Indoor air conditioning method and system based on variable air volume control

Abstract

The invention relates to the technical field of indoor air supply control, in particular to an indoor air conditioning method and system based on variable air volume control, and the method comprises the steps that air to-be-conditioned areas and air conditioning requirements in all real-time monitoring areas in an indoor air monitoring area are obtained; adjusting data reference time is generated according to the air adjusting requirement, and air adjusting reference data corresponding to the adjusting data reference time is obtained; generating an optimal air volume control strategy according to the air conditioning reference data, the air conditioning demand and an air conditioning strategy model; and air conditioning is conducted on the air to-be-conditioned area according to the optimal air volume control strategy. According to the air conditioning method and device, the problems that in the prior art, the air conditioning efficiency is not high and energy consumption is wasted due to overall control over the whole indoor space can be solved, unnecessary excessive ventilation or refrigeration / heating is avoided on the premise that the air conditioning requirement and reference data are accurately analyzed, and therefore energy waste is reduced.

Description

Technical Field

[0001] The present application relates to the technical field of indoor air supply control, and in particular to an indoor air conditioning method and system based on variable air volume control. Background Art

[0002] Indoor air conditioning refers to the process of regulating the indoor air by sensing the indoor air and performing corresponding control. There are many methods for indoor air conditioning in the prior art, such as manually controlling the air supply equipment to control the indoor air as a whole. However, since this method is controlled by the operator based on the operator's experience and habits, it is easy to cause problems such as low air conditioning efficiency, poor conditioning effect and energy waste.

[0003] In order to achieve more precise and efficient control, there is also control through intelligent adjustment of variable air volume. For example, the Chinese invention patent with publication number CN115419990A disclosed on December 02, 2022 a variable air volume control method for air conditioners, an air conditioning linkage control system, and a storage medium. It can achieve energy saving of air conditioning in office spaces, and also enable air conditioning in office spaces to meet the comfort needs of indoor users. However, it is similar to other intelligent adjustment methods in the prior art, and all of them have problems such as poor control efficiency and poor adjustment effect due to oversimplification of adjustment, inaccurate air conditioning requirements, and poor matching of control strategies. Summary of the invention

[0004] Based on this, it is necessary to provide an indoor air conditioning method and system based on variable air volume control that can solve the problems of low air conditioning efficiency and poor adjustment effect caused by air conditioning through the entire area, as well as poor control strategy matching and low adjustment efficiency caused by only simple adjustment methods such as air volume adjustment, in response to the above-mentioned technical problems.

[0005] The technical solution of the present invention is as follows: A method for indoor air conditioning based on variable air volume control, the method comprising: Obtain the air conditioning areas and air conditioning requirements in each real-time monitoring area within the indoor air monitoring area; Generate an adjustment data reference time according to the air conditioning demand, and obtain air conditioning reference data corresponding to the adjustment data reference time; generating an optimal air volume control strategy according to the air conditioning reference data, the air conditioning demand and the air conditioning strategy model; The air conditioning is performed on the air-conditioning area according to the optimal air volume control strategy.

[0006] Optionally, obtaining the air to-be-conditioned area in each real-time monitoring area in the indoor air monitoring area includes: Acquire the real-time detected air parameters detected by the air detection sensors in each real-time monitoring area in the indoor air monitoring area, wherein one real-time monitoring area corresponds to one real-time detected air parameter; According to the real-time detected air parameters corresponding to each of the real-time monitoring areas, the baseline air reference parameters are set based on the following formula: ; in, is the reference air parameter at time point ts, To monitor the number of areas in real time, Real-time detection of air parameters for the x-th real-time monitoring area at time point ts; According to the baseline air reference parameters, the air fluctuation coefficient is set based on the following formula: ; in, is the air fluctuation coefficient at time point ts, To monitor the number of areas in real time, is the real-time detection air parameter of the x-th real-time monitoring area at time point ts, is the reference air parameter at time point ts; The area to be conditioned air is screened out according to the real-time detected air parameters, the baseline air reference parameters and the air fluctuation coefficient.

[0007] Optionally, obtaining the air to-be-conditioned area in each real-time monitoring area in the indoor air monitoring area includes: Acquire a selected area from each real-time monitoring area in the indoor air monitoring area; Set the selected area as the air conditioning area.

[0008] Optionally, the air conditioning demand includes an adjustment demand time and a target area demand parameter; The adjustment data reference time includes a plurality of reference data extraction time periods; The air conditioning reference data includes target area reference data and adjacent area reference data; Generating an adjustment data reference time according to the air conditioning demand, and acquiring air conditioning reference data corresponding to the adjustment data reference time, including: Filtering similar parameters of the target area from historical air conditioning data of the air conditioning area according to the target area demand parameters; Acquire similar parameter time points of similar parameters of the target area, and generate a reference data extraction time period according to the similar parameter time points and the adjustment requirement time; Extracting data from the historical air conditioning data according to the reference data extraction time period, and acquiring a historical conditioning reference data segment, wherein one reference data extraction time period corresponds to one historical conditioning reference data segment; The adjacent area reference data is extracted from the adjacent area historical adjustment data corresponding to the adjacent air monitoring area according to the historical adjustment reference data segment.

[0009] Optionally, the air conditioning reference data includes estimated parameter data of the area to be conditioned and adjacent area parameter data corresponding to the adjacent air monitoring area; The estimated parameter data includes estimated target area parameter values ​​corresponding to each sampling time point; The adjacent region parameter data includes estimated adjacent region parameter values ​​corresponding to each sampling time point; The air conditioning requirements also include adjacent area maintenance parameters; Generating an optimal air volume control strategy according to the air conditioning reference data, the air conditioning demand and the air conditioning strategy model, including: Setting a sampling time interval according to the adjustment requirement time, and setting a sampling time point according to the sampling time interval; Extracting a target area sampling value from the target area reference data according to the sampling time point, and extracting an adjacent area sampling value from the adjacent area reference data according to the sampling time point; Generating an estimated target area parameter value corresponding to each sampling time point according to the target area sampling value corresponding to each target area reference data, wherein one sampling time point corresponds to one estimated target area parameter value; Generating estimated adjacent region parameter values ​​corresponding to each sampling time point according to the adjacent region sampling values ​​corresponding to each adjacent region reference data, wherein one sampling time point corresponds to one estimated adjacent region parameter value; Iterating the air conditioning strategy model according to each estimated target area parameter value, each estimated adjacent area parameter value and adjacent area maintenance parameter and generating an optimal adjustment factor; An optimal air volume control strategy is generated according to the control adjustment parameters corresponding to the optimal adjustment factor.

[0010] Optionally, the estimated target area parameter value corresponding to any target sampling point at each sampling time point is generated based on the following formula: ; in, is the estimated target area parameter value corresponding to the target sampling point, m is the number of reference data of each target area, is the target area sampling value corresponding to the rth target area reference data at the target sampling point.

[0011] Optionally, iterating the air conditioning strategy model according to each estimated target area parameter value, the estimated adjacent area parameter value and the adjacent area maintenance parameter and generating an optimal adjustment factor comprises: Acquiring air conditioning restriction conditions, wherein the air conditioning restriction conditions include air supply angle restriction conditions, maximum flow restriction conditions, and air supply temperature restriction conditions; The air conditioning strategy model is iterated according to the air supply angle restriction condition, the maximum flow restriction condition, the air supply temperature restriction condition, each estimated target area parameter value, each estimated adjacent area parameter value and the adjacent area maintenance parameter to generate the optimal adjustment factor.

[0012] Optionally, obtain air conditioning restriction conditions, including: Obtaining pre-stored original air conditioning restriction conditions; The real-time adjustment limiting condition at the current moment is acquired, and the air conditioning limiting condition is generated according to the real-time adjustment limiting condition and the air conditioning original limiting condition.

[0013] Optionally, the air conditioning strategy model is as follows: , , Among them, S is the air conditioning optimization factor, To adjust the demand time, is the target area adjustment coefficient, is the estimated target area parameter value at time t in the estimated parameter data, is the target area demand parameter, is the adjacent area adjustment coefficient corresponding to the i-th adjacent air monitoring area, is the estimated adjacent region parameter value at time t in the adjacent region parameter data, Maintain the parameters for the adjacent areas corresponding to the i-th adjacent air monitoring area, is the energy consumption adjustment coefficient, is the air supply energy consumption regulation model, M is the number of air supply outlets in the indoor air monitoring area, is the fan energy consumption coefficient, is the air volume of the jth air outlet at time point t, is the preset fan energy consumption coefficient, is the heating energy consumption coefficient, is the air supply temperature of the jth air supply outlet at time point t, is the reference temperature rise, is the first angle adjustment coefficient, is the air supply angle of the jth air outlet at time point t, is the air supply angle of the jth air outlet at time point t-1, is the second angle adjustment coefficient, is the original air supply angle of the jth air outlet.

[0014] Optionally, an indoor air conditioning system based on variable air volume control is also provided, the system comprising: An air conditioning demand acquisition module is used to obtain the air conditioning area and air conditioning demand in each real-time monitoring area in the indoor air monitoring area; A reference adjustment data acquisition module, used to generate an adjustment data reference time according to the air conditioning demand, and obtain air conditioning reference data corresponding to the adjustment data reference time; An optimal air volume strategy generation module, used to generate an optimal air volume control strategy according to the air conditioning reference data, the air conditioning demand and the air conditioning strategy model; The optimal air volume control execution module is used to perform air conditioning on the air-conditioned area according to the optimal air volume control strategy.

[0015] Optionally, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned indoor air conditioning method based on variable air volume control when executing the computer program.

[0016] Optionally, a computer-readable storage medium is also provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the indoor air conditioning method based on variable air volume control are implemented.

[0017] The technical effects achieved by the present invention are as follows: The above-mentioned indoor air conditioning method and system based on variable air volume control obtains the air areas to be conditioned and the air conditioning requirements in each real-time monitoring area in the indoor air monitoring area; generates a conditioning data reference time according to the air conditioning requirements, and obtains the air conditioning reference data corresponding to the conditioning data reference time; generates an optimal air volume control strategy according to the air conditioning reference data, the air conditioning requirements and the air conditioning strategy model; and air conditions the air areas to be conditioned according to the optimal air volume control strategy. In order to meet the different air demands of different indoor areas, various real-time monitoring areas are set up in advance in the indoor air monitoring area, so that the small areas of each real-time monitoring area under the large area of ​​the indoor monitoring area can be controlled separately, so as to adjust the wind volume and air in each area according to actual needs, reduce energy consumption, and avoid the problems of low air conditioning efficiency and energy waste caused by the overall control of the entire indoor room in the prior art; in addition, users in different areas may have different preferences for air parameters such as temperature and humidity. By setting up multiple real-time monitoring areas for zone control, personalized adjustments can be made according to specific needs to improve overall comfort. In this way, by obtaining the air to-be-adjusted areas and air conditioning needs in each real-time monitoring area in the indoor air monitoring area, adjustments can be made according to the needs of different areas. During the adjustment, the air conditioning needs are determined according to the air conditioning needs. Generate an adjustment data reference time, and obtain the air conditioning reference data corresponding to the adjustment data reference time, so as to obtain reference data according to different needs, so as to provide more accurate reference data for more accurate regulation, and finally generate an optimal air volume control strategy according to the air conditioning reference data, the air conditioning demand and the air conditioning strategy model, and finally perform air conditioning on the air area to be conditioned according to the optimal air volume control strategy, and then pre-define the monitoring area, select the reference data according to the adjustment demand, and then iterate and calculate the preset air conditioning strategy model, and finally generate an optimal air volume control strategy that matches the current air area to be conditioned and the corresponding air conditioning demand, so as to avoid unnecessary excessive ventilation or cooling / heating on the premise of accurately analyzing the air conditioning demand and reference data, thereby reducing energy waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a flow chart of an indoor air conditioning method based on variable air volume control in one embodiment; Figure 2 FIG. 4 is a structural block diagram of an indoor air conditioning system based on variable air volume control in one embodiment. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0020] In one embodiment, a terminal is provided, which is used to: obtain the air areas to be conditioned and the air conditioning requirements in each real-time monitoring area in the indoor air monitoring area; generate an adjustment data reference time according to the air conditioning requirements, and obtain air conditioning reference data corresponding to the adjustment data reference time; generate an optimal air volume control strategy according to the air conditioning reference data, the air conditioning requirements and an air conditioning strategy model; and perform air conditioning on the air areas to be conditioned according to the optimal air volume control strategy.

[0021] The terminal may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and portable wearable devices.

[0022] In one embodiment, Figure 1 As shown, a method for indoor air conditioning based on variable air volume control is provided, the method comprising: Step S100: obtaining the air to-be-conditioned areas and air conditioning requirements in each real-time monitoring area within the indoor air monitoring area; Step S200: generating an adjustment data reference time according to the air conditioning demand, and acquiring air conditioning reference data corresponding to the adjustment data reference time; Step S300: generating an optimal air volume control strategy according to the air conditioning reference data, the air conditioning demand and the air conditioning strategy model; Step S400: performing air conditioning on the air-conditioned area according to the optimal air volume control strategy.

[0023] In the present application, in order to meet the different air demands of different indoor areas, various real-time monitoring areas are set up in advance in the indoor air monitoring area, so that the small areas of each real-time monitoring area under the large area of ​​the indoor monitoring area can be controlled separately, so as to adjust the wind volume and air of each area according to actual needs, reduce energy consumption, and avoid the problems of low air conditioning efficiency and energy waste caused by the overall control of the entire indoor room in the prior art; in addition, users in different areas may have different preferences for air parameters such as temperature and humidity. By setting up multiple real-time monitoring areas for zone control, personalized adjustment can be made according to specific needs to improve the overall comfort. In this way, by obtaining the air to-be-adjusted areas and air conditioning demands in each real-time monitoring area in the indoor air monitoring area, adjustments can be made according to the needs of different areas. During the adjustment, according to the air conditioning The control system generates an adjustment data reference time according to the adjustment data demand, and obtains the air conditioning reference data corresponding to the adjustment data reference time, so as to obtain the reference data according to different demands, so as to provide more accurate reference data for more accurate regulation, and finally generates the optimal air volume control strategy according to the air conditioning reference data, the air conditioning demand and the air conditioning strategy model, and finally performs air conditioning on the air area to be conditioned according to the optimal air volume control strategy, and then pre-defines the monitoring area, selects the reference data according to the adjustment demand, and then iterates and calculates the preset air conditioning strategy model, and finally generates the optimal air volume control strategy that matches the current air area to be conditioned and the corresponding air conditioning demand, so as to avoid unnecessary over-ventilation or cooling / heating on the premise of accurately analyzing the air conditioning demand and the reference data, thereby reducing energy waste.

[0024] In one embodiment, in step S100, obtaining the air conditioning area in each real-time monitoring area in the indoor air monitoring area includes: Step S111: obtaining real-time detected air parameters detected by air detection sensors in each real-time monitoring area in the indoor air monitoring area, wherein one real-time monitoring area corresponds to one real-time detected air parameter; Step S112: according to the real-time detected air parameters corresponding to each of the real-time monitoring areas, a baseline air reference parameter is set based on the following formula: ; in, is the reference air parameter at time point ts, To monitor the number of areas in real time, Real-time detection of air parameters for the x-th real-time monitoring area at time point ts; Step S113: According to the baseline air reference parameter, the air fluctuation coefficient is set based on the following formula: ; in, is the air fluctuation coefficient at time point ts, To monitor the number of areas in real time, is the real-time detection air parameter of the x-th real-time monitoring area at time point ts, is the reference air parameter at time point ts; Step S114: Filter out the area to be conditioned air according to the real-time detected air parameters, the baseline air reference parameters and the air fluctuation coefficient.

[0025] In this embodiment, in order to ensure that abnormal positions can be accurately identified under different environmental conditions, the detection standard is dynamically adjusted through the detected real-time data, that is, the baseline air reference parameters are dynamically set and the air fluctuation coefficient is further dynamically set, which solves the problem in the prior art that the abnormality is judged by using a fixed threshold, which leads to the inability to adapt to the changes in the overall air quality level under different time periods or environmental conditions. First, the real-time detection air parameters detected by the air detection sensors in each pre-demarcated real-time monitoring area in the indoor air monitoring area are obtained. The real-time monitoring area is pre-set to multiple, and the area size of each real-time monitoring area is generally different. The number and type of air detection sensors in real-time monitoring areas of different sizes are multiple, and the air detection sensor includes one or more of a carbon dioxide detection sensor, a smoke detection sensor, and a temperature and humidity detection sensor. That is, one or more sensors for detecting air quality can be set in the real-time monitoring area. Then, the baseline air reference parameters are set according to the real-time detection air parameters corresponding to each of the real-time monitoring areas. It reflects the average level of the overall air parameters of each real-time monitoring area in the air monitoring area. Compared with the fixed threshold in the prior art, It will be adaptively adjusted with time and environmental changes, so that it can better adapt to the air changes in the overall area caused by different environmental changes. Then, the air fluctuation coefficient is set according to the reference air reference parameter to achieve the generation of the air fluctuation coefficient at different time points ts. To indicate the degree of deviation between each real-time monitoring area and the overall average level. Furthermore, the air conditioning area is selected based on each of the real-time detected air parameters, the baseline air reference parameters and the air fluctuation coefficient.

[0026] Among them, when judging When, or judge When the air quality of the x-th real-time monitoring area is determined to be abnormal, the x-th real-time monitoring area is screened as the air to be conditioned area.

[0027] Therefore, by monitoring the air in each real-time monitoring area separately and dynamically adjusting the reference parameters, a more accurate and automatic screening of the air conditioning areas that need to be adjusted can be achieved.

[0028] In one embodiment, in step S100, obtaining the air conditioning area in each real-time monitoring area in the indoor air monitoring area includes: Step S121: obtaining an area selected from each real-time monitoring area in the indoor air monitoring area; Step S122: setting the selected area as the air conditioning area.

[0029] In this embodiment, in order to meet the air conditioning needs of different areas in the indoor air monitoring area, the indoor personnel select from each real-time monitoring area. For example, the terminal displays each real-time monitoring area in the indoor air monitoring area, and then the indoor personnel demarcate the area to be conditioned from each real-time monitoring area displayed by the terminal, which is the air conditioning area.

[0030] In another embodiment, after the air-conditioning area is set by the indoor active person, other real-time monitoring areas outside the air-conditioning area can continue to be monitored and further set as air-conditioning areas according to steps S111-S114. It should be understood that there is more than one air-conditioning area, and there can be multiple air-conditioning areas at the same time. For example, when multiple indoor active persons simultaneously select different air-conditioning areas from the real-time monitoring area, or multiple air-conditioning areas are simultaneously screened out according to the method of steps S111-S114.

[0031] In one embodiment, the air conditioning demand includes an adjustment demand time and a target area demand parameter; The adjustment data reference time includes a plurality of reference data extraction time periods; The air conditioning reference data includes target area reference data and adjacent area reference data; In step S200, generating an adjustment data reference time according to the air conditioning demand, and acquiring air conditioning reference data corresponding to the adjustment data reference time, including: Step S210: Filtering out target area similar parameters from historical air conditioning data of the air conditioning area according to the target area demand parameters; Step S220: acquiring similar parameter time points of similar parameters of the target area, and generating a reference data extraction time period according to the similar parameter time points and the adjustment requirement time; Step S230: extracting data from the historical air conditioning data according to the reference data extraction time period, and obtaining a historical conditioning reference data segment, wherein one reference data extraction time period corresponds to one historical conditioning reference data segment; Step S240: extracting adjacent area reference data from adjacent area historical adjustment data corresponding to adjacent air monitoring areas according to the historical adjustment reference data segment.

[0032] In this embodiment, the adjustment requirement time is a time period. For example, when the adjustment requirement time is set to 2 minutes, it means that the air area to be conditioned needs to be regulated within 2 minutes to achieve the target area demand parameters. The target area demand parameters are the regulation parameters that need to be achieved. In order to estimate the changes in the parameters that need to be adjusted in the air area to be conditioned within the adjustment requirement time, it is necessary to obtain historical data as a reference. Specifically, similar parameters of the target area are first screened out from the historical air conditioning data of the air area to be conditioned according to the target area demand parameters, and then similar parameter time points of similar parameters of the target area are obtained, and a reference data extraction time period is generated based on the similar parameter time points and the adjustment requirement time. For example, the target area demand parameter is a first temperature value, that is, it is necessary to adjust the temperature to achieve the purpose of adjusting the temperature and humidity in the area and then adjusting the air quality. First, the target area similarity parameters matching the first temperature value are screened out from the historical air conditioning data of the air conditioning area to be conditioned. The target area similarity parameters are values ​​with a small deviation from the first temperature value, that is, the target area similarity parameters are set according to the target area demand parameters. For example, when the first temperature value is 26°C, the target area similarity parameters are all temperature values ​​within 25.8°C-26.5°C. Since the target area similarity parameters are close to the first temperature value, the deviation for human body induction can be ignored. This setting improves the data reference without affecting comfort. In this way, the data related to the target area demand parameters can be screened out to improve the accuracy of the reference. Next, the time point corresponding to the similar parameters of the target area is obtained, that is, the similar parameter time point, that is, tex. At this time, the time point tex is used as the starting point to extend forward to the same time as the adjustment requirement time to generate a time period, which is the reference data extraction time period. At this time, the number of the reference data extraction time periods is multiple. Further, data is extracted from the historical air conditioning data according to the reference data extraction time period, and a historical adjustment reference data segment is obtained, wherein one reference data extraction time period corresponds to one historical adjustment reference data segment, so that the historical adjustment data with the same adjustment parameters as the current required can be obtained. Finally, according to the historical adjustment reference data segment, the adjacent area reference data is extracted from the adjacent area historical adjustment data corresponding to the adjacent air monitoring area. The adjacent air monitoring area is the area adjacent to the air to be adjusted area. By obtaining the adjacent area reference data, the influence of the previous adjustment of the air to be adjusted area on the adjacent area can be obtained, thereby providing data reference for the influence on the adjacent area when the air is currently adjusted.

[0033] In one embodiment, the air conditioning reference data includes estimated parameter data of the air to be conditioned area and adjacent area parameter data corresponding to the adjacent air monitoring area; The estimated parameter data includes estimated target area parameter values ​​corresponding to each sampling time point; The adjacent region parameter data includes estimated adjacent region parameter values ​​corresponding to each sampling time point; The air conditioning requirements also include adjacent area maintenance parameters; Step S300: generating an optimal air volume control strategy according to the air conditioning reference data, the air conditioning demand and the air conditioning strategy model, including: Step S310: setting a sampling time interval according to the adjustment requirement time, and setting a sampling time point according to the sampling time interval; Step S320: extracting a target area sampling value from the target area reference data according to the sampling time point, and extracting an adjacent area sampling value from the adjacent area reference data according to the sampling time point; Step S330: generating an estimated target area parameter value corresponding to each sampling time point according to the target area sampling value corresponding to each target area reference data, wherein one sampling time point corresponds to one estimated target area parameter value; Step S340: generating an estimated adjacent region parameter value corresponding to each sampling time point according to the adjacent region sampling values ​​corresponding to each adjacent region reference data, wherein one sampling time point corresponds to one estimated adjacent region parameter value; Step S350: iterating the air conditioning strategy model according to each estimated target area parameter value, each estimated adjacent area parameter value and adjacent area maintenance parameter and generating an optimal adjustment factor; Step S360: generating an optimal air volume control strategy according to the control adjustment parameters corresponding to the optimal adjustment factor.

[0034] In one embodiment, in step S330, the estimated target area parameter value corresponding to any target sampling point at each sampling time point is generated based on the following formula: ; in, is the estimated target area parameter value corresponding to the target sampling point, m is the number of reference data of each target area, is the target area sampling value corresponding to the rth target area reference data at the target sampling point.

[0035] In this embodiment, in order to obtain reference data that is beneficial to subsequent air control based on historical data, the sampling time interval is first set according to the adjustment demand time, and the sampling time point is set according to the sampling time interval, and then the target area sampling value is extracted from the target area reference data according to the sampling time point, and the adjacent area sampling value is extracted from the adjacent area reference data according to the sampling time point. It should be understood that the number of the target area reference data is multiple, and each of the target area reference data corresponds to multiple target area sampling values. Similarly, each of the adjacent area reference data also corresponds to multiple adjacent area sampling values.

[0036] For example, if the target area sampling values ​​corresponding to the three target area reference data are three sequences, then for the formula in step S330, m is 3, and the three sequences are respectively recorded as the first sequence, the second sequence and the third sequence, and the first sequence, the second sequence and the third sequence are respectively represented by {P11, P12, P13, P14, P15}, {P21, P22, P23, P24, P25} and {P31, P32, P33, P34, P35}. It can be seen that the first sequence, the second sequence and the third sequence correspond to 5 sampling time points respectively. If the target sampling point is the third, the target area sampling values ​​corresponding to the 1st to 3rd target area reference data at the target sampling point are P13, P23 and P33 respectively. Substituting them into the formula can obtain the target area sampling value. Similarly, the values ​​of other sampling time points and the adjacent area sampling values ​​are set by the same method. Those skilled in the art should understand how to calculate, so this application will not repeat them. Therefore, the above method can be used to generate the estimated target area parameter value corresponding to each sampling time point according to the target area sampling value corresponding to each target area reference data, and generate the estimated adjacent area parameter value corresponding to each sampling time point according to the adjacent area sampling value corresponding to each adjacent area reference data, so that the estimated data within the adjustment demand time of the air conditioning to be performed can be obtained according to the historical data. Then, the air conditioning strategy model is iterated according to each estimated target area parameter value, each estimated adjacent area parameter value and adjacent area maintenance parameter and the optimal adjustment factor is generated. Finally, the optimal air volume control strategy is generated according to the control adjustment parameter corresponding to the optimal adjustment factor, so as to obtain the historical data as a reference according to the current demand and as the reference data required for adjustment in the future, and then the data simulation and iteration are performed to obtain the optimal air conditioning strategy.

[0037] In one embodiment, step S350: iterating the air conditioning strategy model according to each estimated target area parameter value, the estimated adjacent area parameter value and the adjacent area maintenance parameter and generating an optimal adjustment factor includes: Step S351: obtaining air conditioning restriction conditions, wherein the air conditioning restriction conditions include air supply angle restriction conditions, maximum flow restriction conditions and air supply temperature restriction conditions; Step S352: Iterate the air conditioning strategy model according to the air supply angle restriction condition, the maximum flow restriction condition, the air supply temperature restriction condition, each estimated target area parameter value, each estimated adjacent area parameter value and the adjacent area maintenance parameter to generate the optimal adjustment factor.

[0038] In this embodiment, in order to comply with the current indoor air supply hardware adjustment, it is necessary to consider the restriction adjustment when setting the optimal control strategy. Specifically, the air conditioning restriction conditions are first obtained, wherein the air conditioning restriction conditions include air supply angle restriction conditions, maximum flow restriction conditions and air supply temperature restriction conditions, and then the air conditioning strategy model is iterated according to the air supply angle restriction conditions, maximum flow restriction conditions, air supply temperature restriction conditions, each estimated target area parameter value, estimated adjacent area parameter value and adjacent area maintenance parameter to generate the optimal adjustment factor.

[0039] The air supply angle restriction condition is due to the physical adjustment limitation of each air supply outlet, so the air supply outlet can only swing within a certain angle range, such as 0 to 40 degrees up and down. In addition, in order to ensure the comfort of the user, in the case where there are people in the room, or for objects that cannot be directly blown with cold air / warm air, the air supply angle is detected in advance, and the detected air supply angle is added to the air supply angle restriction condition to prevent the air from the air supply outlet from blowing directly on people or objects.

[0040] The maximum flow limit condition refers to the maximum flow that the fan / pipeline / valve equipment related to the air supply outlet can provide. Generally speaking, the maximum flow limit condition is less than the theoretical maximum flow to ensure that the air supply outlet is not continuously in the highest load working state, further ensuring that the air supply outlet can continue to work and improve its service life.

[0041] The air supply temperature restriction condition is due to the limitation of the indoor air supply outlet by factors such as the cooling / heating capacity and the unit operating conditions, and cannot be arbitrarily higher or lower than a certain threshold. For example, the lowest air supply temperature for the chilled water coil is 15°C, and the highest air supply temperature for the electric heating / hot water coil is 35°C.

[0042] In addition, air conditioning restrictions may also include humidity requirements, noise restrictions to avoid excessive noise when the air volume is too large, air outlet adjustment speed, indoor door and window status, emergency stop / fire safety and other actual engineering adjustments, of course, corresponding simulation operations need to be added to the model. In this case, technicians in this field can adjust the settings according to actual needs, and this application does not make specific restrictions.

[0043] In one embodiment, in step S351, obtaining air conditioning restriction conditions includes: Step S3511: obtaining pre-stored original air conditioning restriction conditions; Step S3512: Acquire the real-time adjustment restriction condition at the current moment, and generate the air conditioning restriction condition according to the real-time adjustment restriction condition and the air conditioning original restriction condition.

[0044] In this embodiment, in order to ensure the flexible setting of restriction conditions, on the one hand, the original existing conditions are obtained, specifically, the pre-stored original air conditioning restriction conditions are obtained; on the other hand, the real-time settings are obtained, specifically, the real-time adjustment restriction conditions at the current moment are obtained. Air conditioning restriction conditions are generated according to the real-time adjustment restriction conditions and the original air conditioning restriction conditions. The real-time adjustment restriction conditions are generally added by users who actually need air conditioning. Therefore, this method is used to achieve flexible setting of restriction conditions and improve the comfort of air conditioning.

[0045] In one embodiment, the air conditioning strategy model is as follows: , , Among them, S is the air conditioning optimization factor, To adjust the demand time, is the target area adjustment coefficient, is the estimated target area parameter value at time t in the estimated parameter data, is the target area demand parameter, is the adjacent area adjustment coefficient corresponding to the i-th adjacent air monitoring area, is the estimated adjacent region parameter value at time t in the adjacent region parameter data, Maintain the parameters for the adjacent areas corresponding to the i-th adjacent air monitoring area, is the energy consumption adjustment coefficient, is the air supply energy consumption regulation model, M is the number of air supply outlets in the indoor air monitoring area, is the fan energy consumption coefficient, is the air volume of the jth air outlet at time point t, is the preset fan energy consumption coefficient, is the heating energy consumption coefficient, is the air supply temperature of the jth air supply outlet at time point t, is the reference temperature rise, is the first angle adjustment coefficient, is the air supply angle of the jth air outlet at time point t, is the air supply angle of the jth air outlet at time point t-1, is the second angle adjustment coefficient, is the original air supply angle of the jth air outlet.

[0046] In this embodiment, the air conditioning optimization factor is used to indicate the degree of optimization of the air conditioning strategy. The smaller the air conditioning optimization factor is, the higher the degree of optimization is. When calculating the air conditioning optimization factor, firstly, and To represent the proportion of the air conditioning area and the adjacent air monitoring area in the air conditioning strategy, It indicates the proportion of energy consumption in the entire regulation optimization. , and They represent the proportion of fan energy consumption, heating energy consumption and air supply angle in the control optimization. To express the difference between the estimated target area parameter value at each time t in the air monitoring area during the adjustment demand time and the target area demand parameter to be achieved, the difference is amplified by square calculation. To represent the difference between the possible change values ​​of other adjacent air monitoring areas other than the air monitoring area and the parameters of the adjacent areas to be maintained, the difference is also amplified by square calculation. The overall time integral represents the entire control evaluation within the adjustment demand time from 0 to Tf, and finally by calculating To indicate the energy consumption caused by the air volume, air temperature and angle adjustment of the air outlet during the air supply process.

[0047] The specific values ​​of the target area adjustment coefficient, target area demand parameter, energy consumption adjustment coefficient, fan energy consumption coefficient, heating energy consumption coefficient, and first angle adjustment coefficient can be set by technical personnel in this field according to actual production. This application does not make specific limitations or examples, as long as air conditioning can be achieved.

[0048] Specifically, for , through the preset fan energy consumption coefficient And calculate To express the influence of air volume on energy consumption, by calculating To indicate that the temperature should be changed from Control to The energy consumption is calculated by To express the effect of the difference in air supply angle on energy consumption, by calculating To express the influence of the absolute value of the air supply angle deviating from the reference angle on energy consumption. In the process, , , , are all uncertain values, so simulation calculation is required, that is, in step S352, the first step is to substitute the air supply angle restriction condition, the maximum flow restriction condition, the air supply temperature restriction condition, the estimated target area parameter value, the estimated adjacent area parameter value and the adjacent area maintenance parameter into the air conditioning strategy model; the second step is to calculate the air supply energy consumption adjustment model , , , Simulation calculations of multiple values ​​are performed separately, and an estimated adjustment factor can be obtained for each simulation calculation; the third step is to select the estimated adjustment factor with the smallest value from each estimated adjustment factor, set the smallest estimated adjustment factor as the optimal adjustment factor, and generate an optimal air volume control strategy according to the control adjustment parameters corresponding to the optimal adjustment factor, and control the air supply outlet according to the optimal air volume control strategy.

[0049] In one embodiment, Figure 2 As shown, an indoor air conditioning system based on variable air volume control is also provided, the system comprising: An air conditioning demand acquisition module is used to obtain the air conditioning area and air conditioning demand in each real-time monitoring area in the indoor air monitoring area; A reference adjustment data acquisition module, used to generate an adjustment data reference time according to the air conditioning demand, and obtain air conditioning reference data corresponding to the adjustment data reference time; An optimal air volume strategy generation module, used to generate an optimal air volume control strategy according to the air conditioning reference data, the air conditioning demand and the air conditioning strategy model; The optimal air volume control execution module is used to perform air conditioning on the air-conditioned area according to the optimal air volume control strategy.

[0050] In one embodiment, the air conditioning demand acquisition module is further used to: obtain the real-time detected air parameters detected by the air detection sensors in each real-time monitoring area in the indoor air monitoring area, wherein one real-time monitoring area corresponds to one real-time detected air parameter; and set the benchmark air reference parameter based on the following formula according to the real-time detected air parameters corresponding to each real-time monitoring area: ; in, is the reference air parameter at time point ts, To monitor the number of areas in real time, The real-time detection air parameters of the x-th real-time monitoring area at time point ts; according to the baseline air reference parameters, the air fluctuation coefficient is set based on the following formula: ; in, is the air fluctuation coefficient at time point ts, To monitor the number of areas in real time, is the real-time detection air parameter of the x-th real-time monitoring area at time point ts, is the baseline air reference parameter at time point ts; and the air area to be conditioned is screened out according to each of the real-time detected air parameters, the baseline air reference parameter and the air fluctuation coefficient.

[0051] In one embodiment, the air conditioning demand acquisition module is further used to: acquire an area selected from each real-time monitoring area in the indoor air monitoring area; and set the selected area as the air conditioning area.

[0052] In one embodiment, the air conditioning demand includes an adjustment demand time and a target area demand parameter; the adjustment data reference time includes multiple reference data extraction time periods; the air conditioning reference data includes target area reference data and adjacent area reference data; the reference adjustment data acquisition module is also used to: filter out similar parameters of the target area from the historical air conditioning data of the air area to be adjusted according to the target area demand parameters; obtain similar parameter time points of similar parameters of the target area, and generate a reference data extraction time period according to the similar parameter time points and the adjustment demand time; extract data from the historical air conditioning data according to the reference data extraction time period, and obtain a historical adjustment reference data segment, wherein one reference data extraction time period corresponds to one historical adjustment reference data segment; extract adjacent area reference data from the adjacent area historical adjustment data corresponding to the adjacent air monitoring area according to the historical adjustment reference data segment.

[0053] In one embodiment, the air conditioning reference data includes estimated parameter data of the air area to be conditioned and adjacent area parameter data corresponding to the adjacent air monitoring area; the estimated parameter data includes estimated target area parameter values ​​corresponding to each sampling time point; the adjacent area parameter data includes estimated adjacent area parameter values ​​corresponding to each sampling time point; the air conditioning demand also includes adjacent area maintenance parameters; the optimal air volume strategy generation module is also used to: set a sampling time interval according to the adjustment demand time, and set a sampling time point according to the sampling time interval; extract the target area sampling value from the target area reference data according to the sampling time point, and extract the target area sampling value from the adjacent area according to the sampling time point Extract adjacent area sampling values ​​from the reference data; generate estimated target area parameter values ​​corresponding to each sampling time point according to the target area sampling values ​​corresponding to each target area reference data, wherein one sampling time point corresponds to one estimated target area parameter value; generate estimated adjacent area parameter values ​​corresponding to each sampling time point according to the adjacent area sampling values ​​corresponding to each adjacent area reference data, wherein one sampling time point corresponds to one estimated adjacent area parameter value; iterate the air conditioning strategy model according to each estimated target area parameter value, each estimated adjacent area parameter value and adjacent area maintenance parameter and generate an optimal adjustment factor; generate an optimal air volume control strategy according to the control adjustment parameter corresponding to the optimal adjustment factor.

[0054] In one embodiment, the optimal air volume strategy generation module is further used to generate an estimated target area parameter value corresponding to any target sampling point at each sampling time point based on the following formula: ; in, is the estimated target area parameter value corresponding to the target sampling point, m is the number of reference data of each target area, is the target area sampling value corresponding to the rth target area reference data at the target sampling point.

[0055] In one embodiment, the optimal air volume strategy generation module is also used to: obtain air conditioning restriction conditions, wherein the air conditioning restriction conditions include air supply angle restriction conditions, maximum flow restriction conditions and air supply temperature restriction conditions; iterate the air conditioning strategy model according to the air supply angle restriction conditions, maximum flow restriction conditions, air supply temperature restriction conditions, each estimated target area parameter value, each estimated adjacent area parameter value and adjacent area maintenance parameters and generate the optimal adjustment factor.

[0056] In one embodiment, the optimal air volume strategy generation module is also used to: obtain pre-stored original air conditioning restriction conditions; obtain real-time adjustment restriction conditions at the current moment, and generate air conditioning restriction conditions based on the real-time adjustment restriction conditions and the original air conditioning restriction conditions.

[0057] In one embodiment, the optimal air volume strategy generation module is further used to execute an air conditioning strategy model, and the air conditioning strategy model is as follows: , , Among them, S is the air conditioning optimization factor, To adjust the demand time, is the target area adjustment coefficient, is the estimated target area parameter value at time t in the estimated parameter data, is the target area demand parameter, is the adjacent area adjustment coefficient corresponding to the i-th adjacent air monitoring area, is the estimated adjacent region parameter value at time t in the adjacent region parameter data, Maintain the parameters for the adjacent areas corresponding to the i-th adjacent air monitoring area, is the energy consumption adjustment coefficient, is the air supply energy consumption regulation model, M is the number of air supply outlets in the indoor air monitoring area, is the fan energy consumption coefficient, is the air volume of the jth air outlet at time point t, is the preset fan energy consumption coefficient, is the heating energy consumption coefficient, is the air supply temperature of the jth air supply outlet at time point t, is the reference temperature rise, is the first angle adjustment coefficient, is the air supply angle of the jth air outlet at time point t, is the air supply angle of the jth air outlet at time point t-1, is the second angle adjustment coefficient, is the original air supply angle of the jth air outlet.

[0058] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the indoor air conditioning method based on variable air volume control when executing the computer program.

[0059] In one embodiment, a computer-readable storage medium is further provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the indoor air conditioning method based on variable air volume control are implemented.

[0060] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0061] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0062] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for indoor air conditioning based on variable air volume control, characterized in that: The method comprises: Obtain the air conditioning areas and air conditioning requirements in each real-time monitoring area within the indoor air monitoring area; Generate an adjustment data reference time according to the air conditioning demand, and obtain air conditioning reference data corresponding to the adjustment data reference time; generating an optimal air volume control strategy according to the air conditioning reference data, the air conditioning demand and the air conditioning strategy model; Performing air conditioning on the air-conditioning area according to the optimal air volume control strategy; Obtain the air conditioning area in each real-time monitoring area within the indoor air monitoring area, including: Acquire the real-time detected air parameters detected by the air detection sensors in each real-time monitoring area in the indoor air monitoring area, wherein one real-time monitoring area corresponds to one real-time detected air parameter; According to the real-time detected air parameters corresponding to each of the real-time monitoring areas, the baseline air reference parameters are set based on the following formula: ； in, is the reference air parameter at time point ts, To monitor the number of areas in real time, Real-time detection of air parameters for the x-th real-time monitoring area at time point ts; According to the baseline air reference parameters, the air fluctuation coefficient is set based on the following formula: ； in, is the air fluctuation coefficient at time point ts; The area to be conditioned air is screened out according to the real-time detected air parameters, the baseline air reference parameters and the air fluctuation coefficient.

2. The indoor air conditioning method based on variable air volume control according to claim 1, characterized in that: Obtain the air conditioning area in each real-time monitoring area within the indoor air monitoring area, including: Acquire a selected area from each real-time monitoring area in the indoor air monitoring area; Set the selected area as the air conditioning area.

3. The indoor air conditioning method based on variable air volume control according to claim 1, characterized in that: The air conditioning demand includes the adjustment demand time and target area demand parameters; The adjustment data reference time includes a plurality of reference data extraction time periods; The air conditioning reference data includes target area reference data and adjacent area reference data; Generating an adjustment data reference time according to the air conditioning demand, and acquiring air conditioning reference data corresponding to the adjustment data reference time, including: Filtering similar parameters of the target area from historical air conditioning data of the air conditioning area according to the target area demand parameters; Acquire similar parameter time points of similar parameters of the target area, and generate a reference data extraction time period according to the similar parameter time points and the adjustment requirement time; Extracting data from the historical air conditioning data according to the reference data extraction time period, and acquiring a historical conditioning reference data segment, wherein one reference data extraction time period corresponds to one historical conditioning reference data segment; The adjacent area reference data is extracted from the adjacent area historical adjustment data corresponding to the adjacent air monitoring area according to the historical adjustment reference data segment.

4. The indoor air conditioning method based on variable air volume control according to claim 3, characterized in that: The air conditioning reference data includes estimated parameter data of the air to be conditioned area and adjacent area parameter data corresponding to the adjacent air monitoring area; The estimated parameter data includes estimated target area parameter values ​​corresponding to each sampling time point; The adjacent region parameter data includes estimated adjacent region parameter values ​​corresponding to each sampling time point; The air conditioning requirements also include adjacent area maintenance parameters; Generating an optimal air volume control strategy according to the air conditioning reference data, the air conditioning demand and the air conditioning strategy model, including: Setting a sampling time interval according to the adjustment requirement time, and setting a sampling time point according to the sampling time interval; Extracting a target area sampling value from the target area reference data according to the sampling time point, and extracting an adjacent area sampling value from the adjacent area reference data according to the sampling time point; Generating an estimated target area parameter value corresponding to each sampling time point according to the target area sampling value corresponding to each target area reference data, wherein one sampling time point corresponds to one estimated target area parameter value; Generating estimated adjacent region parameter values ​​corresponding to each sampling time point according to the adjacent region sampling values ​​corresponding to each adjacent region reference data, wherein one sampling time point corresponds to one estimated adjacent region parameter value; Iterate the air conditioning strategy model according to each estimated target area parameter value, each estimated adjacent area parameter value and adjacent area maintenance parameter and generate an optimal adjustment factor; An optimal air volume control strategy is generated according to the control adjustment parameters corresponding to the optimal adjustment factor.

5. The indoor air conditioning method based on variable air volume control according to claim 4, characterized in that: The estimated target area parameter value corresponding to any target sampling point at each sampling time point is generated based on the following formula: ； in, is the estimated target area parameter value corresponding to the target sampling point, m is the number of reference data of each target area, is the target area sampling value corresponding to the rth target area reference data at the target sampling point.

6. The indoor air conditioning method based on variable air volume control according to claim 4, characterized in that: The air conditioning strategy model is iterated according to each estimated target area parameter value, the estimated adjacent area parameter value and the adjacent area maintenance parameter to generate an optimal adjustment factor, including: Acquiring air conditioning restriction conditions, wherein the air conditioning restriction conditions include air supply angle restriction conditions, maximum flow restriction conditions, and air supply temperature restriction conditions; The air conditioning strategy model is iterated according to the air supply angle restriction condition, the maximum flow restriction condition, the air supply temperature restriction condition, each estimated target area parameter value, each estimated adjacent area parameter value and the adjacent area maintenance parameter to generate the optimal adjustment factor.

7. The indoor air conditioning method based on variable air volume control according to claim 6, characterized in that: Get air conditioning constraints, including: Obtaining pre-stored original air conditioning restriction conditions; The real-time adjustment limiting condition at the current moment is acquired, and the air conditioning limiting condition is generated according to the real-time adjustment limiting condition and the air conditioning original limiting condition.

8. The indoor air conditioning method based on variable air volume control according to claim 6, characterized in that: The air conditioning strategy model is as follows: ， ， Among them, S is the air conditioning optimization factor, To adjust the demand time, is the target area adjustment coefficient, is the estimated target area parameter value at time t in the estimated parameter data, is the target area demand parameter, is the adjacent area adjustment coefficient corresponding to the i-th adjacent air monitoring area, is the estimated adjacent region parameter value at time t in the adjacent region parameter data, Maintain the parameters for the adjacent areas corresponding to the i-th adjacent air monitoring area, is the energy consumption adjustment coefficient, is the air supply energy consumption regulation model, M is the number of air supply outlets in the indoor air monitoring area, is the fan energy consumption coefficient, is the air volume of the jth air outlet at time point t, is the preset fan energy consumption coefficient, is the heating energy consumption coefficient, is the air supply temperature of the jth air supply outlet at time point t, is the reference temperature rise, is the first angle adjustment coefficient, is the air supply angle of the jth air outlet at time point t, is the air supply angle of the jth air outlet at time point t-1, is the second angle adjustment coefficient, is the original air supply angle of the jth air outlet.

9. An indoor air conditioning system based on variable air volume control, characterized in that: The system comprises: An air conditioning demand acquisition module is used to obtain the air conditioning area and air conditioning demand in each real-time monitoring area in the indoor air monitoring area; A reference adjustment data acquisition module, used to generate an adjustment data reference time according to the air conditioning demand, and obtain air conditioning reference data corresponding to the adjustment data reference time; An optimal air volume strategy generation module, used to generate an optimal air volume control strategy according to the air conditioning reference data, the air conditioning demand and the air conditioning strategy model; An optimal air volume control execution module, used for performing air conditioning on the air-conditioned area according to the optimal air volume control strategy; The air conditioning demand acquisition module is also used to: acquire the real-time detected air parameters detected by the air detection sensors in each real-time monitoring area in the indoor air monitoring area, wherein one real-time monitoring area corresponds to one real-time detected air parameter; According to the real-time detected air parameters corresponding to each of the real-time monitoring areas, the baseline air reference parameters are set based on the following formula: ； in, is the reference air parameter at time point ts, To monitor the number of areas in real time, Real-time detection of air parameters for the x-th real-time monitoring area at time point ts; According to the baseline air reference parameters, the air fluctuation coefficient is set based on the following formula: ； in, is the air fluctuation coefficient at time point ts; The area to be conditioned air is screened out according to the real-time detected air parameters, the baseline air reference parameters and the air fluctuation coefficient.

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