A control method and device for energy-saving air conditioning

Abstract

The present application relates to the field of air conditioning control technology, and specifically to a control method and device for energy-saving air conditioning, the method comprising: dividing a room equipped with an energy-saving air conditioning into various areas based on the number of air outlets, collecting the temperature of each area at each time in each sampling period, and the temperature and wind speed of each time in each outdoor sampling period; obtaining the temperature difference and wind speed state change of each area at each time; obtaining the temperature trend difference value, neighborhood temperature extreme value, and environmental change correlation degree of each area; determining the influence coefficient of each area; analyzing the similarity relationship between the temperature of any area and other areas at each time, combining the influence coefficient, determining the air conditioning adjustment strength of any area in each sampling period, and controlling the energy-saving air conditioning based on the PID controller. Thereby improving the stability of the wind speed control of the energy-saving air conditioning.

Description

Technical Field

[0001] The present application relates to the technical field of air conditioning control, and in particular to a control method and device for an energy-saving air conditioning. Background Art

[0002] Energy-saving air conditioning is an air conditioning system designed to reduce energy consumption. It can automatically adjust its operating status according to environmental parameters such as indoor and outdoor temperature and humidity to achieve energy conservation and emission reduction.

[0003] However, due to the rapid changes in the external environment, such as temperature and wind speed, which will interfere with indoor air conditioning control, and the wide internal space and complex changes in heat load, achieving energy-saving regulation of the air conditioning system faces certain challenges. The traditional air conditioning control method mainly uses the control system to uniformly control the fan, but fails to fully consider the differences in indoor and outdoor environments, and the mutual influence between different indoor areas, resulting in a low degree of stability in wind speed control at the air outlet of the energy-saving air conditioner, which in turn affects the uniformity of temperature distribution. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a control method and device for energy-saving air conditioning, and the technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present application provides a method for controlling an energy-saving air conditioner, the method comprising the following steps:

[0006] Divide the indoor area equipped with energy-saving air conditioners into different areas based on the number of air outlets, collect the temperature of each area at each time in each sampling period, and the temperature and wind speed of the outdoor area at each time in each sampling period;

[0007] Obtain the temperature difference between each area and the outdoors at each moment, form the temperature difference and wind speed at each moment into two-dimensional data points, and obtain the change in temperature difference and wind speed state of each area at each moment based on the distance distribution relationship of the two-dimensional data points at different moments; obtain the trend statistics of the temperature of each area at all moments in the local time period, and obtain the temperature trend difference value of each area in the local time period based on the difference between the trend statistics of each area and the adjacent area; analyze the temperature distribution correlation between each area and the adjacent area in the local time period, and obtain the neighborhood temperature extreme difference value of each area in the local time period;

[0008] Analyze the correlation between all the changes in each area and the adjacent areas in the local time period to obtain the degree of correlation of the environmental changes in each area in the local time period; determine the influence coefficient of each area in the local time period by combining the temperature trend difference value, the neighborhood temperature extreme value, and the degree of correlation of the environmental changes; analyze the similarity relationship between the temperature of any area and other areas at each moment, and determine the air-conditioning adjustment intensity of any area in each sampling period by combining the influence coefficient, and control the energy-saving air-conditioning based on the PID controller.

[0009] Preferably, the determination of the variation comprises the following steps:

[0010] Cluster the two-dimensional data points at all times in a local time period to obtain clusters, calculate the mean of the metric distances between any data point and all other data points in the same cluster, recorded as the first mean, calculate the mean of the metric distances between any data point and all data points in other clusters, recorded as the second mean, and determine the change at the corresponding moment of any data point based on the first mean and the second mean.

[0011] Preferably, the change amount at the corresponding moment of any data point is the ratio of the second mean to the first mean.

[0012] Preferably, the temperature trend difference value is the average of the absolute values ​​of the difference between the trend statistics of each region and all adjacent regions.

[0013] Preferably, the determination of the neighborhood temperature extreme difference value comprises the following steps:

[0014] The extreme values ​​of all temperatures in each region within a local time period are calculated, and the average of the extreme values ​​of each region and all adjacent regions is taken as the neighborhood temperature extreme value.

[0015] Preferably, the determination of the degree of correlation of the environmental changes comprises the following steps:

[0016] All the changes in each region within a local time period are combined into a change sequence, and the average of the absolute values ​​of the correlation coefficients of the change sequences of each region and all adjacent regions is taken as the degree of correlation of the environmental changes.

[0017] Preferably, the determination of the influence coefficient includes the following steps: calculating a fusion value of the temperature trend difference value and the neighborhood temperature extreme difference value, and determining the ratio of the fusion value to the degree of correlation with the environmental change as the influence coefficient.

[0018] Preferably, the determination of the air conditioning adjustment intensity comprises the following steps:

[0019] Calculate the absolute value of the similarity coefficient of all temperatures between any area and other areas in each sampling period, calculate the mean of the influence coefficient of all local time periods in any area in each sampling period, calculate the sum of the absolute value and a preset value greater than 0, calculate the ratio of the mean to the sum, and fuse the ratios of any area to all other areas to determine the air-conditioning adjustment intensity of any area in each sampling period.

[0020] Preferably, the controlling of the energy-saving air conditioner includes:

[0021] For each area, the sum of the normalized value of the air conditioning adjustment intensity of the previous sampling cycle and the initial proportional term parameter of the PID controller is used as the proportional term parameter of the PID controller in the current sampling cycle, and the wind speed of the energy-saving air conditioning outlet in each area is controlled based on the PID controller.

[0022] In a second aspect, an embodiment of the present application further provides a control device for an energy-saving air conditioner, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of any one of the above-mentioned methods when executing the computer program.

[0023] This application has at least the following beneficial effects:

[0024] (1) The present application divides a room equipped with an energy-saving air conditioner into various areas based on the number of air outlets, collects the temperature of each area at each time in each sampling period, and the temperature and wind speed of the outdoor room at each time in each sampling period; further analyzes the correlation between the collected data; obtains the temperature difference between each area and the outdoor room at each time, and forms two-dimensional data points with the temperature difference and wind speed at each time; based on the distance distribution relationship of the two-dimensional data points at different times, obtains the change in temperature difference and wind speed state of each area at each time; the change reflects the degree of difference in indoor and outdoor temperature difference and wind speed between different times, thereby improving the reliability of energy-saving air conditioner control analysis;

[0025] (2) Further, the trend statistics of the temperature of each area at all times in the local time period are obtained, and based on the difference between the trend statistics of each area and the adjacent areas, the temperature trend difference value of each area in the local time period is obtained; the temperature distribution correlation between each area and the adjacent areas in the local time period is analyzed to obtain the neighborhood temperature extreme difference value of each area in the local time period; the correlation between all the changes in each area and the adjacent areas in the local time period is analyzed to obtain the degree of correlation of the environmental changes in each area in the local time period; the influence coefficient of each area in the local time period is determined by combining the temperature trend difference value, the neighborhood temperature extreme difference value, and the degree of correlation of the environmental changes; the correlation between the temperature changes between different indoor areas is reflected, and the state of temperature difference caused by changes in the indoor and outdoor environments in each area is more accurately reflected, thereby improving the rationality of energy-saving air conditioning control adjustment;

[0026] (3) Analyze the similarity relationship between the temperature of any area and other areas at each time, combine the influence coefficient, determine the air conditioning adjustment intensity of any area in each sampling period, and control the energy-saving air conditioner based on the PID controller; reflect the volatility of the influence coefficient of the temperature trend between adjacent areas and the temperature difference in the global range, adjust the response speed of the energy-saving air conditioner through the PID controller, improve the stability of the air speed control of the air outlet of each area, and improve the uniformity of indoor temperature distribution. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 A flowchart of a method for controlling an energy-saving air conditioner provided in one embodiment of the present application;

[0029] Figure 2 Get a flow chart for the air conditioning intensity adjustment. DETAILED DESCRIPTION

[0030] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of the control method and device of an energy-saving air conditioner proposed in the present application, its specific implementation method, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0031] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0032] The following is a detailed description of a control method and device for an energy-saving air conditioner provided by the present application in conjunction with the accompanying drawings.

[0033] See also Figure 1 , which shows a flow chart of a method for controlling an energy-saving air conditioner provided by an embodiment of the present application, the method comprising the following steps:

[0034] S1, divide the room equipped with energy-saving air conditioner into different areas based on the number of air outlets, collect the temperature of each area at each time in each sampling period, and the temperature and wind speed of each time in each sampling period outdoors.

[0035] First of all, since the internal structure of large buildings is complex and diverse, in order to ensure the accuracy of wind speed control at the air outlet of energy-saving air conditioners, in this embodiment, the air outlet of the energy-saving air conditioner is taken as the center and the radius is 5 meters. The room equipped with the energy-saving air conditioner is divided into different areas according to the number of air outlets. The value of the radius can be set by the implementer according to actual conditions, and this application does not impose any restrictions on this.

[0036] A temperature sensor is used to collect the temperature of each indoor area and the outdoor temperature, and a wind speed sensor is used to collect the outdoor wind speed. In this embodiment, the collection time interval is 1s, and the sampling period length is set to 5min. The implementer can set the collection time interval and the sampling period length according to the actual situation, and this application does not impose any restrictions on this.

[0037] All the temperatures collected in each area during each sampling period are organized into an indoor temperature sequence for each area in chronological order. The same method is used to organize the outdoor temperature and wind speed collected in each sampling period into an outdoor temperature sequence and an outdoor wind speed sequence in chronological order.

[0038] S2, obtaining the temperature difference between each area and the outdoors at each moment, forming the temperature difference and wind speed at each moment into two-dimensional data points, and obtaining the change in temperature difference and wind speed state of each area at each moment based on the distance distribution relationship of the two-dimensional data points at different moments.

[0039] Air conditioners are affected by many factors when adjusting the temperature. For example, changes in wind speed will interfere with the air intake and exhaust of the air conditioning system, and will also affect the heat exchange efficiency between indoor and outdoor. Especially when using the outdoor unit to dissipate heat, strong winds may help improve the heat dissipation efficiency of the air conditioner. Indoor and outdoor temperatures directly affect the cooling and heating loads of the air conditioner. The greater the difference between the outdoor temperature and the indoor set temperature, the higher the energy consumption of the air conditioning system and the greater the adjustment required. Therefore, outdoor wind speed and indoor and outdoor temperature difference are key factors affecting energy-saving air conditioning control.

[0040] Since the changes in wind speed and temperature are random and rapid, the air conditioning adjustment status in different time periods may be inconsistent. Therefore, this embodiment divides each sampling period into local time periods. Among them, the number of local time periods in each sampling period in this embodiment is 5, and the implementer can set it according to the actual situation. This application does not impose any restrictions on this.

[0041] Furthermore, taking the i-th area as an example, the greater the indoor and outdoor temperature difference, the greater the power consumption of the air conditioner for temperature regulation. In addition, when the outdoor wind speed is low or there is no wind, the heat dissipation efficiency of the air conditioner outdoor unit is relatively low, and the air conditioner regulation strength also needs to be increased. Therefore, the correlation between the outdoor wind speed and the indoor and outdoor temperature difference data will affect the air conditioner temperature regulation.

[0042] Specifically, in the jth local time period of the i-th region, the absolute value of the difference between the temperature of the i-th region and the outdoor temperature at each sampling time is calculated, and the absolute value of the difference and the wind speed at the corresponding time form a two-dimensional data point. The two-dimensional data points at all times in the jth local time period of the i-th region are clustered using the local directional centrality clustering algorithm, and the number of clusters is set to 2. Finally, the output of the local directional centrality clustering algorithm is 2 clusters. The local directional centrality clustering algorithm is an existing well-known technology, and this embodiment will not be described in detail here.

[0043] It should be noted that the implementer can choose other feasible clustering algorithms to cluster the two-dimensional data points according to the actual situation, and the implementer can set the number of clusters according to the actual situation, and this application does not impose any restrictions on this.

[0044] The two output clusters are respectively recorded as cluster A and cluster B, the metric distance between any two-dimensional data point in cluster A and the remaining two-dimensional data points in cluster A is calculated, the mean of all the metric distances of any two-dimensional data point is calculated and recorded as the first mean, and the mean of the metric distances between any two-dimensional data point and all two-dimensional data points in cluster B is calculated and recorded as the second mean; the ratio of the second mean to the first mean is determined as the change in temperature difference and wind speed state at the collection time corresponding to any two-dimensional data point.

[0045] It should be noted that, in this embodiment, the metric distance is calculated by sampling the Euclidean distance, and in another embodiment, the metric distance is calculated by sampling the Manhattan distance.

[0046] The smaller the first mean, the closer the indoor and outdoor temperature difference and wind speed state at the corresponding moment are to other data in the same cluster. The larger the second mean, the greater the difference between the data point at the corresponding moment and that of another cluster. The larger the change, the more obvious the change in indoor and outdoor temperature difference and wind speed at the corresponding moment.

[0047] S3, obtaining trend statistics of the temperature of each region at all times in a local time period, and obtaining the temperature trend difference value of each region in the local time period based on the difference between the trend statistics of each region and the adjacent regions; analyzing the temperature distribution correlation between each region and the adjacent regions in the local time period, and obtaining the neighborhood temperature extreme difference value of each region in the local time period.

[0048] In large building environments, air flow patterns are often complex. For example, different areas have different population densities, some areas may not have as good air circulation as others, and some areas are prone to air stagnation. These conditions will lead to different degrees of temperature differences between different areas. However, the temperatures between these areas affect each other to a certain extent. Therefore, the temperature difference between adjacent areas in the room will affect the adjustment strength of the air conditioner.

[0049] Taking the i-th area in the j-th local time period as an example, all temperatures collected in the i-th area in the j-th local time period are organized into a local indoor temperature sequence in chronological order, and the Mann-Kendall test algorithm is used to obtain the trend statistics of the local indoor temperature sequence. The trend statistics reflects the rising or falling trend of the local indoor temperature sequence. The larger the absolute value of the trend statistics, the more obvious the rising or falling trend of the local indoor temperature sequence.

[0050] The Mann-Kendall test algorithm is a well-known technology, and this application will not elaborate on it in detail. The implementer can use other trend test algorithms according to the actual situation, and this application will not limit it.

[0051] For the i-th region, in this embodiment, all regions that have edge connections with the i-th region are recorded as neighboring regions of the i-th region. Within the same local time period, the average of the absolute values ​​of the differences between the trend statistics of the i-th region and all its neighboring regions is calculated as the temperature trend difference value of the i-th region. The larger the temperature trend difference value, the greater the trend of increasing temperature difference between the i-th region and its neighboring regions.

[0052] Further, the extreme difference value of the local indoor temperature sequence of the ith region in the jth local time period is calculated. In the jth local time period, the average of the extreme difference value of the ith region and the extreme difference values ​​of all adjacent regions is calculated as the neighborhood temperature extreme difference value of the ith region in the jth local time period. The larger the neighborhood temperature extreme difference value, the greater the temperature difference between adjacent regions in the local time period.

[0053] S4, analyzing the correlation between all the changes in each area and the adjacent areas in the local time period to obtain the degree of correlation of the environmental changes in each area in the local time period; combining the temperature trend difference value, the neighborhood temperature extreme value, and the degree of correlation of the environmental changes to determine the influence coefficient of each area in the local time period.

[0054] All the changes in the ith region in the jth local time period are organized into a change sequence in time series, and the average of the absolute values ​​of the correlation coefficients of the change sequences of the ith region and all adjacent regions is calculated to determine the environmental change correlation degree of the ith region.

[0055] In this embodiment, the correlation coefficient is calculated by using the Spearman correlation coefficient. In another embodiment, the correlation coefficient can be calculated by using the Pearson correlation coefficient. The calculation of the Spearman correlation coefficient and the Pearson correlation coefficient are both existing well-known technologies, and this application will not be described in detail here.

[0056] The smaller the correlation degree of environmental changes in the i-th area, the smaller the correlation degree between the indoor and outdoor temperature difference and wind speed state of the i-th area and the adjacent areas, which means that the temperature in the i-th area is more likely to fluctuate abnormally, and the energy-saving air conditioner in the i-th area is more likely to be adjusted and controlled.

[0057] Further, the influence coefficient of the ith region in the jth local time period is calculated, specifically, the fusion value of the temperature trend difference value and the neighborhood temperature extreme value of the ith region in the jth local time period is calculated, and the ratio of the fusion value to the degree of correlation with the environmental change is determined as the influence coefficient.

[0058] It should be noted that fusion means performing calculations on multiple variables in a form that enhances the overall effect, such as addition, multiplication, etc. In this embodiment, addition is used as the calculation method for fusion.

[0059] In this embodiment, the expression of the influence coefficient of the i-th region in the j-th local time period can be:

[0060] ; In the formula, represents the influence coefficient of the ith region in the jth local time period, represents the temperature trend difference value of the i-th region in the j-th local time period, represents the extreme difference in neighborhood temperature of the i-th region in the j-th local time period, It indicates the correlation degree of environmental changes in the i-th region in the j-th local time period.

[0061] The influence coefficient of the i-th region in the j-th local time period It reflects the influence of the temperature trend between adjacent regions in the i-th region in the j-th local time period. The larger it is, the greater the difference between the temperature and indoor and outdoor environment changes in the ith area and those in the adjacent areas, the more complex the changes in heat load are, and the more it is necessary to increase the adjustment strength of the energy-saving air conditioning in the ith area.

[0062] S5, analyzing the similarity relationship between the temperature of any area and other areas at each time, combining the influence coefficient, determining the air conditioning adjustment intensity of any area in each sampling period, and controlling the energy-saving air conditioner based on the PID controller.

[0063] The influence coefficient of each area reflects the difference in the local environment of the area. In a large building, it is usually necessary to maintain consistency in temperature among all areas. It may be slow to adjust and control the air conditioning only by relying on the mutual influence characteristics between adjacent areas.

[0064] Therefore, the temperature correlation between the ith area and all indoor areas is further combined to calculate the air conditioning adjustment intensity of the ith area within a sampling period. In this embodiment, the calculation method is:

[0065] ; In the formula, represents the air conditioning intensity of the ith area within a sampling period, represents the number of all remaining regions except the i-th region, represents the mean value of the influence coefficient corresponding to all local time periods of the i-th region within a sampling period, The Jaccard similarity coefficient represents the set of all indoor temperature values ​​of the ith area and the tth area in the same sampling period. The value 1 in the denominator is to avoid the denominator being 0, which makes the calculation impossible. The implementer can set it according to the actual situation, and this application does not limit it. The calculation of the Jaccard similarity coefficient is a well-known technology, and this application will not be described in detail here. The flow chart of obtaining the air conditioning adjustment intensity is as follows Figure 2 shown.

[0066] In another embodiment, the Jaccard similarity coefficient in the air conditioning adjustment intensity calculation process can be replaced by cosine similarity as a similarity measurement method for the set of all indoor temperature values ​​of the ith area and the tth area in the same sampling period.

[0067] The larger the value is, the greater the fluctuation of the temperature and indoor and outdoor environment in the i-th area is. The smaller the temperature, the greater the temperature difference between different areas. The larger it is, the greater the difference between the heat load change in the i-th area and other areas, and the more the air conditioning adjustment needs to be increased.

[0068] The air conditioning adjustment intensity of each area in each sampling period is obtained by adopting the same calculation method as the air conditioning adjustment intensity of the i-th area in a sampling period.

[0069] This application analyzes the indoor and outdoor temperature difference and outdoor wind speed change characteristics of each area, and calculates the air conditioning adjustment intensity value of each area in each sampling period based on the temperature difference between different areas, and controls the fans of the air outlets of each area based on the air conditioning adjustment intensity value.

[0070] Specifically, the wind speed at the air outlet of each area is controlled by the PID controller. The greater the air conditioning adjustment strength value, the higher the possibility of temperature abnormality in the area. Since the proportional term parameter in the PID controller is responsible for adjusting the response speed of the air conditioning system, when the proportional term parameter is set larger, the air conditioning system can make adjustment instructions faster, reducing errors and fluctuations, and when the proportional term parameter is set smaller, the adjustment speed will be correspondingly slowed down. Therefore, when the air conditioning adjustment strength value is larger, it is necessary to increase the proportional term parameter of the PID control to improve the response rate of the air conditioning control in the area.

[0071] In this embodiment, the initial parameters of the PID controller are set with a proportional term of 2, an integral term of 0.5, and a differential term of 0.5. The implementers can set them according to the actual situation, and this application does not impose any restrictions on this. The air conditioning adjustment intensity values ​​corresponding to all areas in the same sampling period are normalized using the Z-score normalization method. Taking the i-th area as an example, the normalized result of the air conditioning adjustment intensity of the i-th area in the sampling period before the current sampling period and the sum of the initial proportional term parameters are calculated and recorded as the first sum. The first sum is used as the proportional term parameter of the current sampling period of the i-th area, thereby completing the adjustment of the wind speed of the air conditioning outlet of the i-th area through the PID controller, and using the same method as the i-th area to adjust all areas divided in the room. PID control in energy-saving air conditioners is an existing well-known technology, and this embodiment will not be described in detail here.

[0072] Based on the same inventive concept as the above method, an embodiment of the present application also provides a control device for an energy-saving air conditioner, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the steps of any one of the above-mentioned methods for controlling an energy-saving air conditioner are implemented.

[0073] In summary, the present application divides the indoor area equipped with energy-saving air conditioners into various areas based on the number of air outlets, collects the temperature of each area at each moment in each sampling period, and the temperature and wind speed of the outdoors at each moment in each sampling period; thereby further analyzing the correlation between the collected data; obtaining the temperature difference between each area and the outdoors at each moment, and forming the temperature difference and wind speed at each moment into two-dimensional data points, and based on the distance distribution relationship of the two-dimensional data points at different moments, obtaining the change in temperature difference and wind speed state of each area at each moment; reflecting the degree of difference in indoor and outdoor temperature difference and wind speed between different moments, and improving the reliability of energy-saving air conditioning control analysis; further, obtaining trend statistics of temperature of each area at all moments in a local time period, and obtaining temperature trend difference values ​​of each area in a local time period based on the difference in trend statistics between each area and adjacent areas; analyzing the temperature distribution correlation between each area and adjacent areas in a local time period, and obtaining the neighborhood temperature extreme difference values ​​of each area in the local time period. ; Analyze the correlation between all the changes in each area and the adjacent areas in the local time period, and obtain the degree of correlation of the environmental changes in each area in the local time period; Combine the temperature trend difference value, the neighborhood temperature extreme value, and the degree of correlation of the environmental changes to determine the influence coefficient of each area in the local time period; Reflect the correlation between the temperature changes between different indoor areas, more accurately reflect the state of temperature differences in each area caused by changes in indoor and outdoor environments, and improve the rationality of energy-saving air-conditioning control and adjustment; Analyze the similarity relationship between the temperature of any area and other areas at each moment, and combine the influence coefficient to determine the air-conditioning adjustment intensity of any area in each sampling period, and control the energy-saving air-conditioning based on the PID controller; Reflect the volatility of the influence coefficient of the temperature trend between adjacent areas and the temperature difference in the global range, and adjust the response speed of the energy-saving air-conditioning adjustment through the PID controller, thereby improving the stability of the air speed control of the air-conditioning outlet in each area and improving the uniformity of indoor temperature distribution.

[0074] It should be noted that the above sequence of the embodiments of the present application is for description only and does not represent the advantages and disadvantages of the embodiments. The above is a description of a specific embodiment of this specification. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0075] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0076] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present application should be included in the protection scope of the present application.

Claims

1. A control method for an energy-saving air conditioner, characterized in that: The method comprises the following steps: Divide the indoor area equipped with energy-saving air conditioners into different areas based on the number of air outlets, collect the temperature of each area at each time in each sampling period, and the temperature and wind speed of the outdoor area at each time in each sampling period; Obtain the temperature difference between each area and the outdoors at each moment, form the temperature difference and wind speed at each moment into two-dimensional data points, and obtain the change in temperature difference and wind speed state of each area at each moment based on the distance distribution relationship of the two-dimensional data points at different moments; obtain the trend statistics of the temperature of each area at all moments in the local time period, and obtain the temperature trend difference value of each area in the local time period based on the difference between the trend statistics of each area and the adjacent area; analyze the temperature distribution correlation between each area and the adjacent area in the local time period, and obtain the neighborhood temperature extreme difference value of each area in the local time period; Analyze the correlation between all the changes in each area and the adjacent areas in the local time period to obtain the degree of correlation of the environmental changes in each area in the local time period; determine the influence coefficient of each area in the local time period by combining the temperature trend difference value, the neighborhood temperature extreme value, and the degree of correlation of the environmental changes; analyze the similarity relationship between the temperature of any area and other areas at each moment, and determine the air-conditioning adjustment intensity of any area in each sampling period by combining the influence coefficient, and control the energy-saving air-conditioning based on the PID controller.

2. The control method of an energy-saving air conditioner according to claim 1, characterized in that: The determination of the variation comprises the following steps: Cluster the two-dimensional data points at all times in a local time period to obtain clusters, calculate the mean of the metric distances between any data point and all other data points in the same cluster, recorded as the first mean, calculate the mean of the metric distances between any data point and all data points in other clusters, recorded as the second mean, and determine the change at the corresponding moment of any data point based on the first mean and the second mean.

3. A control method for energy-saving air conditioning according to claim 2, characterized in that: The change amount at the corresponding moment of any data point is the ratio of the second mean to the first mean.

4. The control method of an energy-saving air conditioner according to claim 1, characterized in that: The temperature trend difference value is the average of the absolute values ​​of the difference between the trend statistics of each region and all adjacent regions.

5. The control method of an energy-saving air conditioner according to claim 1, characterized in that: The determination of the neighborhood temperature extreme difference value comprises the following steps: The extreme values ​​of all temperatures in each region within a local time period are calculated, and the average of the extreme values ​​of each region and all adjacent regions is taken as the neighborhood temperature extreme value.

6. The control method of an energy-saving air conditioner according to claim 1, characterized in that: The determination of the degree of correlation of the environmental changes comprises the following steps: All the changes in each region within a local time period are combined into a change sequence, and the average of the absolute values ​​of the correlation coefficients of the change sequences of each region and all adjacent regions is taken as the degree of correlation of the environmental changes.

7. The control method of an energy-saving air conditioner according to claim 1, characterized in that: The determination of the influence coefficient comprises the following steps: calculating a fusion value of the temperature trend difference value and the neighborhood temperature extreme difference value, and determining the ratio of the fusion value to the degree of correlation with the environmental change as the influence coefficient.

8. The control method of an energy-saving air conditioner according to claim 1, characterized in that: The determination of the air conditioning adjustment intensity comprises the following steps: Calculate the absolute value of the similarity coefficient of all temperatures between any area and other areas in each sampling period, calculate the mean of the influence coefficient of all local time periods in any area in each sampling period, calculate the sum of the absolute value and a preset value greater than 0, calculate the ratio of the mean to the sum, and fuse the ratios of any area to all other areas to determine the air-conditioning adjustment intensity of any area in each sampling period.

9. The control method of an energy-saving air conditioner according to claim 1, characterized in that: The controlling of the energy-saving air conditioner comprises: For each area, the sum of the normalized value of the air conditioning adjustment intensity of the previous sampling cycle and the initial proportional term parameter of the PID controller is used as the proportional term parameter of the PID controller in the current sampling cycle, and the wind speed of the energy-saving air conditioning outlet in each area is controlled based on the PID controller.

10. A control device for an energy-saving air conditioner, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 9 are implemented.

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