An air conditioning system and method for an energy efficient air conditioner

Abstract

The application provides an air conditioning system and method for energy-saving air conditioners, which determines the dynamic coupling relationship between the air flow speed and the temperature in each region by monitoring the temperature and the air flow speed of the energy-saving air conditioner during operation, determines the equivalent energy consumption variation generated by the energy-saving air conditioner in each region by the temperature variation characteristics and the air flow speed variation characteristics of each region, determines the local energy efficiency deviation between each region in the room according to the dynamic coupling relationship between the air flow speed and the temperature in each region and the equivalent energy consumption variation generated by the energy-saving air conditioner in each region, further determines the end air volume distribution parameters of the energy-saving air conditioner for each air outlet of the air conditioner, and further adjusts the air outlet of the energy-saving air conditioner by all the end air volume distribution parameters. According to the application, the energy-saving air conditioner can be dynamically adjusted based on the energy efficiency difference between the indoor regions.

Description

Technical Field

[0001] This application relates to the field of air conditioning technology, and more specifically, to an air conditioning system and method for energy-saving air conditioning. Background Technology

[0002] Air conditioning refers to the use of technical means to adjust and control air parameters (such as temperature, humidity, cleanliness, airflow speed, etc.) in a specific space to meet the requirements of human comfort, production processes, or equipment operation. It is one of the core technologies of modern building environment control.

[0003] Traditional air conditioning systems typically use the average temperature of the entire indoor space or a few fixed monitoring points as the adjustment target, lacking refined perception and control of the microenvironment in different indoor areas (especially the dynamic coupling relationship between airflow speed and temperature). This makes it difficult for air conditioners to accurately match the actual needs of each area, often resulting in localized overcooling, overheating, or uneven airflow distribution, causing unnecessary energy waste (such as lowering the overall temperature or increasing the airflow to compensate for local discomfort). Although existing zoning control technology can identify regional temperature differences, it fails to fully combine dynamic changes in airflow speed, differences in energy efficiency between areas, and the energy consumption status of the air conditioner itself for comprehensive analysis and optimization, limiting the in-depth exploration of energy-saving potential. Therefore, how to dynamically adjust energy-saving air conditioners based on the differences in energy efficiency between indoor areas has become a problem faced by the industry. Summary of the Invention

[0004] This application provides an air conditioning system and method for energy-saving air conditioners, which can dynamically adjust the energy-saving air conditioner based on the energy efficiency differences between indoor areas.

[0005] In a first aspect, this application provides an air conditioning method for an energy-saving air conditioner, wherein an indoor space equipped with an energy-saving air conditioner is divided into multiple zones based on the airflow coverage and location of the air conditioner's air outlet, wherein the energy-saving air conditioner is a central air conditioning system, and the method includes the following steps: Monitor the temperature and airflow velocity in each area during the operation of the energy-saving air conditioner; Based on all monitored temperatures and airflow velocities, the dynamic coupling relationship between airflow velocity and temperature in each region is determined. By combining the temperature change characteristics and airflow velocity change characteristics of each region with the energy consumption status of the energy-saving air conditioner, an equivalent analysis of the energy consumption conversion of the energy-saving air conditioner in the corresponding region is performed to obtain the equivalent energy consumption change generated by the energy-saving air conditioner in each region. Based on the dynamic coupling relationship between airflow velocity and temperature in each area and the change in equivalent energy consumption generated by energy-saving air conditioners in each area, the energy efficiency loss of the indoor space equipped with energy-saving air conditioners is evaluated, and the local energy efficiency deviation between the various areas of the indoor space is obtained. Based on the spatial distribution of various areas in the room equipped with energy-saving air conditioners and all local energy efficiency deviations, combined with the air outlet parameter adjustment range of each air conditioner outlet, the terminal air volume distribution parameters of the energy-saving air conditioner to each air outlet are determined, and then the air outlets of the energy-saving air conditioner are adjusted by all terminal air volume distribution parameters.

[0006] In some embodiments, determining the dynamic coupling relationship between airflow velocity and temperature in each region based on all monitored temperatures and all airflow velocities specifically includes: Select a region as the selected area, and determine the correlation between airflow velocity and temperature in the selected area based on all monitored temperatures and all airflow velocities in the selected area. Based on the aforementioned correlation, the time lag characteristics between airflow changes and temperature changes in the selected region are determined; The dynamic coupling relationship between airflow velocity and temperature in the selected region is determined by the time delay characteristics.

[0007] Continue to determine the dynamic coupling relationship between airflow velocity and temperature in the remaining regions.

[0008] In some embodiments, by combining the temperature change characteristics and airflow speed change characteristics of each region with the energy consumption status of the energy-saving air conditioner, an equivalent analysis is performed on the energy consumption conversion of the energy-saving air conditioner in the corresponding region. The specific changes in equivalent energy consumption generated by the energy-saving air conditioner in each region include: Obtain the energy consumption status of the energy-saving air conditioner; Determine the temperature and airflow velocity characteristics of each region; The temperature contribution characteristics of temperature to energy consumption are determined based on the energy consumption status and the temperature change characteristics of each region. The airflow contribution characteristics of airflow velocity to energy consumption are determined based on the energy consumption status and the airflow velocity change characteristics of each region. The equivalent energy consumption change generated by energy-saving air conditioning in each region is determined by the temperature contribution characteristics and the airflow contribution characteristics.

[0009] In some embodiments, the energy efficiency loss of the indoor space equipped with energy-saving air conditioning is assessed based on the dynamic coupling relationship between airflow velocity and temperature in each area and the equivalent energy consumption change generated by the energy-saving air conditioning in each area, and the local energy efficiency deviation between the various areas of the indoor space specifically includes: The energy efficiency loss areas of each indoor area equipped with energy-saving air conditioners are determined based on the dynamic coupling relationship between airflow velocity and temperature in each area and the change in equivalent energy consumption generated by energy-saving air conditioners in each area. Two regions are selected as the two designated regions, and the difference in energy efficiency distribution between the two selected regions is determined by the energy efficiency loss areas corresponding to the two selected regions. The local energy efficiency deviation between the two selected regions is determined based on the energy efficiency distribution differences. Continue to determine the local energy efficiency deviations between the remaining areas of the room.

[0010] In some embodiments, determining the terminal airflow distribution parameters of the energy-saving air conditioner to each air outlet based on the spatial distribution of various areas in the indoor space equipped with the energy-saving air conditioner and all local energy efficiency deviations, combined with the air outlet parameter adjustment range of each air outlet, specifically includes: Determine the spatial distribution of each area in the indoor space equipped with energy-saving air conditioners; Obtain the air outlet parameter adjustment range for each air conditioner vent; The optimization targets for each air conditioning outlet are determined based on the spatial distribution of each region and all local energy efficiency deviations. The terminal air volume distribution parameters of the energy-saving air conditioner to the corresponding air outlet are determined by adjusting the air outlet parameters of each air outlet and the optimization target.

[0011] In some embodiments, spatial coordinate modeling is used to obtain the spatial location distribution of various areas in the indoor space equipped with energy-saving air conditioning.

[0012] In some embodiments, the temperature and airflow velocity in each area are monitored by an integrated sensor node during the operation of the energy-efficient air conditioner.

[0013] Secondly, this application provides an air conditioning system for energy-saving air conditioning, comprising: The monitoring module is used to monitor the temperature and airflow speed in various areas during the operation of the energy-saving air conditioner; The processing module is used to determine the dynamic coupling relationship between airflow velocity and temperature in each region based on all monitored temperatures and airflow velocities. By combining the temperature change characteristics and airflow velocity change characteristics of each region with the energy consumption status of the energy-saving air conditioner, the module performs an equivalent analysis of the energy consumption conversion of the energy-saving air conditioner in the corresponding region, and obtains the equivalent energy consumption change generated by the energy-saving air conditioner in each region. The processing module is also used to assess the energy efficiency loss of the indoor space equipped with energy-saving air conditioners based on the dynamic coupling relationship between airflow speed and temperature in each area and the equivalent energy consumption change generated by the energy-saving air conditioners in each area, so as to obtain the local energy efficiency deviation between the various areas of the indoor space. The execution module is used to determine the terminal air volume distribution parameters of the energy-saving air conditioner to each air outlet based on the spatial location distribution of each area in the room equipped with the energy-saving air conditioner and all local energy efficiency deviations, combined with the air outlet parameter adjustment range of each air outlet. Then, the air outlet of the energy-saving air conditioner is adjusted by all the terminal air volume distribution parameters.

[0014] Thirdly, this application provides a computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described air conditioning method for energy-saving air conditioning.

[0015] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described air conditioning method for energy-saving air conditioners.

[0016] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects: The air conditioning system and method for energy-saving air conditioners provided in this application first monitor the temperature and airflow velocity in each area during the operation of the energy-saving air conditioner; based on all monitored temperatures and airflow velocities, determine the dynamic coupling relationship between airflow velocity and temperature in each area; perform an equivalent analysis of the energy consumption conversion of the energy-saving air conditioner in the corresponding area by combining the temperature change characteristics and airflow velocity change characteristics of each area with the energy consumption status of the energy-saving air conditioner, and obtain the equivalent energy consumption change generated by the energy-saving air conditioner in each area; assess the energy efficiency loss of the indoor space equipped with the energy-saving air conditioner based on the dynamic coupling relationship between airflow velocity and temperature in each area and the equivalent energy consumption change generated by the energy-saving air conditioner in each area, and obtain the local energy efficiency deviation between the various areas of the indoor space; based on the spatial distribution of each area of ​​the indoor space equipped with the energy-saving air conditioner and all local energy efficiency deviations, combined with the air outlet parameter adjustment range of each air conditioner outlet, determine the terminal air volume distribution parameters of the energy-saving air conditioner to each air conditioner outlet, and then adjust the air conditioner outlet of the energy-saving air conditioner by all terminal air volume distribution parameters.

[0017] Therefore, this application, in the air conditioning process of energy-saving air conditioners, firstly monitors the temperature and airflow velocity in each area during operation. This provides a real-time environmental data foundation, enabling the system to perceive dynamic changes in each area and laying the groundwork for subsequent analysis of differences between areas, thus supporting more precise adjustment decisions. Secondly, based on the monitoring data, the dynamic coupling relationship between airflow velocity and temperature is determined, and combined with the energy consumption status, an equivalent heat load analysis is performed to obtain the equivalent energy consumption change. This facilitates the quantification of the heat load impact and energy efficiency in each area, identifying inefficient hot or cold spots, and providing a basis for evaluating energy efficiency. The differences provide data support; next, energy efficiency loss is assessed based on dynamic coupling relationships and changes in equivalent energy consumption, yielding local energy efficiency deviations. This directly addresses technical issues, assessing the energy efficiency differences and degree of loss between regions, enabling the system to identify which areas require priority optimization, thus improving the targeting and fairness of adjustments. Finally, based on spatial distribution, local energy efficiency deviations, and the range of outlet air parameters, terminal airflow allocation parameters are determined and the air outlets are adjusted. This achieves dynamic airflow allocation, compensating for energy efficiency deviations by optimizing airflow coverage, reducing overall energy waste, and thereby improving the comprehensive energy-saving effect of the air conditioning system. Using the above scheme, energy-saving air conditioning can be dynamically adjusted based on energy efficiency differences between indoor areas. Attached Figure Description

[0018] Figure 1 This is an exemplary flowchart of an air conditioning method for an energy-saving air conditioner according to some embodiments of this application; Figure 2 This is an exemplary flowchart illustrating the determination of dynamic coupling relationships according to some embodiments of this application; Figure 3 This is an exemplary flowchart illustrating the determination of terminal airflow distribution parameters according to some embodiments of this application; Figure 4 This is a schematic diagram of the structure of an air conditioning system for energy-saving air conditioning according to some embodiments of this application; Figure 5 This is a schematic diagram of the structure of a computer device that implements an air conditioning method for energy-saving air conditioning, according to some embodiments of this application. Detailed Implementation

[0019] To better understand the technical solution of this application, the technical solution of this application will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0020] refer to Figure 1 The figure is an exemplary flowchart of an air conditioning method for an energy-saving air conditioner according to some embodiments of this application. The air conditioning method for an energy-saving air conditioner mainly includes the following steps: In some embodiments, dividing an indoor space equipped with an energy-saving air conditioner into multiple zones based on the airflow coverage and location of the air conditioner vent can be achieved in the following way: First, the airflow field of the vent at a typical angle (e.g., 30° downwards and 0° left and right by default) is simulated using computational fluid dynamics to determine the effective coverage area with a wind speed ≥ 0.5 m / s (e.g., a conical area 1-5 meters from the vent and 0-4 meters laterally); simultaneously, combined with the indoor functional layout (e.g., sofa area, activity area, and dining area in a living room) and the distribution of obstacles (e.g., furniture and partitions), the coverage area is divided into 3-5 non-uniform zones, such as: Zone A (high wind speed zone 1-2 meters from the vent), Zone B (medium wind speed zone 2-3 meters in the center), and Zone C (low wind speed zone 3-5 meters at the edge). Temperature, humidity, and wind speed sensors are deployed at the center of each zone, and the zone boundaries are determined based on the wind speed gradient (e.g., 0.5-1 m / s for the A and B boundaries) and functional continuity to ensure that the zoning conforms to both the physical characteristics of airflow and the needs of space use.

[0021] In step 101, the temperature and airflow velocity in each area are monitored during the operation of the energy-saving air conditioner.

[0022] In specific implementation, an integrated sensor node (5cm×5cm×3cm) is deployed at the center of each area, including a high-precision digital temperature sensor (range -20℃~60℃, accuracy ±0.1℃), a hot-wire anemometer (range 0~10m / s, response time <0.5 seconds), and a temperature and humidity compensation module. The deployed integrated sensor node monitors the temperature and airflow velocity in each area during the operation of the energy-saving air conditioner. The temperature represents the temperature of the area where the energy-saving air conditioner is operating, and the airflow velocity represents the speed of the airflow from the air conditioner outlet to the area. Other monitoring methods can also be used in other embodiments, which are not limited here.

[0023] It should be noted that the integrated sensor sampling frequency is set to 1Hz (configurable) to capture dynamic changes. It adopts a self-organizing network topology, and when the signal of a node is weak, it automatically transmits through the relay of adjacent nodes to ensure more than 99% data integrity. In order to eliminate measurement errors, each sensor is calibrated in a wind tunnel before deployment (wind speed calibration points: 0.5m / s, 2m / s, 5m / s; temperature calibration points: 20℃, 26℃, 32℃). Since there are many kinds of interferences during the monitoring process (such as environmental factors and the air conditioner itself), outliers are removed by sliding window filtering (window size 5 seconds) during operation. Finally, the processed data is stored in a circular buffer (capacity 10,000 records) for subsequent analysis.

[0024] In step 102, the dynamic coupling relationship between airflow velocity and temperature in each region is determined based on all monitored temperatures and airflow velocities. The energy consumption conversion of the energy-saving air conditioner in the corresponding region is analyzed by combining the temperature change characteristics and airflow velocity change characteristics of each region with the energy consumption status of the energy-saving air conditioner, and the equivalent energy consumption change generated by the energy-saving air conditioner in each region is obtained.

[0025] In some embodiments, reference Figure 2 As shown, this figure is an exemplary flowchart for determining dynamic coupling relationships in some embodiments of this application. In this embodiment, determining the dynamic coupling relationship between airflow velocity and temperature in each region based on all monitored temperatures and all airflow velocities can be achieved using the following steps: First, in step 1021, a region is selected as the selected region, and the correlation between airflow velocity and temperature in the selected region is determined based on all temperatures and all airflow velocities monitored in the selected region. Secondly, in step 1022, the time lag characteristics between airflow changes and temperature changes in the selected area are determined based on the correlation. Furthermore, in step 1023, the dynamic coupling relationship between airflow velocity and temperature in the selected region is determined by the time delay characteristics.

[0026] Finally, in step 1024, the dynamic coupling relationship between airflow velocity and temperature in the remaining region is determined.

[0027] In specific implementation, the correlation between airflow velocity and temperature in the selected area can be determined by the following method based on all monitored temperatures and airflow velocities in the selected area: All monitored temperatures and airflow velocities in the selected area are arranged in chronological order of monitoring time to obtain a temperature sequence and an airflow velocity sequence. A cross-correlation analysis method is then used to calculate the correlation between airflow velocity and temperature by combining the temperature sequence and the airflow velocity sequence. For example, a positive correlation indicates that the temperature rises as the airflow velocity increases. The correlation represents the relationship between airflow velocity and temperature. Other methods can also be used in other embodiments, which are not limited here.

[0028] In specific implementation, determining the time lag characteristics between airflow changes and temperature changes in a selected region based on the aforementioned correlation can be achieved in the following way: The time lag characteristics are identified by calculating the cross-correlation function between the temperature sequence and the delayed airflow velocity sequence based on the correlation. Specifically, the airflow velocity sequence is sequentially delayed by different time steps, and the cross-correlation analysis method is used to calculate the cross-correlation coefficients of the delayed airflow velocity sequence and temperature sequence respectively. The delay time corresponding to the maximum value of the cross-correlation coefficient is the time lag characteristic between airflow changes and temperature changes. The time lag characteristic represents the characteristics of the time lag between airflow changes and temperature changes in the region. To reduce noise interference, the original data can be smoothed, and the confidence interval of the time lag can be estimated using a bootstrap method to verify the stability of the time lag characteristic. Other methods can also be used in other embodiments, which are not limited here.

[0029] In specific implementation, determining the dynamic coupling relationship between airflow velocity and temperature in a selected region based on the time delay characteristics can be achieved in the following way: A vector autoregressive (VAR) model is constructed based on the identified time delay characteristics, and the time delay values ​​are directly converted into the model's delay order, thereby determining the specific variable combination containing the temperature sequence and the delayed airflow velocity sequence; after estimating the parameters of the VAR model using the least squares method, the merits of models with different delay orders are evaluated using the Bayesian information criterion, and the optimized delay order is used to correct the initial VAR model structure; the optimized VAR model parameters are converted into the state transition matrix and input matrix of the state-space model, implicitly embedding the time delay relationship into the state equation, and then the model parameters are updated using real-time data through Kalman filtering. The system captures time-varying characteristics; utilizing the characteristic that the state-space model already includes delayed airflow velocity variables, a regression equation for Granger causality testing is directly constructed to verify the causality of airflow velocity on temperature. If the test passes, the physical meaning of the model variable relationship is confirmed; based on the causally verified state-space model, a standard deviation shock is applied to the airflow velocity variable to quantify the dynamic response trajectory of the temperature variable through the impulse response function, and further, the contribution ratio of airflow velocity change to temperature fluctuation is calculated through variance decomposition. The combination of the above-mentioned causality of airflow velocity on temperature, the dynamic response trajectory of the temperature variable, and the contribution ratio of airflow velocity change to temperature fluctuation is taken as the dynamic coupling relationship between airflow velocity and temperature in the region; other methods can also be used to determine this in other embodiments, which are not limited here.

[0030] It should be noted that the dynamic coupling relationship in this application represents the interaction mechanism between indoor airflow velocity and temperature over time, which can be used to reflect the mutual influence of airflow and heat transfer processes, and this relationship will change dynamically with the system operating state and environmental conditions.

[0031] In some embodiments, the equivalent energy consumption conversion of the energy-saving air conditioner in the corresponding region is analyzed by combining the temperature change characteristics and airflow speed change characteristics of each region with the energy consumption status of the energy-saving air conditioner. The equivalent energy consumption change generated by the energy-saving air conditioner in each region can be obtained by the following steps: Obtain the energy consumption status of the energy-saving air conditioner; Determine the temperature and airflow velocity characteristics of each region; The temperature contribution characteristics of temperature to energy consumption are determined based on the energy consumption status and the temperature change characteristics of each region. The airflow contribution characteristics of airflow velocity to energy consumption are determined based on the energy consumption status and the airflow velocity change characteristics of each region. The equivalent energy consumption change generated by energy-saving air conditioning in each region is determined by the temperature contribution characteristics and the airflow contribution characteristics.

[0032] It should be noted that, based on the fact that air conditioning energy consumption affects regional temperature by regulating airflow speed, and the characteristics of temperature and airflow speed changes can indirectly reflect the effect of energy consumption in the region, the equivalent analysis establishes a correlation model among the three factors to unify the energy consumption performance of different regions due to environmental differences under the same benchmark and quantify it, thereby determining the equivalent energy consumption change of each region.

[0033] In specific implementation, when obtaining the energy consumption status of an energy-saving air conditioner, it is necessary to collect the real-time operating data of the air conditioner through the built-in energy consumption monitoring module, and use this real-time operating data as the energy consumption status of the air conditioner. The energy consumption status includes the active power per unit time, cumulative power consumption, compressor operating frequency, fan speed, current operating mode (cooling / heating / air supply), and set temperature core parameters. At the same time, the timestamps corresponding to each parameter are recorded to ensure that they are synchronized with the time dimension of subsequent temperature and airflow speed monitoring data. Other methods can be used to obtain the data in other embodiments, which are not limited here.

[0034] In specific implementation, the temperature change characteristics and airflow velocity change characteristics of each region can be determined in the following way: the time series data of temperature and airflow velocity collected by sensors in each region are preprocessed (such as outlier removal and smoothing filtering), and then the temperature change characteristics and airflow velocity change characteristics are calculated by using the sliding window method (window duration is set to 10-15 minutes, step size is 5 minutes). The temperature change characteristics include the average temperature, temperature standard deviation (reflecting the fluctuation amplitude), temperature change rate (the ratio of the temperature difference at the beginning and end of the window to the duration), and cumulative deviation of temperature from the set value within each window. The airflow velocity change characteristics include the average wind speed, wind speed fluctuation coefficient (the ratio of the standard deviation to the mean), frequency of wind speed peak occurrence, and wind speed gradient (the wind speed difference between adjacent regions) within each window. This comprehensively depicts the dynamic change law of temperature and airflow. Other methods can also be used to determine these characteristics in other embodiments, which are not limited here.

[0035] In specific implementation, the temperature contribution characteristics of temperature to energy consumption can be determined based on the energy consumption status and the temperature change characteristics of each region. This can be achieved by using the air conditioning energy consumption per unit time (e.g., instantaneous power) as the dependent variable and the temperature change characteristics of each region (e.g., temperature difference, temperature change rate, cumulative deviation) as the independent variable. Simultaneously, the airflow speed and operating mode are controlled. The regression coefficients corresponding to each temperature change characteristic (i.e., the marginal influence strength of temperature on energy consumption) are obtained by fitting a regression model using the least squares method. Finally, all the obtained regression coefficients are used as the temperature contribution characteristics of temperature to energy consumption, where the temperature contribution characteristics represent the degree of influence of different temperature change patterns on energy consumption. Other methods can also be used to determine this in other embodiments, which are not limited here.

[0036] In specific implementation, the airflow contribution characteristics of airflow speed to energy consumption can be determined based on the energy consumption status and the airflow speed change characteristics of each region. This can be achieved in the following way: keeping the temperature change characteristics and operating mode variables constant, using energy consumption as the dependent variable, and fitting a regression model using the least squares method with the airflow speed change characteristics of each region (such as average wind speed, wind speed fluctuation coefficient, and wind speed gradient) as independent variables to perform regression analysis and obtain the influence coefficients of each airflow change characteristic on energy consumption. At the same time, the influence coefficients are corrected by combining the principle of heat exchange (e.g., increased wind speed promotes heat transfer, which may reduce the temperature difference during cooling and thus reduce energy consumption; positive / negative contributions need to be distinguished). All influence coefficients are used as the airflow contribution characteristics of airflow speed to energy consumption, where the airflow contribution characteristics represent the characteristics of the influence law of different airflow states on energy consumption. Other methods can also be used to determine this in other embodiments, which are not limited here.

[0037] In specific implementation, the equivalent energy consumption change of energy-saving air conditioners in each region can be determined by the temperature contribution characteristics and airflow contribution characteristics in the following way: First, the baseline energy consumption state is determined by using the baseline state setting method based on the air conditioner design parameters and the average energy consumption during the period of lowest energy consumption and environmental stability in historical operating data, ensuring that this state can represent the energy consumption baseline under ideal operation; then, the preprocessed actual temperature change characteristics of each region are substituted into the quantitative model of temperature contribution characteristics (such as a multiple linear regression equation, where the independent variable is the temperature characteristic and the dependent variable is the energy consumption deviation coefficient) using the feature mapping and deviation calculation method, and the actual airflow velocity change characteristics are simultaneously substituted into the quantitative model of airflow contribution characteristics (same type of regression equation, where the independent variable is the airflow characteristic). The energy consumption deviation caused by temperature factors (the portion of the difference between actual energy consumption and baseline energy consumption caused by temperature changes) and the energy consumption deviation caused by airflow factors are calculated separately for each region. Then, a weighted summation method is used to sum the two energy consumption deviation values ​​for each region. Based on the regression coefficients (reflecting the influence intensity of variables on energy consumption) in the quantification model of temperature contribution characteristics and airflow contribution characteristics, the ratio of their absolute values ​​is calculated (absolute value of temperature coefficient ÷ (absolute value of temperature coefficient + absolute value of airflow coefficient) is the temperature weight, and vice versa is the airflow weight). The value obtained by weighted summation is used as the equivalent energy consumption change of the corresponding region, thereby obtaining the equivalent energy consumption change generated by energy-saving air conditioners in each region. In other embodiments, other methods can also be used to determine this, which are not limited here.

[0038] It should be noted that the equivalent energy consumption change in this application represents the difference between the actual energy consumption and the ideal state caused by the dynamic changes in temperature and airflow in the region, and can be used to analyze the optimization and control of energy-saving air conditioning.

[0039] In step 103, the energy efficiency loss of the indoor space equipped with energy-saving air conditioners is evaluated based on the dynamic coupling relationship between airflow velocity and temperature in each area and the equivalent energy consumption change generated by the energy-saving air conditioners in each area, so as to obtain the local energy efficiency deviation between the various areas of the indoor space.

[0040] In some embodiments, the energy efficiency loss of the indoor space equipped with energy-saving air conditioning is assessed based on the dynamic coupling relationship between airflow velocity and temperature in each region and the equivalent energy consumption change generated by the energy-saving air conditioning in each region. The local energy efficiency deviation between the various regions of the indoor space can be obtained by the following steps: The energy efficiency loss areas of each indoor area equipped with energy-saving air conditioners are determined based on the dynamic coupling relationship between airflow velocity and temperature in each area and the change in equivalent energy consumption generated by energy-saving air conditioners in each area. Two regions are selected as the two designated regions, and the difference in energy efficiency distribution between the two selected regions is determined by the energy efficiency loss areas corresponding to the two selected regions. The local energy efficiency deviation between the two selected regions is determined based on the energy efficiency distribution differences. Continue to determine the local energy efficiency deviations between the remaining areas of the room.

[0041] In practice, determining the energy efficiency loss areas of each indoor area equipped with energy-saving air conditioners, based on the dynamic coupling relationship between airflow velocity and temperature in each area and the equivalent energy consumption change generated by the energy-saving air conditioners in each area, can be achieved in the following way: The energy efficiency loss areas of each indoor area equipped with energy-saving air conditioners are determined using a coupling-energy consumption dual-factor threshold method. This involves first extracting key parameters (such as temperature-airflow time lag deviation rate and coupling strength index) based on the dynamic coupling relationship, and then combining this with the ratio of the equivalent energy consumption change to the baseline energy consumption (i.e., the energy consumption exceedance rate). Thresholds are then set for both (e.g., time lag deviation rate > 20%, coupling strength index > 20%). An index < 0.6 is considered a coupling anomaly, and an energy consumption exceedance rate > 15% is considered an energy consumption anomaly. Then, regions that simultaneously satisfy both coupling and energy consumption anomalies are selected through logical AND operations. If a region has only a single abnormal indicator, a secondary judgment is made based on spatial correlation (e.g., adjacent to a identified loss region and sharing an airflow path). Finally, the energy efficiency loss region is defined. The energy efficiency loss region refers to an area in an indoor space equipped with energy-saving air conditioning where the operating parameters of the air conditioning system do not match the actual needs of the region, resulting in an abnormal dynamic coupling relationship between airflow and temperature. In other embodiments, other methods can also be used to determine this, which are not limited here.

[0042] In practice, determining the energy efficiency distribution difference between two selected regions by selecting the corresponding energy efficiency loss areas can be achieved in the following way: The energy efficiency distribution difference between the two selected regions is determined by the distribution characteristic quantification method, specifically by using kernel density estimation to fit the distribution curves of the equivalent energy consumption change and dynamic coupling relationship of the two selected regions respectively; then, the Kolmogorov-Smirnov test is used to determine the differences in the shape of each distribution curve (significance level set at 0.05), and the degree of difference in values ​​on the distribution curves (mean difference, standard deviation ratio, 90th percentile deviation) is calculated: the mean difference is taken as the equivalent energy consumption of the two regions. The absolute difference of the means is divided by the maximum of the two means (to avoid scale bias). The standard deviation ratio is the larger of the standard deviations of the equivalent energy consumption of the two regions divided by the smaller value (to reflect the difference in dispersion). The 90th percentile deviation is the absolute difference of the 90th percentile of the equivalent energy consumption of the two regions divided by the baseline energy consumption (theoretical energy consumption at the set temperature). The differences in the above forms and the differences in the values ​​on the distribution curve are taken as the energy efficiency distribution difference between the two selected regions. The energy efficiency distribution difference represents the difference in the overall distribution of energy efficiency-related characteristics of the two selected indoor regions under the same time conditions. Other methods can be used to determine this in other embodiments, which are not limited here.

[0043] In specific implementation, the local energy efficiency deviation between two selected areas can be determined based on the energy efficiency distribution differences in the following manner: the difference-deviation mapping method is used to determine the local energy efficiency deviation between the two selected areas. That is, the energy efficiency distribution differences are converted into a basic deviation through normalization (mapping to the 0-1 interval) by standardization. Then, a spatial attenuation coefficient is introduced through an exponential decay model (calculated based on the ratio of the straight-line distance between the two areas to the diagonal length of the room; the greater the distance, the smaller the attenuation coefficient). The basic deviation is corrected by combining the airflow connectivity between the two areas. The corrected basic deviation is used as the local energy efficiency deviation between the two selected areas (range -1 to 1, positive value indicates that the energy efficiency of area A is better than that of area B, and negative value indicates the opposite). Other methods can also be used to determine this in other embodiments, which are not limited here.

[0044] It should be noted that the local energy efficiency deviation in this application represents the degree of deviation between the actual energy efficiency performance in a region and the reference benchmark. It can be used to intuitively reflect the energy efficiency shortcomings in a local area (such as abnormal energy consumption caused by equipment aging, airflow short circuits, etc.) and can also provide a basis for targeted optimization. For example, by locating areas with significant local energy efficiency deviations, the air conditioning fan speed and temperature control threshold in that area can be precisely adjusted, or equipment faults can be investigated, thereby achieving a balanced improvement in spatial energy efficiency.

[0045] In step 104, based on the spatial distribution of various areas in the room equipped with the energy-saving air conditioner and all local energy efficiency deviations, combined with the air outlet parameter adjustment range of each air conditioner outlet, the terminal air volume distribution parameters of the energy-saving air conditioner to each air conditioner outlet are determined, and then the air outlet of the energy-saving air conditioner is adjusted by all the terminal air volume distribution parameters.

[0046] In some embodiments, reference Figure 3 As shown, this figure is an exemplary flowchart for determining the terminal airflow distribution parameters in some embodiments of this application. In this embodiment, the terminal airflow distribution parameters of the energy-saving air conditioner to each air outlet can be determined based on the spatial distribution of each area in the room equipped with the energy-saving air conditioner and all local energy efficiency deviations, combined with the air outlet parameter adjustment range of each air outlet. This can be achieved by the following steps: First, in step 1041, the spatial distribution of the various areas of the indoor space equipped with energy-saving air conditioners is determined; Secondly, in step 1042, the air outlet parameter adjustment range of each air outlet is obtained; Furthermore, in step 1043, the optimization target for each air conditioning outlet is determined based on the spatial distribution of each region and all local energy efficiency deviations. Finally, in step 1044, the terminal air volume distribution parameters of the energy-saving air conditioner to the corresponding air outlet are determined by adjusting the air outlet parameters of each air outlet and the optimization target.

[0047] In specific implementation, the spatial distribution of various indoor areas equipped with energy-saving air conditioners can be determined in the following way: using spatial coordinate modeling: establishing a three-dimensional rectangular coordinate system with the midpoint of the wall where the air conditioner outlet is located as the origin (X-axis along the horizontal direction, Y-axis perpendicular to the ground and upward, Z-axis perpendicular to the wall and pointing indoors), measuring the physical boundaries of each area (such as the coordinates of the four corner vertices of the area) using a laser rangefinder and drawing tools, abstracting each area into a polygonal spatial unit, recording the coordinates of the unit's center point, area, and straight-line distance from each air outlet; simultaneously marking the functional attributes of the area (such as densely populated areas of personnel activity, equipment heat dissipation areas) and the distribution of obstacles (such as furniture obstruction positions), forming an area location distribution that includes spatial geometric parameters and environmental characteristics, and using this area location distribution as the spatial location distribution of various indoor areas equipped with energy-saving air conditioners, wherein the spatial location distribution represents the spatial location distribution of each area in the room, providing a spatial benchmark for subsequent airflow coverage analysis; other methods can also be used in other embodiments, which are not limited here.

[0048] When obtaining the air outlet parameter adjustment range of each air conditioner outlet from the database corresponding to the energy-saving air conditioner, the air outlet parameter adjustment range includes the air volume adjustment range (e.g., 80-300m³ / h), the adjustable air outlet angle range (e.g., horizontal 0-90°, vertical -30° to 60°), and the number of wind speed levels (e.g., 1-5 levels, corresponding to wind speeds of 0.5-3.0m / s). In other embodiments, other methods can also be used to obtain the parameters, which are not limited here.

[0049] In practice, when determining the optimization target for each air conditioner outlet based on the spatial distribution of each region and all local energy efficiency deviations, a space-energy efficiency weighted fusion method is adopted: This involves calculating the spatial attenuation weight based on the distance between the region's center point and the outlet (the closer the distance, the higher the weight, quantified according to a function of 1 / (distance+1)), and combining this with the absolute value of the local energy efficiency deviation to determine the energy efficiency correction weight (the larger the deviation, the higher the weight, standardized to the 0.3-1.0 range through maximum-minimum value mapping); then multiplying the two weighted values ​​(60% space weight, 40% energy efficiency weight) to obtain the priority coefficient for each region relative to the corresponding air conditioner outlet, and finally defining the optimization target as " Within the coverage area, the absolute value of the local energy efficiency deviation in high-priority areas is reduced to within 0.1, while the average deviation of the overall area is reduced by 30% compared to the current value. The target is specified to meet the matching degree between the airflow coverage range and the spatial location of the area (overlap rate between the airflow core area and the target area ≥ 70%). Thus, the optimization target of each air conditioning outlet is obtained. The optimization target represents the specific goal that is expected to be achieved in the energy efficiency analysis and control scenario through a series of intervention measures (such as adjusting air conditioning parameters and optimizing equipment operation strategies). Each area corresponds to one air conditioning outlet, with the shortest distance as the corresponding standard. Other methods can be used to determine the target in other embodiments, which are not limited here.

[0050] In practice, when determining the terminal air volume distribution parameters based on the adjustment range of the air outlet parameters of each air conditioning outlet and the optimization target, a constrained optimization iterative method is adopted: that is, guided by the optimization target, firstly, within the adjustment range of the air outlet parameters, the air volume value is initially set according to the heat load demand of the high-priority area (estimated based on the change in equivalent energy consumption) (e.g., the air volume of the corresponding air outlet in areas with excessive deviation is increased by 10%-20%); then, the theoretical value of the air outlet angle is calculated based on the coordinates of the center point of the area (using trigonometric functions to back-calculate so that the airflow axis points to the center of the area), and fine-tuning is performed within the angle adjustment range to avoid obstruction; then, based on the air volume and wind... The matching relationship of air volume (air volume = air speed × air outlet cross-sectional area) is selected within the air speed adjustment range to ensure that the air speed meets the airflow range requirements without exceeding the energy consumption threshold. Finally, the parameter combination is checked to see if it meets the optimization target through simulation (such as fluid dynamics airflow simulation). If there is a deviation, iterative adjustment is made in the order of "air volume → angle → air speed" until all parameters are within the air outlet parameter adjustment range and the target is achieved. The parameters adjusted in each area are used as the terminal air volume distribution parameters of the energy-saving air conditioner to the corresponding air outlet. Other methods can be used to determine the air volume in other embodiments, which are not limited here.

[0051] It should be noted that the terminal air volume distribution parameters in this application represent key parameters of the terminal air outlet air volume distribution status in energy-saving air conditioners (such as air volume, air outlet angle, and wind speed level). These parameters can be used to adjust the air outlet status of each terminal air outlet in order to optimize the energy consumption of the energy-saving air conditioner.

[0052] In practice, adjusting the air outlets of the energy-saving air conditioner using all terminal airflow distribution parameters can be achieved in the following way: First, the optimized calculation of the terminal airflow distribution parameters for each air outlet (including the target airflow value, corresponding airflow angle, and fan speed level for each air outlet) is transmitted to the central controller via the communication bus (such as RS485) of the air conditioning control system. After parsing the parameters, the controller matches the corresponding execution module according to the air outlet number. For airflow adjustment, the controller sends a pulse width modulation adjustment signal to the fan inverter module based on the difference between the target airflow and the current measured airflow (collected by the airflow sensor at the air outlet). Within the airflow adjustment range of the air outlet (e.g., 80-300 m³ / h), the fan speed is dynamically adjusted until the measured airflow stabilizes within ±5% of the target value. Simultaneously, based on the target air outlet angle, the stepper motor of the air guide plate is driven to rotate within its angle adjustment range (e.g., horizontal 0-90°, vertical -30° to 60°). The position is fed back in real time through the angle sensor to ensure that the air guide plate is accurately positioned to the target angle. If a mechanical limit is detected during the adjustment process (e.g., reaching the extreme angle value), it will automatically stop and record. For multi-outlet systems, a timing control strategy is adopted (e.g., prioritizing the adjustment of the air outlet in the farthest area, and sequentially acting on adjacent air outlets at 3-second intervals) to avoid instantaneous airflow disturbances. After the adjustment is completed, the actual airflow and angle parameters of each air outlet are transmitted back to the optimization system. The adjustment effect is verified by combining the regional temperature and energy efficiency deviation monitoring data. If the optimization target is not met, a new round of parameter calculation and adjustment is triggered until all air outlets operate stably according to the allocated parameters and meet the energy efficiency optimization requirements.

[0053] In another aspect, in some embodiments, this application provides an air conditioning system for energy-saving air conditioning, referencing... Figure 4 The figure is a schematic diagram of the structure of an air conditioning system for energy-saving air conditioning according to some embodiments of this application. The air conditioning system 400 for energy-saving air conditioning includes: a monitoring module 401, a processing module 402, and an execution module 403, which are described below: Monitoring module 401, in this application, is mainly used to monitor the temperature and airflow speed in various areas during the operation of the energy-saving air conditioner; Processing module 402, in this application, is used to determine the dynamic coupling relationship between airflow velocity and temperature in each region based on all monitored temperatures and all airflow velocities. By combining the temperature change characteristics and airflow velocity change characteristics of each region with the energy consumption status of the energy-saving air conditioner, it performs an equivalent analysis of the energy consumption conversion of the energy-saving air conditioner in the corresponding region, and obtains the equivalent energy consumption change generated by the energy-saving air conditioner in each region. It should be noted that the processing module 402 in this application is also used to evaluate the energy efficiency loss of the indoor space equipped with energy-saving air conditioners based on the dynamic coupling relationship between airflow speed and temperature in each area and the equivalent energy consumption change generated by the energy-saving air conditioners in each area, so as to obtain the local energy efficiency deviation between the various areas of the indoor space. The execution module 403 in this application is mainly used to determine the terminal air volume distribution parameters of the energy-saving air conditioner to each air outlet based on the spatial location distribution of each area of ​​the indoor space equipped with the energy-saving air conditioner and all local energy efficiency deviations, combined with the air outlet parameter adjustment range of each air outlet. Then, the air outlet of the energy-saving air conditioner is adjusted by all the terminal air volume distribution parameters.

[0054] In addition, this application also provides a computer device, the computer device including a memory and a processor, the memory storing code, the processor being configured to acquire the code and execute the above-described air conditioning method for energy-saving air conditioners.

[0055] In some embodiments, reference Figure 5 The figure is a schematic diagram of the structure of a computer device implementing an air conditioning method for energy-saving air conditioning according to some embodiments of this application. The air conditioning method for energy-saving air conditioning in the above embodiments can be implemented through... Figure 5 The computer device 500 shown is used to implement this, and the computer device 500 includes at least one processor 501, a communication bus 502, a memory 503, and at least one communication interface 504.

[0056] Processor 501 can be a general-purpose central processing unit (CPU) or an application-specific integrated circuit (ASIC).

[0057] The communication bus 502 can be used to transmit information between the aforementioned components.

[0058] Memory 503 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CDROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile optical discs, Blu-ray discs, etc.), magnetic disks or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. Memory 503 may exist independently and be connected to processor 501 via communication bus 502. Memory 503 may also be integrated with processor 501.

[0059] The memory 503 stores program code for executing the scheme of this application, and its execution is controlled by the processor 501. The processor 501 executes the program code stored in the memory 503. The program code may include one or more software modules. The method used in the above embodiments can be implemented by the processor 501 and one or more software modules in the program code in the memory 503.

[0060] Communication interface 504 uses any transceiver-like device to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0061] In a specific implementation, as one example, a computer device may include multiple processors, each of which may be a single-core (single CPU) processor or a multi-core (multi CPU) processor. Here, a processor may refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).

[0062] The aforementioned computer device can be a general-purpose computer device or a special-purpose computer device. In specific implementations, the computer device can be a desktop computer, a portable computer, a network server, a handheld digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. This application does not limit the type of computer device.

[0063] In addition, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described air conditioning method for energy-saving air conditioners.

[0064] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0065] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. An air conditioning method for energy-saving air conditioners, wherein, The indoor space equipped with an energy-saving air conditioner is divided into multiple zones based on the airflow coverage and location of the air conditioner vents. The energy-saving air conditioner is a central air conditioning system. The method is characterized by the following steps: Monitor the temperature and airflow velocity in each area during the operation of the energy-saving air conditioner; Based on all monitored temperatures and airflow velocities, the dynamic coupling relationship between airflow velocity and temperature in each region is determined. By combining the temperature change characteristics and airflow velocity change characteristics of each region with the energy consumption status of the energy-saving air conditioner, an equivalent analysis of the energy consumption conversion of the energy-saving air conditioner in the corresponding region is performed to obtain the equivalent energy consumption change generated by the energy-saving air conditioner in each region. Based on the dynamic coupling relationship between airflow velocity and temperature in each area and the change in equivalent energy consumption generated by energy-saving air conditioners in each area, the energy efficiency loss of the indoor space equipped with energy-saving air conditioners is evaluated, and the local energy efficiency deviation between the various areas of the indoor space is obtained. Based on the spatial distribution of various areas in the room equipped with energy-saving air conditioners and all local energy efficiency deviations, combined with the air outlet parameter adjustment range of each air conditioner outlet, the terminal air volume distribution parameters of the energy-saving air conditioner to each air conditioner outlet are determined, and then the air outlet of the energy-saving air conditioner is adjusted by all terminal air volume distribution parameters. Specifically, determining the dynamic coupling relationship between airflow velocity and temperature in each region based on all monitored temperatures and airflow velocities includes: Select a region as the selected area, and determine the correlation between airflow velocity and temperature in the selected area based on all monitored temperatures and all airflow velocities in the selected area. Based on the aforementioned correlation, the time lag characteristics between airflow changes and temperature changes in the selected region are determined; The dynamic coupling relationship between airflow velocity and temperature in the selected region is determined by the time delay characteristics. Continue to determine the dynamic coupling relationship between airflow velocity and temperature in the remaining regions; Specifically, based on the dynamic coupling relationship between airflow velocity and temperature in each area and the change in equivalent energy consumption generated by energy-saving air conditioners in each area, the energy efficiency loss of the indoor space equipped with energy-saving air conditioners is assessed, and the local energy efficiency deviations between the various areas of the indoor space are obtained, including: The energy efficiency loss areas of each indoor area equipped with energy-saving air conditioners are determined based on the dynamic coupling relationship between airflow velocity and temperature in each area and the change in equivalent energy consumption generated by energy-saving air conditioners in each area. Two regions are selected as the two designated regions, and the difference in energy efficiency distribution between the two selected regions is determined by the energy efficiency loss areas corresponding to the two selected regions. The local energy efficiency deviation between the two selected regions is determined based on the energy efficiency distribution differences. Continue to determine the local energy efficiency deviations between the remaining indoor areas; Specifically, by combining the temperature and airflow velocity variation characteristics of each region with the energy consumption status of the energy-saving air conditioner, an equivalent analysis is performed on the energy consumption conversion of the energy-saving air conditioner in the corresponding region. The specific equivalent energy consumption change generated by the energy-saving air conditioner in each region includes: Obtain the energy consumption status of the energy-saving air conditioner; Determine the temperature and airflow velocity characteristics of each region; The temperature contribution characteristics of temperature to energy consumption are determined based on the energy consumption status and the temperature change characteristics of each region. The airflow contribution characteristics of airflow velocity to energy consumption are determined based on the energy consumption status and the airflow velocity change characteristics of each region. The equivalent energy consumption variation of energy-saving air conditioning in each region is determined by the temperature contribution characteristics and the airflow contribution characteristics. Specifically, determining the terminal airflow distribution parameters of the energy-saving air conditioner to each air outlet based on the spatial distribution of various areas in the indoor space equipped with the energy-saving air conditioner and all local energy efficiency deviations, combined with the air outlet parameter adjustment range of each air outlet, includes: Determine the spatial distribution of each area in the indoor space equipped with energy-saving air conditioners; Obtain the air outlet parameter adjustment range for each air conditioner vent; The optimization targets for each air conditioning outlet are determined based on the spatial distribution of each region and all local energy efficiency deviations. The terminal air volume distribution parameters of the energy-saving air conditioner to the corresponding air outlet are determined by adjusting the air outlet parameters of each air outlet and the optimization target.

2. The method as described in claim 1, characterized in that, The spatial coordinate modeling method was used to obtain the spatial location distribution of each area in the indoor space equipped with energy-saving air conditioners.

3. The method as described in claim 1, characterized in that, The temperature and airflow velocity in each area are monitored by integrated sensor nodes during the operation of the energy-saving air conditioner.

4. An air conditioning system for energy-saving air conditioning, wherein the air is conditioned using the method described in any one of claims 1 to 3, characterized in that, The system includes: The monitoring module is used to monitor the temperature and airflow speed in various areas during the operation of the energy-saving air conditioner; The processing module is used to determine the dynamic coupling relationship between airflow velocity and temperature in each region based on all monitored temperatures and airflow velocities. By combining the temperature change characteristics and airflow velocity change characteristics of each region with the energy consumption status of the energy-saving air conditioner, the module performs an equivalent analysis of the energy consumption conversion of the energy-saving air conditioner in the corresponding region, and obtains the equivalent energy consumption change generated by the energy-saving air conditioner in each region. The processing module is also used to assess the energy efficiency loss of the indoor space equipped with energy-saving air conditioners based on the dynamic coupling relationship between airflow speed and temperature in each area and the equivalent energy consumption change generated by the energy-saving air conditioners in each area, so as to obtain the local energy efficiency deviation between the various areas of the indoor space. The execution module is used to determine the terminal air volume distribution parameters of the energy-saving air conditioner to each air outlet based on the spatial location distribution of each area in the room equipped with the energy-saving air conditioner and all local energy efficiency deviations, combined with the air outlet parameter adjustment range of each air outlet. Then, the air outlet of the energy-saving air conditioner is adjusted by all the terminal air volume distribution parameters.

5. A computer device, characterized in that, The computer device includes a memory and a processor, the memory storing code, and the processor being configured to retrieve the code and execute the air conditioning method for an energy-saving air conditioner as described in any one of claims 1 to 3.

6. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the air conditioning method for energy-saving air conditioning as described in any one of claims 1 to 3.

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