Intelligent building air circulation energy consumption regulation method based on digital operation and maintenance

Abstract

The application discloses a smart building air circulation energy consumption regulation and control method based on digital operation and maintenance, relates to the field of intelligent regulation and control, and solves the problem that air circulation devices cannot be dynamically regulated and controlled based on changes in gas. The method comprises the following steps: collecting real-time concentrations of fixed gas at different positions at different time nodes in a smart building area; analyzing the real-time concentrations of fixed gas at different positions at different time nodes in the smart building area, and obtaining abnormal data of the fixed gas in the smart building area; analyzing required theoretical ventilation rates and natural ventilation conditions in the smart building area according to the abnormal data of the fixed gas; analyzing real-time operation states of air circulation devices in the smart building area according to ventilation data in the smart building area; and analyzing whether the air circulation devices in the working state can meet the required theoretical ventilation rates in the smart building area. The application realizes dynamic regulation and control of air circulation devices based on changes in gas.

Description

Technical Field

[0001] This invention belongs to the field of intelligent control technology, specifically a smart building air circulation energy consumption control method based on digital operation and maintenance. Background Technology

[0002] With the rapid development of technologies such as the Internet of Things, big data, and artificial intelligence, smart buildings have emerged and become the mainstream development direction of modern buildings. Smart buildings achieve high efficiency, comfort, and low carbon emissions by real-time sensing, analysis, and intelligent decision-making of multi-dimensional data such as equipment, environment, and personnel within the building.

[0003] However, most current methods for controlling air circulation devices in smart building areas rely on fixed parameters or simple feedback control. They cannot analyze the dynamic changes in gas concentration within smart building areas based on digital operation and maintenance, and thus make corresponding adjustments to the air circulation devices. At the same time, existing technologies do not consider the impact of natural ventilation conditions on gas circulation within smart building areas, which will lead to problems such as energy waste or poor gas circulation within smart building areas.

[0004] Therefore, this invention proposes a smart building air circulation energy consumption control method based on digital operation and maintenance. Summary of the Invention

[0005] The purpose of this invention is to propose a smart building air circulation energy consumption control method based on digital operation and maintenance, so as to solve the problem mentioned in the background art that the air circulation device cannot be dynamically controlled based on gas changes.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] A smart building air circulation energy consumption control method based on digital operation and maintenance, comprising the following steps:

[0008] Step S1: Collect the real-time concentration of fixed gas at different locations within the smart building area at different time points;

[0009] Step S2: Analyze the real-time concentration of fixed gases at different locations at different time points within the smart building area to obtain abnormal data of fixed gases within the smart building area.

[0010] Step S3: Analyze the required theoretical ventilation rate and natural ventilation conditions within the smart building area based on the abnormal data of the fixed gas.

[0011] Step S4: Analyze the real-time operating status of the air circulation device based on the ventilation data within the smart building area;

[0012] Step S5: Analyze whether the air circulation device in operation can meet the theoretical ventilation rate required in the smart building area.

[0013] Furthermore, the analysis process in step S2 includes the following sub-steps:

[0014] Step S21: Compare the real-time concentration of the fixed gas at different locations at different time points with the standard concentration range;

[0015] If the real-time concentration of the stationary gas at all locations at all time points is within the standard concentration range, then no operation will be performed.

[0016] If the real-time concentration of the fixed gas at any location at any time point is not within the standard concentration range, proceed to step S22.

[0017] Step S22: Record the time node corresponding to when the real-time concentration of the stationary gas does not belong to the standard concentration range as an abnormal time node, and record the position corresponding to when the real-time concentration of the stationary gas does not belong to the standard concentration range as an abnormal position.

[0018] Step S23: Count the number of abnormal time points when the real-time concentration of the stationary gas does not fall within the standard concentration range and record them as the number of abnormal time points.

[0019] Furthermore, the analysis process in step S2 also includes the following sub-steps:

[0020] Step S24: If the real-time concentration of the stationary gas does not fall within the standard concentration range and there is only one abnormal time point, then the abnormal location will be continuously monitored.

[0021] If there are multiple abnormal time points when the real-time concentration of the stationary gas does not fall within the standard concentration range, proceed to step S25.

[0022] Step S25: For the same abnormal location, subtract the real-time concentration of the fixed gas at the abnormal location at the previous time node from the real-time concentration of the fixed gas at the abnormal location at the abnormal time node to obtain the change in the real-time concentration of the fixed gas at the abnormal location at different abnormal time nodes.

[0023] Step S26: Divide the real-time concentration change of the fixed gas at the abnormal location at different abnormal time points by a fixed time interval to obtain the unit time release of the fixed gas at the abnormal location at different abnormal time points.

[0024] Step S27: Record the real-time concentration and release per unit time of the fixed gas at the abnormal location at different abnormal time points as abnormal data of fixed gas within the smart building area.

[0025] Furthermore, the analysis process in step S3 includes the following sub-steps:

[0026] Step S31: Iterate through and compare the real-time concentrations of the fixed gas at the abnormal location at different abnormal time points to obtain the maximum real-time concentration, and record the maximum real-time concentration as the real-time concentration peak.

[0027] Step S32: Record the time node corresponding to the real-time concentration peak of the fixed gas at the abnormal location as the concentration peak time node.

[0028] Step S33: Obtain the unit time release of fixed gas at the abnormal location corresponding to the concentration peak time node, obtain the outdoor concentration of fixed gas in the outdoor environment, and obtain the right endpoint value of the standard concentration range.

[0029] Step S34: Calculate the theoretical ventilation rate required within the smart building area;

[0030] Step S35: Analyze the natural ventilation conditions within the smart building area.

[0031] Furthermore, the analysis process in step S35 includes the following sub-steps:

[0032] Step S351: Measure the ventilation area at the natural ventilation openings within the smart building area, and collect the real-time air intake velocity and real-time air exhaust velocity at the natural ventilation openings at different time points.

[0033] Step S352: Divide the real-time exhaust velocity at the natural ventilation opening at different time points by the real-time intake velocity to obtain the ventilation correction coefficient at the natural ventilation opening at the corresponding time point. Add the ventilation correction coefficients at the natural ventilation opening at different time points, sum them up, and take the average value to obtain the ventilation correction factor at the natural ventilation opening.

[0034] Furthermore, the analysis process in step S35 also includes the following sub-steps:

[0035] Step S353: Multiply the real-time air intake velocity by the ventilation area and then by the ventilation correction factor at the natural ventilation opening to obtain the natural ventilation rate at the current time point.

[0036] Step S354: Sum the natural ventilation rates at different time points and take the average value to obtain the average ventilation rate at the current time point.

[0037] Step S355: Record the required theoretical ventilation rate and the average ventilation rate of the natural ventilation point at the current time point as the ventilation data of the smart building area.

[0038] Furthermore, the analysis process in step S4 includes the following sub-steps:

[0039] Step S41: Divide the real-time operating status of the air circulation device into working status and shutdown status;

[0040] Step S42: Obtain ventilation data within the smart building area and the real-time operating status of the air circulation device at the current time point;

[0041] Step S43: If the real-time operating status of the air circulation device at the current time node is working, then proceed to step S5;

[0042] Step S44: If the real-time operating status of the air circulation device is in a shutdown state at the current time node, then based on digital operation and maintenance analysis, it is necessary to change the real-time operating status of the air circulation device.

[0043] Furthermore, the analysis process in step S44 includes the following sub-steps:

[0044] Step S441: Compare the theoretical ventilation rate required within the smart building area with the average ventilation rate at the current time point at the naturally ventilated area;

[0045] If the theoretical ventilation rate required within the smart building area is less than or equal to the average ventilation rate at the current time point, no action will be taken.

[0046] If the theoretical ventilation rate required in the smart building area is greater than the average ventilation rate of the natural ventilation point at the current time point, the real-time operation status of the air circulation device is switched from the shutdown state to the working state and the process proceeds to step S442.

[0047] Step S442: Subtract the theoretical ventilation rate required within the smart building area from the average ventilation rate at the natural ventilation point to obtain the actual ventilation rate required by the air circulation device;

[0048] Step S443: Obtain the rated ventilation rate and rated frequency of the air circulation device when it is in operation. Divide the actual ventilation rate by the rated ventilation rate and multiply by the rated frequency to obtain the actual frequency of the air circulation device. Then, operate the air circulation device according to the actual frequency.

[0049] Furthermore, the analysis process in step S5 includes the following sub-steps:

[0050] Step S51: Obtain the real-time frequency of the air circulation device at the current time point, divide the real-time frequency by the rated frequency, and multiply by the rated ventilation rate to obtain the actual circulation rate of the air circulation device at the current time point.

[0051] Step S52: Obtain ventilation data within the smart building area, and sum the actual circulation rate with the average ventilation rate at the natural ventilation point to obtain the total ventilation rate within the smart building area at the current time point.

[0052] Step S53: Compare the theoretical ventilation rate required within the smart building area with the total ventilation rate;

[0053] If the theoretical ventilation rate required within the smart building area is less than or equal to the total ventilation rate, no action will be taken.

[0054] If the required theoretical ventilation rate within the smart building area is greater than the total ventilation rate, proceed to step S54.

[0055] Furthermore, the analysis process in step S5 also includes the following sub-steps:

[0056] Step S54: Subtract the average ventilation rate of the natural ventilation points from the theoretical ventilation rate required in the smart building area to obtain the real-time ventilation rate required by the air circulation device at the current time point.

[0057] Step S55: Divide the real-time ventilation rate by the rated ventilation rate and multiply by the rated frequency to obtain the actual frequency of the air circulation device, and adjust the real-time frequency of the air circulation device at the current time point to the actual frequency.

[0058] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0059] 1. This invention first collects the real-time concentration of fixed gases at different locations within a smart building area at different time points, and then analyzes the real-time concentration of fixed gases at different locations within a smart building area at different time points to obtain abnormal data of fixed gases within the smart building area. This invention enables the analysis of abnormal situations of fixed gases within a smart building area.

[0060] 2. The present invention also analyzes the required theoretical ventilation rate and natural ventilation conditions in the smart building area based on the abnormal data of fixed gas, obtains the ventilation data in the smart building area, and analyzes the real-time operating status of the air circulation device based on the ventilation data in the smart building area. The present invention realizes the analysis of natural ventilation conditions in the smart building area.

[0061] 3. Finally, this invention analyzes whether the air circulation device in operation can meet the theoretical ventilation rate required in the smart building area. This invention realizes dynamic regulation of the air circulation device based on the dynamic changes of a fixed gas. Attached Figure Description

[0062] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0063] Figure 1 This is a flowchart of the method of the present invention;

[0064] Figure 2 This is the overall logic block diagram of the present invention;

[0065] Figure 3 This is a flowchart of the sub-steps of step S35 in this invention;

[0066] Figure 4 This is a schematic diagram of the electronic device in this invention. Detailed Implementation

[0067] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0068] Example 1: Please refer to Figures 1-3 As shown, the technical solution provided by this invention is: a smart building air circulation energy consumption control method based on digital operation and maintenance. This method is applicable to analyzing the theoretical ventilation rate required by the area based on the concentration of fixed gases within the smart building area, thereby dynamically controlling the air circulation device. The method includes the following steps:

[0069] Step S1: Collect the real-time concentration of fixed gas at different locations within the smart building area at different time points;

[0070] In the specific implementation process, sensors can be installed at different locations within the smart building area, and then the corresponding stationary gas can be collected through the sensors. The stationary gas can be carbon dioxide, and the sensor can be an NDIR sensor.

[0071] Step S2: Analyze the real-time concentration of fixed gases at different locations at different time points within the smart building area to obtain abnormal data of fixed gases within the smart building area.

[0072] In this embodiment, the analysis process in step S2 includes the following sub-steps:

[0073] Step S21: Compare the real-time concentration of the fixed gas at different locations at different time points with the standard concentration range;

[0074] If the real-time concentration of the stationary gas at all locations at all time points is within the standard concentration range, then no operation will be performed.

[0075] If the real-time concentration of the fixed gas at any location at any time point is not within the standard concentration range, proceed to step S22.

[0076] It should be noted that the standard concentration range can be obtained by consulting relevant data based on the building type of the smart building area. For example, the standard concentration range of carbon dioxide gas in office, classroom and residential areas can be [600, 1000].

[0077] Step S22: Record the time node corresponding to when the real-time concentration of the stationary gas does not belong to the standard concentration range as an abnormal time node, and record the position corresponding to when the real-time concentration of the stationary gas does not belong to the standard concentration range as an abnormal position.

[0078] Step S23: Count the number of abnormal time points when the real-time concentration of the stationary gas does not fall within the standard concentration range and record them as the number of abnormal time points.

[0079] It should be explained that an abnormal location may correspond to one or more abnormal time nodes. In addition, multiple abnormal locations may also correspond to one or more abnormal time nodes. That is, there may be multiple abnormal locations at one abnormal time node or multiple abnormal locations at multiple abnormal time nodes.

[0080] Step S24: If the real-time concentration of the stationary gas does not fall within the standard concentration range and there is only one abnormal time point, then the abnormal location will be continuously monitored.

[0081] If there are multiple abnormal time points when the real-time concentration of the stationary gas does not fall within the standard concentration range, proceed to step S25.

[0082] It should be explained that when there are multiple abnormal time points, it means that abnormal positions have occurred at multiple time points. In this case, regardless of whether the abnormal position is unique or not, the air circulation device needs to be adjusted accordingly. When there is only one abnormal time point, even if there are multiple abnormal positions, it can be considered that the abnormal position is caused by the instantaneous influence of environmental factors. In this case, the abnormal position needs to be continuously monitored.

[0083] Step S25: For the same abnormal location, subtract the real-time concentration of the fixed gas at the abnormal location at the previous time node from the real-time concentration of the fixed gas at the abnormal location at the abnormal time node to obtain the change in the real-time concentration of the fixed gas at the abnormal location at different abnormal time nodes.

[0084] Step S26: Divide the real-time concentration change of the fixed gas at the abnormal location at different abnormal time points by a fixed time interval to obtain the unit time release of the fixed gas at the abnormal location at different abnormal time points.

[0085] Step S27: Record the real-time concentration and release per unit time of the fixed gas at the abnormal location at different abnormal time points as abnormal data of fixed gas within the smart building area.

[0086] Step S3: Analyze the required theoretical ventilation rate and natural ventilation conditions within the smart building area based on the abnormal data of the fixed gas.

[0087] In this embodiment, the analysis process in step S3 includes the following sub-steps:

[0088] Step S31: Iterate through and compare the real-time concentrations of the fixed gas at the abnormal location at different abnormal time points to obtain the maximum real-time concentration, and record the maximum real-time concentration as the real-time concentration peak.

[0089] Step S32: Record the time node corresponding to the real-time concentration peak of the fixed gas at the abnormal location as the concentration peak time node.

[0090] Step S33: Obtain the unit time release amount SL of the fixed gas at the abnormal location corresponding to the concentration peak time node, obtain the outdoor concentration NDW of the fixed gas in the outdoor environment, and obtain the right endpoint value NDM of the standard concentration range.

[0091] Step S34: Calculate the required theoretical ventilation rate LL within the smart building area using the formula LL=SL / (NDM-NDW);

[0092] It should be noted that the unit of release per unit time is weight divided by duration, while the unit of the right endpoint of the outdoor concentration versus standard concentration range is weight divided by volume. For example, if the unit of release per unit time is (mg / h), the unit of outdoor concentration is (mg / m³). 3 ), then (mg / h) / (mg / m 3 ) = m 3 / h, therefore, the unit of theoretical ventilation rate is volume divided by time. In this embodiment, the right endpoint of the standard concentration range represents the maximum allowable concentration of stationary gas in the smart building area, which by default is greater than the outdoor concentration of stationary gas in the outdoor environment.

[0093] Step S35: Analyze the natural ventilation conditions within the smart building area;

[0094] In the specific implementation process, the analysis process in step S35 includes the following sub-steps:

[0095] Step S351: Measure the ventilation area at the natural ventilation openings within the smart building area, and collect the real-time air intake velocity and real-time air exhaust velocity at the natural ventilation openings at different time points.

[0096] In practice, the sensor can be installed at the natural ventilation opening, and then the sensor can be used to collect the real-time air intake speed and real-time air exhaust speed at the natural ventilation opening at different time points.

[0097] Step S352: Divide the real-time exhaust velocity at the natural ventilation opening at different time points by the real-time intake velocity to obtain the ventilation correction coefficient at the natural ventilation opening at the corresponding time point. Add the ventilation correction coefficients at the natural ventilation opening at different time points, sum them up, and take the average value to obtain the ventilation correction factor at the natural ventilation opening.

[0098] Step S353: Multiply the real-time air intake velocity by the ventilation area and then by the ventilation correction factor at the natural ventilation opening to obtain the natural ventilation rate at the current time point.

[0099] In the specific implementation process, the natural ventilation opening can be a window, and the sensor can be a wind speed sensor. It should be explained that in this embodiment, rate and speed are different. The unit of rate is volume divided by time, and the unit of speed is distance divided by time.

[0100] Step S354: Sum the natural ventilation rates at different time points and take the average value to obtain the average ventilation rate at the current time point.

[0101] Step S355: Record the required theoretical ventilation rate and the average ventilation rate of the natural ventilation point at the current time point as the ventilation data of the smart building area.

[0102] Step S4: Analyze the real-time operating status of the air circulation device based on the ventilation data within the smart building area;

[0103] In this embodiment, the analysis process in step S4 includes the following sub-steps:

[0104] Step S41: Divide the real-time operating status of the air circulation device into working status and shutdown status;

[0105] Step S42: Obtain ventilation data within the smart building area and the real-time operating status of the air circulation device at the current time point;

[0106] Step S43: If the real-time operating status of the air circulation device at the current time node is working, then proceed to step S5;

[0107] Step S44: If the real-time operating status of the air circulation device at the current time node is a shutdown state, then based on digital operation and maintenance analysis, it is necessary to change the real-time operating status of the air circulation device.

[0108] In the specific implementation process, the analysis process in step S44 includes the following sub-steps:

[0109] Step S441: Compare the theoretical ventilation rate required within the smart building area with the average ventilation rate at the current time point at the naturally ventilated area;

[0110] If the theoretical ventilation rate required within the smart building area is less than or equal to the average ventilation rate at the current time point, no action will be taken.

[0111] If the theoretical ventilation rate required in the smart building area is greater than the average ventilation rate of the natural ventilation point at the current time point, the real-time operation status of the air circulation device is switched from the shutdown state to the working state and the process proceeds to step S442.

[0112] Step S442: Subtract the theoretical ventilation rate required within the smart building area from the average ventilation rate at the natural ventilation point to obtain the actual ventilation rate required by the air circulation device;

[0113] Step S443: Obtain the rated ventilation rate and rated frequency of the air circulation device when it is in operation. Divide the actual ventilation rate by the rated ventilation rate and multiply by the rated frequency to obtain the actual frequency of the air circulation device. Then, operate the air circulation device according to the actual frequency.

[0114] It should be explained that the rated ventilation rate and rated frequency of the air circulation device when it is in operation can be obtained from the technical specifications of the air circulation device. Calculating the actual frequency of the air circulation device is to allow the air circulation device to dynamically adjust its operating frequency according to the actual ventilation rate required, thereby reducing energy consumption.

[0115] Step S5: Analyze whether the air circulation device in operation can meet the theoretical ventilation rate required in the smart building area.

[0116] In this embodiment, the analysis process in step S5 includes the following sub-steps:

[0117] Step S51: Obtain the real-time frequency of the air circulation device at the current time point, divide the real-time frequency by the rated frequency, and multiply by the rated ventilation rate to obtain the actual circulation rate of the air circulation device at the current time point.

[0118] Step S52: Obtain ventilation data within the smart building area, and sum the actual circulation rate with the average ventilation rate at the natural ventilation point to obtain the total ventilation rate within the smart building area at the current time point.

[0119] Step S53: Compare the theoretical ventilation rate required within the smart building area with the total ventilation rate;

[0120] If the theoretical ventilation rate required within the smart building area is less than or equal to the total ventilation rate, no action will be taken.

[0121] If the theoretical ventilation rate required within the smart building area is greater than the total ventilation rate, proceed to step S54.

[0122] Step S54: Subtract the average ventilation rate of the natural ventilation points from the theoretical ventilation rate required in the smart building area to obtain the real-time ventilation rate required by the air circulation device at the current time point.

[0123] Step S55: Divide the real-time ventilation rate by the rated ventilation rate and multiply by the rated frequency to obtain the actual frequency of the air circulation device, and adjust the real-time frequency of the air circulation device at the current time point to the actual frequency.

[0124] It should be explained that when the required theoretical ventilation rate in the smart building area is greater than the total ventilation rate, the total ventilation rate needs to be further increased. In this case, it is necessary to calculate the real-time ventilation rate required by the air circulation device, and then calculate the actual frequency of the air circulation device. At this time, it is only necessary to adjust the real-time frequency of the air circulation device to the actual frequency to meet the required theoretical ventilation rate.

[0125] Example 2: Figure 4As shown, this embodiment provides an electronic device, which may include a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other via the communication bus. The processor can call logical instructions in the memory to execute a smart building air circulation energy consumption control method based on digital operation and maintenance. This method includes: collecting real-time concentrations of fixed gases at different locations within the smart building area at different time points; analyzing the real-time concentrations of fixed gases at different locations within the smart building area at different time points to obtain abnormal data of fixed gases within the smart building area; analyzing the required theoretical ventilation rate and natural ventilation conditions within the smart building area based on the abnormal data of fixed gases; analyzing the real-time operating status of the air circulation device based on the ventilation data within the smart building area; and analyzing whether the air circulation device in operation can meet the required theoretical ventilation rate within the smart building area.

[0126] Furthermore, when the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0127] On the other hand, this application also provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions, and when the program instructions are executed by a computer, the computer can execute the smart building air circulation energy consumption control method based on digital operation and maintenance provided by the above methods. The method includes: collecting the real-time concentration of fixed gases at different locations at different time points within the smart building area; analyzing the real-time concentration of fixed gases at different locations at different time points within the smart building area to obtain abnormal data of fixed gases within the smart building area; analyzing the required theoretical ventilation rate and natural ventilation conditions within the smart building area based on the abnormal data of fixed gases; analyzing the real-time operating status of the air circulation device based on the ventilation data within the smart building area; and analyzing whether the air circulation device in the working state can meet the required theoretical ventilation rate within the smart building area.

[0128] Furthermore, this application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, performs the aforementioned methods for controlling the energy consumption of air circulation in smart buildings based on digital operation and maintenance. This method includes: collecting real-time concentrations of fixed gases at different locations within a smart building area at different time points; analyzing the real-time concentrations of fixed gases at different locations within a smart building area at different time points to obtain abnormal data of fixed gases within the smart building area; analyzing the required theoretical ventilation rate and natural ventilation conditions within the smart building area based on the abnormal data of fixed gases; analyzing the real-time operating status of the air circulation device based on ventilation data within the smart building area; and analyzing whether the air circulation device in operation can meet the required theoretical ventilation rate within the smart building area.

[0129] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0130] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0131] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A smart building air circulation energy consumption control method based on digital operation and maintenance, characterized in that, The methods include: Step S1: Collect the real-time concentration of fixed gas at different locations within the smart building area at different time points; Step S2: Analyze the real-time concentration of fixed gases at different locations at different time points within the smart building area to obtain abnormal data of fixed gases within the smart building area. Step S3: Analyze the required theoretical ventilation rate and natural ventilation conditions within the smart building area based on the abnormal data of the fixed gas. Step S4: Analyze the real-time operating status of the air circulation device based on the ventilation data within the smart building area; The analysis process in step S4 includes the following sub-steps: Step S41: Divide the real-time operating status of the air circulation device into working status and shutdown status; Step S42: Obtain ventilation data within the smart building area and the real-time operating status of the air circulation device at the current time point; Step S43: If the real-time operating status of the air circulation device at the current time node is working, then proceed to step S5; Step S44: If the real-time operating status of the air circulation device at the current time node is a shutdown state, then based on digital operation and maintenance analysis, it is necessary to determine whether the real-time operating status of the air circulation device needs to be changed. The analysis process in step S44 includes the following sub-steps: Step S441: Compare the theoretical ventilation rate required within the smart building area with the average ventilation rate at the current time point at the naturally ventilated area; If the theoretical ventilation rate required within the smart building area is less than or equal to the average ventilation rate at the current time point, no action will be taken. If the theoretical ventilation rate required in the smart building area is greater than the average ventilation rate of the natural ventilation point at the current time point, the real-time operation status of the air circulation device is switched from the shutdown state to the working state and the process proceeds to step S442. Step S442: Subtract the average ventilation rate of the natural ventilation points from the theoretical ventilation rate required in the smart building area to obtain the actual ventilation rate required by the air circulation device. Step S443: Obtain the rated ventilation rate and rated frequency of the air circulation device when it is in operation. Divide the actual ventilation rate by the rated ventilation rate and multiply by the rated frequency to obtain the actual frequency of the air circulation device. Then, operate the air circulation device according to the actual frequency. Step S5: Analyze whether the air circulation device in operation can meet the theoretical ventilation rate required in the smart building area. The analysis process in step S5 includes the following sub-steps: Step S51: Obtain the real-time frequency of the air circulation device at the current time point, divide the real-time frequency by the rated frequency, and multiply by the rated ventilation rate to obtain the actual circulation rate of the air circulation device at the current time point. Step S52: Obtain ventilation data within the smart building area, and sum the actual circulation rate with the average ventilation rate at the natural ventilation point to obtain the total ventilation rate within the smart building area at the current time point. Step S53: Compare the theoretical ventilation rate required within the smart building area with the total ventilation rate; If the theoretical ventilation rate required within the smart building area is less than or equal to the total ventilation rate, no action will be taken. If the theoretical ventilation rate required within the smart building area is greater than the total ventilation rate, proceed to step S54. Step S54: Subtract the average ventilation rate of the natural ventilation points from the theoretical ventilation rate required in the smart building area to obtain the real-time ventilation rate required by the air circulation device at the current time point. Step S55: Divide the real-time ventilation rate by the rated ventilation rate and multiply by the rated frequency to obtain the actual frequency of the air circulation device, and adjust the real-time frequency of the air circulation device at the current time point to the actual frequency.

2. The method for controlling air circulation energy consumption in smart buildings based on digital operation and maintenance according to claim 1, characterized in that, The analysis process in step S2 includes the following sub-steps: Step S21: Compare the real-time concentration of the fixed gas at different locations at different time points with the standard concentration range; If the real-time concentration of the stationary gas at all locations at all time points is within the standard concentration range, then no operation will be performed. If the real-time concentration of the fixed gas at any location at any time point is not within the standard concentration range, proceed to step S22. Step S22: Record the time node corresponding to when the real-time concentration of the stationary gas does not belong to the standard concentration range as an abnormal time node, and record the position corresponding to when the real-time concentration of the stationary gas does not belong to the standard concentration range as an abnormal position. Step S23: Count the number of abnormal time points when the real-time concentration of the stationary gas does not fall within the standard concentration range and record them as the number of abnormal time points.

3. The method for controlling air circulation energy consumption in smart buildings based on digital operation and maintenance according to claim 2, characterized in that, The analysis process in step S2 also includes the following sub-steps: Step S24: If the real-time concentration of the stationary gas does not fall within the standard concentration range and there is only one abnormal time point, then the abnormal location will be continuously monitored. If there are multiple abnormal time points when the real-time concentration of the stationary gas does not fall within the standard concentration range, proceed to step S25. Step S25: For the same abnormal location, subtract the real-time concentration of the fixed gas at the abnormal location at the previous time node from the real-time concentration of the fixed gas at the abnormal location at the abnormal time node to obtain the change in the real-time concentration of the fixed gas at the abnormal location at different abnormal time nodes. Step S26: Divide the real-time concentration change of the fixed gas at the abnormal location at different abnormal time points by a fixed time interval to obtain the unit time release of the fixed gas at the abnormal location at different abnormal time points. Step S27: Record the real-time concentration and release per unit time of the fixed gas at the abnormal location at different abnormal time points as abnormal data of fixed gas within the smart building area.

4. The method for controlling air circulation energy consumption in smart buildings based on digital operation and maintenance according to claim 3, characterized in that, The analysis process in step S3 includes the following sub-steps: Step S31: Iterate through and compare the real-time concentrations of the fixed gas at the abnormal location at different abnormal time points to obtain the maximum real-time concentration, and record the maximum real-time concentration as the real-time concentration peak. Step S32: Record the time node corresponding to the real-time concentration peak of the fixed gas at the abnormal location as the concentration peak time node. Step S33: Obtain the unit time release of fixed gas at the abnormal location corresponding to the concentration peak time node, obtain the outdoor concentration of fixed gas in the outdoor environment, and obtain the right endpoint value of the standard concentration range. Step S34: Calculate the theoretical ventilation rate required within the smart building area; Step S35: Analyze the natural ventilation conditions within the smart building area.

5. The method for controlling air circulation energy consumption in smart buildings based on digital operation and maintenance according to claim 4, characterized in that, The analysis process in step S35 includes the following sub-steps: Step S351: Measure the ventilation area at the natural ventilation openings within the smart building area, and collect the real-time air intake velocity and real-time air exhaust velocity at the natural ventilation openings at different time points. Step S352: Divide the real-time exhaust velocity at the natural ventilation opening at different time points by the real-time intake velocity to obtain the ventilation correction coefficient at the natural ventilation opening at the corresponding time point. Add the ventilation correction coefficients at the natural ventilation opening at different time points, sum them up, and take the average value to obtain the ventilation correction factor at the natural ventilation opening.

6. The method for controlling air circulation energy consumption in smart buildings based on digital operation and maintenance according to claim 5, characterized in that, The analysis process in step S35 further includes the following sub-steps: Step S353: Multiply the real-time air intake velocity by the ventilation area and then by the ventilation correction factor at the natural ventilation opening to obtain the natural ventilation rate at the current time point. Step S354: Sum the natural ventilation rates at different time points and take the average value to obtain the average ventilation rate at the current time point. Step S355: Record the required theoretical ventilation rate and the average ventilation rate of the natural ventilation point at the current time point as the ventilation data of the smart building area.

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