Intelligent energy efficiency dual-carbon management system and method

Abstract

The invention relates to the technical field of dual-carbon management, and particularly discloses an intelligent energy efficiency dual-carbon management system and method, and the system comprises an acquisition module which is used for collecting the environment information, crowd state information and outdoor environment information of all regions in a shopping mall building; the central air conditioning system comprises a temperature control module and a cold and heat source module; the temperature control module is used for adjusting the air temperature in the designated area; the cold and heat source module is used for providing heat exchange demand supply for all the temperature control modules in the shopping mall building; the analysis module is used for determining an adjustment strategy of the sub-temperature control module in the region according to the environment information and the crowd state information; the environment information and crowd state analysis of each area in the shopping mall building are acquired through the acquisition module, the temperature, humidity and crowd state of each area are analyzed through the analysis module, and the temperature control module of the corresponding area is controlled to perform corresponding adjustment on the basis of the preset heat exchange power.

Description

Technical Field

[0001] The present invention relates to the technical field of dual-carbon management, and in particular to an intelligent energy-efficient dual-carbon management system and method. Background Art

[0002] Dual carbon management usually refers to carbon emission and carbon neutrality management, that is, reducing greenhouse gas emissions and taking measures to offset the emissions that have already been generated. With the development of the economy, green and low-carbon development has become one of the important directions of economic development. Energy conservation in electricity consumption, as a key direction of carbon emission reduction, has a far-reaching impact on achieving green and low-carbon development goals. Among them, according to some industry data and statistics, in the electricity consumption of shopping malls, the proportion of central air-conditioning electricity consumption may reach up to 45% of its total electricity consumption, which is a key power consumption item in shopping malls. Its high energy consumption makes shopping malls face challenges in energy consumption and carbon emissions. Reducing the energy consumption of central air-conditioning systems and reducing carbon emissions are a central goal in the dual carbon management process of shopping malls.

[0003] In the prior art, in order to reduce the energy consumption of the central air-conditioning system and reduce carbon emissions, shopping malls often upgrade air-conditioning equipment, adopt more energy-efficient central air-conditioning equipment, improve the thermal insulation performance of buildings and other related measures to achieve the purpose of reducing the energy consumption of the central air-conditioning system. This method of reducing energy consumption is costly, and in the actual working process of the central air-conditioning system of the shopping mall, in order to ensure the comfort of tourists in the shopping mall, the air outlet temperature is often preset to the comfortable temperature of the corresponding season according to the season and the shopping mall can be continuously exchanged for heat. It is impossible to intelligently adjust according to factors such as the ambient temperature and the flow of people in the shopping mall, and it is impossible to automatically adjust the preset temperature according to the actual outdoor temperature. It may happen that the outdoor temperature is not high in summer, but the preset temperature of the central air-conditioning in the shopping mall is low, causing tourists to feel cold and uncomfortable or even sick after entering the shopping mall. It may also happen that the outdoor temperature is low in winter, and the preset temperature of the central air-conditioning in the shopping mall is high, causing tourists to sweat after entering the shopping mall because of wearing thick clothes. When leaving the shopping mall later, they may feel cold and uncomfortable or even sick because of the low outdoor temperature and the underwear being soaked by sweat. Summary of the invention

[0004] The purpose of the present invention is to provide a smart energy efficiency dual carbon management system and method to solve the following technical problems:

[0005] The problem of how to intelligently adjust the central air-conditioning system of a shopping mall.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A smart energy efficiency dual carbon management system, the system comprising:

[0008] The collection module is used to collect environmental information and crowd status information of each area in the shopping mall building and outdoor environmental information;

[0009] Central air conditioning system, the central air conditioning system includes a temperature control module and a cold and heat source module;

[0010] Temperature control module, used to adjust the air temperature in the designated area;

[0011] The cold and heat source module is used to provide heat exchange demand for all temperature control modules in the shopping mall building;

[0012] The analysis module is used to determine the adjustment strategy of the temperature control module in the area according to the environmental information and the crowd status information, and to intelligently control the cold and hot source modules or generate early warning signals;

[0013] The early warning module is used to execute early warning signals.

[0014] A method for a smart energy efficiency dual carbon management system, the method comprising the following steps:

[0015] S1, collecting temperature and humidity information of each area in the shopping mall building and temperature and humidity information outside the shopping mall building based on temperature sensors and humidity sensors;

[0016] S2, collecting crowd status information in various areas of the shopping mall building based on surveillance cameras;

[0017] S3. Perform a comprehensive analysis based on the crowd status information, temperature and humidity of each area to determine whether the preset heat exchange power of the temperature control module in each area needs to be adjusted. If adjustment is required, adjust the heat exchange power of the temperature control module in the corresponding area;

[0018] S4. Preliminary adjustment is made to the operation of the cold and hot source modules according to the information on adjusting the heat exchange power of each temperature control module.

[0019] In one embodiment, the process of determining whether the preset heat exchange power of the temperature control module in each area is adjusted includes:

[0020] By formula Calculate the perceived temperature in the i-th region

[0021] in, is the air temperature monitored and collected by the temperature sensor in the i-th area, is the air humidity monitored and collected by the humidity sensor in the i-th area, and μ is the influence coefficient of humidity on the perceived temperature;

[0022] The body temperature With the preset temperature threshold [T p -T e ,T p +T e ] for comparison;

[0023] like or Adjusting the heat exchange power of the temperature control module in the i-th area;

[0024] like Then analyze the crowd status information in the area;

[0025] Among them, T p is the preset optimum temperature value, T e is the human body comfort temperature error value.

[0026] Furthermore, the process of adjusting the heat exchange power of the temperature control module in the i-th area includes:

[0027] like or Control the temperature control module in the i-th area to adjust the power accordingly based on the preset power. The adjusted power P Δt It can be obtained according to the following formula;

[0028]

[0029] Among them, S i is the spatial volume in the i-th region, is the real-time number of people collected by the surveillance camera in the i-th area, C x is the influence coefficient of human body on indoor temperature, and Q is the regional heat exchange demand power coefficient.

[0030] In one embodiment, the process of determining whether the preset heat exchange power of the temperature control module in each area is adjusted further includes:

[0031] when hour,

[0032] The total number of people in the i-th area is obtained in real time through surveillance cameras, and the change curve of the total number of people is fitted by linear regression algorithm

[0033] Analyze the changes in the total number of people within the preset time interval [t1, t2];

[0034] By formula Calculate the average number of people in the corresponding area within the preset time interval [t1, t2]

[0035] Wherein, Δt=t2-t1, t1 and t2 are adjacent time nodes adjusted by the analysis module, and Δt is the interval time adjusted by the analysis module;

[0036] The average number of With the preset standard number of people Make a comparison;

[0037] like Then it is necessary to control the temperature control module in the i-th area to adjust the power accordingly based on the preset power. It can be obtained according to the following formula;

[0038]

[0039] In one embodiment, the process of pre-adjusting the cold and hot source modules includes:

[0040] By formula Calculate the total power P required by all heat exchange modules in the shopping mall building A ;

[0041] The power P that the cold and hot source module needs to output is B =P A *(1-μ),

[0042] Among them, μ is the loss rate during the output process of the cold and hot source module;

[0043] The power P output by the cold and hot source modules at each time node t adjusted by the statistical analysis module B , the power change curve P required to be output by the cold and hot source module is fitted by linear regression algorithm B (t);

[0044] By formula P C (t) = P B (t+Δθ) calculates the real-time output power output P of the cold and hot source modules C (t),

[0045] Wherein, Δθ is the time taken for the heat exchange medium output by the cold and heat source modules to be transported to each temperature control module through the heat exchange pipeline.

[0046] In one embodiment, the process of analyzing and obtaining the preset optimum temperature value includes:

[0047] By formula T p =(T w +RH w *μ-T sth )*α+T sth Calculate the preset optimal temperature value T p ;

[0048] Among them, T w is the outdoor temperature of the shopping mall building, RH w is the outdoor humidity of the shopping mall building, T sth is the standard comfortable temperature value for human body, and α is the temperature adjustment parameter.

[0049] In one embodiment, the method further comprises:

[0050] S5. Analyze and compare the temperature and humidity information monitored at adjacent adjustment time nodes in each area. If the perceived temperature obtained by the latest time node analysis is not between the perceived temperature obtained by the previous monitoring time node analysis and the preset optimal temperature value, generate a warning signal that the temperature control module corresponding to the area has a fault.

[0051] Beneficial effects of the present invention:

[0052] (1) The present invention collects the outdoor environmental information of the shopping mall building through the collection module, analyzes the outdoor environmental information through the analysis module to obtain the optimal temperature value required by tourists in the shopping mall building, and then presets and controls the central air-conditioning system in the shopping mall building.

[0053] (2) The present invention collects environmental information and crowd status analysis of each area in the shopping mall building through the collection module, analyzes the temperature, humidity and crowd status of each area through the analysis module, and controls the temperature control module of the corresponding area to make corresponding adjustments based on the preset heat exchange power.

[0054] (3) The present invention obtains the heat exchange output power of the corresponding cold and hot source modules by counting the heat exchange power of the temperature control modules in each area, and pre-adjusts the heat exchange source modules.

[0055] (4) The present invention compares the environmental information of the previous and next adjustment time nodes in each area with the preset optimal temperature value to determine whether the temperature control module in the corresponding area is abnormal and issue an early warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The present invention will be further described below in conjunction with the accompanying drawings.

[0057] Figure 1 It is a schematic block diagram of the intelligent energy-efficient dual-carbon management system proposed by the present invention;

[0058] Figure 2 It is a flowchart of the steps of the smart energy-efficiency dual-carbon management method proposed in the present invention. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] See also Figure 1As shown, in one embodiment, a smart energy efficiency dual carbon management system is provided, the system comprising:

[0061] The collection module is used to collect environmental information and crowd status information of each area in the shopping mall building and outdoor environmental information;

[0062] Central air conditioning system, the central air conditioning system includes a temperature control module and a cold and heat source module;

[0063] Temperature control module, used to adjust the air temperature in the designated area;

[0064] The cold and heat source module is used to provide heat exchange demand for all temperature control modules in the shopping mall building;

[0065] The analysis module is used to determine the adjustment strategy of the temperature control module in the area according to the environmental information and the crowd status information, and to intelligently control the cold and hot source modules or generate early warning signals;

[0066] The early warning module is used to execute early warning signals.

[0067] Through the above technical scheme, this embodiment provides a smart energy-efficient dual-carbon management system, in which the environmental information and crowd status information of each area in the shopping mall building and the outdoor environmental information are collected through the collection module, and the outdoor environmental information is analyzed through the analysis module. The central air-conditioning system in the shopping mall building is preset and controlled. According to the environmental information of each area in the shopping mall building, it is analyzed whether the preset heat exchange power of the temperature control module in each area needs to be adjusted. If adjustment is required, corresponding adjustments are made according to the environmental information and crowd status information of the area. The cold and heat source modules of the central air-conditioning system in the shopping mall building are analyzed, and the output heat exchange power is pre-adjusted according to its historical output heat exchange power changes. The working status of the heat exchange module in each area is analyzed. If a heat exchange module fails, an early warning signal is issued in time.

[0068] See also Figure 2 As shown, in one embodiment, a method for a smart energy efficiency dual carbon management system is provided, the method comprising the following steps:

[0069] S1, collecting temperature and humidity information of each area in the shopping mall building and temperature and humidity information outside the shopping mall building based on temperature sensors and humidity sensors;

[0070] S2, collecting crowd status information in various areas of the shopping mall building based on surveillance cameras;

[0071] S3. Perform a comprehensive analysis based on the crowd status information, temperature and humidity of each area to determine whether the preset heat exchange power of the temperature control module in each area needs to be adjusted. If adjustment is required, adjust the heat exchange power of the temperature control module in the corresponding area;

[0072] S4. Preliminary adjustment is made to the operation of the cold and hot source modules according to the information on adjusting the heat exchange power of each temperature control module.

[0073] Through the above technical scheme, this embodiment provides a method for an intelligent energy-efficient dual-carbon management system. Specifically, based on temperature sensors and humidity sensors, the temperature and humidity information of each area in the shopping mall building is monitored, as well as the temperature and humidity outside the shopping mall building. The preset optimal temperature value in the shopping mall is obtained according to the temperature and humidity analysis outside the shopping mall building, and the shopping mall central air-conditioning system is controlled to adjust the temperature in the shopping mall according to the preset heat exchange power. During the adjustment process, the perceived temperature of the corresponding area is obtained by analyzing the temperature and humidity information of each area in the shopping mall building, and the heat exchange power adjustment power of the temperature control module in the corresponding area is obtained according to the perceived temperature and crowd status information analysis. The cold and heat source modules are pre-adjusted according to the historical output power of the cold and heat sources, so that the output heat exchange power can meet the heat exchange demand power of each temperature control module when it is transported to each temperature control module through the heat exchange medium.

[0074] As an implementation mode of the present invention, the process of determining whether the preset heat exchange power of the temperature control module in each area is adjusted includes:

[0075] By formula Calculate the perceived temperature in the i-th region

[0076] in, is the air temperature monitored and collected by the temperature sensor in the i-th area, is the air humidity monitored and collected by the humidity sensor in the i-th area, and μ is the influence coefficient of humidity on the perceived temperature;

[0077] The body temperature With the preset temperature threshold [T p -T e ,T p +T e ] for comparison;

[0078] like or Adjusting the heat exchange power of the temperature control module in the i-th area;

[0079] like Then analyze the crowd status information in the area;

[0080] Among them, T p is the preset optimum temperature value, T e is the human body comfort temperature error value.

[0081] Through the above technical solution, this embodiment provides a method for determining whether the preset heat exchange power of the temperature control module in each area needs to be adjusted. Specifically, the temperature and humidity in each area are collected by the temperature sensor and humidity sensor in each area, and the formula The perceived temperature in each area is analyzed and obtained, where μ is the influence coefficient of humidity on the perceived temperature, which can be obtained by fitting experimental data. Then the perceived temperature is compared with the preset temperature threshold. If the perceived temperature is within the preset temperature threshold, it means that the current perceived temperature in the area is within the comfortable temperature range of the human body. Tourists will not feel uncomfortable when they are in this area. The crowd status information in the area can be further analyzed to determine whether the preset heat exchange power of the heat exchange module in the area needs to be adjusted. If the perceived temperature is not within the preset temperature threshold, it means that the current perceived temperature in the area is not within the comfortable temperature range of the human body, and the heat exchange power of the temperature control module needs to be adjusted. p To preset the optimum temperature value, it can be obtained by analyzing the collected outdoor environment information of the shopping mall, T e is the human body comfort temperature error value, which can be obtained based on multiple groups of experimental analyses.

[0082] As an implementation mode of the present invention, the process of adjusting the heat exchange power of the temperature control module in the i-th area includes:

[0083] like or Control the temperature control module in the i-th area to adjust the power accordingly based on the preset power. The adjusted power P Δt It can be obtained according to the following formula;

[0084]

[0085] Among them, S i is the spatial volume in the i-th region, is the real-time number of people collected by the surveillance camera in the i-th area, C x is the influence coefficient of human body on indoor temperature, and Q is the regional heat exchange demand power coefficient.

[0086] Through the above technical solution, this embodiment provides a method for adjusting the heat exchange power of the temperature control module in the corresponding interval. Specifically, when the perceived temperature in the interval is not in the comfortable temperature range of the human body, the formula The power size that needs to be adjusted for the temperature control module in this interval is analyzed and obtained. In the specific adjustment process, the adjustment is made based on the preset heat exchange power of the temperature control module in this interval, and the preset heat exchange power is preset according to the difference between the outdoor sensible temperature and the indoor preset optimal temperature value. Specifically, during the installation of the central air-conditioning in the shopping mall, it is related to the space size of each area set by the shopping mall and the speed of heat exchange between the shopping mall as a whole and the outside world. It can be obtained based on multiple groups of central air-conditioning operation experimental data of the shopping mall. When the heat exchange modules in each area maintain the preset heat exchange power state and there are no tourists, the sensible temperature in the shopping mall can be kept stable at the preset optimal temperature value indoors, and the direction of the heat exchange power adjustment of the heat exchange module can be based on whether the sensible temperature in the area is greater than or equal to. When the sensible temperature in the area is greater than the preset temperature threshold and the outdoor sensible temperature is also greater than the preset temperature threshold, the heat exchange module in the area increases the cooling power by a corresponding amount; when the sensible temperature in the area is greater than the preset temperature threshold and the outdoor sensible temperature is less than the preset temperature threshold, the heat exchange module in the area reduces the heating power by a corresponding amount; when the sensible temperature in the area is less than the preset temperature threshold and the outdoor sensible temperature is greater than the preset temperature threshold, the heat exchange module in the area reduces the cooling power by a corresponding amount; when the sensible temperature in the area is less than the preset temperature threshold and the outdoor sensible temperature is less than the preset temperature threshold, the heat exchange module in the area increases the heating power by a corresponding amount, wherein C x is the influence coefficient of human body on indoor temperature, which can be obtained based on multiple sets of experimental data; Q is the regional heat exchange demand power coefficient, which can be obtained based on empirical data.

[0087] As an implementation mode of the present invention, the process of determining whether the preset heat exchange power of the temperature control module in each area is adjusted further includes:

[0088] when hour,

[0089] The total number of people in the i-th area is obtained in real time through surveillance cameras, and the change curve of the total number of people is fitted by linear regression algorithm

[0090] Analyze the changes in the total number of people within the preset time interval [t1, t2];

[0091] By formula Calculate the average number of people in the corresponding area within the preset time interval [t1, t2]

[0092] Wherein, Δt=t2-t1, t1 and t2 are adjacent time nodes adjusted by the analysis module, and Δt is the interval time adjusted by the analysis module;

[0093] The average number of With the preset standard number of people Make a comparison;

[0094] like Then it is necessary to control the temperature control module in the i-th area to adjust the power accordingly based on the preset power. It can be obtained according to the following formula;

[0095]

[0096] Through the above technical solution, this embodiment provides a method for further analyzing whether the preset heat exchange power of the temperature control module in each area needs to be adjusted. Specifically, when the monitored body temperature in the corresponding area is within the preset temperature threshold, a change curve is obtained by fitting the change of the total number of people in the area, and then the average number of people in the area between the time node t1 adjusted by the current analysis module and the time node t2 adjusted by the next analysis module is obtained by analyzing the change curve. The average number of With the preset standard number of people If the average number of people is greater than the preset standard number of people, the temperature control module in the area needs to be controlled to adjust the corresponding heat exchange power at the preset heat exchange power. According to the formula The adjustment direction is to increase the cooling or heating power of the temperature control module in the area by the corresponding adjustment power.

[0097] As an embodiment of the present invention, the process of pre-adjusting the cold and hot source modules includes:

[0098] By formula Calculate the total power P required by all heat exchange modules in the shopping mall building A ;

[0099] The power P that the cold and hot source module needs to output is B =P A *(1-μ),

[0100] Among them, μ is the loss rate during the output process of the cold and hot source module;

[0101] The power P output by the cold and hot source modules at each time node t adjusted by the statistical analysis module B , the power change curve P required to be output by the cold and hot source module is fitted by linear regression algorithm B (t);

[0102] By formula P C (t) = P B (t+Δθ) calculates the real-time output power output P of the cold and hot source modules C (t),

[0103] Wherein, Δθ is the time taken for the heat exchange medium output by the cold and heat source modules to be transported to each temperature control module through the heat exchange pipeline.

[0104] Through the above technical solution, this embodiment provides a method for pre-adjusting the cold and hot source modules, by formula and P B =P A *(1-μ) Analyze and obtain the output power of the cold and heat sources when they meet all the heat exchange requirements in each shopping mall building, and then analyze the output power of the cold and heat sources at each time node to obtain the real-time output power of the cold and heat sources. This output power can meet the required heat exchange power of each heat exchange module after Δθ time, where Δθ is the time for the heat exchange medium output by the cold and heat source module to be transported to each temperature control module through the heat exchange pipeline. The specific time can be obtained based on the central air-conditioning system experiment in the corresponding shopping mall building.

[0105] As an embodiment of the present invention, the process of analyzing and obtaining the preset optimum temperature value includes:

[0106] By formula T p =(T w +RH W *μ-T sth )*α+T sth Calculate the preset optimal temperature value T p ;

[0107] Among them, T w is the outdoor temperature of the shopping mall building, RH w is the outdoor humidity of the shopping mall building, T sth is the standard comfortable temperature value for human body, and α is the temperature adjustment parameter.

[0108] The present embodiment provides a method for analyzing and obtaining a preset optimum temperature value. The preset optimum temperature value in the mall is obtained by analyzing the collected outdoor temperature and humidity of the shopping mall building in combination with the standard comfort temperature value of the human body. This optimum temperature value can avoid the low cooling temperature in the mall in summer and the large temperature difference between the inside and the outside, which may cause tourists to feel cold or even sick in the mall. It can also avoid tourists from sweating due to the high temperature in the mall after entering the mall in winter, and feeling cold and uncomfortable or even sick when leaving the mall later. Moreover, compared with the standard comfort temperature value of the human body, it is closer to the outdoor temperature. During the operation of the central air-conditioning system of the mall, it effectively reduces the power consumption and will not make tourists feel uncomfortable. Among them, α is a temperature adjustment parameter, which can be obtained by experiments on a large number of tourists.

[0109] As an embodiment of the present invention, the method further includes:

[0110] S5. Analyze and compare the temperature and humidity information monitored at adjacent adjustment time nodes in each area. If the perceived temperature obtained by the latest time node analysis is not between the perceived temperature obtained by the previous monitoring time node analysis and the preset optimal temperature value, generate a warning signal that the temperature control module corresponding to the area has a fault.

[0111] Through the above technical scheme, this embodiment provides a method for early warning of each temperature control module. Specifically, the temperature and humidity information monitored at adjacent adjustment time nodes in each interval are analyzed and compared. If the perceived temperature obtained by monitoring and analyzing the latest adjustment time node is not between the perceived temperature obtained by analyzing the previous monitoring time node and the preset optimal temperature value, it means that the adjustment of the heat exchange power of the temperature control module in the interval is unsuccessful, and the temperature control module in the interval may fail, and a warning signal of the failure of the temperature control module corresponding to the area is generated.

[0112] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A smart energy efficiency dual carbon management system, characterized in that: The system comprises: The collection module is used to collect environmental information and crowd status information of each area in the shopping mall building and outdoor environmental information; Central air conditioning system, the central air conditioning system includes a temperature control module and a cold and heat source module; Temperature control module, used to adjust the air temperature in the designated area; The cold and heat source module is used to provide heat exchange demand for all temperature control modules in the shopping mall building; The analysis module is used to determine the adjustment strategy of the temperature control module in the area according to the environmental information and the crowd status information, and to intelligently control the cold and hot source modules or generate early warning signals; The early warning module is used to execute early warning signals.

2. The method of using a smart energy efficiency dual carbon management system as claimed in claim 1 is characterized in that: The method comprises the following steps: S1, collecting temperature and humidity information of each area in the shopping mall building and temperature and humidity information outside the shopping mall building based on temperature sensors and humidity sensors; S2, collecting crowd status information in various areas of the shopping mall building based on surveillance cameras; S3. Perform a comprehensive analysis based on the crowd status information, temperature and humidity of each area to determine whether the preset heat exchange power of the temperature control module in each area needs to be adjusted. If adjustment is required, adjust the heat exchange power of the temperature control module in the corresponding area; S4. Preliminary adjustment is made to the operation of the cold and hot source modules according to the information on adjusting the heat exchange power of each temperature control module.

3. According to claim 2, a smart energy efficiency and dual carbon management method is characterized in that: The process of determining whether the preset heat exchange power of the temperature control module in each area is adjusted includes: By formula Calculate the perceived temperature in the i-th region in, is the air temperature monitored and collected by the temperature sensor in the i-th area, is the air humidity monitored and collected by the humidity sensor in the i-th area, and μ is the influence coefficient of humidity on the perceived temperature; The body temperature With the preset temperature threshold [T p -T e ,T p +T e ] for comparison; like or Adjusting the heat exchange power of the temperature control module in the i-th area; like Then analyze the crowd status information in the area; Among them, T p is the preset optimum temperature value, T e is the human body comfort temperature error value.

4. According to claim 3, a smart energy efficiency dual carbon management method is characterized in that: The process of adjusting the heat exchange power of the temperature control module in the i-th area includes: like or Control the temperature control module in the i-th area to adjust the power accordingly based on the preset power. The adjusted power P Δt It can be obtained according to the following formula; Among them, S i is the spatial volume in the i-th region, is the real-time number of people collected by the surveillance camera in the i-th area, C x is the influence coefficient of human body on indoor temperature, and Q is the regional heat exchange demand power coefficient.

5. According to claim 4, a smart energy efficiency dual carbon management method is characterized in that: The process of determining whether the preset heat exchange power of the temperature control module in each area is adjusted also includes: when hour, The total number of people in the i-th area is obtained in real time through surveillance cameras, and the change curve of the total number of people is fitted by linear regression algorithm Analyze the changes in the total number of people within the preset time interval [t1, t2]; By formula Calculate the average number of people in the corresponding area within the preset time interval [t1, t2] Wherein, Δt=t2-t1, t1 and t2 are adjacent time nodes adjusted by the analysis module, and Δt is the interval time adjusted by the analysis module; The average number of With the preset standard number of people Make a comparison; like Then it is necessary to control the temperature control module in the i-th area to adjust the power accordingly based on the preset power. It can be obtained according to the following formula; 6. According to claim 5, a smart energy efficiency and dual carbon management method is characterized in that: The process of pre-conditioning the cold and hot source modules includes: By formula Calculate the total power P required by all heat exchange modules in the shopping mall building A ; The power P that the cold and heat source module needs to output is B =P A *(1-μ), Among them, μ is the loss rate during the output process of the cold and hot source module; The power P output by the cold and hot source modules at each time node t adjusted by the statistical analysis module B , the power change curve P required to be output by the cold and hot source module is fitted by linear regression algorithm B (t); By formula P C (t) = P B (t+Δθ) calculates the real-time output power output P of the cold and hot source modules C (t), Wherein, Δθ is the time taken for the heat exchange medium output by the cold and heat source modules to be transported to each temperature control module through the heat exchange pipeline.

7. The intelligent energy efficiency and carbon management method according to claim 6 is characterized in that: The process of analyzing and obtaining the preset optimum temperature value includes: By formula T p =(T w +RH w *μ-T sth )*α+T sth Calculate the preset optimal temperature value T p ; Among them, T w is the outdoor temperature of the shopping mall building, RH w is the outdoor humidity of the shopping mall building, T sth is the standard comfortable temperature value for human body, and α is the temperature adjustment parameter.

8. The intelligent energy efficiency and carbon management method according to claim 7 is characterized in that: The method further comprises: S5. Analyze and compare the temperature and humidity information monitored at adjacent adjustment time nodes in each area. If the perceived temperature obtained by the latest time node analysis is not between the perceived temperature obtained by the previous monitoring time node analysis and the preset optimal temperature value, generate a warning signal that the temperature control module corresponding to the area has a fault.

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