Cooling Capacity Allocation Method, Device and Storage Medium for Intelligent Building

Abstract

The present application discloses a method, device, and storage medium for cold quantity allocation of an intelligent building. The present application relates to the technical field of air conditioner control. The cold quantity allocation method for the intelligent building includes: if a temperature setting instruction triggered by the air conditioner is detected, determining the set temperature corresponding to the temperature setting instruction; determining the expected cold quantity of the air conditioner according to the set temperature; obtaining the current cold storage quantity of the cold storage module; and determining the allocated cold quantity of the air conditioner according to the node level of the cold quantity pipeline associated with the air conditioner, the expected cold quantity, and the current cold storage quantity. Furthermore, the technical problem that the building air conditioner management solution in the related art may cause a large amount of electric energy to be consumed invalidly, resulting in power waste, is solved, and the technical effect of accurately supplying cold quantity and saving electric energy is achieved.

Description

Technical Field

[0001] The present application relates to the field of air conditioner control technology, and in particular to a cooling capacity allocation method, device and storage medium for an intelligent building. Background Art

[0002] Central air conditioning systems have become a standard temperature control solution for all types of office buildings. The current commonly used management model is that each office in the office building can independently control the cooling parameters of its air conditioner. This decentralized control method has significant disadvantages. Due to the differences in usage needs and personnel activities in each office and the lack of coordination, some areas are usually over-cooled or over-heated, causing the air conditioner to be in an unreasonable operating state for a long time. Therefore, the above solution will cause a large amount of electricity to be consumed ineffectively, resulting in a waste of electricity. Summary of the invention

[0003] The main purpose of this application is to provide a cooling capacity allocation method, device and storage medium for an intelligent building, aiming to solve the technical problem that traditional building air conditioning management solutions will cause a large amount of electricity to be consumed ineffectively, resulting in power waste.

[0004] To achieve the above-mentioned purpose, the present application provides a cooling capacity allocation method for an intelligent building, which is applied to a cooling capacity allocation system. The cooling capacity allocation system includes a cold storage module, a cooling capacity pipeline and an air conditioner. The cooling capacity allocation method for the intelligent building includes:

[0005] If a temperature setting instruction triggered by the air conditioner is detected, determining a set temperature corresponding to the temperature setting instruction;

[0006] Determining the expected cooling capacity of the air conditioner according to the set temperature;

[0007] Obtaining the current cold storage capacity of the cold storage module;

[0008] The allocated cooling capacity of the air conditioner is determined according to the node level of the cooling pipeline associated with the air conditioner, the expected cooling capacity and the current cooling capacity.

[0009] In one embodiment, the step of determining the expected cooling capacity of the air conditioner according to the set temperature comprises:

[0010] Acquire the indoor temperature of the working area where the air conditioner is located, and the outdoor temperature of the floor where the working area is located;

[0011] An expected cooling capacity is determined based on the set temperature, the indoor temperature, and the outdoor temperature.

[0012] In one embodiment, the step of determining the expected cooling capacity based on the set temperature, the indoor temperature and the outdoor temperature comprises:

[0013] determining a first difference between the set temperature and the indoor temperature;

[0014] determining a second difference between the indoor temperature and the outdoor temperature;

[0015] Obtaining the heat transfer coefficient of the floor where the working area is located;

[0016] determining a corrected cooling capacity according to the second difference and the heat transfer coefficient, and determining a first cooling capacity according to the first difference;

[0017] The expected cooling capacity is determined based on the sum of the first cooling capacity and the corrected cooling capacity.

[0018] In one embodiment, the step of determining the allocated cooling capacity of the air conditioner according to the node level of the cooling pipeline associated with the air conditioner, the expected cooling capacity and the current cooling capacity comprises:

[0019] Determining a correction factor associated with the node level;

[0020] Determining a first ratio of the number of working air conditioners to the number of all air conditioners;

[0021] determining a second cooling capacity according to the first ratio, the expected cooling capacity and the current cooling capacity;

[0022] The allocated cooling capacity is determined based on the second cooling capacity and the correction coefficient.

[0023] In one embodiment, the cooling capacity allocation system further includes a refrigeration pump, one end of the refrigeration pump is connected to the air conditioner through the cooling capacity pipeline, and the other end of the refrigeration pump is connected to the cold storage module through the cooling capacity pipeline. The step of determining the second cooling capacity according to the first ratio, the expected cooling capacity and the current cooling capacity includes:

[0024] Based on the building map, determining the refrigeration pump associated with the air conditioner;

[0025] Determine a refrigeration pump with the same node level and an assembly position less than or equal to a preset distance among the refrigeration pumps as a transit refrigeration pump;

[0026] Determining the transfer cooling capacity according to the sum of the current cooling capacity flow rates of the transfer refrigeration pumps and the transfer coefficient;

[0027] The second cooling capacity is determined according to the first ratio, the expected cooling capacity, the transfer cooling capacity and the current cold storage capacity.

[0028] In one embodiment, the step of determining the second cooling capacity according to the first ratio, the expected cooling capacity, the transfer cooling capacity and the current cooling capacity includes:

[0029] The difference between the expected cooling capacity and the transfer cooling capacity is used as the third cooling capacity;

[0030] taking the fourth cooling capacity as the product of the third cooling capacity and the first ratio;

[0031] Determining a unit cooling capacity upper limit based on the current cooling capacity divided by the total number of the air conditioners;

[0032] If the fourth cooling capacity is higher than the upper limit of the unit cooling capacity, the upper limit of the unit cooling capacity is used as the second cooling capacity; if the fourth cooling capacity is not higher than the upper limit of the unit cooling capacity, the fourth cooling capacity is used as the second cooling capacity.

[0033] In one embodiment, the method further includes:

[0034] At the cooling capacity settlement time, obtaining the total cooling capacity of each of the air conditioners on that day;

[0035] The cold storage capacity of the cold storage module is determined according to the total cold capacity of each of the air conditioners, the outdoor temperature of the day and the predicted temperature of the next day.

[0036] In one embodiment, the step of determining the cold storage capacity of the cold storage module according to the total cold capacity of each of the air conditioners, the outdoor temperature of the day, and the predicted temperature of the next day includes:

[0037] Acquire the trigger frequency of the temperature setting instruction corresponding to each of the air conditioners, wherein the trigger frequency includes a lowering frequency and a highering frequency;

[0038] Determining a target cooling capacity of the air conditioner according to the total cooling capacity and the trigger frequency;

[0039] The cold storage capacity of the cold storage module is determined based on the target cooling capacity of each of the air conditioners, the outdoor temperature of the day and the predicted temperature of the next day.

[0040] In addition, to achieve the above-mentioned purpose, the present application also provides a cooling capacity allocation device for an intelligent building, the cooling capacity allocation device for an intelligent building comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, the computer program being configured to implement the steps of the cooling capacity allocation method for the intelligent building as described above.

[0041] In addition, to achieve the above-mentioned purpose, the present application also provides a storage medium, which is a computer-readable storage medium, and the computer-readable storage medium stores a program for implementing the cold energy allocation method of the smart building. The program for implementing the cold energy allocation method of the smart building is executed by a processor to implement the steps of the cold energy allocation method of the smart building as described above.

[0042] The present application provides a method for allocating cooling capacity of an intelligent building. In the present application, if a temperature setting instruction triggered by the air conditioner is detected, the set temperature corresponding to the temperature setting instruction is determined; the expected cooling capacity of the air conditioner is determined according to the set temperature; the current cooling capacity of the cold storage module is obtained; and the allocated cooling capacity of the air conditioner is determined according to the node level of the cooling pipeline associated with the air conditioner, the expected cooling capacity and the current cooling capacity. That is, in the present application, a node level is assigned to each air conditioner, and the cooling capacity of the air conditioner is uniformly allocated by the cold storage module located in the basement of the building. Then, when the temperature setting instruction is triggered for each air conditioner, that is, when the user turns on the air conditioner or adjusts the temperature, the expected cooling capacity of the air conditioner is determined based on the set temperature, and then the node level of the cooling pipeline associated with the air conditioner, the expected cooling capacity and the current cooling capacity of the cold storage module are combined to determine the final allocated cooling capacity to the air conditioner, thereby solving the technical problem that the building air conditioning management scheme in the related technology will cause a large amount of electric energy to be consumed ineffectively, resulting in a waste of electricity, and achieving the technical effect of accurately supplying cooling capacity and saving electric energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0044] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0045] Figure 1 A flow chart of a first embodiment of a cooling capacity allocation method for an intelligent building of the present application;

[0046] Figure 2 A flow chart of the third embodiment of the cooling capacity allocation method for the intelligent building of the present application;

[0047] Figure 3 This is a schematic diagram of the structure of the cooling capacity allocation system of the intelligent building in this application;

[0048] Figure 4This is a schematic diagram of the hardware structure involved in the cold quantity allocation device of the intelligent building in this application.

[0049] The implementation, functional features, and advantages of this application will be further described with reference to the embodiments and the accompanying drawings. Detailed implementation manners

[0050] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of this application and are not used to limit this application.

[0051] To better understand the technical solutions of this application, the following will be described in detail with reference to the accompanying drawings of the specification and specific implementation manners.

[0052] Currently, for various office buildings, the central air-conditioning system has become a standard temperature control solution. The currently commonly used management mode is that each office in the office building can independently control the cold quantity parameters of its affiliated air conditioner. This decentralized control method has significant drawbacks. Due to the differences in the usage requirements and personnel activities of each office and the lack of coordination, there is usually a situation where some areas are over-cooled or over-heated, resulting in the air conditioner being in an unreasonable operating state for a long time. Therefore, the above solution will cause a large amount of electric energy to be consumed ineffectively, resulting in a waste of electricity.

[0053] The main solution of this application is: if a temperature setting instruction triggered by the air conditioner is detected, determine the set temperature corresponding to the temperature setting instruction; determine the expected cold quantity of the air conditioner according to the set temperature; obtain the current cold storage capacity of the cold storage module; determine the allocated cold quantity of the air conditioner according to the node level of the cold quantity pipeline associated with the air conditioner, the expected cold quantity, and the current cold storage capacity.

[0054] In this application, each air conditioner is assigned a node level, and the cold quantity of the air conditioner is uniformly allocated by the cold storage module located underground in the building. Then, when each air conditioner is triggered with a temperature setting instruction, that is, when the user turns on the air conditioner or adjusts the temperature, the expected cold quantity of the air conditioner is determined based on the set temperature. Then, by combining the node level of the cold quantity pipeline associated with the air conditioner, the expected cold quantity, and the current cold storage capacity of the cold storage module, the allocated cold quantity finally to be assigned to the air conditioner is determined, thereby solving the technical problem that the building air-conditioning management solution in the related art will cause a large amount of electric energy to be consumed ineffectively and result in a waste of electricity, and achieving the technical effect of accurately supplying cold quantity and saving electric energy.

[0055] It should be noted that the execution subject of this embodiment may be a cooling capacity allocation system, or a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or a cooling capacity allocation device of a smart building that can realize the above functions, etc., and this embodiment does not specifically limit this. The following takes the cooling capacity allocation system as an example to illustrate this embodiment and the following embodiments.

[0056] Based on this, the first embodiment of the present application proposes a cooling capacity allocation method for a smart building, please refer to Figure 1 The cooling capacity allocation method of the intelligent building includes steps S10 to S40:

[0057] Step S10: If a temperature setting instruction triggered by the air conditioner is detected, a set temperature corresponding to the temperature setting instruction is determined.

[0058] In this embodiment, the cold capacity allocation system includes a cold storage module, a cold capacity pipeline and an air conditioner. The cold storage module is connected to each air conditioner through the cold capacity pipeline to transmit cold capacity to the air conditioner. The temperature setting instruction is an instruction containing a set temperature. The set temperature is the temperature set for the air conditioner, that is, the temperature expected to be reached in the working area where the air conditioner is located.

[0059] As an optional implementation, a start instruction for the air conditioner is detected, a default temperature or a historical set temperature is obtained, a temperature setting instruction is generated, and a temperature corresponding to the temperature setting instruction is determined as the set temperature.

[0060] As another optional implementation, the air conditioner has been started, and the adjusted temperature is determined for the temperature adjustment instruction of the air conditioner, and the temperature setting instruction is generated with the adjusted temperature, that is, the adjusted temperature is used as the set temperature.

[0061] Step S20, determining the expected cooling capacity of the air conditioner according to the set temperature.

[0062] In this embodiment, the expected cooling capacity is the cooling capacity that the air conditioner expects the cold storage module to provide. When the air conditioner outputs cooling capacity, the cooling capacity source is the air conditioner outdoor unit connected to the air conditioner and the cold storage module.

[0063] As an optional implementation, the operation of the air conditioner is determined according to the set temperature so that the indoor temperature changes to the set temperature, and the required cooling capacity is used as the expected cooling capacity.

[0064] As another optional implementation, the air conditioner operation is determined according to the set temperature so that the indoor temperature changes to the set temperature. The required cooling capacity is taken as the demand cooling capacity, the supply cooling capacity of the air conditioner outdoor unit is determined, and the difference between the demand cooling capacity and the supply cooling capacity is taken as the expected cooling capacity.

[0065] Step S30, obtaining the current cold storage capacity of the cold storage module.

[0066] In this embodiment, the cold storage module is located underground in the building, which helps to preserve cold. The cold storage module stores cold at night or during periods of low electricity costs. The current cold storage refers to the capacity of cold currently remaining in the cold storage module.

[0067] Step S40, determining the allocated cooling capacity of the air conditioner according to the node level of the cooling pipeline associated with the air conditioner, the expected cooling capacity and the current cold storage capacity.

[0068] In this embodiment, each air conditioner is associated with a node level according to its installation location. The node level contains two dimensions, the first dimension is the floor, and the second dimension is the proximity to the refrigeration pump. For example, the cold storage module is located in the basement of the building, connected to the refrigeration pump through the cold capacity pipeline, and then at least one refrigeration pump is installed in one floor, and the second dimension is determined according to the relative distance between the air conditioner and the refrigeration pump connected to it. The allocated cold capacity is the final cold capacity transmitted by the cold storage module to the air conditioner.

[0069] As an optional implementation, a correction coefficient is determined according to the node level, the second cooling capacity is determined according to the expected cooling capacity and the current cold storage capacity, and the allocated cooling capacity is determined according to the second cooling capacity and the correction coefficient.

[0070] As an overall implementation method, the cold capacity allocation system is mainly composed of a cold storage module, cold capacity pipelines and multiple air conditioners. The cold storage module is placed underground in the building and uses nighttime or low electricity price periods to store cold. It is interconnected with each air conditioner through cold capacity pipelines to build a cold capacity transmission network. The system continuously monitors the operating status and related instructions of the air conditioner. When a startup instruction for the air conditioner is detected, the default temperature (pre-set initial temperature value) or historical set temperature of the air conditioner is first obtained to generate a temperature setting instruction containing the set temperature, and the temperature is determined as the set temperature. For example, when the air conditioner in an office is started for the first time on a weekday morning, the system retrieves the average set temperature of 24°C (degrees Celsius) in the morning of the office on weekdays in the past week from the preset database, and uses this temperature as the set temperature for this startup. If the air conditioner is already in the startup state, when a temperature adjustment instruction for the air conditioner is received, the system directly determines the adjusted temperature and generates a temperature setting instruction based on it. The adjusted temperature is the new set temperature. For example, when the number of office workers increases in the afternoon and they feel stuffy, the air conditioner temperature is lowered from 26°C to 22°C, and the system immediately identifies 22°C as the new set temperature. The expected cooling capacity is the cooling capacity required to achieve the set temperature, and its sources include the air conditioner outdoor unit connected to the air conditioner and the cold storage module. One way is to calculate the cooling capacity required to change the indoor temperature to the set temperature based on the set temperature through the built-in thermodynamic model, and use this cooling capacity as the expected cooling capacity. For example, for an office with an area of ​​30 square meters and a floor height of 3 meters, the initial indoor temperature is 28°C and the set temperature is 22°C. According to parameters such as the specific heat capacity of air, the indoor space volume, and the temperature difference, the required expected cooling capacity is calculated to be 50kW・h (kilowatt-hours). Another optional method is to first determine the required cooling capacity to make the indoor temperature reach the set temperature, and then obtain the supply cooling capacity that the air conditioner outdoor unit can currently provide. The difference between the two is the expected cooling capacity. For example, in the above office, the required cooling capacity is calculated to be 50kW・h. At this time, the maximum cooling capacity of the air conditioner outdoor unit is 30kW・h due to factors such as the outdoor ambient temperature. The expected cooling capacity is 20kW・h, which needs to be supplemented by the cold storage module. The cold storage module is located underground in the building and has good thermal insulation performance to reduce the loss of cold. The system monitors and obtains the current cold storage capacity data in real time through sensors installed inside the cold storage module. The data represents the cold storage capacity currently available for allocation in the cold storage module. For example, at a certain moment, the current cold storage capacity of the cold storage module is detected to be 800kW・h. Each air conditioner is assigned a corresponding node level based on its floor location and its proximity to the refrigeration pump. The node level contains two dimensional information. For example, in a 20-story office building, floors 1 to 5 are low-floor areas, floors 6 to 15 are middle-floor areas, and floors 16 to 20 are high-floor areas. Each floor is distributed with several refrigeration pumps connected to the cold pipeline.For the air conditioner located on the 8th floor and close to the chiller pump on this floor, its node level is "middle floor" in the floor dimension and "close" in the proximity dimension to the chiller pump. The system determines the correction coefficient based on the node level, which comprehensively considers factors such as the pressure loss caused by the height difference of the floors and the influence of the distance of the cold transmission on the cold loss. For example, for the node level of "middle floor-close" mentioned above, the correction coefficient is determined to be 1.1 through the pre-set correction coefficient table. Then, the second cold capacity is determined based on the expected cold capacity and the current cold storage capacity. If the current cold storage capacity is sufficient, the second cold capacity can be directly equal to the expected cold capacity; if the current cold storage capacity is limited, it needs to be allocated proportionally. For example, if the expected cold capacity is 30kW・h, and the current cold storage capacity can only meet 60% of the demand, the second cold capacity is determined to be 18kW・h. Finally, the allocated cold capacity is determined based on the second cold capacity and the correction coefficient. Using the above example as an example, the allocated cooling capacity = the second cooling capacity × correction coefficient, that is, 18kW・h × 1.1 = 19.8kW・h. This is the cooling capacity that the cold storage module ultimately transmits to the air conditioner, thereby achieving precise cooling capacity allocation and avoiding energy waste.

[0071] For example, a 15-story office building, each floor has an area of ​​1,000 square meters, and is divided into 10 offices on average. Each office is equipped with an air conditioner, which is connected to the cooling pipe of the central air conditioning system and is supported by the underground cold storage module. On a hot summer afternoon, the indoor temperature of Office A on the 5th floor reached 29°C. The office staff started the air conditioner and set the temperature to 24°C. The cooling allocation system performs cooling allocation according to the following steps: First, the system detects the start-up instruction and the set temperature of 24°C, and determines it as the set temperature for this time. Then, based on the spatial parameters of Office A (100 square meters, floor height 3 meters), the indoor and outdoor temperature difference, and the heat transfer coefficient of the building envelope, the built-in thermodynamic algorithm calculates that the cooling required to reduce the indoor temperature to 24°C is 40kW・h (assuming that the air conditioner outdoor unit can provide 25kW・h of cooling under the current working conditions), and the expected cooling is determined to be 15kW・h (40kW・h -25kW・h). Next, the system obtains the current cold storage capacity of the underground cold storage module, which is 500kW・h. Finally, since the air conditioner in Office A is located on a low floor and is at a moderate distance from the refrigeration pump on the same floor, its node level is determined to be "low floor-medium", and the corresponding correction coefficient is 1.05. After calculation, the second cooling capacity is 15kW・h (the current cold storage capacity is sufficient), then the allocated cooling capacity = 15kW・h × 1.05 = 15.75kW・h. The cold storage module delivers cold capacity to the air conditioner in Office A according to this allocated cooling capacity, ensuring that the indoor temperature can approach the set temperature efficiently and energy-savingly, while avoiding energy waste caused by over-cooling, and realizing intelligent cooling capacity management and energy consumption optimization for the entire building.

[0072] In the present application, a node level is assigned to each air conditioner, and the cooling capacity of the air conditioner is uniformly allocated by the cold storage module located in the basement of the building. Then, when the temperature setting instruction is triggered for each air conditioner, that is, when the user turns on the air conditioner or adjusts the temperature, the expected cooling capacity of the air conditioner is determined based on the set temperature, and then the node level of the cooling pipeline associated with the air conditioner, the expected cooling capacity and the current cooling capacity of the cold storage module are combined to determine the final allocated cooling capacity to the air conditioner. This solves the technical problem in the related art that the building air conditioning management scheme will cause a large amount of electricity to be consumed ineffectively, resulting in a waste of electricity, and achieves the technical effect of accurately supplying cooling capacity and saving electricity.

[0073] Based on the first embodiment, in the second embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to the above description, and will not be described in detail later. On this basis, step S20 includes:

[0074] Step S21, obtaining the indoor temperature of the working area where the air conditioner is located, and the outdoor temperature of the floor where the working area is located;

[0075] Step S22, determining the expected cooling capacity based on the set temperature, the indoor temperature and the outdoor temperature.

[0076] In this embodiment, the indoor temperature refers to the average temperature of the air in a specific enclosed space (i.e., a work area, such as an office, a conference room, etc.) served by the air conditioner, which is monitored and collected in real time by a temperature sensor installed at a suitable location in the work area (usually avoiding direct sunlight, close to the personnel activity area, and representing the overall room temperature). For example, in an office with an area of ​​50 square meters and a floor height of 3 meters, the temperature sensor may be installed on a wall 1.5 meters above the ground and near the center of the room, and the indoor air temperature data is collected once every certain period of time (such as 5 minutes) and transmitted to the control unit of the cooling capacity allocation system. The outdoor temperature refers to the temperature of the outdoor ambient air around the floor of the building where the work area is located. Generally, an outdoor temperature sensor is installed on each floor or every few floors on the outer wall of the building to measure the outdoor air temperature near the floor. These sensors need to be installed in a location that can accurately reflect the outdoor ambient temperature and avoid interference from factors such as the building's own heat radiation and vents, such as the outer wall on the north side of the building, about 2 meters above the ground. The outdoor temperature data will also be transmitted to the cooling capacity allocation system in real time to provide a basis for subsequent cooling capacity calculations. The data update frequency can be consistent with the indoor temperature sensor or set according to actual needs. The set temperature is the indoor air temperature value that the air conditioner is set by the user to achieve, which represents the comfort requirements of the personnel in the working area. For example, in summer, the user may set the air conditioner to 24°C, indicating that the indoor temperature is expected to be maintained at this relatively cool and comfortable level. The expected cooling capacity is the cooling capacity that the air conditioner is expected to obtain from the cold storage module under the current indoor and outdoor temperature conditions in order to make the indoor temperature reach the set temperature. The calculation process is based on thermodynamic principles and a mathematical model pre-set in the cooling capacity allocation system. The model takes into account the influence of multiple factors on the cooling demand, such as indoor and outdoor heat exchange, the heat transfer coefficient of the building envelope structure, and the heat generation of indoor personnel and equipment.

[0077] As an optional implementation, first, the system reads the values ​​of indoor temperature (Tin), outdoor temperature (Tout) and set temperature (Tset) from the acquired real-time data. For example, the indoor temperature is 28°C, the outdoor temperature is 35°C, and the set temperature is 24°C. Then, according to the design parameters and historical operation data of the building, the parameters such as the heat transfer coefficient of the building envelope (K), the heating power of indoor personnel and equipment (Qint), and the space volume (V) corresponding to the work area are determined. Assume that the heat transfer coefficient of the building envelope of the office is measured to be 2 watts per square meter Celsius, the total heating power of indoor personnel and equipment is 1000 watts, and the space volume is 150 cubic meters. Then, the expected cooling capacity (Qe) is calculated using the following formula: Qe = (Tin - Tset) * K * A + V * ρ * cp * (Tin - Tset) + Qint - (Tset - Tout) * K *A. Among them, ρ is the air density, which is about 1.2 kilograms per cubic meter, cp is the specific heat capacity of air, which is about 1.005 kilojoules per kilogram of degrees Celsius, and A is the surface area of ​​the enclosure structure (assuming that the office is a rectangular space with a length of 10 meters, a width of 5 meters, and a height of 3 meters, the surface area of ​​the enclosure structure is 190 square meters). Substituting the above values ​​into the formula, we can get: Qe = (28 - 24) * 2 * 190 + 150 * 1.2 * 1.005 * (28 - 24) + 1000 - (24 - 35) * 2 *190; Qe = 1520 + 723.6 + 1000 + 4180; Qe = 7423.6 watts, which is approximately equal to 7.42 kilowatts.

[0078] Through the above steps, the expected cooling capacity of the air conditioner can be accurately determined according to the set temperature, indoor temperature and outdoor temperature, providing key data support for the subsequent cooling capacity distribution of the cold storage module and the air conditioner outdoor unit, thereby realizing precise cooling capacity allocation of smart buildings and improving energy utilization efficiency and indoor comfort.

[0079] As another optional implementation, step S22 includes:

[0080] Step S221, determining a first difference between the set temperature and the indoor temperature.

[0081] In this embodiment, set temperature (Tset): the target indoor temperature value set by the user through the control terminal of the air conditioner (such as a remote control, an intelligent control panel, etc.) according to the user's expectation of the indoor environmental comfort. For example, in a summer office scene, the user may set it to 24°C to create a cool and comfortable working environment. Indoor temperature (Tin): the average indoor air temperature obtained by real-time monitoring by a temperature sensor installed at a specific location in the working area served by the air conditioner. The sensor is generally placed in a place that can represent the overall indoor temperature conditions, such as the center of the room and about 1.5 meters above the ground, to avoid direct interference from local heat sources (such as computers, lighting equipment, etc.) or cold sources (such as vents), so as to ensure the accuracy and reliability of the measurement, and its value reflects the actual thermal environment state of the room at the moment. The first difference (ΔT1): obtained by calculating the difference between the set temperature and the indoor temperature, that is, ΔT1 = Tset - Tin. This difference indicates the magnitude and direction of the indoor temperature adjustment. If ΔT1 is a positive value, it means that the indoor temperature needs to be lowered; if it is a negative value, it means that the indoor temperature needs to be increased. Its absolute value has a direct impact on the calculation of subsequent cooling demand and is one of the key intermediate variables for determining the expected cooling capacity.

[0082] Step S222, determining a second difference between the indoor temperature and the outdoor temperature.

[0083] In this embodiment, outdoor temperature (Tout): the outdoor air temperature value collected by the outdoor temperature sensor installed on the outer wall of the building at the corresponding floor position. The installation location of the sensor needs to be carefully selected, and should avoid interference factors such as direct sunlight, building shadows, and vents to accurately reflect the actual outdoor air temperature conditions. It is usually selected on the north side of the building at a height of about 2 meters above the ground. The outdoor temperature reflects the thermal environment conditions outside the building and is one of the important factors affecting indoor heat transfer and cooling demand. The second difference (ΔT2): calculate the difference between the indoor temperature and the outdoor temperature, that is, ΔT2 = Tin - Tout. This difference shows the temperature difference between indoor and outdoor, and its positive and negative values ​​and size reflect the trend and intensity of heat transfer from outdoor to indoor. When ΔT2 is a positive value, it indicates that the indoor temperature is higher than the outdoor temperature, and there is a trend of natural heat transfer from indoor to outdoor; when ΔT2 is a negative value, it indicates that the outdoor heat has a tendency to transfer to the indoor, which is of great significance for evaluating the heat load of the building envelope and determining the required cooling compensation. It is one of the key parameters for calculating the corrected cooling.

[0084] Step S223, obtaining the heat transfer coefficient of the floor where the working area is located.

[0085] In this embodiment, the heat transfer coefficient (K): also known as the heat transfer coefficient, is a parameter that comprehensively reflects the thermal insulation performance of the building envelope (covering walls, windows, roofs, etc.). It represents the amount of heat transferred through the envelope structure per unit area in a unit time when the indoor and outdoor temperature difference is 1°C (in units of W / (m²・°C)). The size of the heat transfer coefficient depends on factors such as the type, thickness, construction method of the building materials, and the sealing of doors and windows. For different buildings or different floors of the same building, the heat transfer coefficient may be different due to differences in their envelope structures. This parameter is generally obtained through building design data, professional thermal performance tests, or statistical analysis of historical operating data. Its accuracy is crucial for accurately calculating the cooling demand, and directly affects the calculation results of the corrected cooling and expected cooling.

[0086] Step S224, determining a corrected cooling capacity according to the second difference and the heat transfer coefficient, and determining a first cooling capacity according to the first difference.

[0087] In this embodiment, determining the first cooling capacity according to the first difference includes determining the required cooling capacity according to the first difference, and determining the first cooling capacity according to the difference between the cooling capacity of the air conditioner corresponding to the air conditioner outdoor unit and the required cooling capacity.

[0088] Corrected cooling capacity (Qadj): The part of the cooling demand that is corrected by taking into account the indoor and outdoor temperature difference and the heat transfer characteristics of the enclosure structure. The calculation formula is Qadj = ΔT2 × K × A, where A is the surface area of ​​the enclosure structure (in m²). This part of cooling capacity is mainly used to compensate for the heat transferred into the room through the enclosure structure due to the indoor and outdoor temperature difference, ensuring that the indoor temperature can be stabilized near the set temperature, and is one of the important components of the expected cooling capacity. Required cooling capacity (Qreq): The total cooling capacity theoretically required to make the indoor temperature reach the set temperature without considering the cooling capacity of the air conditioner outdoor unit. The calculation formula is Qreq = V × ρ × cp × |ΔT1| + Qint, where V is the spatial volume of the working area (in m³), ​​ρ is the air density (about 1.2 kg / m³), cp is the specific heat capacity of air (about 1.005 kJ / (kg・°C)), and Qint is the total heat generated by indoor personnel, equipment, etc. (in W). The required cooling capacity reflects the total cooling capacity required for the indoor environment to reach the set temperature, and is the basis for the subsequent calculation of the first cooling capacity and the expected cooling capacity. Cooling capacity of the air conditioner outdoor unit (Qoutdoor): The cooling capacity that the air conditioner outdoor unit can provide under the current operating conditions, usually in watts (W). This parameter can be obtained through the technical specifications of the air conditioner outdoor unit or actual operation tests. Its value represents the contribution of the air conditioner outdoor unit to indoor cooling, and together with the required cooling capacity, it determines the size of the first cooling capacity. First cooling capacity (Q1): When the required cooling capacity is greater than the cooling capacity of the air conditioner outdoor unit, the difference between the two is the first cooling capacity, that is, Q1 = Qreq -Qoutdoor. This part of cooling capacity is the additional cooling capacity that needs to be provided by the cold storage module when the air conditioner outdoor unit is insufficient. It is a key component of the expected cooling capacity, and its calculation result directly affects the cooling capacity allocation strategy of the cold storage module.

[0089] Step S225: taking the expected cooling capacity as the sum of the first cooling capacity and the corrected cooling capacity.

[0090] In this embodiment, expected cooling capacity (Qexp) is the cooling capacity that the air conditioner expects to obtain from the cold storage module, which is used to supplement the insufficient cooling of the air conditioner outdoor unit and compensate for the indoor and outdoor heat transfer. The calculation formula is Qexp = Q1 + Qadj. By adding the first cooling capacity and the corrected cooling capacity, the cooling capacity that the cold storage module should provide to achieve the indoor temperature stable at the set temperature under the current indoor and outdoor temperature conditions and the operating conditions of the air conditioner outdoor unit is obtained, thereby providing an accurate basis for the cooling capacity allocation of the cold storage module, achieving efficient and energy-saving operation of the central air-conditioning system of the intelligent building, and minimizing energy consumption while ensuring indoor comfort.

[0091] For example, an office on the 10th floor has an area of ​​50 m², a floor height of 3 m, and a surface area of ​​160 m². There are 5 office workers and some office equipment in the room. According to statistics, the total heat generated by the indoor workers and equipment Qint is about 1000 W. Assume that at a certain moment, the indoor temperature Tin is 28°C, the outdoor temperature Tout is 32°C, and the user sets the air conditioner temperature Tset to 24°C. By querying the architectural design data, it is known that the heat transfer coefficient K of this floor is 2 W / (m²・°C). First, calculate the first difference: ΔT1 = Tset - Tin = 24 - 28 = -4°C (the negative sign indicates that the indoor temperature needs to be lowered). Then, calculate the second difference: ΔT2 = Tin - Tout = 28 - 32 = -4°C. Next, calculate the corrected cooling capacity: Qadj = ΔT2 × K × A = (-4) × 2 × 160 = 1280 W. Then calculate the required cooling capacity: V = 50 × 3 = 150 m³. Qreq = V × ρ × cp × |ΔT1| + Qint = 150 × 1.2 ×1.005 × 4 + 1000 = 1722.4 W. The cooling capacity Qoutdoor of the air conditioner outdoor unit is 1000 W, so the first cooling capacity is: Q1 = Qreq - Qoutdoor = 1722.4 - 1000 = 722.4 W. Finally, calculate the expected cooling capacity: Qexp = Q1 + Qadj = 722.4 + 1280 = 2002.4 W ≈ 2 kW.

[0092] In this scenario, in order to reduce the indoor temperature from 28°C to the set 24°C, when the outdoor temperature is 32°C and the air conditioner outdoor cooling capacity is 1000 W, the air conditioner expects to obtain about 2 kW of cooling capacity from the cold storage module to meet the indoor cooling demand, achieve comfortable indoor environmental temperature control, and optimize the energy efficiency of the entire central air-conditioning system.

[0093] By adopting the methods of determining a first difference between the set temperature and the indoor temperature; determining a second difference between the indoor temperature and the outdoor temperature; obtaining a heat transfer coefficient of the floor where the working area is located; determining a corrected cooling capacity based on the second difference and the heat transfer coefficient, and determining a first cooling capacity based on the first difference; and using the sum of the first cooling capacity and the corrected cooling capacity as the expected cooling capacity, the accuracy of the expected cooling capacity that the air conditioner expects to obtain from the cold storage module is improved, thereby reducing the waste of invalid electricity.

[0094] Based on any of the above embodiments, the third embodiment of the present application proposes a cooling capacity allocation method for a smart building, step S40, comprising:

[0095] Step S41, determining the correction coefficient of the node level association;

[0096] Step S42, determining a first ratio of the number of working air conditioners to the number of all air conditioners;

[0097] Step S43, determining a second cooling capacity according to the first ratio, the expected cooling capacity and the current cooling capacity;

[0098] Step S44: determining the allocated cooling capacity based on the second cooling capacity and the correction coefficient.

[0099] As an optional implementation, first, the cooling pipe system of the building is modeled, and the node location information of each air conditioner is entered into the system. The node level not only considers the floor factor, but also integrates the layout and length information of the cooling pipe. For example, the node farther away from the cold storage module and with more pipe elbows and resistance components has a relatively low level and a corresponding correction coefficient, so as to compensate for the loss of cooling during transmission. Through a pre-set algorithm, the correction coefficient of each node is dynamically calculated according to the topological position and distance information of the node in the pipe system. The system monitors the working status of all air conditioners in real time, and obtains the opening or closing signal of each air conditioner through the communication interface with the air conditioner or the sensor installed on the circuit. At a certain time interval (such as 5 minutes), the number of air conditioners currently in working state is counted and compared with the total number of all air conditioners in the building, and the first ratio of the working air conditioners to all air conditioners is calculated. This ratio reflects the overall load of the current system. When the ratio is high, it means that more air conditioners are running at the same time, and the cooling distribution of the system needs to be more cautious and optimized to avoid insufficient cooling in some areas. When the system receives the cooling demand (i.e., expected cooling capacity) of a certain air conditioner, it makes a preliminary allocation based on the cooling capacity of the current cold storage module. If the current cooling capacity is sufficient and the first ratio is low, it means that the overall system load is light, and the expected cooling demand of the air conditioner can be met first. At this time, the second cooling capacity is approximately equal to the expected cooling capacity. However, if the first ratio is high, it means that the system load is heavy. In order to ensure that all working air conditioners can obtain a certain amount of cooling supply and avoid overheating of some areas, it is necessary to reduce the expected cooling capacity according to a certain proportion to obtain the second cooling capacity. For example, a linear reduction method can be used to adjust the expected cooling capacity according to the size of the first ratio and a preset proportional coefficient (such as between 0.8 and 1, which decreases as the ratio increases) to ensure that the cooling capacity distribution is more balanced under high system load. Finally, the calculated second cooling capacity is multiplied by the correction coefficient associated with the node level to obtain the final allocated cooling capacity for the air conditioner. The function of the correction coefficient is to further adjust the cooling capacity to compensate for the cooling capacity transmission loss caused by the node position. For example, if an air conditioner is located on a higher floor with longer pipes, its correction coefficient is 1.2. When the second cooling capacity is 10kW, the allocated cooling capacity is 10kW *1.2 = 12kW, ensuring that the air conditioner can obtain sufficient cooling capacity to meet the cooling needs of the area where it is located. At the same time, it also takes into account the cooling distribution balance and transmission loss compensation of the entire system.

[0100] As another optional implementation, different priorities are set for each node level. The priority division is not only based on the floor and pipeline location, but also takes into account factors such as the use function and population density of the area. For example, the priority of the air conditioner node in the office area may be higher than that of the node in the public corridor and other areas. According to the priority level, a corresponding correction coefficient is assigned to each node level. The higher the priority, the smaller the correction coefficient, so as to ensure that important areas have an advantage in cooling capacity allocation. At the same time, the system will dynamically adjust the correction coefficient based on historical operation data and real-time environmental information (such as outdoor temperature change trends, personnel activity patterns in different time periods, etc.). For example, in the hot summer afternoon, the personnel activities in the office area are frequent and the demand for cooling capacity is large. At this time, the correction coefficient of the office area node is appropriately reduced, and the cooling capacity allocation ratio is increased to improve the indoor comfort; at night or on holidays, when the office area is unused, the correction coefficient is increased to reduce cooling capacity allocation and avoid unnecessary energy waste. In addition to monitoring the switch status of the air conditioner, the intelligent monitoring system is also combined with indoor personnel activity sensors and light sensors to determine whether the area where the air conditioner is located really needs cooling. For example, if there is no one in an office and the light intensity is low, even if the air conditioner is turned on, the system will regard it as an air conditioner that is not actually working, and will not be included in the statistical scope when calculating the first ratio. This can more accurately reflect the actual cooling demand of the system and avoid unreasonable cooling distribution caused by the air conditioner being turned on by mistake. In this way, the first ratio is updated at regular intervals to provide a more accurate basis for subsequent cooling allocation decisions. The system establishes a cold storage prediction model to predict the change in the cold storage capacity of the cold storage module in the next few hours based on the current time, outdoor temperature, historical electricity consumption data, and weather forecast for a period of time in the future. Combined with the current expected cooling demand and the first ratio of the working air conditioner, a dynamic cooling allocation strategy is formulated. If it is predicted that the future cooling capacity is sufficient and the first ratio is low, the system can allocate the expected cooling capacity in full to each air conditioner, and the second cooling capacity is equal to the expected cooling capacity. However, if it is predicted that the cooling capacity will be tight in the future or the first ratio is high, the system will start the intelligent allocation algorithm. For example, according to the priority and temperature setting of different areas, the expected cooling capacity is weightedly allocated, giving priority to meeting the basic cooling demand of high-priority areas, while appropriately reducing the cooling supply of low-priority areas, and obtaining a reasonable second cooling capacity allocation plan. After determining the second cooling capacity, the final cooling capacity is calculated based on the correction coefficient of each air conditioner node. For nodes with high priority and small correction coefficients, the cooling capacity allocated is closer to the second cooling capacity to ensure the comfort of key areas; while for nodes with low priority and large correction coefficients, the cooling capacity allocated is relatively reduced, and cooling resources are saved as much as possible while meeting the basic cooling demand.In this way, intelligent cooling allocation based on node priority and cooling capacity prediction is achieved, which improves the energy efficiency and comfort of the central air-conditioning system of the entire building, while meeting the personalized needs of different areas.

[0101] Optionally, step S43 includes:

[0102] Step S431, determining the refrigeration pump associated with the air conditioner based on the building map.

[0103] In this embodiment, refer to Figure 3 , Figure 3 An example of a cold allocation system is shown, in which the lower right corner is a cold storage module, which is shown to have 10,000 cubic meters of refrigerant. The refrigerant flows to each freezing pump, cold storage host and refrigeration host through the cold pipeline. The end, i.e., the air conditioner, is divided into a high zone, a low zone and a middle zone in the figure. Each air conditioner is connected to a freezing pump. The cold allocation system also includes a freezing pump, one end of which is connected to the air conditioner through the cold pipeline, and the other end of which is connected to the cold storage module through the cold pipeline. The building map is a digital presentation of the layout of the cold allocation system in the entire building, which includes the location information and connection relationship of the cold storage module, cold pipeline, air conditioner, freezing pump and other equipment, and is displayed in the software interface of the control system in a two-dimensional or three-dimensional form, so that the system can quickly query and locate the location and association of each component, and provide an intuitive topological structure basis for subsequent cold allocation decisions. The associated chiller pump is a chiller pump that is directly connected to a specific air conditioner in the cooling pipe network and is responsible for transferring cooling from the cold storage module to the air conditioner, or transferring heat generated by the air conditioner back to the cold storage module (in some heat recovery systems). Through the pre-set connection lines and equipment identifiers in the building map, the system can accurately identify the chiller pump corresponding to each air conditioner, which is the basic link for subsequent cooling distribution and deployment, ensuring that cooling can be accurately transferred between the cold storage module and the air conditioner to maintain a stable indoor temperature.

[0104] Step S432, determining the freezing pumps with the same node level and whose assembly positions are less than or equal to a preset distance among the freezing pumps as transit freezing pumps.

[0105] In this embodiment, the node level is a level identification that is comprehensively evaluated based on factors such as the importance of the location of the refrigeration pump in the cold allocation system, the priority of the service area, and its relative distance from the cold storage module and the key load area. For example, a refrigeration pump close to the core office area or an area with high temperature requirements may have a higher node level, while a refrigeration pump serving an auxiliary area or an area with strong tolerance to temperature fluctuations has a relatively low node level. The division of node levels helps to prioritize the cold demand of key areas in the cold allocation process, achieve reasonable allocation and efficient utilization of resources, and also provides a screening dimension for determining the transit refrigeration pump. The assembly location refers to the physical location coordinates of the actual installation of the refrigeration pump in the building, which is usually accurately described in terms of floor, room number, or distance relative to a certain reference point. Through the location information recorded in the building map, the system can calculate the actual distance between different refrigeration pumps in order to screen out the transit refrigeration pumps that meet the distance requirements. The preset distance is a distance threshold pre-set based on factors such as cold transmission efficiency, pipeline pressure loss, and overall system layout. The refrigeration pumps within this distance range are considered to be able to serve as transit nodes during the cold transmission process to assist in the allocation of cold, without causing excessive cold loss or transmission delay due to the long distance. The setting of this parameter needs to be optimized and adjusted in combination with the specific structure of the building and the performance characteristics of the cold allocation system to ensure that the selection of the transit refrigeration pump can not only meet the flexibility requirements of the current cold allocation, but also ensure the efficient and stable operation of the entire system. In the cold allocation process, in addition to the refrigeration pumps directly associated with the air conditioner, those refrigeration pumps with the same node level and whose assembly positions are within the preset distance range are selected as transit refrigeration pumps. They can play a role in temporary storage and transfer of cold in the cold allocation process. When the directly associated refrigeration pumps cannot meet the cold demand of the air conditioner, or the system needs to optimize the allocation of cold, the transit refrigeration pumps can obtain cold from other cold sources (such as cold surplus in adjacent areas or centralized cooling of cold storage modules) and transmit it to the target air conditioner through the cold pipeline, thereby improving the flexibility and balance of cold allocation and enhancing the ability of the entire system to cope with complex working conditions.

[0106] Step S433, determining the transfer cooling capacity according to the sum of the current cooling capacity flow rates of the transfer refrigeration pumps and the transfer coefficient.

[0107] In this embodiment, the current cold flow refers to the amount of cold actually transmitted by each transfer refrigeration pump at a certain moment, which is usually expressed as a cold value per unit time (such as kW / h). This parameter can be obtained by real-time monitoring of the flow sensor installed on the cold pipeline. These sensors can accurately measure the flow of cold in the pipeline, reflecting the current workload and cold output capacity of each transfer refrigeration pump, and are one of the basic data for calculating the transfer cold. The current cold flow of different transfer refrigeration pumps will be affected by many factors such as its own operating state, the cold source and load conditions connected, and the pipeline resistance. Therefore, real-time monitoring of these data is crucial for accurate allocation of cold. The transfer coefficient is a correction coefficient that comprehensively considers the performance parameters of the transfer refrigeration pump (such as head, flow characteristics, efficiency, etc.), the material and diameter of the cold transmission pipeline, and the cold loss during the transfer process. Its value range is usually between 0 and 1, obtained through experimental testing, theoretical calculations or statistical analysis of historical operating data, and pre-stored in the database of the cold allocation system. The transfer coefficient is used to correct the sum of the current cooling flow of the transfer refrigeration pump to more accurately reflect the amount of cooling that can be effectively utilized in the actual transfer process, ensure that the calculation result of the transfer cooling capacity conforms to the physical characteristics of the actual cooling transmission and the system operation conditions, and avoid unreasonable or insufficient cooling capacity allocation due to the deviation between theoretical calculation and actual conditions. The transfer cooling capacity is obtained by adding the current cooling flow of each transfer refrigeration pump and multiplying it by the transfer coefficient. It represents the cooling potential that can be provided to the target air conditioner through the transfer refrigeration pump under the current system operation state. The determination of the transfer cooling capacity provides an important basis for the subsequent comprehensive consideration of the first ratio, expected cooling capacity and current cold storage capacity, and the formulation of a more accurate and reasonable second cooling capacity allocation plan, so that the cooling capacity allocation system can fully tap and utilize the cooling resources within the system, improve energy utilization efficiency and the balance of cooling capacity distribution, and meet the changes in cooling demand of different air conditioners under various working conditions.

[0108] Step S434, determining the second cooling capacity according to the first ratio, the expected cooling capacity, the transfer cooling capacity and the current cold storage capacity.

[0109] In this embodiment, the difference between the expected cooling capacity and the transfer cooling capacity is used as the third cooling capacity; the product of the third cooling capacity and the first ratio is used as the fourth cooling capacity; the upper limit of unit cooling capacity is determined based on the current cold storage capacity divided by the total number of the air conditioners; if the fourth cooling capacity is higher than the upper limit of unit cooling capacity, the upper limit of unit cooling capacity is used as the second cooling capacity, and if the fourth cooling capacity is not higher than the upper limit of unit cooling capacity, the fourth cooling capacity is used as the second cooling capacity.

[0110] As an optional implementation, the system first obtains the expected cooling capacity of the air conditioner, which is calculated by a pre-set thermodynamic model based on factors such as the indoor temperature, set temperature and outdoor temperature of the area where the air conditioner is located, and represents the cooling capacity required to make the indoor temperature reach the set value under ideal conditions. At the same time, the transfer cooling capacity is obtained. The transfer cooling capacity is the cooling potential that can be additionally provided to the target air conditioner by a specific transfer refrigeration pump in the system. The determination process involves the screening of the transfer refrigeration pump (based on conditions such as the node level and assembly position of the refrigeration pump associated with the target air conditioner) and the monitoring and calculation of its current cooling flow, and the correction value obtained by combining factors such as cooling loss during the transfer process. Then, the difference between the expected cooling capacity and the transfer cooling capacity is calculated, and this difference is defined as the third cooling capacity. The purpose of this step is to clarify the cooling capacity that the air conditioner needs to obtain from other cold sources (mainly cold storage modules) after removing the transfer cooling capacity without considering the system load, so as to provide basic data for further adjusting the cooling capacity distribution according to the overall system load. Next, the system obtains the first ratio of the number of working air conditioners to all air conditioners, which reflects the overall load level of the current cooling capacity allocation system in real time. The fourth cooling capacity is obtained by multiplying the third cooling capacity obtained by the above calculation with the first ratio. This step takes into account the load of the system. When the system load is high (i.e., the first ratio is large), the fourth cooling capacity will be reduced accordingly, which means that each air conditioner may be allocated relatively less cooling capacity under high load conditions, so as to ensure that the cooling capacity distribution of the entire system is more balanced, and avoid some air conditioners from excessively occupying cooling resources and causing insufficient cooling capacity of other air conditioners; on the contrary, when the system load is low, the fourth cooling capacity is relatively large, and each air conditioner has the opportunity to obtain a cooling capacity allocation that is closer to its ideal demand, while meeting the indoor temperature regulation requirements, improving energy utilization efficiency and indoor comfort. The system monitors the current cooling capacity of the cold storage module in real time and obtains the total number of air conditioners. The current cooling capacity is divided by the total number of air conditioners to obtain the upper limit of the unit cooling capacity. This value represents the maximum cooling capacity value that each air conditioner can theoretically obtain if the cooling capacity is evenly distributed under the current cooling capacity conditions. It provides a reference standard for judging whether the fourth cooling capacity is reasonable. If the fourth cooling capacity exceeds the upper limit of the unit cooling capacity, it means that the cooling capacity allocation scheme calculated according to the current system load and cooling capacity demand may cause the cooling capacity of the cold storage module to be exhausted in a short period of time, affecting the stable operation of the entire system; therefore, it is necessary to adjust the cooling capacity allocation to ensure that the system can continuously and stably provide cooling capacity for each air conditioner for a long time and maintain the indoor temperature within an acceptable range. Finally, the system compares the fourth cooling capacity with the upper limit of the unit cooling capacity.If the fourth cooling capacity is higher than the upper limit of the unit cooling capacity, it means that according to the initial calculation, the cooling demand of the air conditioner is too high, which may affect the overall stability of the system and the cooling supply of other air conditioners. At this time, the upper limit of the unit cooling capacity is allocated to the air conditioner as the second cooling capacity, that is, its cooling demand is restricted, and the overall balance and stable operation of the system are prioritized; if the fourth cooling capacity is not higher than the upper limit of the unit cooling capacity, the fourth cooling capacity is directly allocated to the air conditioner as the second cooling capacity. This can not only meet the basic cooling demand of the air conditioner, but also take into account the overall load of the system and the cooling reserve of the cold storage module, thereby realizing the reasonable allocation and efficient utilization of cooling capacity, improving the performance and reliability of the entire cooling capacity allocation system, and providing stable and comfortable indoor environment temperature control for smart buildings.

[0111] As an overall implementation method, the system first retrieves the building map information, which details the locations and connection relationships of various components in the cooling capacity distribution system, including the cold storage module, cooling pipelines, air conditioners, and chilled water pumps, etc. Through this map, the chilled water pump directly connected to the target air conditioner is accurately located, which is one of the key nodes for subsequent cooling capacity transmission. Then, according to the pre-set node level evaluation rules, all chilled water pumps in the system are classified. The determination of the node level comprehensively considers factors such as the distance of the chilled water pump from the key area, the importance of the area it serves, and its position in the entire cooling capacity transmission network. At the same time, based on the actual installation position information of the chilled water pumps, other chilled water pumps with the same node level as the chilled water pump associated with the target air conditioner and whose installation positions are within the preset distance range are selected, and these chilled water pumps are defined as transfer chilled water pumps. The setting of the preset distance aims to ensure that during the cooling capacity transmission process, the transfer chilled water pumps can effectively assist in the distribution of cooling capacity, while avoiding excessive cooling capacity loss or too low transmission efficiency due to too long a distance, thus ensuring the high efficiency and stability of the entire cooling capacity distribution system. For each determined transfer chilled water pump, the system uses the flow sensors installed on its connected cooling pipelines to continuously monitor and obtain the current cooling capacity flow data of each transfer chilled water pump. Let the number of transfer chilled water pumps be n, and the current cooling capacity flow of the i-th transfer chilled water pump be denoted as Q_flowi (i takes values from 1 to n). First, calculate the sum of the current cooling capacity flows of all transfer chilled water pumps, that is, sum Q_flowi from i = 1 to n (which can be expressed as ∑Q_flowi, i = 1 to n). Considering that there will be certain losses in the cooling capacity during the transfer process due to factors such as pipeline heat dissipation and pump efficiency, a transfer coefficient k (0 < k < 1) is introduced to correct the total cooling capacity flow value. The transfer coefficient is a parameter determined through in-depth analysis and experimental tests of the physical characteristics of the cooling capacity distribution system, equipment performance, and historical operation data. Its specific value is related to various factors such as the material, diameter, length of the cooling capacity transmission pipeline, the performance of the transfer chilled water pumps, and the ambient temperature. By multiplying the total cooling capacity flow value by the transfer coefficient, the transfer cooling capacity Q_trans is finally determined, and its calculation formula is Q_trans = k * ∑Q_flowi (i = 1 to n). This part of the cooling capacity will be an important component for subsequent calculation of the secondary cooling capacity, providing additional cooling capacity resources and distribution flexibility for optimizing the cooling capacity distribution. The system obtains the expected cooling capacity Q_exp of the air conditioner, which is the theoretical cooling capacity demand value calculated through the built-in advanced thermodynamic model based on factors such as the real-time indoor temperature of the area where the air conditioner is located, the target temperature set by the user, and the outdoor ambient temperature, representing the amount of cooling capacity required to reach the set value of the indoor temperature under ideal conditions.Calculate the difference between the expected cooling capacity and the transfer cooling capacity to obtain the third cooling capacity Q_3, the calculation formula is Q_3 = Q_exp - Q_trans. This step aims to clarify the cooling capacity that the air conditioner still needs to obtain from other cold sources (mainly the cold storage module) after deducting the contribution of the transfer cooling capacity, so as to more accurately distribute the cooling capacity according to the overall system conditions. Next, obtain the first ratio r of the working air conditioner to all air conditioners. This ratio reflects the load level of the current cooling capacity allocation system in real time. By multiplying the third cooling capacity by the first ratio, the fourth cooling capacity Q_4 is obtained, and the calculation formula is Q_4 = Q_3 * r. This calculation process fully considers the overall load of the system. When the system load is high, the fourth cooling capacity will be reduced accordingly to ensure that the cooling capacity distribution of each air conditioner under high load is more balanced and reasonable, avoiding excessive occupation of cooling resources by individual air conditioners and affecting the normal operation of other air conditioners; on the contrary, when the system load is low, the fourth cooling capacity is relatively large, and each air conditioner has the opportunity to obtain a cooling capacity distribution closer to its ideal demand, while meeting the indoor temperature regulation requirements, improving energy efficiency and indoor comfort. At the same time, the system monitors the current cooling capacity Q_store of the cold storage module in real time and obtains the total number of air conditioners in the building m. The current cooling capacity is divided by the total number of air conditioners to obtain the upper limit of unit cooling capacity Q_unit. The calculation formula is Q_unit = Q_store / m. This value represents the maximum cooling capacity that each air conditioner can theoretically obtain if the cooling capacity is evenly distributed under the current cooling capacity conditions. It provides a key reference for judging the rationality of the fourth cooling capacity. If Q_4>Q_unit, it means that the cooling allocation scheme calculated according to the current system load and cooling demand may cause the cooling capacity of the cold storage module to be exhausted in a short period of time, affecting the stable operation of the entire system; therefore, in this case, the upper limit of the unit cooling capacity is allocated to the air conditioner as the second cooling capacity, that is, its cooling capacity demand is limited, giving priority to the overall balance and stable operation of the system. If Q_4<= Q_unit, the fourth cooling capacity is directly allocated to the air conditioner as the second cooling capacity, which can not only meet the basic cooling capacity demand of the air conditioner, but also fully consider the overall load of the system and the cooling capacity reserve of the cold storage module, realize the reasonable allocation and efficient use of cooling capacity, improve the performance and reliability of the entire cooling capacity allocation system, and provide stable and comfortable indoor environmental temperature control for smart buildings.

[0112] Exemplarily, there is a modern office building with 25 floors. Each floor is divided into 10 office spaces, and each office space is equipped with an independent air conditioner. The chilled water distribution system of the entire office building consists of a large chilled water storage module located in the basement floor, multiple chilled water pumps distributed on each floor, and a complex chilled water pipeline network connecting them. As the outdoor temperature gradually rises, many air conditioners in the office spaces are successively turned on. Suppose the air conditioner in a certain office space on the 12th floor calculates the expected chilled water quantity Q_exp (where Q_exp is a theoretical value without a specific numerical value here, only for illustration) based on factors such as the number of people in the room, the heat generation of office equipment, and the current indoor-outdoor temperature difference through the intelligent algorithm built into the system. The system quickly determines the chilled water pump directly associated with this air conditioner (marked as P_1) by querying the building map, and based on the pre-set node level and assembly position information, selects two other chilled water pumps (marked as P_2 and P_3 respectively) with the same node level as P_1 and within a preset distance (such as 8 meters) of the assembly position as transfer chilled water pumps. At this time, the number of transfer chilled water pumps n = 2. The current chilled water flow rate corresponding to P_2 is denoted as Q_flow1, and the current chilled water flow rate corresponding to P_3 is denoted as Q_flow2. The corresponding flow rate values are monitored in real time through high-precision flow sensors installed on the chilled water pipelines connecting these three chilled water pumps. Suppose the transfer coefficient k (0 < k < 1, and no specific numerical value is given here) is determined through a large number of experiments and data analysis, then the transfer chilled water quantity Q_trans can be calculated according to the formula Q_trans = k * (Q_flow1 + Q_flow2) (because when n = 2, ∑Q_flowi (i = 1 to n) is Q_flow1 + Q_flow2). After statistics, at this time, there are 150 air conditioners in the office building in a working state, so the total number of air conditioners m = 25 * 10 = 250, and the first ratio r = 150 / m = 150 / 250 = 0.6. Then calculate the third chilled water quantity Q_3 = Q_exp - Q_trans, and then the fourth chilled water quantity Q_4 = Q_3 * r. At the same time, the system monitors that the current chilled water storage quantity of the chilled water storage module is Q_store (also a specific energy value without a specific numerical value here for illustration), then the upper limit of unit chilled water quantity Q_unit = Q_store / m.If Q_4>Q_unit, the second cooling capacity finally allocated by the air conditioner in the office space will be set to Q_unit, which means that due to the high overall load of the system and the limited cooling capacity reserve of the cold storage module, the cooling capacity allocation of the air conditioner will be restricted to ensure that the cooling capacity allocation of the entire office building can be maintained relatively balanced, avoiding the serious shortage of cooling capacity in other areas due to excessive cooling capacity allocation in some areas, and ensuring that the indoor temperature of each office space can be maintained within a relatively reasonable range. Although it may not be possible to fully achieve the ideal temperature setting in some areas, it can guarantee basic office comfort and stable operation of the system. On the contrary, if Q_4<= Q_unit, the second cooling capacity is determined to be Q_4. At this time, the air conditioner in the office space can obtain a relatively reasonable cooling capacity allocation. While meeting the indoor temperature adjustment requirements, it also fully considers the overall operation status of the system and the effective use of cooling resources, achieving the optimization goal of cooling capacity allocation, improving the energy utilization efficiency and indoor environmental quality of the entire office building, and providing office staff with a relatively comfortable and stable working environment temperature condition.

[0113] Through the above implementation methods and examples, the cooling allocation system can flexibly and reasonably allocate cooling according to actual conditions, adapt to different indoor and outdoor environmental conditions and system load changes, improve cooling efficiency and indoor comfort, and at the same time ensure the stable operation of the system, meeting the needs of smart buildings for efficient and intelligent management of central air-conditioning systems.

[0114] Based on any of the above embodiments, in a possible embodiment of the present application, the method further includes:

[0115] Step A10, at the cooling capacity settlement time, obtain the total cooling capacity of each of the air conditioners on that day.

[0116] In this embodiment, the cooling amount settlement time is a set time, that is, the time when the cooling module needs to be recharged with cooling to determine the required cooling amount. The total cooling amount is the cooling amount allocated from the cooling module by all air conditioners on that day.

[0117] Step A20, determining the cold storage capacity of the cold storage module according to the total cold capacity of each of the air conditioners, the outdoor temperature of the day and the predicted temperature of the next day.

[0118] In this embodiment, the cold storage capacity is the cold storage capacity that needs to be re-stored this time.

[0119] As an optional implementation, at the preset cooling settlement time every day (for example, late at night, when the power demand is relatively low, which is convenient for subsequent cooling storage operations and has minimal interference with users' daily use), the cooling allocation system starts the data statistics process. Through the communication link established with each air conditioner, the system collects the operating data of each air conditioner from startup to cooling settlement time in real time, including but not limited to: the cooling time of the air conditioner, the cooling power in different time periods and other information. Based on these detailed operating data, the built-in cooling calculation model is used to accurately calculate the cooling consumed by each air conditioner on the day, and then the cooling of all air conditioners on the day is accumulated to obtain the total cooling of each air conditioner on the day. For example, if a smart building has 50 air conditioners, through the system to collect and analyze the data of each unit, it is known that the cooling consumption of air conditioner 1 on the day is 100kW・h, air conditioner 2 consumes 120kW・h... After accumulation in sequence, the total cooling of each air conditioner on the day is 8000kW・h. Consider the total cooling capacity of the air conditioner on that day: The total cooling capacity of each air conditioner on that day is a key indicator to measure the overall cooling demand on that day. Because it directly reflects the total cooling capacity consumed to maintain a comfortable temperature in each room in the actual usage scenario. If the total cooling capacity on that day is high, it means that the users in the building have a strong demand for cooling. When planning the cooling capacity for the next day, it is necessary to make appropriate adjustments based on this to ensure sufficient cooling supply for the next day. Combined with the outdoor temperature factor of the day: Through the high-precision temperature sensors deployed around the building, the outdoor temperature data of the day is collected in real time, and the temperature change curves at different times are recorded. The outdoor temperature of the day has a significant impact on the heat transfer of the building's envelope structure. When the outdoor temperature is high, the heat exchange between the building and the outside world is more intense, and the indoor heat loss rate is accelerated. The air conditioner needs to consume more cooling capacity to maintain the set temperature. For example, in the hot summer, when the average outdoor temperature reaches 35℃, the heat transmitted into the building through the walls, windows and other enclosures may increase by 20%-30% compared to the weather with an average temperature of 30℃, which will lead to an increase in the cooling consumption of the air conditioner. Therefore, when determining the cooling capacity, it is necessary to adjust the cooling capacity according to a certain proportional coefficient based on the outdoor temperature of the day. Generally speaking, for every 5℃ increase in outdoor temperature, the cooling capacity reserve can be appropriately increased by 10%-15%. Incorporate the next day's predicted temperature factor: The cooling capacity allocation system is connected to a professional meteorological forecast data interface to obtain the next day's temperature forecast information, including the highest temperature, the lowest temperature and the temperature change trend throughout the day. The next day's predicted temperature is directly related to the next day's cooling demand trend in the building. If the next day's predicted temperature rises significantly, it means that the indoor cooling load will increase, and the frequency and duration of users turning on the air conditioner may increase. At this time, it is necessary to significantly increase the cooling capacity of the cooling storage module.For example, if the outdoor temperature on the day averages 30°C, and the predicted maximum temperature the next day will rise to 38°C, based on historical data and simulation analysis, it is expected that the overall cooling demand of the air conditioner may increase by 30% - 40%, so the cold storage capacity must be increased accordingly. On the contrary, if the predicted temperature the next day is relatively stable or slightly lower, the cold storage capacity can be appropriately fine-tuned or maintained at a level similar to that of the day. Comprehensive calculation to determine the cold storage capacity: Based on the above three key factors, the cold storage allocation system has a built-in intelligent cold storage capacity decision algorithm. First, the weight coefficient of the total cooling capacity of each air conditioner on the day is set to 0.4, the weight coefficient of the outdoor temperature on the day is set to 0.3, and the weight coefficient of the predicted temperature the next day is set to 0.3 (these weight coefficients can be dynamically adjusted and optimized based on the analysis of actual operating data and the climate characteristics of different regions). Assuming that the total cooling capacity of each air conditioner on that day is 8000kW・h, the cooling capacity adjusted according to the outdoor temperature on that day is 8000×(1 + 0.1) =8800kW・h (the outdoor temperature on that day was high, so it was adjusted up by 10%), and the cooling capacity adjusted according to the predicted temperature of the next day is 8800×(1 + 0.3) = 11440kW・h (the temperature on the next day will rise sharply, so it will be adjusted up by 30%). By weighted average calculation: cooling capacity = 8000×0.4 + 8800×0.3 + 11440×0.3 = 9472kW・h. Finally, it is determined that the cooling capacity that the cold storage module needs to reserve on the next day is 9472kW・h, so as to ensure that the cold storage module can meet the cooling demand of the air conditioners in the smart building on the next day, and realize efficient allocation and rational use of cooling capacity.

[0120] By comprehensively considering various factors, the required cold storage capacity of the cold storage module at the time of cold storage settlement is accurately determined, ensuring the stability and reliability of the cold supply of the smart building.

[0121] Optionally, step A20 includes:

[0122] Step A21, obtaining the triggering frequency of the temperature setting instruction corresponding to each of the air conditioners, wherein the triggering frequency includes a lowering frequency and a highering frequency.

[0123] In this embodiment, the trigger frequency of the temperature setting instruction refers to the number of times the user performs temperature setting operations on each air conditioner in a day. Among them, the frequency of lowering the temperature setting of the air conditioner refers to the number of times the air conditioner set temperature is lowered, which usually means that the user feels that the indoor temperature is too high and needs to increase the cooling capacity to make the environment cooler; the frequency of raising the temperature setting of the air conditioner refers to the number of times the air conditioner set temperature is raised, which generally means that the indoor temperature is low enough or even too cold, and the user hopes to reduce the cooling capacity to save energy or improve comfort. These frequency data can intuitively reflect the user's real-time feelings and demand changes on the indoor temperature.

[0124] As an optional implementation, a dedicated command monitoring module is embedded in the communication link between the cooling capacity allocation system and each air conditioner. This module can capture the temperature setting commands issued by the user in real time through any means such as remote control, mobile phone APP or indoor temperature control panel. Whenever a new command is generated, it is immediately classified and counted according to the command type (lowering the temperature or raising the temperature). The system sets a very short counting update cycle, such as updating the trigger frequency data of each air conditioner every 5 minutes, to ensure the timeliness and accuracy of the data, so as to accurately reflect the user's dynamic demand for temperature at different time periods.

[0125] As an optional implementation, a day is divided into several fixed time periods, for example, 2 hours per time period. At the end of each time period, the cooling allocation system collects statistics on the temperature setting instructions received by each air conditioner during the time period. By analyzing the temperature change direction in the instructions, the frequency of lowering and higher adjustments are accumulated respectively. Compared with the real-time monitoring and recording method, this method has relatively less data processing pressure and can highlight the user's temperature preference trend in different time periods, which is convenient for subsequent cooling demand analysis based on the characteristics of the time period.

[0126] Step A22, determining the target cooling capacity of the air conditioner according to the total cooling capacity and the trigger frequency.

[0127] In this embodiment, the target cooling capacity is a cooling capacity value that is more in line with the actual needs of the user after comprehensive consideration of the total cooling capacity actually consumed by the air conditioner on the day and the frequency of temperature adjustment by the user. If the frequency of temperature adjustment is high, it means that the user has a large demand for cooling capacity, and the target cooling capacity may need to be appropriately increased to meet the needs of similar subsequent periods; conversely, if the frequency of temperature adjustment is high, the target cooling capacity can be appropriately reduced to avoid energy waste caused by excessive cooling. The total cooling capacity reflects the actual energy consumption of the air conditioner over a period of time in the past, and combined with the trigger frequency, it can accurately locate the cooling capacity supply level preferred by the user.

[0128] As an optional implementation, first, pre-set weight values ​​are assigned to the frequency of lowering and the frequency of higher adjustment, for example, the weight of the frequency of lowering is set to 0.7, and the weight of the frequency of higher adjustment is set to 0.3 (the weight value can be optimized and adjusted based on a large amount of historical operation data and user feedback). Then, the adjustment coefficient is calculated according to the formula: adjustment coefficient = (frequency of lowering × weight of frequency of lowering - frequency of higher adjustment × weight of frequency of higher adjustment). Finally, the target cooling capacity of each air conditioner is obtained through the formula: target cooling capacity = total cooling capacity × (1 + adjustment coefficient). This method is simple and direct, and can quickly quantify the user's temperature adjustment behavior and integrate it into the cooling capacity calculation.

[0129] As an optional implementation, a piecewise function model is constructed based on the operation data accumulated over a long period of time in the past. The difference between the frequency of lowering and the frequency of higher adjustment is used as the independent variable, and the target cooling capacity is used as the dependent variable. For example, when the difference is between 0 and 3, the target cooling capacity = total cooling capacity × (1 + 0.1 × difference); when the difference is between 4 and 6, the target cooling capacity = total cooling capacity × (1 + 0.2 × difference); when the difference is greater than 6, the target cooling capacity = total cooling capacity × (1 + 0.3 × difference). Through such a piecewise function, the target cooling capacity can be adjusted more finely according to the different degrees of frequency of temperature adjustment by users to adapt to a variety of usage scenarios.

[0130] Step A23, determining the cold storage capacity of the cold storage module based on the target cooling capacity of each of the air conditioners, the outdoor temperature of the day and the predicted temperature of the next day.

[0131] In this embodiment, the cold storage capacity of the cold storage module: as the "reserve" for the cold supply of the entire intelligent building, the accurate determination of its cold storage capacity is crucial. The target cold capacity of each air conditioner is combined here because it reflects the ideal cold demand of each house based on user habits and energy consumption of the day; the outdoor temperature of the day affects the heat exchange of the building as a whole, which in turn affects the cold loss; the predicted temperature of the next day informs the future cold demand trend in advance. The combination of the three can scientifically plan the cold storage module to reserve and ensure that the cold supply of the next day is sufficient and not wasted.

[0132] As an optional implementation, weights are assigned to the total target cooling capacity of each air conditioner, the influence factor of the outdoor temperature on the day, and the influence factor of the predicted temperature on the next day. For example, the weight of the total target cooling capacity is set to 0.5, the weight of the influence factor of the outdoor temperature on the day is set to 0.3, and the weight of the influence factor of the predicted temperature on the next day is set to 0.2 (similarly, the weights can be optimized according to actual conditions). First, based on the difference between the outdoor temperature on the day and the preset reference temperature (such as 25°C), combined with historical heat conduction data, the additional cooling capacity required due to the outdoor temperature on the day is calculated; then, based on the trend and amplitude of the change between the predicted temperature on the next day and the outdoor temperature on the day, the additional cooling capacity required due to the predicted temperature on the next day is estimated. Finally, according to the weighted average formula: cooling capacity = total target cooling capacity × weight of total target cooling capacity + cooling capacity added by the outdoor temperature on the day × weight of the influence factor of the outdoor temperature on the day + cooling capacity added by the predicted temperature on the next day × weight of the influence factor of the predicted temperature on the next day, the cooling capacity is calculated. This method takes all factors into consideration and highlights the key points through weight distribution, making the calculation of cooling capacity more scientific and reasonable.

[0133] As an optional implementation, in the first step, the sum of the target cooling capacity of each air conditioner is used as the basic cooling capacity. In the second step, the outdoor temperature of the day is analyzed. For every 1°C higher than the preset benchmark temperature, the basic cooling capacity is increased proportionally (such as 5%) according to historical experience data to obtain the cooling capacity corrected based on the outdoor temperature of the day. In the third step, combined with the predicted temperature of the next day, if the temperature rises, the cooling capacity is further increased according to the temperature increase (such as 10% increase for every 2°C increase); if the temperature drops, the cooling capacity is reduced by a certain proportion (such as 8% reduction for every 2°C decrease). Through such a step-by-step correction, the cooling capacity can be adjusted intuitively according to the changes in ambient temperature, which is easy to understand and operate.

[0134] For example, a smart office building with 200 offices uses a real-time monitoring and recording method to obtain the trigger frequency of the corresponding temperature setting instructions for each air conditioner. For the air conditioner in Room 1201 on the 12th floor of a company, employees issued a total of 8 temperature setting instructions through the mobile phone APP between 9:00 and 11:00 a.m. on weekdays, including 5 times of lowering the temperature and 3 times of raising the temperature. The system records and updates the trigger frequency data of the air conditioner in real time. Then, when determining the target cooling capacity of the air conditioner based on the total cooling capacity and the trigger frequency, the linear weighted calculation method is used. It is known that the total cooling capacity of the air conditioner in the morning of that day is 30kW・h, the weight of the frequency of lowering is 0.6, and the weight of the frequency of raising is 0.4. Calculate the adjustment coefficient: (5×0.6 - 3×0.4) = 1.8, target cooling capacity = 30×(1 + 0.18) = 35.4kW・h. The system calculates the target cooling capacity of each air conditioner in the building in this way. Finally, the cold storage capacity of the cold storage module is determined based on the target cooling capacity of each air conditioner, the outdoor temperature of the day, and the predicted temperature of the next day, using the weighted average comprehensive method. The total target cooling capacity of all air conditioners is 6000kW・h. The average outdoor temperature of the day is 30℃ (based on 25℃, 5% cooling reserve is added for every 1℃ increase). The additional cooling reserve required due to the outdoor temperature of the day is 6000×(30 - 25)×5% = 1500kW・h; the predicted maximum temperature of the next day is 33℃, which is expected to increase the cooling demand by about 8% compared with the cooling demand of the day. Therefore, the cooling capacity required to be increased due to the predicted temperature of the next day is (6000 + 1500)×8% = 600kW・h. The cooling capacity of the cold storage module is determined to be 6000×0.5 + 1500×0.3 + 600×0.3 = 3630kW・h. In this way, the cold storage module can accurately store cold according to the actual needs of the office building, ensuring a comfortable cooling environment in the office area the next day.

[0135] The present application provides a cooling capacity allocation device for an intelligent building, the cooling capacity allocation device for an intelligent building comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the cooling capacity allocation method for the intelligent building in the above-mentioned embodiment one.

[0136] Reference below Figure 4 , which shows a schematic diagram of the structure of a cooling capacity allocation device for a smart building suitable for implementing the embodiment of the present application. The cooling capacity allocation device for a smart building in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptops, tablet computers, vehicle-mounted terminals, etc., and fixed terminals such as desktop computers, etc. Figure 4 The cooling capacity allocation equipment of the smart building shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0137] like Figure 4 As shown, the cooling capacity allocation device of the intelligent building may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 1002 or the program loaded from the storage device 1003 to the random access memory (RAM) 1004. In the random access memory 1004, various programs and data required for the operation of the cooling capacity allocation device of the intelligent building are also stored. The processing device 1001, the read-only memory 1002 and the random access memory 1004 are connected to each other through a bus 1005. The input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the cooling capacity allocation device of the intelligent building to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows the cooling capacity allocation device of the intelligent building with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have alternatively.

[0138] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a read-only memory 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0139] The cooling capacity allocation device for smart buildings provided by the present application adopts the cooling capacity allocation method for smart buildings in the above embodiment, which can solve the technical problem that the traditional building air conditioning management scheme will cause a large amount of electric energy to be ineffectively consumed, resulting in a waste of electricity. Compared with the prior art, the beneficial effects of the cooling capacity allocation device for smart buildings provided by the present application are the same as the beneficial effects of the cooling capacity allocation device for smart buildings provided by the above embodiment, and the other technical features of the cooling capacity allocation device for smart buildings are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0140] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0141] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0142] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the cooling capacity allocation method for the smart building in the above-mentioned embodiment.

[0143] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, radio frequencies (RF, Radio Frequency), etc., or any suitable combination of the above.

[0144] The computer-readable storage medium may be included in the cooling allocation device of the intelligent building; or it may exist independently without being installed in the cooling allocation device of the intelligent building.

[0145] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the cooling capacity allocation device of the intelligent building, the cooling capacity allocation device of the intelligent building: if a temperature setting instruction triggered by the air conditioner is detected, determine the set temperature corresponding to the temperature setting instruction; determine the expected cooling capacity of the air conditioner according to the set temperature; obtain the current cooling capacity of the cold storage module; determine the allocated cooling capacity of the air conditioner according to the node level of the cooling pipeline associated with the air conditioner, the expected cooling capacity and the current cooling capacity.

[0146] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0147] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0148] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0149] The readable storage medium provided in the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned cooling capacity allocation method for smart buildings, and can solve the technical problem that the traditional building air conditioning management solution causes a large amount of electric energy to be ineffectively consumed, resulting in a waste of electric power. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the present application are the same as the beneficial effects of the cooling capacity allocation method for smart buildings provided in the above-mentioned embodiments, and will not be elaborated here.

[0150] An embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the cooling capacity allocation method for the smart building as described above.

[0151] The computer program product provided by the present application can solve the technical problem that the traditional building air conditioning management solution causes a large amount of electric energy to be ineffectively consumed, resulting in a waste of electricity. Compared with the prior art, the beneficial effects of the computer program product provided by the embodiment of the present application are the same as the beneficial effects of the cooling capacity allocation method of the intelligent building provided by the above embodiment, which will not be repeated here.

[0152] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent processing scope of the present application.

Claims

1. A cooling capacity allocation method for an intelligent building, characterized in that: Applied to a cold capacity allocation system, the cold capacity allocation system includes a refrigeration pump, a cold storage module, a cold capacity pipeline and an air conditioner, one end of the refrigeration pump is connected to the air conditioner through the cold capacity pipeline, and the other end of the refrigeration pump is connected to the cold storage module through the cold capacity pipeline. The cold capacity allocation method of the intelligent building includes: If a temperature setting instruction triggered by the air conditioner is detected, determining a set temperature corresponding to the temperature setting instruction; Determining the expected cooling capacity of the air conditioner according to the set temperature; Obtaining the current cold storage capacity of the cold storage module; Determining a correction coefficient associated with a node level of the cooling pipeline associated with the air conditioner; Determining a first ratio of the number of working air conditioners to the number of all air conditioners; Based on the building map, determining the refrigeration pump associated with the air conditioner; Determine a refrigeration pump with the same node level and an assembly position less than or equal to a preset distance among the refrigeration pumps as a transit refrigeration pump; The transfer cooling capacity is determined by summing the current cooling capacity flow of each of the transfer refrigeration pumps and multiplying it by a transfer coefficient, wherein the transfer coefficient is a correction coefficient that comprehensively considers the head, flow characteristics, efficiency, material and diameter of the cooling capacity transmission pipeline of the transfer refrigeration pump, and cooling capacity loss during the transfer process; The difference between the expected cooling capacity and the transfer cooling capacity is used as the third cooling capacity; taking the fourth cooling capacity as the product of the third cooling capacity and the first ratio; Determining a unit cooling capacity upper limit based on the current cooling capacity divided by the total number of the air conditioners; If the fourth cooling capacity is higher than the upper limit of the unit cooling capacity, the upper limit of the unit cooling capacity is used as the second cooling capacity; if the fourth cooling capacity is not higher than the upper limit of the unit cooling capacity, the fourth cooling capacity is used as the second cooling capacity; The allocated cooling capacity of the air conditioner is determined based on the second cooling capacity and the correction coefficient.

2. The cooling capacity allocation method of the intelligent building according to claim 1, characterized in that: The step of determining the expected cooling capacity of the air conditioner according to the set temperature comprises: Acquire the indoor temperature of the working area where the air conditioner is located, and the outdoor temperature of the floor where the working area is located; An expected cooling capacity is determined based on the set temperature, the indoor temperature, and the outdoor temperature.

3. The cooling capacity allocation method of the intelligent building according to claim 2, characterized in that: The step of determining the expected cooling capacity based on the set temperature, the indoor temperature and the outdoor temperature comprises: determining a first difference between the set temperature and the indoor temperature; determining a second difference between the indoor temperature and the outdoor temperature; Obtaining the heat transfer coefficient of the floor where the working area is located; determining a corrected cooling capacity according to the second difference and the heat transfer coefficient, and determining a first cooling capacity according to the first difference; The expected cooling capacity is determined based on the sum of the first cooling capacity and the corrected cooling capacity.

4. The cooling capacity allocation method of the intelligent building according to claim 1, characterized in that: The method further comprises: At the cooling capacity settlement time, obtaining the total cooling capacity of each of the air conditioners on that day; The cold storage capacity of the cold storage module is determined according to the total cold capacity of each of the air conditioners, the outdoor temperature of the day and the predicted temperature of the next day.

5. The cooling capacity allocation method of the intelligent building according to claim 4, characterized in that: The step of determining the cold storage capacity of the cold storage module according to the total cold capacity of each of the air conditioners, the outdoor temperature of the day and the predicted temperature of the next day comprises: Acquire the trigger frequency of the temperature setting instruction corresponding to each of the air conditioners, wherein the trigger frequency includes a lowering frequency and a highering frequency; Determining a target cooling capacity of the air conditioner according to the total cooling capacity and the trigger frequency; The cold storage capacity of the cold storage module is determined based on the target cooling capacity of each of the air conditioners, the outdoor temperature of the day and the predicted temperature of the next day.

6. A cooling capacity allocation device for an intelligent building, characterized in that: The cooling capacity allocation device of the intelligent building includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the cooling capacity allocation method of the intelligent building as described in any one of claims 1 to 5.

7. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the cooling capacity allocation method for an intelligent building as described in any one of claims 1 to 5 are implemented.

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