Air conditioner control method and device and vrf air conditioner

Abstract

The application relates to air conditioning technology and provides an air conditioner control method, device and VRF air conditioner, which are applied to a variable refrigerant flow (VRF) air conditioner. The method comprises the following steps: acquiring current operation data collected within a preset time length after the VRF air conditioner starts on the day; determining a target load group to which the current operation data belongs from a plurality of preset load groups, wherein the plurality of preset load groups are determined after a plurality of historical operation data collected in a preset historical period are subjected to load grouping, preset load types of the plurality of preset load groups are different from each other, each preset load type corresponds to a compensation value for compensating for a phase change reference temperature of the VRF air conditioner to meet a corresponding preset load type; and compensating for the phase change reference temperature according to the compensation value corresponding to the target load group, so as to control the VRF air conditioner according to the compensated temperature. The application can realize precise temperature compensation energy-saving control of the VRF air conditioner according to load.

Description

Technical Field

[0001] This invention relates to the field of air conditioning technology, and more specifically, to an air conditioning control method, device, and VRF air conditioner. Background Technology

[0002] In office buildings and commercial facilities, air conditioning equipment has always accounted for a high proportion of the building's total electricity consumption. In recent years, from an energy-saving perspective, the industry has increasingly looked forward to improving the operational energy efficiency of air conditioning, especially VRF (Variable Refrigerant Flow) systems. The operating conditions of air conditioning in these buildings differ significantly between weekdays and weekends: on weekdays, due to higher occupancy, the air conditioning load is higher; on weekends, the load is lower. Therefore, the load changes significantly over time depending on the air conditioning's load status. For example, on weekday mornings, cooling demand rises rapidly as the number of users increases; while on weekend mornings, the increase in cooling demand is gradual. Furthermore, if office buildings and similar structures do not use air conditioning on weekends, the building envelope will continuously accumulate heat, causing the air conditioning load to peak on the first morning of the workday.

[0003] However, traditional VRF control logic typically adjusts compressor control synchronously based on the varying capacity demands of multiple indoor units. To avoid insufficient cooling capacity, the compressor operating frequency is often set too high, resulting in the unit continuously operating at excess capacity and thus increasing power consumption. Summary of the Invention

[0004] The purpose of this invention is to provide an air conditioning control method, device, and VRF air conditioner.

[0005] The embodiments of the present invention can be implemented as follows: In a first aspect, the present invention provides an air conditioning control method applied to a variable refrigerant flow (VRF) air conditioner, the method comprising: Obtain the current operating data collected by the VRF air conditioner within a preset time period after it is started on the same day; The target load group to which the current operating data belongs is determined from multiple preset load groups. The multiple preset load groups are determined by grouping multiple historical operating data collected within a preset historical period. The preset load types of the multiple preset load groups are different. Each preset load type corresponds to temperature compensation of the phase change reference temperature of the VRF air conditioner to meet the compensation value of the corresponding preset load type. The phase change reference temperature is compensated according to the compensation value corresponding to the target load group, so as to control the VRF air conditioner according to the compensated temperature.

[0006] In an optional implementation, the current operating data includes the outer ring temperature, the outer ring temperature change rate, and the load change rate; the step of determining the target load group to which the current operating data belongs from multiple preset load groups includes: Obtain the central operating data for each preset load group, wherein the central operating data includes the outer ring temperature, the outer ring temperature change rate, and the load change rate, which characterize the load characteristics of the corresponding preset load group; Based on the outer ring temperature, outer ring temperature change rate, and load change rate of the current operating data, and the outer ring temperature, outer ring temperature change rate, and load change rate of each of the central operating data, calculate the comprehensive distance between the current operating data and each of the central operating data; The preset load group to which the central operation data corresponding to the minimum value of multiple comprehensive distances belongs is taken as the target load group.

[0007] In an optional implementation, before the step of determining the target load group to which the current operating data belongs from a plurality of preset load groups, the method further includes: The load sequence is obtained by sorting the load change rates of the various historical operating data from largest to smallest. The load sequence is segmented according to the preset load type to obtain multiple initial load groups; Based on the multiple initial load groups, cluster analysis is performed on the multiple historical operating data to obtain the multiple preset load groups.

[0008] In an optional implementation, each of the historical operating data includes outer ring temperature, outer ring temperature change rate, load change rate and daily maximum load peak value, and the initial center operating data of each initial load group includes outer ring temperature, outer ring temperature change rate, load change rate and daily maximum load peak value, which characterize the load characteristics of the corresponding preset load group. The step of performing cluster analysis on the historical operating data based on the multiple initial load groups to obtain the multiple preset load groups includes: Traverse each of the historical operating data, and calculate the reference distance between the current historical operating data and each of the initial load groups based on the outer ring temperature, outer ring temperature change rate, load change rate and daily maximum load peak of the current historical operating data traversed in this round, and the outer ring temperature, outer ring temperature change rate, load change rate and daily maximum load peak of the center operating data of each initial load group; The initial load group corresponding to the minimum reference distance in this round is taken as the load group to which the current historical operation data belongs, until all the historical operation data has been traversed in this round; If this round is the first round, or if the initial load group obtained in this round is different from the initial load group obtained in the previous round, then the central operation data of each initial load group obtained in this round is updated and the traversal of the next round continues, and each initial load group obtained in the last round is used as each of the preset load groups.

[0009] In an optional implementation, after the step of using each initial load group obtained in the last round as each of the preset load groups, the method further includes: The compensation value for each preset load group is set according to the building characteristics where the VRF air conditioner is located, the type of refrigerant used, the compressor specifications, and the type of each preset load group.

[0010] In an optional implementation, the current operating data includes the outer ring temperature, the outer ring temperature change rate, and the load change rate; After the step of compensating the phase change reference temperature according to the compensation value corresponding to the target load group, and controlling the VRF air conditioner according to the compensated temperature, the method further includes: Obtain the peak daily load of the VRF air conditioner on that day; Based on the outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak of the current operating data, and the outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak of the center operating data of each preset load group, the actual load group to which the current operating data belongs is determined from the plurality of preset load groups; If the actual load group and the target load group are consistent, the compensation value of the target load group shall be used as the reference compensation value; otherwise, the preset compensation value shall be used as the reference compensation value. The phase change reference temperature is compensated according to the reference compensation value on the next day, so that the VRF air conditioner is controlled according to the compensated temperature on the next day.

[0011] In an optional implementation, after the step of using the preset compensation value as the reference compensation value, the method further includes: Retrieve the target load grouping and actual load grouping for each day within the most recent preset number of days; Count the number of invalid days in the recent preset number of days where the target load grouping and the actual load grouping are inconsistent; If the ratio of the invalid days to the preset number of days is greater than the preset ratio, then multiple historical operating data collected within the most recent preset historical period are reacquired and the load is regrouped to obtain the latest preset load group. On the next day, the target load group is determined from the latest preset load group, and the phase change reference temperature is compensated according to the compensation value corresponding to the determined target load group. The VRF air conditioner is then controlled on the next day according to the compensated temperature.

[0012] In an optional implementation, after the step of compensating the phase change reference temperature according to the compensation value corresponding to the target load group, so as to control the VRF air conditioner according to the compensated temperature, the method further includes: Obtain the daily maximum load peak value of the VRF air conditioner and the actual load group to which the current operating data belongs; Replace the earliest collected daily maximum load peak and operating data in the actual load group with the daily maximum load peak and the current operating data respectively to obtain the updated actual load group; Update the central operation data of the updated actual load group.

[0013] In an optional implementation, the step of obtaining the current operating data collected by the VRF air conditioner within a preset time period after it is started on the same day includes: Obtain the outdoor temperature of the VRF air conditioner at the time of its start-up on the same day, and use the outdoor temperature at the time of its start-up on the same day as the outer ring temperature; Calculate the rate of change of the outer ring temperature on that day based on the outer ring temperature; The air conditioning load is collected in real time according to a preset cycle within the preset time period; Calculate the load change rate based on all the air conditioning loads and the preset duration; The outer ring temperature, the outer ring temperature change rate, and the load change rate are used as the current operating data.

[0014] In an optional implementation, the step of calculating the rate of change of the outer ring temperature on a given day based on the outer ring temperature includes: The outdoor temperature is collected in real time according to a preset cycle within the preset duration. The outer ring temperature change rate is calculated based on the outer ring temperature, all outdoor temperatures, and the preset duration. or, Get the day's forecast maximum temperature; The outer ring temperature change rate is calculated based on the outer ring temperature, the highest air temperature, and the preset reference duration.

[0015] In a second aspect, the present invention provides an air conditioning control device for use in a variable refrigerant flow (VRF) air conditioner, the device comprising: The acquisition module is used to acquire the current operating data collected by the VRF air conditioner within a preset time after it is started on the same day; The determination module is used to determine the target load group to which the current operating data belongs from multiple preset load groups. The multiple preset load groups are determined by grouping multiple historical operating data collected within a preset historical period. The preset load types of the multiple preset load groups are different. Each preset load type corresponds to temperature compensation of the phase change reference temperature of the VRF air conditioner to meet the compensation value of the corresponding preset load type. The compensation module is used to compensate the phase change reference temperature according to the compensation value corresponding to the target load group, so as to control the VRF air conditioner according to the compensated temperature.

[0016] Thirdly, the present invention provides a VRF air conditioner, including a controller and a memory, wherein the memory is used to store a program, and the controller is used to implement the air conditioner control method as described in the first aspect when executing the program.

[0017] Compared with the prior art, the present invention has the following beneficial effects: This invention groups multiple historical operating data collected within a preset historical time period into load groups, determining multiple preset load groups with different preset load types. For each preset load type, temperature compensation is set for the phase change reference temperature of the VRF air conditioner to meet the corresponding preset load type's compensation value. The invention acquires current operating data collected within a preset time period after the VRF air conditioner starts on the same day, determines the target load group to which the current operating data belongs from the multiple preset load groups, and then compensates the phase change reference temperature based on the compensation value corresponding to the target load group. The VRF air conditioner is then controlled according to the compensated temperature. This approach satisfies the air conditioner's load requirements while avoiding increased power consumption caused by the air conditioner operating at excessive capacity, thus achieving energy-saving control of the VRF air conditioner. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating the air conditioning control method provided in this embodiment.

[0020] Figure 2 Example diagram of the running data provided in this embodiment.

[0021] Figure 3 This is a flowchart illustrating the overall process of the air conditioning control method provided in this embodiment.

[0022] Figure 4 This is a block diagram of the air conditioning control device provided in this embodiment.

[0023] Figure 5 This is a block diagram of the VRF air conditioner provided in this embodiment.

[0024] Icons: 10-VRF air conditioner; 11-Controller; 12-Memory; 13-Bus; 100-Air conditioner control device; 110-Acquisition module; 120-Determination module; 130-Compensation module. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0026] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0027] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0028] In the description of this invention, it should be noted that if terms such as "upper," "lower," "inner," or "outer" are used to indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the product of this invention is usually placed, they are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention.

[0029] Furthermore, the terms "first" and "second" are used only to distinguish descriptions and should not be interpreted as indicating or implying relative importance.

[0030] It should be noted that, where there is no conflict, the features in the embodiments of the present invention can be combined with each other.

[0031] After researching relevant air conditioning control methods, the applicant discovered that the reason for setting the compressor operating frequency and other parameters too high is that the air conditioning control only relies on the load data at the moment the air conditioner starts operating (such as the required output capacity of each indoor unit), prioritizing the supply of cooling capacity needed at that instant. This method does not consider the temporal changes in load and cannot predict subsequent load fluctuations. To avoid insufficient cooling capacity in practical applications, a higher value is set to meet the cooling needs. This method causes the unit to operate with excess capacity, leading to increased power consumption. Furthermore, under most operating conditions, the unit continues to run 30 minutes after startup, without implementing load prediction-based optimized control for subsequent actual load changes during this period, which is also a contributing factor to increased power consumption.

[0032] Another related air conditioning control method involves pre-setting the load using calendar information (date, day of the week) and devices such as weekly timers. However, this method requires not only auxiliary equipment with calendar functions, but also individual parameter settings for non-periodic load fluctuations such as holidays and the end of the year. This not only makes the setting and operation complex, but also fails to provide energy-saving control based on actual operating conditions.

[0033] In view of this, this embodiment provides an air conditioning control method, device, and VRF air conditioner. Its core improvement lies in: analyzing historical operating data, grouping it into load groups, monitoring the operating conditions for a period after the start of daily operation, and predicting the air conditioning load for the day; adapting the calculated target evaporation temperature to the remaining operating time of the day, thereby achieving energy-saving control that conforms to the actual usage conditions of the building. This will be described in detail below.

[0034] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating the air conditioning control method provided in this embodiment. The method includes the following steps: Step S101: Obtain the current operating data collected by the VRF air conditioner within a preset time period after it is started on the same day.

[0035] In this embodiment, the preset duration can be set according to the actual application scenario, for example, the preset duration can be set to 30 minutes. Current operating data includes, but is not limited to, outer ring temperature, outer ring temperature change rate, and air conditioning load change rate. The outer ring temperature is the temperature of the external environment detected by the outer ring temperature sensor at the start of VRF operation. The outer ring temperature change rate is the slope of the change in inner and outer ring temperatures over time after the preset duration begins VRF operation. The air conditioning load change rate is the slope of the change in air conditioning load (cooling / heating demand capacity) over time within the preset duration after the start of VRF operation. The air conditioning load is the rated capacity value of the indoor unit of the VRF air conditioner during operation; the load of a stopped VRF air conditioner is 0. For example, if one 14kW indoor unit is operating, its air conditioning load is 14; if two 8kW indoor units are operating simultaneously, their air conditioning load is 16. Furthermore, after the VRF air conditioner finishes operating for the day, the maximum peak load of the VRF air conditioner during that day can also be obtained. For a more intuitive explanation of these dimensions of data, please refer to [link / reference needed]. Figure 2 , Figure 2 This is an example diagram of the operating data provided in this embodiment. Figure 2 In the diagram, the red line represents the change of external ambient temperature over time within a day, the blue line represents the change of air conditioning load over time within a day, t0 is the start time of the air conditioner's operation within a day, t1 is the time 30 minutes after t0, and t2 is the stop time of the air conditioner's operation within a day.

[0036] Step S102: Determine the target load group to which the current operating data belongs from multiple preset load groups. The multiple preset load groups are determined by grouping multiple historical operating data collected within a preset historical period. The preset load types of the multiple preset load groups are different. Each preset load type corresponds to temperature compensation of the phase change reference temperature of the VRF air conditioner to meet the compensation value of the corresponding preset load type.

[0037] In this embodiment, the preset historical time period corresponds to the most recent preset data collection cycle. If the preset data collection cycle is 14 days, then the preset historical time period is the daily historical operating data of the VRF air conditioner collected over the past 14 days. The historical operating data includes, but is not limited to, the outer ring temperature, the outer ring temperature change rate, the air conditioner load change rate, and the daily maximum load peak. The preset load types include, but are not limited to, high, medium, and low load modes. The load grouping methods include, but are not limited to, K-means algorithm, logistic regression algorithm, decision tree algorithm, etc.

[0038] It should be noted that the preset data collection period is set to cover a sufficient number of different preset load types. For example, if the preset data collection period is 7 days (1 week), then only one weekday and one rest day can be covered. If the preset collection period is set to 14 days (2 weeks), it can cover 10 weekdays and 4 rest days, and can obtain multiple sets of measured data for high-load days, medium-load days, and low-load days respectively. This can smooth out the fluctuations in operating patterns caused by different weeks and ensure the stability of the data distribution required for the first group analysis.

[0039] It should also be noted that the aforementioned 14-day preset collection period is only one way to achieve stable initial grouping. In fact, the preset collection period can also be used as a parameter that system designers can flexibly adjust according to the building's operating mode.

[0040] In this embodiment, the phase change reference temperature is the reference temperature for achieving energy-saving performance of the VRF air conditioner in the corresponding operating mode. For the cooling operation mode, the phase change reference temperature is the evaporation temperature, and for the heating operation mode, the phase change reference temperature is the condensation temperature. For different preset load types, the compensation value required to compensate for the phase change reference temperature is different.

[0041] Taking evaporation temperature as an example, historical operating data includes four dimensions: outer ring temperature, outer ring temperature change rate, air conditioning load change rate, and daily maximum load peak. For high-load conditions, if one or more of these four dimensions exceed the corresponding preset maximum value, it indicates at least one of the following: high outer ring temperature, rapid rise in outer ring temperature, or rapid load increase. The control strategy in this case is: if the compressor capacity is insufficient, execute control operations to avoid insufficient capacity, reduce the evaporation temperature, and minimize the low-pressure area to ensure cooling capacity as the top priority. The compensation value corresponding to the high-load condition will be adjusted accordingly. Set to a negative value, for example, = 2.0℃. For the medium-load type, these four dimensions are at a moderate level between the preset maximum and preset minimum values, which means the standard working day operating conditions during a comfortable climate season. The control strategy adopted at this time is: with a moderate ambient temperature, operating efficiency and load level in balance, maintain the standard setpoint, and adjust the compensation value corresponding to the medium-load type. Set to 0, for example, =0℃. For low-load types, if one or more of these four dimensions are less than the preset minimum value, it means that in low-temperature environments such as winter or early morning, the absolute value of the load is low and the increase is gradual. In this case, the control strategy is as follows: since the outdoor temperature is low and the unit's cooling capacity is sufficient, energy saving is prioritized by increasing the evaporation temperature and raising the low-pressure level to improve efficiency and save energy. The compensation value corresponding to the low-load type is adjusted accordingly. Set to a positive value, for example, =+1.5℃.

[0042] Step S103: Compensate the phase change reference temperature according to the compensation value corresponding to the target load group, so as to control the VRF air conditioner according to the compensated temperature.

[0043] In this embodiment, the formula for compensating the phase transition reference temperature can be: ,in, To replenish the temperature, The phase transition reference temperature is relative to the evaporation temperature. It can be the nominal setpoint of the evaporation temperature using conventional control methods before compensation. Indicates load grouping The corresponding compensation value. Based on the compensated temperature calculated using this formula, the compressor frequency and expansion valve opening of the outdoor unit are adjusted and controlled.

[0044] The method provided in this embodiment groups multiple historical operating data collected within a preset historical time period into load groups, and determines multiple preset load groups with different preset load types. For each preset load type, temperature compensation is set for the phase change reference temperature of the VRF air conditioner to meet the compensation value of the corresponding preset load type. Based on the current operating data collected within a preset time after the VRF air conditioner is started on the same day, the current target load group is determined. Then, based on the compensation value corresponding to the target load group, the phase change reference temperature is compensated and the VRF air conditioner is controlled. This can meet the air conditioner load demand and avoid the increase in power consumption caused by the air conditioner operating at excess capacity, thus realizing energy-saving control of VRF air conditioners.

[0045] In an optional implementation, to improve the accuracy of target load group determination, this embodiment comprehensively considers three dimensions: outer ring temperature, outer ring temperature change rate, and load change rate, to predict the target load group to which the current operating data belongs. One implementation method is as follows: First, acquire the central operating data for each preset load group. The central operating data includes the outer ring temperature, outer ring temperature change rate, and load change rate, which characterize the load characteristics of the corresponding preset load group. In this embodiment, the central operating data for each preset load group is data calculated from the operating data in each preset load group, which characterizes the load characteristics of the corresponding preset load group. Each dimension of the operating data in the preset load group corresponds to the corresponding dimension of the central operating data. For example, if the operating data in the preset load group includes four dimensions—outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak—then the central operating data also includes these four dimensions. Table 1 shows an example of three preset load groups.

[0046] Table 1

[0047] In Table 1, , , , These are the outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak value for the i-th group. In this embodiment, since the daily maximum load peak value can only be obtained after the VRF air conditioning has finished operating for the day, and the daily maximum load peak value cannot be known within a preset time after startup, the central operating data of the four dimensions are projected onto the outer ring temperature. , outer ring temperature change rate Load change rate These three dimensions are used to predict and determine the target load grouping by calculating the three-dimensional distance between them. This method allows the prediction and the final determination of the four dimensions to share the same grouping structure. Therefore, the difference between the two results can correspond to the daily maximum load peak that cannot be captured within the preset time after operation begins. The deviations caused by the measured values ​​have clear physical meaning.

[0048] Secondly, based on the current operating data's outer ring temperature, outer ring temperature change rate, and load change rate, as well as the operating data of each center's outer ring temperature, outer ring temperature change rate, and load change rate, calculate the comprehensive distance between the current operating data and the operating data of each center. In this embodiment, taking three groups as an example, the comprehensive distance between the current running data and the central running data of the i-th group can be calculated using the following formula. : Where i is the group number, , , , , and , respectively, represent the outer ring temperature, outer ring temperature change rate, and load change rate of the i-th group. , , These are the outer ring temperature, outer ring temperature change rate, and load change rate of the current operating data, respectively.

[0049] Finally, the preset load group to which the central operation data corresponding to the minimum value of multiple comprehensive distances belongs is taken as the target load group.

[0050] In this embodiment, taking the above three groups as an example, , , The group corresponding to the minimum of these three combined distances is the target load group.

[0051] In an optional implementation, to ensure the stability and reliability of the preset load grouping and to make the target load grouping determined based on the preset load grouping closer to the actual operating conditions, this embodiment provides a method for obtaining the preset load grouping by performing load analysis on historical operating data: First, the load sequence is obtained by sorting the load change rates of multiple historical operating data from largest to smallest; In this embodiment, if a certain grouping includes only 1 or 2 data points (for example, historical operational data is data from the most recent 7 days), there may be a risk of significant deviation in the classification center due to outliers. Therefore, in order to fully cover different preset load types, each grouping in multiple historical operational data sets needs at least 2 to 3 or more data points.

[0052] Secondly, the load sequence is segmented according to the preset load type to obtain multiple initial load groups; In this embodiment, taking 14 days of historical operating data as an example, the 14 days of data are sorted from largest to smallest according to the load change rate. The data of the first 5 days are classified as high load type, the data of the middle 5 days are classified as medium load type, and the data of the last 4 days are classified as low load type. Each category is assigned multiple sets of measured data, which can ensure that the calculation results of the classification center have statistical stability.

[0053] Finally, based on multiple initial load groups, cluster analysis is performed on multiple historical operating data to obtain multiple preset load groups.

[0054] In this embodiment, since the initial composite grouping is only a rough grouping based on the load change rate, in order to obtain a more stable preset load grouping, it is necessary to perform cluster analysis on multiple historical operating data based on the initial load grouping, and finally obtain a stable preset load grouping with convergent classification results.

[0055] In an optional implementation, since historical operating data can provide data on four dimensions—outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak—cluster analysis of historical operating data can be performed by integrating these four dimensions. One specific implementation method is as follows: First, iterate through each historical operating data. Based on the outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak of the current historical operating data traversed in this round, and the outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak of the center operating data of each initial load group, calculate the reference distance between the current historical operating data and each initial load group. In this embodiment, the reference distance between the historical operating data of day j and the initial load group of day i can be calculated using the following formula: ,in, , , , These are the outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak value on day j, respectively. , , , The outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak value are the central operating data of the initial load group of the i-th group.

[0056] Secondly, the initial load group corresponding to the minimum reference distance in this round is taken as the load group to which the current historical operation data belongs, until all historical operation data has been traversed in this round; Finally, if this round is the first round, or if the initial load group obtained in this round is different from the initial load group obtained in the previous round, then the central operation data of each initial load group obtained in this round is updated and the traversal of the next round continues, and each initial load group obtained in the last round is used as each preset load group.

[0057] In this embodiment, if this round is the first round, it is temporarily impossible to determine whether the result is stable based on the result of this round. If the initial load group obtained in this round is different from the initial load group obtained in the previous round, it means that the initial load group obtained in this round has not yet converged. It is necessary to use the initial load group obtained in this round as the initial load group before the next round update, and proceed to the step of traversing each historical operating data, calculating the reference distance between the current historical operating data and each initial load group based on the outer ring temperature, outer ring temperature change rate, load change rate and daily maximum load peak of the current historical operating data traversed in this round and the outer ring temperature, outer ring temperature change rate, load change rate and daily maximum load peak of the center operating data of each initial load group, and continue the execution of the next round until this round is not the first round and the initial load group obtained in this round is the same as the initial load group obtained in the previous round.

[0058] In an optional implementation, to improve the rationality of the compensation value corresponding to the type of each preset load group, this embodiment also provides a method for setting the compensation value: The compensation value for each preset load group is set according to the building characteristics, refrigerant type, compressor specifications, and type of each preset load group.

[0059] In this embodiment, for a phase change reference temperature of evaporation temperature, the compensation value for the preset load group is set considering the impact of a 1°C change on the unit's cooling capacity and power consumption. This value can be a parameter adjusted by the system designer based on the building's characteristics. The impact on the unit's cooling capacity and power consumption is determined by the refrigerant type and compressor specifications. A higher compressor efficiency ratio allows for greater cooling capacity with the same power consumption. Different types of preset load groups require different compensation values; for example, high-load groups require larger compensation values.

[0060] In an optional implementation, since the target load grouping is only predicted based on the current operating data collected within a preset time after the VRF air conditioner starts on the same day, in order to avoid inconsistency between the target load grouping and the actual grouping, which would affect the accuracy of compensation on the next day, this embodiment provides an implementation method: First, obtain the peak daily load of the VRF air conditioner on that day; In this embodiment, the maximum load of the day, i.e., the peak value of the maximum load of the day, can be obtained after the VRF air conditioner has finished operating.

[0061] Secondly, based on the outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak of the current operating data, as well as the outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak of the central operating data of each preset load group, the actual load group to which the current operating data belongs is determined from multiple preset load groups. In this embodiment, the method for determining the actual load group can also be to first calculate the reference distance between the current operating data and the center operating data of each preset load group, and then select the preset load group corresponding to the minimum reference distance as the actual load group.

[0062] Third, if the actual load grouping is consistent with the target load grouping, the compensation value of the target load grouping will be used as the reference compensation value; otherwise, the preset compensation value will be used as the reference compensation value. In this embodiment, the preset compensation value can be set to 0. That is, if the actual load group and the target load group are inconsistent, it means that the predicted target load group is not very meaningful and the target load group needs to be re-determined the next day.

[0063] One implementation method is to set a consistency level based on the actual load grouping and the target load grouping. The rule is: when the two are consistent, the consistency level is 1; otherwise, it is 0. The consistency level can be continuously monitored, allowing for a quantitative assessment of the accuracy of temporary judgments based on data from three dimensions: outer ring temperature, outer ring temperature change rate, and load change rate. A higher consistency level indicates stronger reliability of early judgment results at the preset start-up time (e.g., 30 minutes).

[0064] Fourth, the phase change reference temperature is compensated based on the reference compensation value on the next day, so that the VRF air conditioner can be controlled on the next day based on the compensated temperature.

[0065] In an optional implementation, besides setting the reference compensation value to 0 when the actual load group and the target load group are inconsistent, thereby avoiding the control risk of the next day caused by temporary judgment errors, when the inconsistency between the two accounts for a large proportion, in order to prevent the actual situation from deviating further and further from the preset load group, causing the predicted target load group to continuously deviate from the actual load group, this embodiment also provides an implementation method: First, obtain the target load grouping and actual load grouping for each day in the most recent preset number of days; In this embodiment, the preset number of days can be set according to actual needs, for example, the preset number of days can be set to 7 days.

[0066] Secondly, count the number of invalid days in the most recent preset number of days where the target load grouping and the actual load grouping are inconsistent; In this embodiment, if the target load group and the actual load group are inconsistent on a certain day within the most recent preset number of days, it is considered an invalid day, and the number of invalid days is the total number of invalid days. As one implementation, the number of invalid days can be either the number of days within the most recent preset number of days where the target load group and the actual load group are continuously inconsistent, or the total number of days within the most recent preset number of days where the target load group and the actual load group are inconsistent.

[0067] Finally, if the ratio of invalid days to the preset number of days is greater than the preset ratio, multiple historical operating data collected in the most recent preset historical period are re-acquired and the load is regrouped to obtain the latest preset load group. On the next day, the target load group is determined from the latest preset load group, and the phase change reference temperature is compensated according to the compensation value corresponding to the determined target load group. The VRF air conditioner is then controlled on the next day according to the compensated temperature.

[0068] In this embodiment, the preset ratio can be set according to actual needs. With a preset number of days of 7, the preset ratio can be the ratio of 3 invalid days to the preset number of days of 7, which is approximately 43%. A ratio greater than the preset ratio means that the current preset load grouping can no longer adapt to the actual load characteristics of the building. At this time, a forced re-initialization operation of the grouping needs to be performed. The re-initialization operation includes resetting the grouping center and statistical information, fully retaining multiple historical operation data collected within the most recent preset historical period, and recalculating the grouping allocation results from zero. Forced grouping re-initialization should be performed after the FIFO (First-In-First-Out) update (i.e., adding new data and deleting the oldest data) is completed. After the re-initialization is completed, normal control is restored, and consistent historical records are reset synchronously. Through this correction logic, it is possible to cope with seasonal changes and drastic changes in building operation modes: in the short term, control risks are avoided by setting the reference compensation value to 0; in the medium term, the accuracy of temporary judgment is continuously improved by automatically correcting the preset load grouping.

[0069] In an optional implementation, to automatically adapt to seasonal fluctuations and changes in building operation modes, this embodiment also provides a method for updating load groups: First, obtain the daily maximum load peak of the VRF air conditioner and the actual load group to which the current operating data belongs; Secondly, replace the earliest collected daily maximum load peak and operating data in the actual load group with the daily maximum load peak and the previous operating data respectively to obtain the updated actual load group; In this embodiment, the data for the current day is the latest data in the most recent preset historical time period. A FIFO mechanism can be used to replace the oldest data in its load group with the latest data, so that the preset load group always retains only the latest data in the preset historical time period.

[0070] Finally, the central operation data of the updated actual load groups is updated.

[0071] In this embodiment, the central operating data of the actual load group can be obtained by averaging or standard deviation of the operating data in the actual load group.

[0072] Through the aforementioned relearning mechanism, the intra-class variance of the group center and each dimension of data is updated daily, continuously improving prediction accuracy. Especially during seasonal transitions, when outdoor temperature ranges shift and building air conditioning load patterns gradually change, the FIFO mechanism automatically eliminates outdated data, ultimately forming preset load groups adapted to the latest temperature conditions.

[0073] In an optional implementation, this embodiment also provides a method for obtaining currently running data: First, obtain the outdoor temperature at the time the VRF air conditioner starts on the same day, and use the outdoor temperature at the time of start-up as the outer ring temperature; Secondly, the rate of change of the outer ring temperature on that day is calculated based on the outer ring temperature. In this embodiment, the outer ring temperature change rate can be obtained in at least two ways: (1) Collect outdoor temperature in real time according to a preset cycle within a preset duration; calculate the rate of change of outer ring temperature based on outer ring temperature, all outdoor temperatures and preset duration; In this embodiment, the preset period can be set as needed. For example, if the preset period is 5 minutes and the preset duration is 30 minutes, then the outdoor temperature is collected every 5 minutes within 30 minutes of the VRF air conditioner being turned on. The rate of change of the outer ring temperature is calculated by linear fitting using the least squares method. The calculation formula can be: ,in, The rate of change of the outer ring temperature. The m-th sequence number is the sampled sequence number, and n is the total number of sequence numbers collected within the preset time period (i.e., the total number of collections). This is the average value. This is the average of all collected outdoor temperatures. The outer ring temperature, It is the average value of n serial numbers.

[0074] (2) Obtain the highest temperature forecast for the day; calculate the rate of change of the outer ring temperature based on the outer ring temperature, the highest temperature and the preset reference duration.

[0075] In this embodiment, the outer ring temperature can be obtained from the cloud service, which is the real-time temperature at the location corresponding to the VRF air conditioner when it starts operating. The maximum temperature can be obtained from the cloud service, which is the maximum temperature in the daily weather forecast. The preset reference duration can be set as needed. The outer ring temperature change rate = (maximum temperature - outer ring temperature) / preset reference duration. Method (2) can reflect the overall temperature rise trend of the day, making up for the deficiency that the measured trend in the first 30 minutes after operation starts cannot capture the long-term trend, thus improving the prediction accuracy. In addition, if method (2) fails to obtain the outer ring temperature and maximum temperature from the cloud service, method (1) can be used as a backup solution.

[0076] Third, collect air conditioning load in real time according to a preset cycle within a preset time period; Fourth, calculate the load change rate based on the total air conditioning load and the preset duration; In this embodiment, the load change rate can be calculated by linear fitting using the least squares method. The calculation formula is as follows: ,in, For the load change rate, The m-th sequence number is the sampled sequence number, and n is the total number of sequence numbers collected within the preset time period (i.e., the total number of collections). The air conditioning load collected at time m is... This is the average value of all collected air conditioning loads. It is the average value of n serial numbers.

[0077] To illustrate the calculation formula for the load change rate more intuitively, this embodiment uses three scenarios—low load, heavy load, and high load—to specifically explain the process of calculating the load change rate using the above formula.

[0078] For low load, n is 7, and the data for each time point is shown in Table 2.

[0079] Table 2

[0080] The data calculated based on Table 1 is shown in Table 3.

[0081] Table 3

[0082] According to Table 3, the results are as follows: .

[0083] For medium load, n is 7, and the data for each time point are shown in Table 4.

[0084] Table 4

[0085] The data calculated based on Table 3 is shown in Table 5.

[0086] Table 5

[0087] According to Table 5, the results are as follows: .

[0088] For high load, n is 7, and the data for each time point is shown in Table 6.

[0089] Table 6

[0090] The data calculated based on Table 6 are shown in Table 7.

[0091] Table 7

[0092] According to Table 7, the results are as follows: .

[0093] Fifth, the outer ring temperature, the rate of change of the outer ring temperature, and the rate of change of the load are used as the current operating data.

[0094] In this embodiment, to illustrate the air conditioning control method provided in this embodiment as a whole, this embodiment uses a preset duration of 30 minutes and a preset historical period of 14 days as an example for explanation. Please refer to [link / reference]. Figure 3 , Figure 3 This is an example flowchart of the overall air conditioning control method provided in this embodiment. The process includes three stages: Phase 1 (Initial Learning): The VRF air conditioner operates for 14 days as a data acquisition cycle. At the end of each day's operation, four key parameters are stored in RAM: the outer ring temperature at the start of operation, the rate of change of the outer ring temperature after 30 minutes of operation, the load change rate, and the peak daily load during operation. After collecting 14 days of complete data, a K-means grouping operation is performed to generate three load modes: high, medium, and low. Before data acquisition is complete, the target evaporating temperature compensation value is set to 0 (or the original set value is retained) for unit operation control.

[0095] Phase 2 (Grouping Decision and Predictive Control): Starting from day 15, the outer ring temperature will be monitored 30 minutes after the start of daily operation. , outer ring temperature change rate Load change rate Once all data is determined, the predicted grouping category for the day is inferred by calculating the distance between each running data point and the grouping centers that have completed learning in truncation 1. (i.e., the target load group in this embodiment). Based on this determination result, a compensation value for the target evaporation temperature is immediately set. And react throughout the entire subsequent operating period of the day.

[0096] Phase 3 (Final Judgment, Verification, and Model Update) After daily operation ceases and the daily maximum load peak is determined, the final actual grouping determination is completed using four characteristic quantities: the rate of change of outer ring temperature, the rate of change of load, and the daily maximum load peak during operation. (i.e., the actual load grouping in this embodiment), and record the agreement between the final judgment and the previous provisional prediction. If an inconsistency occurs, the evaporation temperature compensation value will be adjusted the following day. = 0, to avoid and control abnormal risks.

[0097] Furthermore, if inconsistencies persist to a set proportion, a classification center shift is identified, and the classification model (i.e., the preset load grouping in this embodiment) is forcibly reinitialized. Simultaneously, after confirming daily downtime measurement data, the day's operational data is added to the learning dataset; and a FIFO (First-In, First-Out) mechanism is used to delete the oldest historical data. Through this mechanism, the system always retains only the most recent 14 days of data, automatically adapting to seasonal fluctuations and changes in building usage patterns.

[0098] To perform the corresponding steps in the above embodiments and various possible implementations, an implementation of the air conditioning control device 100 is given below. Please refer to... Figure 4 , Figure 4 This is a block diagram of the air conditioning control device provided in this embodiment, which is applied to a variable refrigerant flow (VRF) air conditioner. It should be noted that the basic principle and technical effects of the air conditioning control device 100 provided by this invention are the same as those of the corresponding embodiments described above. For the sake of brevity, some parts of this embodiment are not mentioned.

[0099] The air conditioning control device 100 includes an acquisition module 110, a determination module 120, and a compensation module 130.

[0100] The acquisition module 110 is used to acquire the current operating data collected by the VRF air conditioner within a preset time after it is started on the same day.

[0101] The determination module 120 is used to determine the target load group to which the current operating data belongs from multiple preset load groups. The multiple preset load groups are determined by grouping multiple historical operating data collected within a preset historical period. The preset load types of the multiple preset load groups are different. Each preset load type corresponds to temperature compensation of the phase change reference temperature of the VRF air conditioner to meet the compensation value of the corresponding preset load type.

[0102] The compensation module 130 is used to compensate the phase change reference temperature according to the compensation value corresponding to the target load group, so as to control the VRF air conditioner according to the compensated temperature.

[0103] In an optional implementation, the current operating data includes the outer ring temperature, the outer ring temperature change rate, and the load change rate; the determination module 120 is specifically used for: Acquire the central operating data for each preset load group. The central operating data includes the outer ring temperature, outer ring temperature change rate, and load change rate, which characterize the load characteristics of the corresponding preset load group. Based on the current operating data of outer ring temperature, outer ring temperature change rate and load change rate, and the operating data of each center of outer ring temperature, outer ring temperature change rate and load change rate, calculate the comprehensive distance between the current operating data and the operating data of each center of outer ring temperature and load change rate. The preset load group to which the central operation data corresponding to the minimum value of multiple comprehensive distances belongs is taken as the target load group.

[0104] In an optional implementation, the determining module 120 is further configured to: The load sequence is obtained by sorting the load change rates from largest to smallest based on multiple historical operating data. The load sequence is segmented according to the preset load type to obtain multiple initial load groups; Based on multiple initial load groups, cluster analysis is performed on multiple historical operating data to obtain multiple preset load groups.

[0105] In an optional implementation, each historical operating data includes outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak value. The initial center operating data of each initial load group includes outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak value, which characterize the load characteristics of the corresponding preset load group. The determination module 120 is also specifically used to perform cluster analysis on multiple historical operating data based on multiple initial load groups to obtain multiple preset load groups, and is also specifically used for: Traverse each historical operating data point, and calculate the reference distance between the current historical operating data and each initial load group based on the outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak of the current historical operating data traversed in this round, as well as the outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak of the center operating data of each initial load group. The initial load group corresponding to the minimum reference distance in this round is taken as the load group to which the current historical operation data belongs, until all historical operation data has been traversed in this round; If this round is the first round, or if the initial load group obtained in this round is different from the initial load group obtained in the previous round, then the central operation data of each initial load group obtained in this round is updated and the traversal of the next round continues, and each initial load group obtained in the last round is used as each preset load group.

[0106] In an optional implementation, the determining module 120 is further configured to: The compensation value for each preset load group is set according to the building characteristics, refrigerant type, compressor specifications, and type of each preset load group.

[0107] In an optional implementation, the current operating data includes the outer ring temperature, the outer ring temperature change rate, and the load change rate; the compensation module 130 is further used for: Obtain the peak daily load of the VRF air conditioner on that day; Based on the outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak of the current operating data, and the outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak of the center operating data of each preset load group, determine the actual load group to which the current operating data belongs from multiple preset load groups; If the actual load grouping is consistent with the target load grouping, the compensation value of the target load grouping will be used as the reference compensation value; otherwise, the preset compensation value will be used as the reference compensation value. The phase change reference temperature is compensated based on the reference compensation value on the next day, and the VRF air conditioner is controlled based on the compensated temperature on the next day.

[0108] In an optional implementation, the compensation module 130 is further configured to: Retrieve the target load grouping and actual load grouping for each day within the most recent preset number of days; Count the number of invalid days in the recent preset number of days where the target load grouping and the actual load grouping are inconsistent; If the ratio of invalid days to the preset number of days is greater than the preset ratio, multiple historical operating data collected in the most recent preset historical period will be re-acquired and the load will be regrouped to obtain the latest preset load group. On the next day, the target load group will be determined from the latest preset load group, and the phase change reference temperature will be compensated according to the compensation value corresponding to the determined target load group. The VRF air conditioner will be controlled on the next day according to the compensated temperature.

[0109] In an optional implementation, the compensation module 130 is further configured to: Obtain the daily maximum load peak value of the VRF air conditioner and the actual load group to which the current operating data belongs; Replace the earliest collected daily maximum load peak and operating data in the actual load group with the daily maximum load peak and current operating data respectively to obtain the updated actual load group; Update the central operation data of the updated actual load groups.

[0110] In an optional implementation, the acquisition module 110 is specifically used for: Obtain the outdoor temperature at the time the VRF air conditioner starts on the same day, and use the outdoor temperature at the time of start-up as the outer ring temperature; Calculate the rate of change of the outer ring temperature on the same day based on the outer ring temperature; Collect air conditioning load in real time according to a preset cycle within a preset time period; Calculate the load change rate based on the total air conditioning load and the preset duration; The outer ring temperature, the rate of change of the outer ring temperature, and the rate of change of the load are used as the current operating data.

[0111] In an optional implementation, when the acquisition module 110 is specifically used to calculate the daily rate of change of the outer ring temperature based on the outer ring temperature, it is further used to: The outdoor temperature is collected in real time according to a preset cycle within a preset duration. Calculate the rate of change of the outer ring temperature based on the outer ring temperature, the total outdoor temperature, and the preset duration; or, Get the day's forecast maximum temperature; The rate of change of outer ring temperature is calculated based on the outer ring temperature, the highest air temperature, and the preset reference duration.

[0112] This invention also provides a block diagram of a VRF air conditioner 10, which implements the air conditioning control method described in the foregoing embodiments. Please refer to... Figure 5 , Figure 5 This is a block diagram of the VRF air conditioner 10 provided in this embodiment. The VRF air conditioner 10 includes a controller 11, a memory 12 and a bus 13. The controller 11 and the memory 12 are connected through the bus 13.

[0113] The controller 11 can be an integrated circuit chip with signal processing capabilities. In implementation, each step of the air conditioning control method described in the above embodiments can be completed by the integrated logic circuits in the hardware of the controller 11 or by software instructions. The controller 11 can be a general-purpose processor, including a DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), FPGA (Field Programmable Logic Gate Array), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0114] The memory 12 is used to store the program that implements the air conditioning control method. The program can be stored in the memory 12 in the form of software or firmware or a software function module embedded in the OS (Operating System) of the VRF air conditioner 10.

[0115] After receiving the execution instruction, the controller 11 executes the program to implement the air conditioning control method of the aforementioned embodiment.

[0116] VRF air conditioning regulates the temperature of different rooms or areas by controlling the flow of refrigerant, thereby achieving high efficiency, energy saving, and precise temperature control. A VRF air conditioning system consists of an outdoor unit connected to multiple indoor units. Each indoor unit can independently adjust the temperature according to actual needs, making the operation of the entire VRF air conditioning system more flexible and efficient.

[0117] In summary, the embodiments of the present invention provide an air conditioning control method, device, and VRF air conditioner. The method includes: acquiring current operating data collected by the VRF air conditioner within a preset time period after its startup on a given day; determining the target load group to which the current operating data belongs from multiple preset load groups, wherein the multiple preset load groups are determined by grouping multiple historical operating data collected within a preset historical time period, and the preset load types of the multiple preset load groups are different, each preset load type corresponding to temperature compensation of the phase change reference temperature of the VRF air conditioner to meet the compensation value of the corresponding preset load type; and compensating the phase change reference temperature according to the compensation value corresponding to the target load group, so as to control the VRF air conditioner according to the compensated temperature. Compared with the prior art, this embodiment has at least the following advantages: (1) After grouping multiple historical operating data collected within a preset historical period into load groups, multiple preset load groups with different preset load types are determined. For each preset load type, temperature compensation is set for the phase change reference temperature of the VRF air conditioner to meet the compensation value of the corresponding preset load type. Based on the current operating data collected within a preset time after the VRF air conditioner is started on the same day, the current target load group is determined. Then, based on the compensation value corresponding to the target load group, the phase change reference temperature is compensated and the VRF air conditioner is controlled. This can meet the air conditioner load demand and avoid the air conditioner from overloading. (1) Increased power consumption due to capacity operation enables energy-saving control of VRF air conditioning; (2) Based on advance prediction, proactive control can be achieved, which can avoid the problem of insufficient unit capacity while achieving efficient operation; (3) Daily monitoring of prediction accuracy: when the accuracy drops, the standard operation mode is automatically restored to avoid control risks; if the accuracy is consistently low, forced group re-initialization is performed to improve the overall reliability of the system; (4) Prediction calculation and model relearning are both lightweight logics, which do not require external communication and high-performance computing support. They can be directly added to the controller of the existing VRF air conditioning system, so the import cost and development load are at a low level.

[0118] The above descriptions are merely various embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An air conditioning control method, characterized in that, Applied to variable refrigerant flow (VRF) air conditioners, the method includes: Obtain the current operating data collected by the VRF air conditioner within a preset time period after it is started on the same day; The target load group to which the current operating data belongs is determined from multiple preset load groups. The multiple preset load groups are determined by grouping multiple historical operating data collected within a preset historical period. The preset load types of the multiple preset load groups are different. Each preset load type corresponds to temperature compensation of the phase change reference temperature of the VRF air conditioner to meet the compensation value of the corresponding preset load type. The phase change reference temperature is compensated according to the compensation value corresponding to the target load group, so as to control the VRF air conditioner according to the compensated temperature.

2. The method according to claim 1, characterized in that, The current operating data includes outer ring temperature, outer ring temperature change rate, and load change rate; The step of determining the target load group to which the current operating data belongs from multiple preset load groups includes: Obtain the central operating data for each preset load group, wherein the central operating data includes the outer ring temperature, the outer ring temperature change rate, and the load change rate, which characterize the load characteristics of the corresponding preset load group; Based on the outer ring temperature, outer ring temperature change rate, and load change rate of the current operating data, and the outer ring temperature, outer ring temperature change rate, and load change rate of each of the central operating data, calculate the comprehensive distance between the current operating data and each of the central operating data; The preset load group to which the central operation data corresponding to the minimum value of multiple comprehensive distances belongs is taken as the target load group.

3. The method according to claim 1, characterized in that, Before the step of determining the target load group to which the current operating data belongs from multiple preset load groups, the method further includes: The load sequence is obtained by sorting the load change rates of the various historical operating data from largest to smallest. The load sequence is segmented according to the preset load type to obtain multiple initial load groups; Based on the multiple initial load groups, cluster analysis is performed on the multiple historical operating data to obtain the multiple preset load groups.

4. The method according to claim 3, characterized in that, Each set of historical operating data includes outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak value. The initial center operating data of each initial load group includes outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak value, which characterize the load characteristics of the corresponding preset load group. The step of performing cluster analysis on the historical operating data based on the multiple initial load groups to obtain the multiple preset load groups includes: Traverse each of the historical operating data, and calculate the reference distance between the current historical operating data and each of the initial load groups based on the outer ring temperature, outer ring temperature change rate, load change rate and daily maximum load peak of the current historical operating data traversed in this round, and the outer ring temperature, outer ring temperature change rate, load change rate and daily maximum load peak of the center operating data of each initial load group; The initial load group corresponding to the minimum reference distance in this round is taken as the load group to which the current historical operation data belongs, until all the historical operation data has been traversed in this round; If this round is the first round, or if the initial load group obtained in this round is different from the initial load group obtained in the previous round, then the central operation data of each initial load group obtained in this round is updated and the traversal of the next round continues, and each initial load group obtained in the last round is used as each of the preset load groups.

5. The method according to claim 4, characterized in that, After the step of using each initial load group obtained in the last round as each of the preset load groups, the method further includes: The compensation value for each preset load group is set according to the building characteristics where the VRF air conditioner is located, the type of refrigerant used, the compressor specifications, and the type of each preset load group.

6. The method according to claim 1, characterized in that, The current operating data includes the outer ring temperature, the outer ring temperature change rate, and the load change rate; After the step of compensating the phase change reference temperature according to the compensation value corresponding to the target load group, and controlling the VRF air conditioner according to the compensated temperature, the method further includes: Obtain the peak daily load of the VRF air conditioner on that day; Based on the outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak of the current operating data, and the outer ring temperature, outer ring temperature change rate, load change rate, and daily maximum load peak of the center operating data of each preset load group, the actual load group to which the current operating data belongs is determined from the plurality of preset load groups; If the actual load group and the target load group are consistent, the compensation value of the target load group shall be used as the reference compensation value; otherwise, the preset compensation value shall be used as the reference compensation value. The phase change reference temperature is compensated based on the reference compensation value on the next day, so that the VRF air conditioner is controlled based on the compensated temperature on the next day.

7. The method according to claim 6, characterized in that, After the step of using the preset compensation value as the reference compensation value, the method further includes: Retrieve the target load grouping and actual load grouping for each day within the most recent preset number of days; Count the number of invalid days in the recent preset number of days where the target load grouping and the actual load grouping are inconsistent; If the ratio of the invalid days to the preset number of days is greater than the preset ratio, then multiple historical operating data collected within the most recent preset historical period are reacquired and the load is regrouped to obtain the latest preset load group. On the next day, the target load group is determined from the latest preset load group, and the phase change reference temperature is compensated according to the compensation value corresponding to the determined target load group. The VRF air conditioner is then controlled on the next day according to the compensated temperature.

8. The method according to claim 1, characterized in that, After the step of compensating the phase change reference temperature according to the compensation value corresponding to the target load group, and controlling the VRF air conditioner according to the compensated temperature, the method further includes: Obtain the daily maximum load peak value of the VRF air conditioner and the actual load group to which the current operating data belongs; Replace the earliest collected daily maximum load peak and operating data in the actual load group with the daily maximum load peak and the current operating data respectively to obtain the updated actual load group; Update the central operation data of the updated actual load group.

9. The method according to claim 1, characterized in that, The steps for obtaining the current operating data collected by the VRF air conditioner within a preset time period after it is started on the same day include: Obtain the outdoor temperature of the VRF air conditioner at the time of its start-up on the same day, and use the outdoor temperature at the time of its start-up on the same day as the outer ring temperature; Calculate the rate of change of the outer ring temperature on that day based on the outer ring temperature; The air conditioning load is collected in real time according to a preset cycle within the preset time period; Calculate the load change rate based on all the air conditioning loads and the preset duration; The outer ring temperature, the outer ring temperature change rate, and the load change rate are used as the current operating data.

10. The method according to claim 9, characterized in that, The step of calculating the rate of change of the outer ring temperature on a given day based on the outer ring temperature includes: The outdoor temperature is collected in real time according to a preset cycle within the preset duration. The outer ring temperature change rate is calculated based on the outer ring temperature, all outdoor temperatures, and the preset duration. or, Get the day's forecast maximum temperature; The outer ring temperature change rate is calculated based on the outer ring temperature, the highest air temperature, and the preset reference duration.

11. An air conditioning control device, characterized in that, The device, applied to a variable refrigerant flow (VRF) air conditioner, includes: The acquisition module is used to acquire the current operating data collected by the VRF air conditioner within a preset time after it is started on the same day; The determination module is used to determine the target load group to which the current operating data belongs from multiple preset load groups. The multiple preset load groups are determined by grouping multiple historical operating data collected within a preset historical period. The preset load types of the multiple preset load groups are different. Each preset load type corresponds to temperature compensation of the phase change reference temperature of the VRF air conditioner to meet the compensation value of the corresponding preset load type. The compensation module is used to compensate the phase change reference temperature according to the compensation value corresponding to the target load group, so as to control the VRF air conditioner according to the compensated temperature.

12. A VRF air conditioner, characterized in that, It includes a controller and a memory, the memory being used to store a program, and the controller being used to implement the air conditioning control method as described in any one of claims 1-10 when executing the program.

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