool The cooling water supply temperature t output by the second sub-model _cool,out And the return water temperature t of the chilled water output by the third sub-model _chilled,out Inputting the temperature t of the cooling water returned by the fourth sub-model into the fourth sub-model to obtain the temperature t of the cooling water returned by the fourth sub-model _cool,in' Power W of cooler _chilled And an evaporation load Q _e Comprising:

the set chilled water supply temperature t _chilled,in The flow m of the frozen water output by the first submodel _w,chilled And the return water temperature t of the chilled water output by the third sub-model _chilled,out Input into the evaporator model to obtain the evaporation temperature t output by the evaporator model _e Condensation temperature t _c And an evaporation load Q _e ；

The evaporation temperature t output by the evaporator model _e And condensation temperature t _c Input to the compressor model to obtain the cold machine power W output by the compressor model _chilled And condensing load Q _c ；

Flow of cooling water m _w,cool The cooling water supply temperature t output by the second sub-model _cool,out And evaporator dieCondensation load Q of output _c Inputting the temperature t of the cooling water returned by the condenser model into the condenser model to obtain the temperature t of the cooling water returned by the condenser model _cool,in' 。

It will be appreciated that the chiller includes an evaporator connected to a surface chiller and a condenser connected to a cooling tower, and that the above embodiment subdivides the fourth sub-model for characterizing the chiller into an evaporator model, a compressor model and a condenser model, such that the accuracy of the fourth sub-model is higher and modeling is simpler.

In some embodiments, step 130, determining a maximum energy efficiency and a corresponding operation mode of the air conditioning system before and after the replacement of the target device based on the energy efficiency model, includes:

based on the energy efficiency of each operation mode, obtaining the maximum energy efficiency of the air conditioning system before replacing the target equipment and the corresponding operation mode;

In other words, before and after the target device is replaced, the energy efficiency in each operation mode can be determined one by one in an exhaustive manner, and then the maximum energy efficiency and the corresponding operation mode are obtained.

For example, for the air conditioning system shown in fig. 6, there are 2 cryopumps, 2 chillers, 2 cooling pumps, and 2 cooling towers, so that there are 16 operation modes in total theoretically, and the 16 operation modes are input to the energy efficiency model one by one, so that the corresponding energy efficiency can be obtained.

In some embodiments, the energy efficiency optimization method of the air conditioning system may further include:

Updating a system form of an air conditioning system to be optimized;

and determining the maximum energy efficiency and the corresponding operation mode of the updated air conditioning system based on the updated energy efficiency model of the air conditioning system, wherein the maximum energy efficiency and the corresponding operation mode of the updated air conditioning system are used for determining an optimization scheme of the air conditioning system.

In other words, in this embodiment, the system form needs to be re-designed and the device model needs to be selected, and then the corresponding energy efficiency model is obtained in the same manner as before, and then the maximum energy efficiency and the corresponding operation mode are obtained.

For example, the air conditioning system in fig. 6 is in the form of a primary air return system, after all fresh air and return air loads are mixed, the cold water with the lowest temperature is treated, and the energy efficiency of the chiller is limited; the system form is redesigned, as shown in fig. 7, the loads of fresh air and return air are treated by high-temperature, medium-temperature and low-temperature cold water with different temperatures in consideration of different grades of the system loads, the energy efficiency model of the updated air conditioning system is redetermined, and the maximum energy efficiency and the corresponding operation mode of the updated air conditioning system are determined based on the energy efficiency model, so that the energy efficiency of the system can be obviously improved.

System optimization energy efficiency boost potential = maximum energy efficiency of updated air conditioning system/maximum energy efficiency before target device replacement-1.

The energy efficiency optimization method of the air conditioning system provided by the embodiment of the application gives the energy efficiency potential values of three layers (operation mode optimization, equipment optimization and system optimization) of the air conditioning system, can evaluate the operation energy efficiency condition of the air conditioning system according to the meteorological parameters and the load characteristics under the actual working condition, and indicates the direction and the potential of the energy efficiency improvement of each link of the air conditioning system.

The improvement degree of three levels (operation mode optimization, equipment optimization and system optimization) is easy to achieve and difficult, namely the operation mode optimization can be realized (the energy efficiency improvement degree is smaller) without adding more transformation cost; equipment optimization requires a certain degree of equipment acquisition cost and construction transformation cost, and corresponding energy efficiency improvement (the energy efficiency improvement degree is larger) is realized; the system optimization gives out the ideal state (maximum energy efficiency improvement degree) of the system energy efficiency under the same using building object and using environment as a reference.

An energy efficiency optimization method for an air conditioning system according to an embodiment of the present application is described below with reference to fig. 2 to 8.

As shown in fig. 6, the air conditioning system is a primary return air system, and includes: the surface cooler 610, the blower 620, the first freezing pump 631, the second freezing pump 632, the first cooler 641, the second cooler 642, the first cooling pump 651, the second cooling pump 652, the first cooling tower 661, and the second cooling tower 662.

The number of the intercoolers, the freezing pumps, the cooling pumps and the cooling towers in the air conditioning system is 2. The chilled water system is a primary pump system and is supplied to each end device via a water separator.

Table 1 shows the energy efficiency optimization direction of the air conditioning system.

TABLE 1

Table 2 shows an initial operation mode and initial energy efficiency of the air conditioning system.

TABLE 2

In this operation mode, the number of operation of the chiller was 1, and the number of operation of the cooling tower, the number of operation of the cooling pump, and the number of operation of the cryopump were all 2. The actual operating parameters of the air conditioning system and the energy consumption of each device are shown in table 2. Under the working condition, the total power consumption of the system is 124797W, the load is 419328W, and the energy efficiency of the system is 3.36.

As shown in fig. 2, the air conditioning system form is digitally modeled to predict the energy efficiency of the system in a certain mode of operation.

As shown in fig. 2, the energy efficiency optimization method of the air conditioning system includes: step 201-step 214.

Step 201, describing the characteristics of each link device;

including the characteristics of a surface cooler, a cooling tower, a cooler, a water pump and a pipe network.

Step 202, inputting parameters of an operation mode;

including ambient weather conditions, load conditions of the surface chiller, and the number of equipment runs (modes of operation). The external weather conditions include outdoor dry bulb temperature and outdoor wet bulb temperature; the load conditions of the surface cooler comprise an air inlet parameter and an air supply parameter.

203, freezing water, a pipe network of cooling water and a water pump model;

in the step, the target load condition and the target external weather condition are input into a first sub-model to obtain the flow m of the refrigerating water output by the first sub-model _w,chilled Cooling water flow m _w,cool Power W of freeze pump _pump,chilled And cooling pump power W _pump,cool The method comprises the steps of carrying out a first treatment on the surface of the Wherein the first sub-model is used to characterize the pipe network and pump characteristics in the air conditioning system.

Step 204, assuming the return water temperature of the cooling water;

the return water temperature of the cooling water is set firstly, so that the operation of the subsequent second sub-model is facilitated.

Step 205, cooling tower model;

in the step, the target air inlet parameter and the set backwater temperature t of the cooling water are adopted _cool,in And cooling water flow m output by the first submodel _w,cool Inputting the cooling water into the second sub-model to obtain the cooling water supply temperature t output by the second sub-model _cool,out And cooling tower power W _tower The method comprises the steps of carrying out a first treatment on the surface of the Wherein the second sub-model is used to characterize the cooling tower.

Step 206, assuming chilled water supply temperature;

the water supply temperature of the chilled water is set firstly, so that the operation of the third sub-model and the fourth sub-model is convenient to follow.

Step 207, a surface cooler model;

in the step, the target air inlet parameter and the set chilled water supply temperature t _chilled,in And the flow rate m of the frozen water output by the first submodel _w,chilled Inputting the temperature t of the returned chilled water output by the third sub-model into the third sub-model _chilled,out And supply air temperature t _a,out' The method comprises the steps of carrying out a first treatment on the surface of the Wherein the third sub-model is used to characterize the surface cooler.

Step 208, judging the matching performance of the air supply temperature;

The air supply temperature t output by the third sub-model _a,out' About equal to the target supply air temperature t _a,out If so, go to step 209, otherwise go back to step 206 to adjust the set chilled water supply temperature t _chilled,in 。

Step 209, an evaporator model;

in this step, the set chilled water supply temperature t _chilled,in The flow m of the frozen water output by the first submodel _w,chilled And the return water temperature t of the chilled water output by the third sub-model _chilled,out Input into the evaporator model to obtain the evaporation temperature t output by the evaporator model _e Condensation temperature t _c And an evaporation load Q _e 。

Step 210, a compressor model;

in this step, the evaporation temperature t outputted from the evaporator model _e And condensation temperature t _c Input to the compressor model to obtain a compressor modelOutput cold machine power W _chilled And condensing load Q _c 。

Step 211, a condenser model;

in this step, the cooling water flow rate m _w,cool The cooling water supply temperature t output by the second sub-model _cool,out And condensing load Q output by evaporator model _c Inputting the temperature t of the cooling water returned by the condenser model into the condenser model to obtain the temperature t of the cooling water returned by the condenser model _cool,in' 。

212, judging the matching property of the return water temperature of the cooling water;

the return water temperature t of the cooling water output by the condenser model _cool,in' About equal to the set return water temperature t of the cooling water _cool,in If so, go to step 213, otherwise go back to step 204 to adjust the set return water temperature t of the cooling water _cool,in 。

Step 213, calculating the total system energy consumption;

the cryopump power W to be output by the first sub-model _pump,chilled And cooling pump power W _pump,cool Cooling tower power W output by second sub-model _tower Cold machine power W output by fourth sub-model _chilled Adding to obtain the total power W of the system _sys 。

Step 214, computing the energy efficiency of the system.

By evaporation of load Q _e With the total power W of the system _sys Determining energy efficiency COP of air conditioning system _sys 。

As shown in fig. 3, the operation mode optimization method of the air conditioning system includes: step 301-step 307.

Step 301, describing the characteristics of the existing equipment;

Step 302, inputting parameters of an operation mode;

including ambient weather conditions, load conditions of the surface cooler. The external weather conditions include outdoor dry bulb temperature and outdoor wet bulb temperature; the load conditions of the surface cooler comprise an air inlet parameter and an air supply parameter.

Step 303, selecting different equipment operation modes;

including the number of equipment runs and the operating frequency.

Step 304, calculating the total cold of the system;

step 305, calculating the total system energy consumption under different equipment operation modes;

The calculation is referred to step 213.

Step 306, calculating system energy efficiency under different equipment operation modes;

the calculation is referred to in step 214.

Step 307, determining an operation mode optimization scheme of the system energy efficiency and the maximum energy efficiency.

Table 3 shows an operation mode optimization scheme of the air conditioning system.

TABLE 3 Table 3

Changing the number of cooling towers, the number of cooling pumps and the number of freezing pumps, calculating the operation parameters and the energy consumption of the prediction system under different control methods according to the built system digital model, and determining that in the system of the embodiment, the optimal control method is as follows: the number of the running cooling machines is 1, the number of the running cooling towers is 2, the number of the running cooling pumps is 1, and the number of the running freezing pumps is 1. The system operating parameters and the energy consumption of each device after the system operates according to the operating mode optimizing method are shown in table 3. Under the working condition, the total power consumption of the system is 116573W, and the energy efficiency of the system is 3.56; compared with the original operation strategy, the energy can be saved by 6.6%, and the energy efficiency can be improved by 5.9%.

As shown in fig. 4, the operation mode optimization method of the air conditioning system includes: step 401-step 408.

Step 401, equipment replacement;

and replacing the existing equipment with poor performance in the system with equipment with better performance.

Step 402, describing characteristics of the replaced device;

Step 403, inputting parameters of an operation mode;

Step 404, selecting different equipment operation modes;

including the number of equipment runs and the operating frequency.

Step 405, calculating the total cold of the system;

step 406, calculating the total system energy consumption under different equipment operation modes;

the calculation is referred to step 213.

Step 407, calculating system energy efficiency under different equipment operation modes;

the calculation is referred to in step 214.

Step 408, determining an operation mode optimization scheme of the energy efficiency of the system and the maximum energy efficiency.

Table 4 shows a system form optimization scheme of the air conditioning system.

TABLE 4 Table 4

In this embodiment, the chiller of the air conditioning system is a screw chiller with poor performance (coefficient of performance is only 4.25 under nominal conditions), and if replaced with a higher performance screw chiller (coefficient of performance is 4.97 under nominal conditions), the chiller energy can be reduced from 99.4kW to 82.4kW under the conditions as shown in table 4. The total system energy consumption of the embodiment can be reduced by 14.5% on the basis of reducing the total system energy consumption by 6.6% by the optimized control method, and accordingly, the energy efficiency improvement of 29.9% is further realized.

As shown in fig. 5, the operation mode optimization method of the air conditioning system includes: step 501-step 508.

Step 501, optimizing and designing a system;

and designing a high-efficiency air conditioning system form according to a commentator of the heat and humidity load of the air conditioning system.

Step 502, describing the device characteristics of the new system;

Step 503, inputting parameters of an operation mode;

Step 505, selecting different equipment operation modes;

including the number of equipment runs and the operating frequency.

Step 505, calculating the total cold of the system;

step 506, calculating the total system energy consumption under different equipment operation modes;

the calculation is referred to step 213.

Step 507, calculating system energy efficiency under different equipment operation modes;

the calculation is referred to in step 215.

Step 508, determining a system optimization scheme of the system energy efficiency and the maximum energy efficiency.

Table 5 shows a system form optimization scheme of the air conditioning system.

TABLE 5

The initial air conditioning system of the embodiment is in a common primary air return system mode, after all fresh air and return air loads are mixed, cold water with the lowest temperature is treated, and the energy efficiency of a chiller is limited; if the loads of the fresh air and the return air are treated by the cold water with high temperature, medium temperature and low temperature with different temperatures after different grades of the loads of the system are considered, and the system schematic diagram is shown in fig. 7, the energy efficiency of the system can be obviously improved. At this time, the load levels borne by the high-temperature chiller, the medium-temperature chiller, and the low-temperature chiller, and the corresponding chiller COPs and energy consumption are shown in table 5. At the moment, the energy consumption of the system can be further saved by 8.7% on the basis of optimizing the control method and the equipment performance, and the energy efficiency is improved by 9.6%.

As shown in fig. 8, the energy efficiency optimization method of the air conditioning system provided by the embodiment of the application can provide a larger energy efficiency improvement potential through three-level optimization.

According to the energy efficiency optimization method for the air conditioning system, provided by the embodiment of the application, the execution main body can be an energy efficiency optimization device for the air conditioning system. In the embodiment of the application, an energy efficiency optimization method of an air conditioning system executed by an energy efficiency optimization device of the air conditioning system is taken as an example, and the energy efficiency optimization device of the air conditioning system provided by the embodiment of the application is described.

The embodiment of the application also provides an energy efficiency optimizing device of the air conditioning system.

As shown in fig. 9, the energy efficiency optimizing apparatus of the air conditioning system includes: a first acquisition module 810, a first processing module 820, a second processing module 830, and a third processing module 840.

A first obtaining module 810, configured to obtain an equipment operation characteristic of an air conditioning system to be optimized, and an actual power of each equipment under a target load condition and a target external weather condition, where the equipment operation characteristic of a target equipment to be replaced in the air conditioning system includes a first equipment operation characteristic before replacement and a second equipment operation characteristic after replacement;

the first processing module 820 is configured to determine an energy efficiency model of the air conditioning system before and after the replacement of the target device based on the device operation characteristic and the actual power, where the energy efficiency model is used to characterize a relationship between an operation mode of the air conditioning system and a system energy efficiency;

The second processing module 830 is configured to determine, based on the energy efficiency model, a maximum energy efficiency and a corresponding operation mode of the air conditioning system before and after the replacement of the target device;

the third processing module 840 is configured to determine an optimization scheme of the air conditioning system based on a maximum energy efficiency of the air conditioning system before and after the replacement of the target device and a corresponding operation mode.

According to the energy efficiency optimizing device of the air conditioning system, provided by the embodiment of the application, at least two optimizing schemes with different costs are determined according to the external weather conditions of the place where the air conditioning system is located, so that the accuracy is higher, and the actual using effect is better.

In some embodiments, the first processing module 820 is further configured to determine a sub-model corresponding to each device of the air conditioning system based on the device operating characteristics and the actual power; and adjusting the value of the target setting parameter based on the matching relation between the target output of the sub-model corresponding to each device of the air conditioning system and the target setting parameter, and determining the energy efficiency model of the air conditioning system.

In some embodiments, an air conditioning system includes: the cooling system comprises a surface cooler, a freezing pump connected between the surface cooler and the cooler, a cooling tower and a cooling pump connected between the cooler and the cooling tower; the target load condition comprises a target air inlet parameter and a target air supply temperature; the first processing module 820 is also used for

the target air inlet parameter and the set chilled water supply temperature t _chilled,in And the flow rate m of the frozen water output by the first submodel _w,chilled Inputting the temperature t of the returned chilled water output by the third sub-model into the third sub-model _chilled,out And supply air temperature t _a,out' The method comprises the steps of carrying out a first treatment on the surface of the Wherein the third sub-model is used for characterizing the characteristics of the surface cooler; set chilled water supply temperature t _chilled,in Air supply temperature t output through third sub-model _a,out' Matching with the target air supply temperature;

In some embodiments, the first processing module 820 is also configured to

Cooling water flowQuantity m _w,cool The cooling water supply temperature t output by the second sub-model _cool,out And condensing load Q output by evaporator model _c Inputting the temperature t of the cooling water returned by the condenser model into the condenser model to obtain the temperature t of the cooling water returned by the condenser model _cool,in' 。

In some embodiments, the energy efficiency optimizing apparatus of an air conditioning system may further include:

the fourth processing module is used for updating the system form of the air conditioning system to be optimized;

the second acquisition module is used for acquiring the updated equipment operation characteristics of the air conditioning system;

a fifth processing module for determining an energy efficiency model of the updated air conditioning system based on the updated equipment operating characteristics of the air conditioning system;

and the sixth processing module is used for determining the maximum energy efficiency and the corresponding operation mode of the updated air conditioning system based on the updated energy efficiency model of the air conditioning system, and determining the optimization scheme of the air conditioning system.

In some embodiments, the second processing module 830 is further configured to

The energy efficiency optimizing device of the air conditioning system in the embodiment of the application can be electronic equipment, and can also be a component in the electronic equipment, such as an integrated circuit or a chip. The electronic device may be a terminal, or may be other devices than a terminal. By way of example, the electronic device may be a mobile phone, tablet computer, notebook computer, palm computer, vehicle-mounted electronic device, mobile internet appliance (Mobile Internet Device, MID), augmented reality (augmented reality, AR)/Virtual Reality (VR) device, robot, wearable device, ultra-mobile personal computer, UMPC, netbook or personal digital assistant (personal digitalassistant, PDA), etc., but may also be a server, network attached storage (Network Attached Storage, NAS), personal computer (personal computer, PC), television (TV), teller machine or self-service machine, etc., and the embodiments of the present application are not limited in particular.

The energy efficiency optimizing device of the air conditioning system in the embodiment of the application can be a device with an operating system. The operating system may be a microsoft (Windows) operating system, an Android operating system, an IOS operating system, or other possible operating systems, and the embodiment of the present application is not limited specifically.

The energy efficiency optimizing device of the air conditioning system provided by the embodiment of the application can realize each process realized by the method embodiments of fig. 1 to 5, and in order to avoid repetition, the description is omitted here.

In some embodiments, as shown in fig. 10, an electronic device 900 is further provided in the embodiments of the present application, which includes a processor 901, a memory 902, and a computer program stored in the memory 902 and capable of running on the processor 901, where the program when executed by the processor 901 implements the respective processes of the embodiments of the energy efficiency optimization method of the air conditioning system, and the same technical effects can be achieved, and for avoiding repetition, a detailed description is omitted herein.

The electronic device in the embodiment of the application includes the mobile electronic device and the non-mobile electronic device.

The embodiment of the application also provides a non-transitory computer readable storage medium, on which a computer program is stored, which when executed by a processor, realizes the processes of the energy efficiency optimization method embodiment of the air conditioning system, and can achieve the same technical effects, and in order to avoid repetition, the description is omitted here.

Wherein the processor is a processor in the electronic device described in the above embodiment. The readable storage medium includes computer readable storage medium such as computer readable memory ROM, random access memory RAM, magnetic or optical disk, etc.

The embodiment of the application also provides a computer program product, which comprises a computer program, wherein the computer program realizes the energy efficiency optimization method of the air conditioning system when being executed by a processor.

The embodiment of the application further provides a chip, the chip comprises a processor and a communication interface, the communication interface is coupled with the processor, the processor is used for running programs or instructions, the processes of the energy efficiency optimization method embodiment of the air conditioning system can be realized, the same technical effects can be achieved, and the repetition is avoided, and the description is omitted here.

It should be understood that the chips referred to in the embodiments of the present application may also be referred to as system-on-chip chips, chip systems, or system-on-chip chips, etc.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. Furthermore, it should be noted that the scope of the methods and apparatus in the embodiments of the present application is not limited to performing the functions in the order shown or discussed, but may also include performing the functions in a substantially simultaneous manner or in an opposite order depending on the functions involved, e.g., the described methods may be performed in an order different from that described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a computer software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present application.

The embodiments of the present application have been described above with reference to the accompanying drawings, but the present application is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those having ordinary skill in the art without departing from the spirit of the present application and the scope of the claims, which are to be protected by the present application.

In the description of the present specification, reference to the terms "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples," etc., means 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 application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

While embodiments of the present application have been shown and described, it will be understood by those of ordinary skill in the art that: many changes, modifications, substitutions and variations may be made to the embodiments without departing from the spirit and principles of the application, the scope of which is defined by the claims and their equivalents.

Claims

1. An energy efficiency optimization method for an air conditioning system, comprising:

2. The energy efficiency optimization method of an air conditioning system according to claim 1, wherein the determining an energy efficiency model of the air conditioning system before and after replacement of a target device based on the device operation characteristics and the actual power includes:

3. The energy efficiency optimizing method of an air conditioning system according to claim 2, characterized in that the air conditioning system comprises: a surface cooler, a chiller, a freeze pump connected between the surface cooler and the chiller, a cooling tower, and a cooling pump connected between the chiller and the cooling tower; the target load condition comprises a target air inlet parameter and a target air supply temperature;

the air supply temperature t output by the third sub-model _a,out' When the water supply temperature matches the target air supply temperature, the set chilled water supply temperature t _chilled,in The flow m of the frozen water output by the first submodel _w,chilled And cooling water flow rate m _w,cool The cooling water supply temperature t output by the second sub-model _cool,out And the return water temperature t of the chilled water output by the third sub-model _chilled,out Inputting the temperature t of the cooling water returned by the fourth sub-model into the fourth sub-model to obtain the temperature t of the cooling water returned by the fourth sub-model _cool,in' Power W of cooler _chilled And an evaporation load Q _e The method comprises the steps of carrying out a first treatment on the surface of the Wherein the fourth sub-model is used for characterizing the characteristics of the chiller; the set backwater temperature t of the cooling water _cool,in The return water temperature t of the cooling water output by the fourth sub-model _cool,in' And the set return water temperature t of the cooling water _cool,in Matching condition adjustment of (2);

4. The energy efficiency optimizing method of an air conditioning system according to claim 3, wherein said setting of the chilled water supply temperature t _chilled,in The flow m of the frozen water output by the first submodel _w,chilled And cooling water flow rate m _w,cool The cooling water supply temperature t output by the second sub-model _cool,out And the return water temperature t of the chilled water output by the third sub-model _chilled,out Inputting the temperature t of the cooling water returned by the fourth sub-model into the fourth sub-model to obtain the temperature t of the cooling water returned by the fourth sub-model _cool,in' Power W of cooler _chilled And an evaporation load Q _e Comprising:

5. The energy efficiency optimizing method of an air conditioning system according to any one of claims 1 to 4, further comprising:

updating the system form of the air conditioning system to be optimized;

6. The energy efficiency optimization method of an air conditioning system according to any one of claims 1-4, wherein determining a maximum energy efficiency and a corresponding operation mode of the air conditioning system before and after replacement of a target device based on the energy efficiency model includes:

7. An energy efficiency optimizing apparatus of an air conditioning system, comprising:

8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the energy efficiency optimization method of an air conditioning system of any of claims 1-6 when the program is executed by the processor.

9. A non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor, implements the energy efficiency optimization method of an air conditioning system according to any one of claims 1-6.

10. A computer program product comprising a computer program which, when executed by a processor, implements the energy efficiency optimization method of an air conditioning system according to any one of claims 1-6.