Fresh air handling unit energy-saving regulation and control system based on distributed collaboration

Abstract

The invention relates to the technical field of air conditioning treatment, in particular to a fresh air handling unit energy-saving regulation and control system based on distributed cooperation, and the system comprises a fresh air handling unit data collection module which obtains the operation power of a fresh air handling unit and the environment parameters of a region where the fresh air handling unit is located; the fresh air handling unit ventilation quality obtaining module is used for comparing the difference condition between each regional environment parameter and the corresponding threshold value to obtain the proportionality coefficient adjusting effect after each PID parameter adjustment; the fresh air handling unit power analysis module takes the area where each fresh air handling unit is located as a target area in sequence, and analyzes the influence degree of the operating power change condition of the fresh air handling units in other areas on the air condition of the target area; and the fresh air handling unit PID coefficient adjusting module is used for screening the main influence area and determining the proportionality coefficient of the target area after the current PID parameter is adjusted. According to the method, the proportionality coefficient of the fresh air handling unit in each area is corrected in a self-adaptive mode, and energy consumption of the fresh air handling unit is reduced.

Description

Technical Field

[0001] The present application relates to the field of air conditioning processing technology, and specifically to an energy-saving control system for fresh air units based on distributed collaboration. Background Art

[0002] In today's society, with the dual focus on indoor air quality and energy conservation, fresh air systems are becoming increasingly important in all types of buildings. Traditional centralized fresh air systems, due to issues such as energy waste and difficulty adapting to the differentiated ventilation needs of different areas, are increasingly unable to meet the complex requirements of modern buildings. Distributed fresh air unit systems have emerged as a response to this. These systems consist of multiple small fresh air units distributed throughout the building, each independently providing fresh air to its own area. This layout provides the system with greater flexibility, better adapting to the personalized needs of different areas.

[0003] Traditional ventilation systems often waste energy during operation, especially in large buildings or areas. A single centralized control approach struggles to meet the diverse ventilation needs of different areas, resulting in low system efficiency and high energy consumption. Therefore, a method is needed to coordinate multiple ventilation units and adjust the power of each unit to achieve energy savings.

[0004] When regulating multiple fresh air units, PID control algorithms are typically used to adjust ventilation parameters for each zone. However, existing PID algorithms often use fixed parameter settings, failing to consider the impact of variations in fresh air unit power between zones and natural ventilation conditions on regulation. In reality, variations in fan power in adjacent zones can interfere with the regulation results in the current zone, leading to reduced PID control accuracy, impacting air quality control, and increasing energy consumption. Summary of the Invention

[0005] In view of the above, it is necessary to provide a distributed collaborative fresh air unit energy-saving control system to more accurately remove the interference noise signal of the vibration signal during the operation of the wind turbine and improve the accuracy of the vibration fault diagnosis of the wind turbine.

[0006] One embodiment of the present application provides a distributed collaborative fresh air unit energy-saving control system, the system comprising:

[0007] Fresh air unit data acquisition module, used to obtain the operating power of each fresh air unit and the environmental parameters of the area where it is located;

[0008] The ventilation quality acquisition module of the fresh air unit is used to obtain the proportional coefficient adjustment effect of each area after each PID parameter adjustment based on the difference between the environmental parameters and their corresponding thresholds at all times during the period from each PID parameter adjustment to the next PID parameter adjustment of the fresh air unit in each area;

[0009] The fresh air unit power analysis module is used to take the area where each fresh air unit is located as the target area in turn, select any area except the target area, and perform a first clustering of the operating power of all areas at all historical moments based on the operating power changes of all areas except the said any area at historical moments; perform a second clustering of the operating power of any area in each cluster obtained by the first clustering; based on the degree of dispersion of the environmental parameters of the target area at the corresponding moment of each operating power in the cluster obtained by the second clustering, combined with the degree of similarity between the overall distribution of the operating power and the environmental parameters, obtain the degree of influence of the fresh air unit in any area on the air condition of the target area;

[0010] The PID coefficient adjustment module of the fresh air unit is used to perform threshold segmentation on the impact degree of all air conditions obtained in the target area and screen the main impact area; perform a third clustering on the operating power change values ​​of all historical PID parameter adjustments that meet the proportional coefficient conditions in each main impact area, and screen the adjustment reference cluster cluster; obtain the proportional coefficient adjustment factor of the target area based on the proportional parameter change of each element in the adjustment reference cluster cluster corresponding to the target area; based on the proportional coefficient adjustment factor of the target area and the proportional coefficient before the current PID parameter is adjusted and its proportional coefficient adjustment effect, determine the proportional coefficient of the target area after the current PID parameter is adjusted.

[0011] The steps of obtaining the proportional coefficient adjustment effect of each region after each PID parameter adjustment include:

[0012] The environmental parameters include temperature data and carbon dioxide concentration data;

[0013] The difference between the temperature data of each area at each time and the temperature threshold is recorded as the first difference; the difference between the carbon dioxide concentration data of each area at each time and the carbon dioxide concentration threshold is recorded as the second difference, and the normalized value of the sum of the first difference and the second difference at each time in each area is used as the air quality index of each area at each time;

[0014] The negative correlation mapping result of the discrete degree of the air quality index of each area at all times in the time period corresponding to each PID parameter adjustment is used as the proportional coefficient adjustment effect of each area after each PID parameter adjustment.

[0015] The metric distance of the first clustering is specifically the absolute value of the difference between the operating power of each area except any one of the areas at all historical moments of each two combinations.

[0016] The specific process of obtaining the degree of influence of the fresh air unit in any area on the air condition of the target area is as follows:

[0017] Obtain the temperature data and carbon dioxide concentration of the target area at the corresponding time for each element in each cluster obtained by the second clustering, and analyze the degree of dispersion of various environmental parameters of the target area at the corresponding time for all elements in each cluster;

[0018] Calculate the mean of each cluster element obtained by the second clustering and the mean of various environmental parameters in the target area;

[0019] Based on the similarity between the sequence composed of the mean values ​​of the elements in all clusters and the sequence composed of the mean values ​​of the environmental parameters of the target area, combined with the discrete degree of all environmental parameters corresponding to each cluster, the impact factor of the fresh air unit in any area of ​​each cluster obtained by the first clustering on the air condition of the target area is obtained;

[0020] The average of the impact factors of the fresh air unit in any area on the air condition of the target area in all clusters obtained by the first clustering is used as the impact degree of the fresh air unit in any area on the air condition of the target area.

[0021] The influence factor of the fresh air unit in any area of ​​each cluster obtained by the first clustering on the air condition of the target area is specifically:

[0022] The sequence consisting of the mean operating power values ​​of any area in all clusters obtained by the second clustering, the sequence consisting of the mean temperature data of the target area, and the sequence consisting of the mean carbon dioxide concentration of the target area are recorded as the first sequence, the second sequence, and the third sequence respectively;

[0023] Obtaining the similarity between the first sequence and the second sequence and the third sequence, respectively, and recording them as a first similarity degree and a second similarity degree;

[0024] The product of the discrete degree of the temperature data and the discrete degree of the carbon dioxide data of the target area in each cluster obtained by the second clustering is calculated, the corresponding products of all clusters obtained by the second clustering are accumulated, and the results of forward fusion are combined with the first similarity degree and the second similarity degree as the impact factor of the fresh air unit in any area of ​​each cluster obtained by the first clustering on the air condition of the target area.

[0025] The specific steps for screening the main impact areas include:

[0026] Threshold segmentation is performed on all air condition impact levels obtained in the target area to obtain an impact level threshold, and areas greater than the impact level threshold are extracted, and the screened-out areas are used as the main impact areas.

[0027] The proportional coefficient condition is specifically the same as the proportional coefficient when the target area is not currently undergoing PID parameter adjustment.

[0028] The adjustment reference cluster is specifically a cluster whose element mean is closest to the operating power change value when the target area is not currently undergoing PID parameter adjustment.

[0029] The specific steps of obtaining the proportional coefficient adjustment factor of the target area include:

[0030] The difference between the proportional parameter obtained by adjusting the PID parameter of each element in the reference cluster and the proportional parameter obtained by adjusting the target area of ​​the next PID parameter is used as the proportional parameter change value of the target area corresponding to each element;

[0031] Obtain the mean value of the proportional parameter change corresponding to all elements in the adjusted reference cluster;

[0032] Calculate the proportion of the impact of each major impact area on the air conditions in the target area to the proportion of the impact of all major impact areas on the air conditions in the target area, and use this as the weight of the mean change value of the proportional parameter of each major impact area corresponding to the target area. The weighted sum is used to obtain the proportional coefficient adjustment factor of the target area.

[0033] The specific formula for determining the proportional coefficient after the current PID parameter adjustment of the target area is: a =Hv a ×Hi a +(1-Hv a )×Ht a Where, Hc a Indicates the proportional coefficient of the target area a after the current PID parameters are adjusted; Hv a Indicates the proportional coefficient adjustment effect before the current PID parameter adjustment in target area a; Hi a Indicates the proportional coefficient before the current PID parameter adjustment; Ht a Indicates the scale coefficient adjustment factor of the target area a.

[0034] This application has at least the following beneficial effects:

[0035] This application obtains the proportional coefficient adjustment effect of each area after each PID parameter adjustment by analyzing the differences between the environmental parameters and their corresponding thresholds at all times in the time period from each PID parameter adjustment to the next PID parameter adjustment of the fresh air unit, which helps to analyze and evaluate the proportional coefficient adjustment effect of each area after each PID parameter adjustment; through these differences, we can more clearly understand the actual effect of PID adjustment on environmental parameter control, thereby providing data support for the next adjustment. The area where each fresh air unit is located is taken as the target area in turn, and the degree of influence of the operating power changes of other areas on the control status of the target area is analyzed through clustering. The first clustering can identify the power change pattern of different areas at historical moments; the second clustering can further refine the power change characteristics of different areas under different conditions; based on the clustering results, the degree of influence of the fresh air unit on the air condition of the target area can be quantified.

[0036] By applying a threshold segmentation based on the impact of the air condition in the target area, the areas most significantly impacting the target area's air quality can be identified. This helps focus resources on optimizing those areas with the greatest impact, thereby improving air quality control effectiveness. By analyzing and adjusting the changes in the proportional parameters of each element in the reference cluster relative to the target area, the proportional coefficient adjustment factor for the target area can be derived. This factor facilitates dynamic adjustment of the proportional coefficient, thereby improving the flexibility and adaptability of air quality control. The proportional coefficient of each regional fresh air unit is adaptively corrected. This adaptive adjustment allows the PID control parameters to more accurately adapt to the actual needs of the fresh air unit in different regions, avoiding the potential over- or under-adjustment of fixed parameters and thus reducing unnecessary energy consumption. Furthermore, the performance of the fresh air unit in the target area under the current PID parameter proportional coefficient is evaluated based on the adjustment effect. If the adjustment effect is unsatisfactory, the proportional coefficient is adjusted appropriately, taking into account factors such as the impact of other regions, to optimize the operating power of the fresh air unit and maintain stable air quality with the lowest energy consumption. This not only helps improve energy efficiency but also achieves energy conservation goals. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A block diagram of the distributed collaborative energy-saving control system for fresh air units provided in this application;

[0038] Figure 2 This is a specific flow chart for adjusting the PID parameters of the fresh air unit in the target area provided in this application. DETAILED DESCRIPTION

[0039] In the description of the embodiments of this application, words such as "exemplary," "or," and "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary," "or," and "for example" is intended to present the relevant concepts in a concrete manner.

[0040] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art in the art of this application. The terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application.

[0041] It should also be noted that the terms "first" and "second" in this application and its accompanying drawings are used to distinguish similar objects, rather than to describe a specific order or precedence. The methods disclosed in the embodiments of this application or the methods shown in the flowcharts include one or more steps for implementing the methods. Without departing from the scope of protection of this application, the order of execution of multiple steps can be interchanged with each other, and some steps can also be deleted.

[0042] 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.

[0043] The specific scheme of the distributed collaborative fresh air unit energy-saving control system provided by this application is described in detail below with reference to the accompanying drawings.

[0044] See also Figure 1 , which shows a block diagram of a fresh air unit energy-saving control system based on distributed collaboration provided by an embodiment of the present application. The system includes: a fresh air unit data acquisition module, a fresh air unit ventilation quality acquisition module, a fresh air unit power analysis module, and a fresh air unit PID coefficient adjustment module.

[0045] The present application embodiment first proposes a distributed collaborative fresh air unit energy-saving control system, which is applied to the field of air conditioning processing technology. The system includes:

[0046] Fresh air unit data acquisition module: obtains the operating power of each fresh air unit and the environmental parameters of the area where it is located.

[0047] The operating power of the factory's fresh air units at each collection moment is collected in real time. The fresh air units in the locations being regulated are numbered. In this application, there are m fresh air units that coordinately control the ventilation system of the entire factory. The area where each unit is located is analyzed, and sensors are used to collect environmental parameters such as temperature and carbon dioxide concentration in the corresponding area. This allows for timely adjustment of the fresh air unit operating parameters based on the environmental conditions of the monitored area.

[0048] In this embodiment, the operating power, temperature data and carbon dioxide concentration data are collected once every minute. It should be noted that various environmental parameters are collected synchronously; the time interval for adjusting the PID parameters is set to 10 minutes.

[0049] Fresh air unit ventilation quality acquisition module: According to the difference between the environmental parameters and their corresponding thresholds at all times in the time period from each PID parameter adjustment to the next PID parameter adjustment of the fresh air unit in each area, the proportional coefficient adjustment effect of each area after each PID parameter adjustment is obtained.

[0050] As for air quality, the closer the relevant environmental parameters are to the preset threshold and the higher the stability is, the more ideal the proportional coefficient adjustment effect of the fresh air unit in the area is; the area corresponding to the ath fresh air unit is referred to as area a. This application takes area a as an example for analysis, and the difference between the temperature data at each moment in area a and the temperature threshold is recorded as the first difference; the difference between the carbon dioxide concentration data at each moment in area a and the carbon dioxide concentration threshold is recorded as the second difference, and the normalized value after adding the first difference and the second difference at each moment in area a is used as the air quality index of area a at each moment, which is used to measure the proportional coefficient adjustment effect of the fresh air unit at each moment in area a. In the embodiment of the present application, the temperature threshold T is set to 20°C, and the carbon dioxide concentration threshold C is set to 0.01; the difference between the variables is calculated by the absolute value of the difference, and the normalization method adopts the maximum and minimum value normalization method.

[0051] The time period from each PID parameter adjustment to the next PID parameter adjustment is used as the time period corresponding to each PID parameter adjustment, and the changes in the relevant parameters of the areas where all fresh air units are located at various times within the time period are analyzed. Specifically, the negative correlation mapping result of the discrete degree of the air quality index of area a at all times within the time period corresponding to each PID parameter adjustment is used as the proportional coefficient adjustment effect of area a during each PID parameter adjustment. In this embodiment, the discrete degree between multiple variables is measured by variance, and the negative correlation mapping of the variables is specifically the inverse of the variables. In order to prevent the negative correlation mapping result of the variables from having a denominator of 0, a preset parameter is added to the denominator, and the value in this embodiment is 0.01.

[0052] It should be understood that when the value of the proportional coefficient adjustment effect is larger, it means that the operating power of the fresh air unit in area a adjusted under the corresponding PID parameter proportional coefficient has a more significant effect on improving the air quality in area a.

[0053] Fresh air unit power analysis module: the area where each fresh air unit is located is taken as the target area in turn, and any area except the target area is selected. Based on the operating power changes of all areas except the said any area at historical moments, the operating power of all areas at all historical moments is clustered for the first time; the operating power of any area in each cluster obtained by the first clustering is clustered for the second time; based on the discrete degree of the environmental parameters of the target area at the corresponding moment of each operating power in the cluster obtained by the second clustering, combined with the similarity of the overall distribution of the operating power and the environmental parameters, the degree of influence of the fresh air unit in any area on the air condition of the target area is obtained.

[0054] Because the operation of fresh air units in various areas of a factory building may affect the ventilation quality of other areas, this application analyzes historical data to evaluate the impact of fresh air units in each area on the ventilation quality of other areas during each PID parameter adjustment. Based on these evaluation results, the impact of fresh air units in other areas on the air quality of the target area can be taken into account during the control process, and corresponding adjustments can be made based on the degree of impact, thereby achieving the goals of energy saving and optimized control.

[0055] This application analyzes area a as the target area and analyzes the degree of influence of the fresh air unit in area b on the ventilation effect of the target area a. In order to analyze the influence of the power change of the fresh air unit in area b on the air quality of area a, it is necessary to ensure that the power of the fresh air units in other areas except area b remains relatively close; only when the power of the fresh air units in other areas is consistent can the specific impact of the power fluctuation of the fresh air unit in area b on the air quality of area a be more accurately evaluated: first, the operating power of all areas at all historical moments is clustered for the first time, and the absolute value of the difference between the operating power of each area except area b at all historical combinations is used as the metric distance for the first clustering; the embodiment of this application adopts the DBSCAN clustering algorithm for clustering, and the number of cluster clusters obtained by the first clustering is recorded as L.

[0056] Furthermore, if the environmental parameters in area a also change predictably as the operating power of the fresh air unit in area b increases or decreases, it means that the fresh air unit b has a greater impact on the air condition in area a: perform a second clustering on the operating power of area b in each cluster, and use the absolute value of the operating power difference of area b as the metric distance of the second clustering; the embodiment of the present application adopts the DBSCAN clustering algorithm for clustering, and the number of clusters obtained by the second clustering is recorded as R; obtain the environmental parameters of the target area a at the corresponding moment for each element in each cluster obtained by the second clustering; calculate the mean operating power of area b, the mean temperature data of the target area a, and the mean carbon dioxide concentration of the target area a in each cluster obtained by the second clustering respectively; record the sequence composed of the mean operating power of area b in all clusters as the first sequence; record the sequence composed of the mean temperature data of the target area a in all clusters as the second sequence. Two sequences; a sequence consisting of the mean carbon dioxide concentrations of target area a across all clusters is recorded as a third sequence; the similarities between the first sequence and the second and third sequences are obtained, recorded as first and second similarities, respectively; in this embodiment, the similarities between sequences are calculated using the Pearson correlation coefficient; the product of the discreteness of the temperature data and the discreteness of the carbon dioxide data for target area a in each cluster obtained from the second clustering is calculated, the corresponding products for all clusters obtained from the second clustering are accumulated, and the result is forward-fused with the first and second similarities to serve as the air condition impact factor of the fresh air unit in area b on area a in each cluster obtained from the first clustering; the average of the air condition impact factors of the fresh air unit in area b on area a across all clusters obtained from the first clustering is used as the air condition impact factor of area b on target area a. In this embodiment, the discreteness of multiple variables is calculated using variance; and the forward fusion of multiple variables is calculated using multiplication.

[0057] It should be understood that the stronger the correlation between the distribution of the operating power of the fresh air unit in area b and the distribution of the carbon dioxide concentration and temperature data in the target area a, and the smaller the variance of the carbon dioxide concentration and temperature values ​​in each cluster, the greater the impact of the operating power of the fresh air unit in area b on the air conditions in the target area a.

[0058] Fresh air unit PID coefficient adjustment module: threshold segmentation is performed on all air condition impact levels obtained in the target area to screen the main impact area; the operating power change values ​​of all historical PID parameter adjustments that meet the proportional coefficient conditions in each main impact area are clustered for the third time to screen the adjustment reference cluster cluster; the proportional coefficient adjustment factor of the target area is obtained based on the proportional parameter changes of each element in the adjustment reference cluster cluster corresponding to the target area; based on the proportional coefficient adjustment factor of the target area and the proportional coefficient before the current PID parameter is adjusted and its proportional coefficient adjustment effect, the proportional coefficient of the target area after the current PID parameter is adjusted is determined.

[0059] According to the above method, the proportional coefficient adjustment effect of each area after each PID parameter adjustment is obtained, and based on the degree of influence of the operating power changes of the fresh air units in all areas on the target area a, the proportional coefficient of the fresh air unit in the target area a after the PID parameter adjustment is obtained, that is, if the operating power changes of the fresh air units in other areas currently change significantly, and the target area a has not undergone PID parameter adjustment, that is, the result of the previous PID parameter adjustment, the smaller the proportional coefficient adjustment effect corresponding to the current time period, the more the current PID parameter needs to be adjusted. Specifically: first, the degree of influence of the operating power of the fresh air units in all areas on the air condition of the target area a is obtained, and the Otsu threshold algorithm is used to process the influence degrees of all air conditions corresponding to the target area a to obtain an influence degree threshold, and the areas greater than the influence degree threshold are extracted, and the screened-out areas are used as the main influence areas.

[0060] The power changes of the fresh air units in the main influencing area c are analyzed, and the operating power change values ​​of the main influencing area c in all historical PID parameter adjustment corresponding time periods with the same proportional coefficient as the target area a when the PID parameters are not currently adjusted are extracted, that is, the operating power difference between the power at the end time and the operating power at the starting time of each historical PID parameter adjustment corresponding time period. The operating power change values ​​of all historical PID parameter adjustments are clustered for the third time, and the distance measurement is Euclidean distance; the mean power change value in each cluster is calculated, and the cluster closest to the operating power change value of the target area a when the PID parameters are not currently adjusted is used as the adjustment reference cluster.

[0061] Get the proportional coefficient change value obtained from the time period corresponding to each power change value in the adjustment reference cluster and the target area in the next time period. Specifically: take the difference between the proportional parameter obtained from the PID parameter adjustment of each element in the adjustment reference cluster and the target area a of the next PID parameter adjustment as the proportional parameter change value of the target area a corresponding to each element; get the average proportional parameter change value corresponding to all elements in the adjustment reference cluster; calculate the proportion of the degree of influence of each major influencing area on the air condition of the target area a to the degree of influence of all major influencing areas on the air condition of the target area a, as the weight of the average proportional parameter change value of each major influencing area corresponding to the target area a, and obtain the proportional coefficient adjustment factor of the target area a by weighted summation; based on the proportional coefficient adjustment factor of the target area a and the proportional coefficient before the current PID parameter is adjusted and its proportional coefficient adjustment effect, determine the proportional coefficient after the current PID parameter is adjusted. The specific formula is: Hc a =Hv a ×Hi a +(1-Hv a )×Ht a Where, Hc a Indicates the proportional coefficient of the target area a after the current PID parameters are adjusted; Hv a Indicates the proportional coefficient adjustment effect before the current PID parameter adjustment in target area a; Hi a Indicates the proportional coefficient before the current PID parameter adjustment; Ht a Indicates the scale coefficient adjustment factor of the target area a.

[0062] Based on this, each area is analyzed as the target area in turn to obtain the proportional coefficient of the fresh air unit in each area after the current PID parameters are adjusted.

[0063] Among them, the specific flow chart of PID parameter adjustment of fresh air unit in target area is as follows: Figure 2 shown.

[0064] The flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, methods and computer program products according to the embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the part of the module, program segment or code contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in an order different from that disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified function or action, or may be implemented by a combination of dedicated hardware and computer instructions.

[0065] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. The energy-saving control system of fresh air units based on distributed collaboration is characterized by: The system includes: Fresh air unit data acquisition module, used to obtain the operating power of each fresh air unit and the environmental parameters of the area where it is located; The ventilation quality acquisition module of the fresh air unit is used to obtain the proportional coefficient adjustment effect of each area after each PID parameter adjustment based on the difference between the environmental parameters and their corresponding thresholds at all times during the period from each PID parameter adjustment to the next PID parameter adjustment of the fresh air unit in each area; The fresh air unit power analysis module is used to take the area where each fresh air unit is located as the target area in turn, select any area except the target area, and perform a first clustering of the operating power of all areas at all historical moments based on the operating power changes of all areas except the said any area at historical moments; perform a second clustering of the operating power of any area in each cluster obtained by the first clustering; based on the degree of dispersion of the environmental parameters of the target area at the corresponding moment of each operating power in the cluster obtained by the second clustering, combined with the degree of similarity between the overall distribution of the operating power and the environmental parameters, obtain the degree of influence of the fresh air unit in any area on the air condition of the target area; The PID coefficient adjustment module of the fresh air unit is used to perform threshold segmentation on the impact degree of all air conditions obtained in the target area and screen the main impact area; perform a third clustering on the operating power change values ​​of all historical PID parameter adjustments that meet the proportional coefficient conditions in each main impact area, and screen the adjustment reference cluster cluster; obtain the proportional coefficient adjustment factor of the target area based on the proportional parameter change of each element in the adjustment reference cluster cluster corresponding to the target area; based on the proportional coefficient adjustment factor of the target area and the proportional coefficient before the current PID parameter is adjusted and its proportional coefficient adjustment effect, determine the proportional coefficient of the target area after the current PID parameter is adjusted.

2. The distributed collaborative fresh air unit energy-saving control system according to claim 1 is characterized in that: The specific steps of obtaining the proportional coefficient adjustment effect of each region after each PID parameter adjustment include: The environmental parameters include temperature data and carbon dioxide concentration data; The difference between the temperature data of each area at each time and the temperature threshold is recorded as the first difference; the difference between the carbon dioxide concentration data of each area at each time and the carbon dioxide concentration threshold is recorded as the second difference, and the normalized value of the sum of the first difference and the second difference at each time in each area is used as the air quality index of each area at each time; The negative correlation mapping result of the discrete degree of the air quality index of each area at all times in the time period corresponding to each PID parameter adjustment is used as the proportional coefficient adjustment effect of each area after each PID parameter adjustment.

3. The distributed collaborative fresh air unit energy-saving control system according to claim 1 is characterized in that: The metric distance of the first clustering is specifically the absolute value of the difference between the operating power of each area except any one of the areas at all historical moments of all two combinations.

4. The distributed collaborative fresh air unit energy-saving control system according to claim 2, characterized in that: The specific process of obtaining the degree of influence of the fresh air unit in any area on the air condition of the target area is as follows: Obtain the temperature data and carbon dioxide concentration of the target area at the corresponding time for each element in each cluster obtained by the second clustering, and analyze the degree of dispersion of various environmental parameters of the target area at the corresponding time for all elements in each cluster; Calculate the mean of each cluster element obtained by the second clustering and the mean of various environmental parameters in the target area; Based on the similarity between the sequence composed of the mean values ​​of the elements in all clusters and the sequence composed of the mean values ​​of the environmental parameters of the target area, combined with the discrete degree of all environmental parameters corresponding to each cluster, the impact factor of the fresh air unit in any area of ​​each cluster obtained by the first clustering on the air condition of the target area is obtained; The average of the impact factors of the fresh air unit in any area on the air condition of the target area in all clusters obtained by the first clustering is used as the impact degree of the fresh air unit in any area on the air condition of the target area.

5. The distributed collaborative fresh air unit energy-saving control system according to claim 4 is characterized in that: The influence factor of the fresh air unit in any area of ​​each cluster obtained by the first clustering on the air condition of the target area is specifically: The sequence consisting of the mean operating power values ​​of any area in all clusters obtained by the second clustering, the sequence consisting of the mean temperature data of the target area, and the sequence consisting of the mean carbon dioxide concentration of the target area are recorded as the first sequence, the second sequence, and the third sequence respectively; Obtaining the similarity between the first sequence and the second sequence and the third sequence, respectively, and recording them as a first similarity degree and a second similarity degree; The product of the discrete degree of the temperature data and the discrete degree of the carbon dioxide data of the target area in each cluster obtained by the second clustering is calculated, the corresponding products of all clusters obtained by the second clustering are accumulated, and the results of forward fusion are combined with the first similarity degree and the second similarity degree as the impact factor of the fresh air unit in any area of ​​each cluster obtained by the first clustering on the air condition of the target area.

6. The distributed collaborative fresh air unit energy-saving control system according to claim 1, characterized in that: The specific steps of screening the main impact areas include: Threshold segmentation is performed on all air condition impact levels obtained in the target area to obtain an impact level threshold, and areas greater than the impact level threshold are extracted, and the screened-out areas are used as the main impact areas.

7. The distributed collaborative fresh air unit energy-saving control system according to claim 1, characterized in that: The proportional coefficient condition is specifically the same as the proportional coefficient when the target area is not currently undergoing PID parameter adjustment.

8. The distributed collaborative fresh air unit energy-saving control system according to claim 1 is characterized in that: The adjustment reference cluster is specifically a cluster whose element mean is closest to the operating power change value when the target area is not currently undergoing PID parameter adjustment.

9. The distributed collaborative fresh air unit energy-saving control system according to claim 1, characterized in that: The specific steps of obtaining the proportional coefficient adjustment factor of the target area include: The difference between the proportional parameter obtained by adjusting the PID parameter of each element in the reference cluster and the proportional parameter obtained by adjusting the target area of ​​the next PID parameter is used as the proportional parameter change value of the target area corresponding to each element; Obtain the mean value of the proportional parameter change corresponding to all elements in the adjusted reference cluster; Calculate the proportion of the impact of each major impact area on the air conditions in the target area to the proportion of the impact of all major impact areas on the air conditions in the target area, and use this as the weight of the mean change value of the proportional parameter of each major impact area corresponding to the target area. The weighted sum is used to obtain the proportional coefficient adjustment factor of the target area.

10. The distributed collaborative fresh air unit energy-saving control system according to claim 1, characterized in that: The specific formula for determining the proportional coefficient after the current PID parameter adjustment of the target area is: Hc a =Hv a ×Hi a +(1-Hv a )×Ht a Where, Hc a Indicates the proportional coefficient of the target area a after the current PID parameters are adjusted; Hv a Indicates the proportional coefficient adjustment effect before the current PID parameter adjustment in target area a; Hi a Indicates the proportional coefficient before the current PID parameters are adjusted; Ht a Indicates the scale coefficient adjustment factor of the target area a.

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