Disclosure of Invention
In order to solve the technical problems, the application aims to provide a control method and equipment of an energy-saving air conditioner, and the adopted technical scheme is as follows:
in a first aspect, an embodiment of the present application provides a control method of an energy-saving air conditioner, including the steps of:
Dividing an indoor room provided with an energy-saving air conditioner into areas based on the number of air outlets, and collecting the temperature of each area at each moment in each sampling period, and the temperature and the air speed of each moment in each outdoor sampling period;
Acquiring the temperature difference between each area at each moment and the outside of a room, forming two-dimensional data points by the temperature difference at each moment and the wind speed, and obtaining the variation of the temperature difference and the wind speed state of each area at each moment based on the distance distribution relation of the two-dimensional data points at different moments; obtaining trend statistics of temperatures of each region in a local time period, and obtaining a temperature trend difference value of each region in the local time period based on the difference of the trend statistics of each region and an adjacent region;
The method comprises the steps of analyzing the correlation relation between all the variation amounts of each area and the adjacent area in a local time period to obtain the environmental variation correlation degree of each area in the local time period, combining the temperature trend difference value, the neighborhood temperature difference value and the environmental variation correlation degree to determine the influence coefficient of each area in the local time period, analyzing the similarity relation between the temperatures of any area and other areas at each moment, combining the influence coefficient to determine the air conditioning adjustment force of any area in each sampling period, and controlling the energy-saving air conditioner based on a PID controller.
Preferably, the determining of the variation includes the steps of:
Clustering two-dimensional data points at all moments in a local time period to obtain clusters, calculating the average value of measurement distances between any data point and all other data points in the same cluster, marking the average value as a first average value, calculating the average value of measurement distances between any data point and all data points in other clusters, marking the average value as a second average value, and determining the variation of the moment corresponding to any data point based on the first average value and the second average value.
Preferably, the change amount of the moment corresponding to any one data point is a ratio of the second average value to the first average value.
Preferably, the temperature trend difference value is a mean value of absolute values of differences of the trend statistics of each region and all neighboring regions.
Preferably, the determining of the neighborhood temperature limit value includes the following steps:
and calculating the extreme difference value of all temperatures of each region in a local time period, and taking the average value of the extreme difference values of each region and all adjacent regions as the neighborhood temperature extreme difference value.
Preferably, the determining of the degree of correlation of the environmental change includes the steps of:
And forming a change sequence by all the change amounts of each region in a local time period, and taking the average value of absolute values of correlation coefficients of the change sequences of each region and all adjacent regions as the environmental change correlation degree.
Preferably, the determination of the influence coefficient comprises the steps of calculating a fusion value of the temperature trend difference value and the neighborhood temperature difference value, and determining the ratio of the fusion value to the degree of correlation of the environmental change as the influence coefficient.
Preferably, the determining of the air conditioning adjustment force comprises the following steps:
Calculating absolute values of similarity coefficients of all temperatures of any area and other areas in each sampling period, calculating an average value of influence coefficients of all local time periods of any area in each sampling period, calculating a sum value of the absolute values and a numerical value which is preset to be larger than 0, calculating a ratio of the average value to the sum value, and determining a fusion result of the ratio of any area to all other areas as air conditioning adjustment force of any area in each sampling period.
Preferably, the controlling the energy-saving air conditioner includes:
and aiming at each region, taking the sum of the normalized value of the air conditioning adjusting force of the current previous sampling period and the initial proportional term parameter of the PID controller as the proportional term parameter of the PID controller of the current sampling period, and controlling the wind speed of the energy-saving air conditioner air outlet of each region based on the PID controller.
In a second aspect, an embodiment of the present application further provides a control device for an energy-saving air conditioner, including a memory, a processor, and a computer program stored in the memory and running on the processor, where the processor executes the computer program to implement the steps of any one of the methods described above.
The application has at least the following beneficial effects:
(1) The method comprises the steps of dividing an indoor space provided with an energy-saving air conditioner into areas based on the number of air outlets, collecting the temperature of each area at each moment in each sampling period, and the temperature and the wind speed of each moment in each outdoor sampling period, further analyzing the correlation between the collected data, acquiring the temperature difference between each area at each moment and the outside, forming two-dimensional data points by the temperature difference and the wind speed at each moment, and obtaining the variation of the temperature difference and the wind speed state of each area at each moment based on the distance distribution relation of the two-dimensional data points at different moments, wherein the variation reflects the difference degree of the indoor and outdoor temperature differences and the wind speed at different moments, thereby improving the reliability of the control analysis of the energy-saving air conditioner;
(2) Further, the trend statistics of the temperatures of all the areas in the local time period are obtained, the temperature trend difference value of the areas in the local time period is obtained based on the difference of the trend statistics of the areas and the adjacent areas, the neighborhood temperature extreme value of the areas in the local time period is obtained by analyzing the temperature distribution correlation relationship of the areas and the adjacent areas in the local time period, the environmental change correlation degree of the areas in the local time period is obtained by analyzing the correlation relationship of all the variation amounts of the areas and the adjacent areas in the local time period, the influence coefficient of the areas in the local time period is determined by combining the temperature trend difference value, the neighborhood temperature extreme value and the environmental change correlation degree, the correlation relationship of the temperature change of the areas in different indoor areas is reflected, the state of the temperature difference caused by the indoor and outdoor environment change in each area is reflected more accurately, and the rationality of energy-saving air conditioner control adjustment is improved;
(3) The method comprises the steps of analyzing the similarity relation between the temperatures of any area and other areas at each moment, combining the influence coefficients, determining the air conditioning adjustment force of any area in each sampling period, controlling the energy-saving air conditioner based on a PID controller, reflecting the fluctuation of the influence coefficients of the temperature trend between adjacent areas and the temperature difference in the global range, adjusting the response speed of the energy-saving air conditioner adjustment through the PID controller, improving the stability of the air conditioning air outlet wind speed control of each area, and improving the uniformity of indoor temperature distribution.
Detailed Description
In order to further describe the technical means and effects adopted by the application to achieve the preset aim, the following is a detailed description of specific implementation, structure, characteristics and effects of the control method and apparatus for an energy-saving air conditioner according to the present application with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
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.
The following specifically describes a control method and a specific scheme of equipment for an energy-saving air conditioner provided by the application with reference to the accompanying drawings.
Referring to fig. 1, a flowchart illustrating a control method of an energy-saving air conditioner according to an embodiment of the application is shown, the method includes the following steps:
S1, dividing an indoor room with the energy-saving air conditioner into areas based on the number of air outlets, and collecting the temperature of each area at each moment in each sampling period, and the temperature and the air speed of each moment in each outdoor sampling period.
Firstly, because the internal patterns of a large building are complex and various, in order to ensure the accuracy of wind speed control of the air outlet of the energy-saving air conditioner, in the embodiment, the air outlet of the energy-saving air conditioner is taken as the center, the air outlet is taken as the radius of 5 meters, the indoor space provided with the energy-saving air conditioner is divided into various areas according to the number of the air outlets, wherein the value implementation of the radius can be set by a practitioner according to actual conditions, and the application is not limited to the above.
The temperature sensor is used for collecting the temperature of each indoor area, the temperature outside the room is collected, and the wind speed sensor is used for collecting the wind speed outside the room, wherein in the embodiment, the time interval for collection is 1s, the length of the sampling period is set to be 5min, and an operator can set the time interval for collection and the length of the sampling period according to the actual situation by himself, so that the application is not limited.
And forming an indoor temperature sequence of each region according to the time sequence by all temperatures acquired by each region in each sampling period, and forming an outdoor temperature sequence and an outdoor wind speed sequence of each sampling period according to the time sequence by adopting the same method for the acquired outdoor temperature and wind speed.
S2, acquiring temperature differences between each area at each moment and the outside of the room, forming two-dimensional data points by the temperature differences at each moment and the wind speed, and obtaining the variation of the temperature differences and the wind speed state of each area at each moment based on the distance distribution relation of the two-dimensional data points at different moments.
The air conditioner is comprehensively influenced by various factors when the temperature is regulated. For example, the change of wind speed may interfere with the air intake and exhaust of the air conditioning system, and may affect the indoor and outdoor heat exchange efficiency, and especially when the outdoor unit is used for heat dissipation, strong wind may help to improve the heat dissipation efficiency of the air conditioner. The indoor and outdoor temperature directly affects the cold and hot load of the air conditioner, and the larger the difference between the outdoor temperature and the indoor set temperature is, the higher the energy consumption of the air conditioning system is, and the larger the required adjusting force is. Therefore, the outdoor wind speed and the indoor and outdoor temperature difference are key factors affecting the control of the energy-saving air conditioner.
Because the changes of the wind speed and the temperature are random and rapid, the air conditioner adjusting states in different time periods may not be consistent, and therefore, the embodiment equally divides each sampling period into each local time period, wherein the number of the local time periods of each sampling period in the embodiment is 5, and an implementer can set the local time periods according to the actual situation, and the application is not limited to this.
Further, taking the ith area as an example, the larger the indoor and outdoor temperature difference is, the larger the power consumption of the air conditioner for temperature adjustment is, and the heat dissipation efficiency of the air conditioner is relatively low under the condition of small outdoor wind speed or no wind, and the adjusting force of the air conditioner is required to be increased. Therefore, the correlation between the outdoor wind speed and the indoor and outdoor temperature difference data can influence the temperature regulation of the air conditioner.
Specifically, in the jth local time zone of the ith area, calculating the absolute value of the difference between the temperature of the ith area and the outdoor temperature at each sampling moment, forming a two-dimensional data point by the absolute value of the difference and the wind speed at the corresponding moment, clustering the two-dimensional data points at all moments in the jth local time zone of the ith area by adopting a local direction centrality clustering algorithm, setting the clustering quantity as 2, and finally outputting the local direction centrality clustering algorithm as 2 clusters. The local direction centrality clustering algorithm is a known technology, and the embodiment is not described in detail here.
It should be noted that, the implementer may select other feasible clustering algorithms to cluster the two-dimensional data points according to the actual situation, and the number of clusters implemented by the implementer may be set according to the actual situation, which is not limited in the present application.
The method comprises the steps of respectively marking the output 2 clusters as a cluster A and a cluster B, calculating the measurement distance between any two-dimensional data point in the cluster A and other two-dimensional data points in the cluster A, calculating the average value of all the measurement distances of any two-dimensional data point, marking the average value as a first average value, calculating the average value of the measurement distances between any two-dimensional data point and all two-dimensional data points in the cluster B, marking the average value as a second average value, and determining the ratio of the second average value to the first average value as the variation of the temperature difference and the wind speed state of any two-dimensional data point at the corresponding acquisition time.
In this embodiment, the euclidean distance is sampled and calculated, and in another embodiment, the manhattan distance is used to calculate the metric distance.
The smaller the first average value is, the closer the indoor and outdoor temperature value differences and the wind speed states at corresponding moments are to other data in the same cluster, the larger the second average value is, the larger the difference between the data point at the corresponding moments and the other cluster is, and the larger the variation is, the more obvious the variation of the indoor and outdoor temperature differences and the wind speed at the corresponding moments is.
S3, obtaining trend statistics of temperatures of each area in all time points in the local time period, obtaining a temperature trend difference value of each area in the local time period based on the difference of the trend statistics of each area and the adjacent area, and analyzing a temperature distribution correlation relationship of each area and the adjacent area in the local time period to obtain a neighborhood temperature extreme value of each area in the local time period.
In large building environments, the pattern of air flow is often complex. For example, there are differences in personnel density in different areas, some areas may not be vented as well as other areas, some areas may be prone to air stagnation, etc. These conditions can lead to varying degrees of temperature variation between the different regions. However, the temperatures between these zones interact to some extent. Therefore, the temperature difference between the adjacent indoor areas may affect the adjusting force of the air conditioner.
Taking the example that the ith area is in the jth local time period, forming a local indoor temperature sequence by all temperatures acquired by the ith area in the jth local time period according to a time sequence, acquiring trend statistics of the local indoor temperature sequence by adopting a Mann-Kendall test algorithm, wherein the trend statistics reflect the rising or falling trend of the local indoor temperature sequence, and if the absolute value of the trend statistics is larger, the rising or falling trend of the local indoor temperature sequence is more obvious.
The Mann-Kendall test algorithm is a prior art, the present application is not described in detail herein, and the practitioner may use other trend test algorithms according to the actual situation, which is not limited herein.
In this embodiment, the area connected with the edge of the ith area is marked as the adjacent area of the ith area, and the average value of the absolute values of the differences of the trend statistics of the ith area and all the adjacent areas is calculated as the temperature trend difference value of the ith area in the same local time period, wherein the larger the temperature trend difference value is, the more the temperature trend difference value is, the trend of the temperature difference of the ith area and the adjacent areas is increased.
Further, the difference value of the local indoor temperature sequence of the ith area in the jth local time period is calculated, and in the jth local time period, the average value of the difference value of the ith area and the difference values of all adjacent areas is calculated and used as the neighborhood temperature difference value of the ith area in the jth local time period, and the larger the neighborhood temperature difference value is, the larger the difference value is, which indicates that the difference exists between the temperatures of the adjacent areas in the local time period.
And S4, analyzing the correlation relation between each region and all the variation amounts of the adjacent regions in the local time period to obtain the environmental variation correlation degree of each region in the local time period, and determining the influence coefficient of each region in the local time period by combining the temperature trend difference value, the neighborhood temperature difference value and the environmental variation correlation degree.
And forming a change sequence by all the change amounts of the ith area in the jth local time period according to time sequence, calculating the average value of absolute values of the correlation coefficients of the ith area and all the change sequences of all the adjacent areas, and determining the average value as the environmental change correlation degree of the ith area.
In this embodiment, the correlation coefficient is calculated using a spearman correlation coefficient, and in another embodiment, the correlation coefficient may be calculated using a pearson correlation coefficient. The calculation of the spearman correlation coefficient and the pearson correlation coefficient are all known techniques, and the present application is not described in detail herein.
The smaller the environmental change correlation degree of the ith area is, the smaller the correlation degree of the indoor and outdoor temperature difference and the wind speed state of the ith area and the adjacent areas is, and the more likely to cause abnormal fluctuation of the temperature of the ith area is, the greater the possibility that the energy-saving air conditioner of the ith area needs to be regulated and controlled is.
Further, calculating an influence coefficient of the ith area in the jth local time period, specifically calculating a fusion value of the temperature trend difference value of the ith area in the jth local time period and the neighborhood temperature difference value, and determining a ratio of the fusion value to the environmental change correlation degree as the influence coefficient.
In addition, fusion means that a plurality of variables are added, multiplied, or the like as a result of enhancing the overall effect, and in this embodiment, addition is used as a calculation method of fusion.
In this embodiment, the expression of the influence coefficient of the i-th region at the j-th local period may be:
In the formula (I), in the formula (II),Representing the coefficient of influence of the ith region at the jth local time period,Representing the temperature trend difference value of the ith zone at the jth local time period,Representing the neighborhood temperature tolerance value of the ith region at the jth local time period,Indicating the degree of environmental change correlation of the ith region at the jth local time period.
Influence coefficient of the ith region at the jth local time periodReflecting the extent of influence of the temperature trend between adjacent regions of the ith region at the jth local time period,The larger the temperature of the ith area and the difference between the indoor and outdoor environment change states and the adjacent areas are, the more complicated the change of the heat load is, and the more the adjusting force of the energy-saving air conditioner of the ith area is required to be increased.
S5, analyzing the similarity relation between the temperatures of any area and other areas at each moment, and determining the air conditioning adjusting force of any area in each sampling period by combining the influence coefficients, and controlling the energy-saving air conditioner based on the PID controller.
The influence coefficients of the areas reflect the difference of the local environment of the areas, and in a large building, the consistency of the temperature among all the areas is generally required to be maintained, and the air conditioner can be controlled slowly only by means of the mutual influence characteristics among the adjacent areas.
Therefore, further combining the correlation between the temperature of the ith area and all the indoor areas, the air conditioning adjustment force of the ith area in one sampling period is calculated, and in this embodiment, the calculation mode is as follows:
In the formula (I), in the formula (II),Indicating the air conditioning level of the ith zone in one sample period,Indicating the number of all regions remaining except the i-th region,Representing the mean value of the influence coefficients corresponding to all local time periods of the ith region in one sampling period,The value 1 in the denominator is used for avoiding incapacity of calculation because the denominator is 0, and an implementer can set the value according to the actual situation without limiting the application. The calculation of the Jacquard similarity coefficients is known in the art, and the present application is not described in detail herein. The air conditioning adjusting force obtaining flow chart is shown in fig. 2.
In another embodiment, the Jacquard similarity coefficient in the air conditioner adjusting force calculation process can be replaced by cosine similarity, and the cosine similarity is used as a similarity measurement mode that all indoor temperature values in the ith area and the nth area form a set in the same sampling period.
The larger the i-th zone, the greater the degree of fluctuation of the indoor and outdoor environments,Smaller indicates a larger temperature difference between the different regions, resulting inThe larger the i-th region, the larger the difference between the heat load change and other regions, and the more the air conditioner adjusting force is required to be increased.
And acquiring the air conditioning adjustment force of each region in each sampling period by adopting the same calculation mode as the air conditioning adjustment force of the ith region in one sampling period.
According to the application, the air conditioning adjusting force values of the areas in each sampling period are obtained by analyzing the indoor and outdoor temperature difference and the outdoor wind speed change characteristics of the areas and combining the temperature differences among the different areas, and the fans at the air outlets of the areas are controlled based on the air conditioning adjusting force values.
The air speed of the air outlet of each area is controlled by the PID controller, the larger the air conditioning adjusting force value is, the higher the possibility of abnormal temperature of the area is, because the proportional item parameter in the PID controller is responsible for adjusting the response speed of the air conditioning system, when the proportional item parameter is set larger, the air conditioning system can make adjusting instructions faster, errors and fluctuation are reduced, and when the proportional item parameter is set smaller, the adjusting speed is correspondingly slowed down. Therefore, when the air conditioner adjusting force value is larger, the proportional term parameter of PID control needs to be increased, and the response rate of the air conditioner control in the area is improved.
In this embodiment, the initial parameter of the PID controller sets the proportional term to 2, the integral term to 0.5, and the differential term to 0.5, which can be set by the practitioner according to the actual situation, which is not limited in the present application. And normalizing the air conditioning adjustment force values corresponding to all the areas in the same sampling period by adopting a Z-score normalization method, taking the ith area as an example, calculating the sum value of the normalization result and the initial proportional term parameter of the air conditioning adjustment force of the ith area in the previous sampling period of the current sampling period, marking the sum value as a first sum value, taking the first sum value as the proportional term parameter of the current sampling period of the ith area, thereby completing the adjustment of the air speed of the air conditioning air outlet of the ith area by a PID controller, and adopting the same method as the ith area to adjust all the areas divided indoors. PID control in the energy-saving air conditioner is a known technology, and the embodiment is not described in detail here.
Based on the same inventive concept as the above method, the embodiment of the application further provides a control device of an energy-saving air conditioner, which comprises a memory, a processor and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to realize the steps of any one of the above control methods of the energy-saving air conditioner.
In summary, the application divides the indoor space with the energy-saving air conditioner into each area based on the number of air outlets, and collects the temperature of each area at each moment in each sampling period, and the temperature and the air speed of each moment in each sampling period outdoors; the method comprises the steps of acquiring the temperature difference between each area and the outside of a room, forming two-dimensional data points by the temperature difference and the wind speed at each moment, obtaining the variation of the temperature difference and the wind speed state of each area at each moment based on the distance distribution relation of the two-dimensional data points at different moments, reflecting the difference degree of the indoor and outdoor temperature differences and the wind speed between different moments, improving the reliability of energy-saving air conditioner control analysis, further acquiring the trend statistics of the temperature of each area in a local time period, obtaining the temperature trend difference value of each area in the local time period based on the difference of the trend statistics of each area and the adjacent area, analyzing the neighborhood temperature difference value of each area in the local time period, analyzing the correlation of all the variation of each area and the adjacent area in the local time period, obtaining the environment variation correlation degree of each area in the local time period, combining the temperature trend value, the neighborhood temperature difference value and the environment variation correlation degree, determining the influence coefficient of each area in the local time period, accurately reflecting the difference of the temperature in the local time period, and improving the temperature distribution relation of each area in the local time period, and the difference of the air conditioner control system, the fluctuation of the influence coefficient of the temperature trend between adjacent areas and the difference of the temperature in the global range are reflected, the response speed of the energy-saving air conditioner regulation is adjusted through the PID controller, the stability of the air conditioner air outlet air speed control of each area is improved, and the uniformity of indoor temperature distribution is improved.
It should be noted that the sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. And the foregoing description has been directed to specific embodiments of this specification. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments.
The foregoing description of the preferred embodiments of the present application is not intended to be limiting, but rather, any modifications, equivalents, improvements, etc. that fall within the principles of the present application are intended to be included within the scope of the present application.