Intelligent air conditioner resource energy-saving control method and system

Abstract

The invention provides an intelligent air conditioner resource energy-saving control method and system, and the method comprises the steps: carrying out the region division of a performance place based on functionality, and obtaining different functional regions which at least comprise an audience core region and a corridor channel region; different operation stages of the corresponding performance place are obtained, and at least comprise a pre-cooling stage, a warm field stage, a peak stage and a scattering stage; on the basis of the obtained multi-terminal data of the corresponding performance place, predicting the regional predicted cooling load of each functional region in each operation stage, and comparing the obtained regional predicted cooling load with the regional actual cooling load corresponding to the same functional region and the operation stage in real time; and responding to a cooling load difference value between the actual cooling load of the region at any moment and the predicted cooling load of the region, and executing dynamic energy-saving temperature control of the corresponding operation stage on the functional region. According to the invention, the resource energy-saving efficiency is at least improved.

Description

Technical Field

[0001] The present invention relates to data processing technologies, and in particular, to an intelligent-based air-conditioning resource energy-saving control method and system. Background Art

[0002] At present, with the booming development of the cultural and entertainment industry, the frequency and scale of large-scale concerts, sports events and other activities continue to climb. As a public space with a high concentration of people, the energy consumption of the air-conditioning system in concert venues has accounted for 60%-70% of the total energy consumption of the venue. This data not only reflects the core position of the air-conditioning system in the operation of the venue, but also exposes a huge space for energy-saving optimization.

[0003] From the perspective of energy consumption composition, the high energy consumption characteristics of the air-conditioning system in concert venues are closely related to special usage scenarios. On the one hand, during large-scale events, the personnel density in the venue can reach 1.5-2 people per square meter, and the heat and moisture dissipation from the human body is 3-5 times higher than that in daily life. Coupled with the instantaneous power of stage lighting equipment reaching the megawatt level, the indoor sensible heat load increases sharply. Measured data of a large stadium shows that the air-conditioning load surges by 40% within 1 hour after the start of the performance, and the heat dissipation from personnel and equipment accounts for more than 60%. On the other hand, in order to meet the requirements of stage effects, venues often adopt a tall space design, with a floor height generally exceeding 20 meters, resulting in a vertical temperature gradient that causes cold and hot air stratification. It is difficult for traditional constant air volume air-conditioning systems to control accurately, resulting in 30%-40% of ineffective energy consumption.

[0004] This high energy consumption situation not only brings significant economic costs - the air-conditioning electricity cost for a single event in a stadium with a capacity of 10,000 people can reach 150,000-200,000 yuan, but also causes a severe environmental burden. Calculated based on a venue with 200 events held annually, the annual carbon emissions can reach 5,000-8,000 tons, which is equivalent to the annual emissions of 3,000-5,000 household cars.

[0005] Therefore, there is an urgent need for an intelligent-based air-conditioning resource energy-saving control method and system that can optimize resource energy conservation. Summary of the Invention

[0006] Based on the above problems, the present invention is proposed to provide an intelligent-based air-conditioning resource energy-saving control method and system that can overcome or at least partially solve the above problems.

[0007] According to one aspect of the present invention, there is provided an intelligent-based air-conditioning resource energy-saving control method, including the following steps:

[0008] Perform functional-based regional division on the performance venue to obtain different functional areas, where at least the core audience area and the corridor passage area are included;

[0009] Obtain different operation stages of the corresponding performance venue, including at least a pre-cooling stage, a warm-up stage, a peak stage, and a post-performance stage;

[0010] Predict the regional predicted cooling load of each functional area at each operation stage based on the multi-terminal data of the corresponding performance venue, and compare the obtained regional predicted cooling load with the regional actual cooling load of the same functional area and operation stage in real time;

[0011] In response to a cooling load difference between the regional actual cooling load and the regional predicted cooling load at any moment, perform dynamic energy-saving temperature control for the corresponding operation stage of this functional area.

[0012] Optionally, in the method according to the present invention, obtaining different operation stages of the corresponding performance venue includes:

[0013] Determine different operation stages and the stage time periods corresponding to each operation stage based on the activity schedule of the corresponding performance venue;

[0014] Based on the comparison result between the current moment and different stage time periods, determine the operation stage in which the current moment is located, and perform dynamic verification on the operation stage based on the real-time data collection of the corresponding functional area;

[0015] In response to the verification result being a stage deviation, determine the operation stage corresponding to the next stage time period as the updated operation stage based on the activity schedule.

[0016] Optionally, in the method according to the present invention, performing dynamic verification on the operation stage based on the real-time data collection of the corresponding functional area includes:

[0017] In response to the operation stage being the pre-cooling stage, if the current total number of tickets checked in the corresponding core audience area is greater than the preset total number of tickets checked, determine the verification result as a stage deviation;

[0018] In response to the operation stage being the warm-up stage, obtain the regional heat load and regional carbon concentration of the corresponding core audience area based on thermal imaging technology and respiration detection technology, and if the regional heat load and regional carbon concentration are respectively greater than the preset heat load and preset carbon concentration, determine the verification result as a stage deviation;

[0019] In response to the operation stage being the peak stage, if the regional traffic flow determined based on the pressure sensors set in the corridor passage area is greater than the preset traffic flow, determine the verification result as a stage deviation.

[0020] Optionally, in the method according to the present invention, predicting the regional predicted cooling load of each functional area at each operation stage based on the multi-terminal data of the corresponding performance venue includes;

[0021] Build a BIM model based on the BIM data of the corresponding performance venue, and perform grid processing on the BIM model to obtain each grid unit;

[0022] Based on the real-time equipment power, seat distribution data, and real-time meteorological data respectively output by the performance equipment terminal, ticket terminal, and meteorological terminal of the corresponding performance venue, and combine the real-time meteorological data with the determined unit population density and unit power density corresponding to each grid unit to form grid prediction data;

[0023] Obtain historical load data corresponding to different operation stages, and based on training the historical load data, obtain each load prediction model corresponding to different operation stages;

[0024] Based on the prediction results obtained by sequentially inputting each grid prediction data into each load prediction model, determine the regional predicted cooling load of each functional area at each operation stage.

[0025] Optionally, in the method according to the present invention, the method further includes:

[0026] Extract the media text data related to the performance venue output by the social media terminal, and based on the extraction result, determine the target dress as the dress type with the largest corresponding dress ratio;

[0027] Determine the suitable dress based on the regional predicted cooling load of any functional area at any operation stage, and compare the suitable dress with the target dress;

[0028] In response to the existence of a dress deviation between the suitable dress and the target dress, update the regional predicted cooling load based on the deviation degree corresponding to the dress deviation.

[0029] Optionally, in the method according to the present invention, determining the regional predicted cooling load of each functional area at each operation stage based on the prediction results obtained by sequentially inputting each grid prediction data into each load prediction model includes:

[0030] Input each grid prediction data into the load prediction model corresponding to any operation stage to obtain the grid predicted cooling load corresponding to this operation stage;

[0031] Obtain the air-conditioning distribution data corresponding to the same functional area, and based on the air-conditioning distribution data, determine the grid units within the air-conditioning coverage range of the same air-conditioning equipment unit as the air-conditioning radiation group;

[0032] Calculate the average value of the grid predicted cooling loads corresponding to each grid unit located in the same air-conditioning radiation group, and determine all the air-conditioning predicted cooling loads corresponding to the same functional area as the regional predicted cooling load at this operation stage.

[0033] Optionally, in the method according to the present invention, when there is a cooling load difference between the actual regional cooling load and the predicted regional cooling load at any moment, dynamic energy-saving temperature control for the corresponding operation stage is performed on the functional area, including:

[0034] When the cooling load difference between the actual regional cooling load and the predicted regional cooling load at any moment is a positive difference, the positive difference is compared with a preset upper limit value, and when the positive difference is less than the preset upper limit value, the air-conditioning flow rate of the corresponding area is increased;

[0035] When the cooling load difference between the actual regional cooling load and the predicted regional cooling load at any moment is a negative difference, the negative difference is compared with a preset lower limit value, and when the negative difference is less than the preset lower limit value, the air-conditioning flow rate of the corresponding area is decreased.

[0036] According to another aspect of the present invention, there is provided an intelligent air-conditioning resource energy-saving control system, including:

[0037] A division module configured to perform functional-based regional division on the performance venue to obtain different functional areas, including at least a core audience area and a corridor passage area;

[0038] An acquisition module configured to acquire different operation stages of the corresponding performance venue, including at least a precooling stage, a warm-up stage, a peak stage, and a dispersal stage;

[0039] A comparison module configured to predict the predicted regional cooling load of each functional area in each operation stage based on multi-terminal data of the corresponding performance venue, and perform real-time comparison between the obtained predicted regional cooling load and the actual regional cooling load of the same functional area and operation stage;

[0040] A regulation module configured to perform dynamic energy-saving temperature control for the corresponding operation stage on the functional area in response to a cooling load difference between the actual regional cooling load and the predicted regional cooling load at any moment.

[0041] Optionally, in the system according to the present invention, acquiring different operation stages of the corresponding performance venue includes:

[0042] Determining different operation stages and the stage time periods corresponding to each operation stage based on the activity schedule of the corresponding performance venue;

[0043] Based on the comparison result between the current moment and different stage time periods, determining the operation stage in which the current moment is located, and dynamically verifying the operation stage based on real-time data collection of the corresponding functional area;

[0044] If the response verification result is a stage deviation, the operation stage corresponding to the next stage period is determined as the updated operation stage based on the activity flow table.

[0045] Optionally, in the system according to the present invention, the operation stage is dynamically verified based on real-time data collection of the corresponding functional area, including:

[0046] In response to the operation stage being the pre-cooling stage, based on the fact that the current total number of tickets checked in the corresponding audience core area obtained is greater than the preset total number of tickets checked, the verification result is determined as a stage deviation;

[0047] In response to the operation stage being the warm-up stage, based on the thermal imaging technology and the respiration detection technology, the regional heat load and the regional carbon concentration of the corresponding audience core area are obtained, and based on the regional heat load and the regional carbon concentration being greater than the preset heat load and the preset carbon concentration respectively, the verification result is determined as a stage deviation;

[0048] In response to the operation stage being the peak stage, based on the pressure sensors set in the corridor passage area, it is determined that the regional traffic flow is greater than the preset traffic flow, and the verification result is determined as a stage deviation. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 Shows a flowchart of an intelligent air-conditioning resource energy-saving control method according to an embodiment of the present invention;

[0050] Figure 2 Shows a structural block diagram of an intelligent air-conditioning resource energy-saving control system according to another embodiment of the present invention. DETAILED DESCRIPTION

[0051] Hereinafter, exemplary embodiments of the present disclosure will be described in more detail with reference to the drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be completely conveyed to those skilled in the art.

[0052] To solve the problems existing in the above-mentioned prior art, the inventors propose a solution of the present invention. An embodiment of the present invention provides an intelligent air-conditioning resource energy-saving control method and system, and the method can be executed in a computing device.

[0053] According to one aspect of the present invention, there is provided an intelligent air-conditioning resource energy-saving control method, including the following steps:

[0054] Perform functional-based regional division on the performance venue to obtain different functional areas, where at least the audience core area and the corridor passage area are included;

[0055] Obtain different operation stages of the corresponding performance venue, including at least a precooling stage, a warm-up stage, a peak stage, and a post-performance stage;

[0056] Predict the regional predicted cooling load of each functional area at each operation stage based on the multi-terminal data of the corresponding performance venue obtained, and compare the obtained regional predicted cooling load with the regional actual cooling load of the corresponding same functional area and operation stage in real time;

[0057] In response to a cooling load difference between the regional actual cooling load and the regional predicted cooling load at any moment, perform dynamic energy-saving temperature control for the corresponding operation stage of this functional area.

[0058] Optionally, in the method according to the present invention, obtaining different operation stages of the corresponding performance venue includes:

[0059] Determine different operation stages and the stage time periods corresponding to each operation stage based on the activity schedule of the corresponding performance venue;

[0060] Based on the comparison result between the current moment and different stage time periods, determine the operation stage in which the current moment is located, and perform dynamic verification on the operation stage based on the real-time data collection of the corresponding functional area;

[0061] In response to the verification result being a stage deviation, determine the operation stage corresponding to the next stage time period as the updated operation stage based on the activity schedule.

[0062] Optionally, in the method according to the present invention, performing dynamic verification on the operation stage based on the real-time data collection of the corresponding functional area includes:

[0063] In response to the operation stage being the precooling stage, if the current total number of tickets checked in the corresponding core audience area obtained is greater than the preset total number of tickets checked, determine the verification result as a stage deviation;

[0064] In response to the operation stage being the warm-up stage, obtain the regional heat load and regional carbon concentration of the corresponding core audience area based on thermal imaging technology and respiration detection technology, and if the regional heat load and regional carbon concentration are respectively greater than the preset heat load and preset carbon concentration, determine the verification result as a stage deviation;

[0065] In response to the operation stage being the peak stage, if the regional traffic flow determined based on the pressure sensors set in the corridor passage area is greater than the preset traffic flow, determine the verification result as a stage deviation.

[0066] Optionally, in the method according to the present invention, predicting the regional predicted cooling load of each functional area at each operation stage based on the multi-terminal data of the corresponding performance venue obtained includes;

[0067] Build a BIM model based on the BIM data of the corresponding performance venue, and perform grid processing on the BIM model to obtain each grid unit;

[0068] Based on the real-time equipment power, seat distribution data, and real-time meteorological data respectively output by the performance equipment terminal, ticket terminal, and meteorological terminal of the corresponding performance venue, and combine the real-time meteorological data with the determined unit population density and unit power density corresponding to each grid unit to form grid prediction data;

[0069] Obtain historical load data corresponding to different operation stages, and based on the training of the historical load data, obtain each load prediction model corresponding to different operation stages;

[0070] Based on each prediction result obtained by sequentially inputting each grid prediction data into each load prediction model, determine the regional predicted cooling load of each functional area at each operation stage.

[0071] Optionally, in the method according to the present invention, the method further includes:

[0072] Extract the media text data related to the performance venue output by the social media terminal, and based on the extraction result, determine the target dress as the dress type with the largest corresponding dress ratio;

[0073] Based on the regional predicted cooling load of any functional area at any operation stage, determine the suitable dress, and compare the suitable dress with the target dress;

[0074] In response to the existence of a dress deviation between the suitable dress and the target dress, update the regional predicted cooling load based on the degree of the corresponding dress deviation.

[0075] Optionally, in the method according to the present invention, determining the regional predicted cooling load of each functional area at each operation stage based on each prediction result obtained by sequentially inputting each grid prediction data into each load prediction model includes:

[0076] Input each grid prediction data into the load prediction model corresponding to any operation stage to obtain the grid predicted cooling load corresponding to this operation stage;

[0077] Obtain the air-conditioning distribution data corresponding to the same functional area, and based on the air-conditioning distribution data, determine each grid unit within the air-conditioning coverage range of the same air-conditioning equipment unit as an air-conditioning radiation group;

[0078] Calculate the mean value of the grid predicted cooling loads corresponding to each grid unit located in the same air-conditioning radiation group, and determine all the air-conditioning predicted cooling loads corresponding to the same functional area as the regional predicted cooling load at this operation stage.

[0079] Optionally, in the method according to the present invention, when there is a cooling load difference between the actual regional cooling load and the predicted regional cooling load at any moment, dynamic energy-saving temperature control for the corresponding operation stage is performed on this functional area, including:

[0080] When the cooling load difference between the actual regional cooling load and the predicted regional cooling load at any moment is a positive difference, compare the positive difference with a preset upper limit value, and increase the air-conditioning flow rate of the corresponding area when the positive difference is less than the preset upper limit value;

[0081] When the cooling load difference between the actual regional cooling load and the predicted regional cooling load at any moment is a negative difference, compare the negative difference with a preset lower limit value, and reduce the air-conditioning flow rate of the corresponding area when the negative difference is less than the preset lower limit value.

[0082] According to another aspect of the present invention, there is provided an intelligent air-conditioning resource energy-saving control system, including:

[0083] A division module configured to perform functional-based regional division on the performance venue to obtain different functional areas, including at least a core audience area and a corridor passage area;

[0084] An acquisition module configured to acquire different operation stages of the corresponding performance venue, including at least a precooling stage, a warm-up stage, a peak stage, and a post-performance stage;

[0085] A comparison module configured to predict the predicted regional cooling load of each functional area at each operation stage based on multi-terminal data of the corresponding performance venue, and perform real-time comparison between the obtained predicted regional cooling load and the actual regional cooling load of the same functional area and operation stage;

[0086] A regulation module configured to perform dynamic energy-saving temperature control for the corresponding operation stage on this functional area when there is a cooling load difference between the actual regional cooling load and the predicted regional cooling load at any moment.

[0087] Optionally, in the system according to the present invention, acquiring different operation stages of the corresponding performance venue includes:

[0088] Determine different operation stages and the stage time periods corresponding to each operation stage based on the activity schedule of the corresponding performance venue;

[0089] Based on the comparison result between the current moment and different stage time periods, determine the operation stage in which the current moment is located, and perform dynamic verification on the operation stage based on real-time data acquisition of the corresponding functional area;

[0090] When the response verification result is a phase deviation, the operation phase corresponding to the next phase period is determined as the updated operation phase based on the activity flow table.

[0091] Optionally, in the system according to the present invention, the operation phase is dynamically verified based on real-time data collection of the corresponding functional area, including:

[0092] When the operation phase is the pre-cooling phase, based on the fact that the current total number of tickets checked in the corresponding core area of the audience is greater than the preset total number of tickets checked, the verification result is determined as a phase deviation;

[0093] When the operation phase is the warm-up phase, based on the thermal imaging technology and the respiration detection technology, the regional heat load and the regional carbon concentration of the corresponding core area of the audience are obtained, and based on the fact that the regional heat load and the regional carbon concentration are respectively greater than the preset heat load and the preset carbon concentration, the verification result is determined as a phase deviation;

[0094] When the operation phase is the peak phase, based on the pressure sensors arranged in the corridor passage area, it is determined that the regional traffic flow is greater than the preset traffic flow, and the verification result is determined as a phase deviation.

[0095] In the specification provided herein, the algorithms and displays are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems can also be used in conjunction with the examples of the present invention. Based on the above description, the structure required to construct such systems is obvious. In addition, the present invention is not directed to any particular programming language. It should be understood that the content of the present invention described herein can be implemented using various programming languages, and the description of the specific language above is for disclosing the preferred embodiments of the present invention.

[0096] In the specification provided herein, a large number of specific details are described. However, it can be understood that the embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures, and technologies are not shown in detail so as not to obscure the understanding of this specification.

[0097] Similarly, it should be understood that, in order to streamline the present disclosure and assist in understanding one or more of the various inventive aspects, in the above description of the exemplary embodiments of the present invention, the various features of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof.

[0098] Those skilled in the art should understand that the modules or units or components of the devices in the examples disclosed herein can be arranged in the devices as described in the embodiments, or alternatively can be located in one or more devices different from the devices in the examples. The modules in the foregoing examples can be combined into one module or further divided into multiple sub-modules.

[0099] Those skilled in the art can understand that the modules in the devices in the embodiments can be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments can be combined into one module or unit or component, and in addition, they can be divided into multiple sub-modules or sub-units or sub-components.

[0100] In addition, those skilled in the art can understand that although some of the embodiments described herein include certain features included in other embodiments rather than other features, the combination of the features of different embodiments means that it is within the scope of the present invention and forms different embodiments.

[0101] In addition, some of the embodiments herein are described as a combination of methods or method elements that can be implemented by a processor of a computer system or by other devices performing the functions. Therefore, a processor having the necessary instructions for implementing the method or method element forms a device for implementing the method or method element. In addition, the elements described herein in the device embodiments are examples of such devices: the device is used to implement the functions performed by the elements for the purpose of implementing the invention.

[0102] As used herein, unless otherwise specified, the use of ordinal numbers "first", "second", "third", etc. to describe ordinary objects only indicates different instances of similar objects, and does not intend to imply that the objects so described must have a given order in terms of time, space, sorting, or in any other way.

[0103] Although the present invention is described in terms of a limited number of embodiments, those skilled in the art in this technical field will understand, from the above description, that other embodiments can be envisaged within the scope of the present invention thus described. In addition, it should be noted that the language used in this specification is mainly selected for the purpose of readability and teaching, rather than for the purpose of explaining or limiting the subject matter of the present invention.

Claims

1. An intelligent-based energy-saving control method for air-conditioning resources, characterized in that, Including the following steps: Conduct a functional-based regional division of the performance venue to obtain different functional areas, where at least the core audience area and the corridor passage area are included; Obtain different operation stages of the corresponding performance venue, where at least the precooling stage, the warm-up stage, the peak stage, and the dispersal stage are included; Predict the regional predicted cooling load of each functional area at each operation stage based on the multi-terminal data of the corresponding performance venue obtained, and compare the obtained regional predicted cooling load with the regional actual cooling load of the corresponding same functional area and operation stage in real time; In response to the presence of a cooling load difference between the regional actual cooling load and the regional predicted cooling load at any moment, perform dynamic energy-saving temperature control for this functional area at the corresponding operation stage.

2. The intelligent-based air-conditioning resource energy-saving control method according to claim 1, wherein: Obtaining different operation stages of the corresponding performance venue includes: Determine different operation stages and the stage time periods corresponding to each operation stage based on the activity schedule of the corresponding performance venue; Based on the comparison result between the current moment and different stage time periods, determine the operation stage where the current moment is located, and perform dynamic verification on the operation stage based on the real-time data collection of the corresponding functional area; In response to the verification result being a stage deviation, determine the operation stage corresponding to the next stage time period as the updated operation stage based on the activity schedule.

3. The intelligent-based air-conditioning resource energy-saving control method according to claim 2, wherein: Performing dynamic verification on the operation stage based on the real-time data collection of the corresponding functional area includes: In response to the operation stage being the precooling stage, based on the current total number of tickets checked in the corresponding core audience area being greater than the preset total number of tickets checked, determine the verification result as a stage deviation; In response to the operation stage being the warm-up stage, obtain the regional heat load and regional carbon concentration of the corresponding core audience area based on thermal imaging technology and respiration detection technology, and based on the regional heat load and regional carbon concentration being greater than the preset heat load and preset carbon concentration respectively, determine the verification result as a stage deviation; In response to the operation stage being the peak stage, based on the pressure sensors set in the corridor passage area, determine that the regional traffic flow is greater than the preset traffic flow, and determine the verification result as a stage deviation.

4. The intelligent-based air-conditioning resource energy-saving control method according to claim 1, wherein: Predicting the regional predicted cooling load of each functional area at each operation stage based on the multi-terminal data of the corresponding performance venue obtained includes; Establish a BIM model based on the BIM data of the corresponding performance venue, and perform grid processing on the BIM model to obtain each grid unit; Based on the real-time equipment power, seat distribution data, and real-time meteorological data respectively output by the performance equipment terminal, ticket terminal, and meteorological terminal of the corresponding performance venue, and form grid prediction data by combining the real-time meteorological data with the determined unit personnel density and unit power density corresponding to each grid unit; Obtain historical load data corresponding to different operation stages, and based on the training of the historical load data, obtain each load prediction model corresponding to different operation stages; Based on the prediction results obtained by sequentially inputting each grid prediction data into each load prediction model, determine the regional predicted cooling load of each functional area at each operation stage.

5. The intelligent air-conditioning resource energy-saving control method according to claim 4, wherein: The method further includes: Extract the media text data related to the performance venue output by the social media terminal, and based on the extraction result, determine the target dress type with the largest corresponding dress ratio as the target dress; Determine the suitable dress based on the regional predicted cooling load of any functional area at any operation stage, and compare the suitable dress with the target dress; In response to the existence of a dress deviation between the suitable dress and the target dress, update the regional predicted cooling load based on the deviation degree corresponding to the dress deviation.

6. The intelligent air-conditioning resource energy-saving control method according to claim 4, wherein: Based on the prediction results obtained by sequentially inputting each grid prediction data into each load prediction model, determining the regional predicted cooling load of each functional area at each operation stage includes: Input each grid prediction data into the load prediction model corresponding to any operation stage to obtain the grid predicted cooling load corresponding to this operation stage; Obtain the air-conditioning distribution data corresponding to the same functional area, and based on the air-conditioning distribution data, determine each grid unit within the air-conditioning coverage range of the same air-conditioning equipment unit as an air-conditioning radiation group; Calculate the average value of the grid predicted cooling loads corresponding to each grid unit located in the same air-conditioning radiation group, and determine all the air-conditioning predicted cooling loads corresponding to the same functional area as the regional predicted cooling load at this operation stage.

7. The intelligent air-conditioning resource energy-saving control method according to claim 1, wherein: In response to the existence of a cooling load difference between the regional actual cooling load and the regional predicted cooling load at any moment, perform dynamic energy-saving temperature control for this functional area at the corresponding operation stage, including: In response to the cooling load difference between the regional actual cooling load and the regional predicted cooling load at any moment being a positive difference, compare the positive difference with a preset upper limit value, and increase the air-conditioning flow rate of the corresponding area when the positive difference is less than the preset upper limit value; In response to the cooling load difference between the regional actual cooling load and the regional predicted cooling load at any moment being a negative difference, compare the negative difference with a preset lower limit value, and reduce the air-conditioning flow rate of the corresponding area when the negative difference is less than the preset lower limit value.

8. An intelligent-based energy-saving control system for air-conditioning resources, characterized in that, including: A division module configured to perform functional-based regional division on the performance venue to obtain different functional areas, including at least a core audience area and a corridor passage area; An acquisition module configured to acquire different operation stages corresponding to the performance venue, including at least a precooling stage, a warm-up stage, a peak stage, and a dispersal stage; A comparison module, configured to predict the regional predicted cooling load of each functional area at each operation stage based on the multi-terminal data of the corresponding performance venue obtained, and compare the obtained regional predicted cooling load with the regional actual cooling load of the corresponding same functional area and operation stage in real time; A regulation module, configured to perform dynamic energy-saving temperature control for the corresponding operation stage of the functional area in response to a cooling load difference between the regional actual cooling load and the regional predicted cooling load at any moment.

9. The intelligent air-conditioning resource energy-saving control system according to claim 8, wherein Obtaining different operation stages of the corresponding performance venue includes: Determining different operation stages and the stage time periods corresponding to each operation stage based on the activity schedule of the corresponding performance venue; Based on the comparison result between the current moment and different stage time periods, determining the operation stage corresponding to the current moment, and dynamically verifying the operation stage based on the real-time data collection of the corresponding functional area; In response to the verification result being a stage deviation, determining the operation stage corresponding to the next stage time period as the updated operation stage based on the activity schedule.

10. The intelligent air-conditioning resource energy-saving control system according to claim 9, wherein Dynamically verifying the operation stage based on the real-time data collection of the corresponding functional area includes: In response to the operation stage being the pre-cooling stage, based on the fact that the current total number of tickets checked in the corresponding core audience area obtained is greater than the preset total number of tickets checked, determining the verification result as a stage deviation; In response to the operation stage being the warm-up stage, obtaining the regional heat load and regional carbon concentration of the corresponding core audience area based on thermal imaging technology and respiration detection technology, and based on the regional heat load and regional carbon concentration being greater than the preset heat load and preset carbon concentration respectively, determining the verification result as a stage deviation; In response to the operation stage being the peak stage, based on the pressure sensor set in the corridor passage area, determining that the regional traffic flow is greater than the preset traffic flow, and determining the verification result as a stage deviation.

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