Building air conditioner control system and method based on internet of things joint driving

Abstract

The application discloses a building air conditioner control system and method based on Internet of Things joint driving, and relates to the technical field of air conditioner control. The control method specifically comprises the following steps: obtaining installation position information of each indoor unit; dividing an air flow adjustment area corresponding to each indoor unit; judging whether the air speed of an auxiliary node needs to be adjusted; inputting the current air speed of the target node and the current air speed of the auxiliary node into the air speed cooperative adjustment model, and outputting a target adjustment air speed for the auxiliary node. The application dynamically divides the air flow adjustment area through the wind field diffusion model, accurately identifies the coupling relationship between the target node and the auxiliary node, and combines the multi-target constraint air speed cooperative adjustment model to reduce energy consumption under the premise of ensuring comfort. According to temperature changes, the air speed of two adjacent indoor units is automatically adjusted to break the information island between devices and realize real cooperation.

Description

Technical Field

[0001] This invention relates to the field of air conditioning control technology, specifically to a building air conditioning control system and method based on Internet of Things (IoT) joint drive. Background Technology

[0002] In some buildings, each floor is equipped with a central air conditioning system to regulate the temperature. A central air conditioning system usually consists of one outdoor unit and multiple indoor units, with one outdoor unit driving the operation of multiple indoor units.

[0003] Each indoor unit is assigned to a different area and works together to regulate the airflow. Although the room is divided into several areas, the air between these areas is interconnected.

[0004] The air outlets of each indoor unit are generally not easily changed after being set. However, the indoor units that belong to the common area work together to adjust the temperature of the public area to an appropriate temperature. Since the air volume of each indoor unit is set independently, information silos exist. Summary of the Invention

[0005] The purpose of this invention is to provide a building air conditioning control system and method based on Internet of Things (IoT) joint drive, so as to solve the problems raised in the prior art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a building air conditioning control method based on Internet of Things (IoT) joint drive, wherein the control method specifically includes the following steps:

[0007] S1. Obtain the floor plan information of each floor and the installation location information of each indoor unit on that floor;

[0008] S2. Based on the floor plan information and the indoor unit installation location information, construct an air field diffusion model to simulate the airflow diffusion range of each indoor unit, and divide the airflow adjustment area corresponding to each indoor unit according to the simulation results.

[0009] S3. Select an indoor unit as the target node, and mark at least one other indoor unit that is adjacent to or has an overlapping area with the airflow adjustment area of ​​the target node as an auxiliary node. Determine whether the wind speed of the auxiliary node needs to be adjusted. If it is determined that adjustment is needed, proceed to step S4.

[0010] S4. The current wind speed of the target node and the current wind speed of the auxiliary node are obtained in real time through the Internet of Things sensor network.

[0011] S5. Establish a wind speed coordinated adjustment model, input the current wind speed of the target node and the current wind speed of the auxiliary node into the wind speed coordinated adjustment model, and output the target adjusted wind speed for the auxiliary node.

[0012] S6. Adjust the wind speed according to the target, generate control commands and send them to the indoor unit actuator of the auxiliary node to adjust the actual air supply speed of the auxiliary node.

[0013] Furthermore, the wind field diffusion model is constructed based on computational fluid dynamics simulation. By simulating the airflow trajectory under different indoor unit air supply parameters, the airflow regulation zone corresponding to each indoor unit is divided. The division process is as follows:

[0014] A circular diffusion range is preset with the indoor unit's air outlet as the center;

[0015] Simulate the gas flow trajectory of the indoor unit under different air supply parameters to form an airflow diffusion path;

[0016] Obtain the wind speed for gas diffusion at different radii;

[0017] The boundary range where the wind speed decreases to a set threshold is marked as the simulated coverage area, forming the airflow regulation zone of the indoor unit.

[0018] Furthermore, in step S3,

[0019] Obtain the current air supply parameters of the indoor unit and the airflow adjustment area of ​​the indoor unit corresponding to the current air supply parameters. With the radius of the airflow adjustment area as the direction, set several temperature sensors extending outward from the center, set the interval distance, and measure the temperature of the airflow adjustment area at different radii.

[0020] Obtain the set air supply temperature of each indoor unit. If the set air supply temperatures of two indoor units that are adjacent to each other or have overlapping areas are different, mark the indoor unit with the higher set air supply temperature as the target node and mark the other indoor unit with the lower set air supply temperature as the auxiliary node.

[0021] Connect the target node and the auxiliary node as two endpoints with an auxiliary line. Mark the temperatures corresponding to different radii on the auxiliary line. Starting from the target node, arrange the temperature values ​​sequentially towards the auxiliary node, with the temperature values ​​decreasing gradually in sequence. Obtain the radius corresponding to the last temperature data in the arrangement as the temperature radius. Use the radius of the airflow adjustment area of ​​the target node as the adjustment radius. If the temperature radius is greater than the adjustment radius, it is determined that the wind speed of the auxiliary node needs to be adjusted.

[0022] Furthermore, the overlapping area is defined as follows: if the overlapping area of ​​the airflow adjustment areas of two indoor units exceeds a set percentage of the area of ​​either area, then it is determined that there is an overlapping area.

[0023] Furthermore, the process of establishing the wind speed coordinated regulation model includes:

[0024] Collect historical operational data and construct a training set with the target node wind speed and auxiliary node wind speed as inputs and the comfort level after target node adjustment as output;

[0025] A wind speed coordinated regulation model is generated by fitting the mapping relationship between input and output through machine learning algorithms.

[0026] The auxiliary node's supply air temperature is input into the wind speed collaborative regulation model, and the target regulation wind speed and recommended supply air temperature of the auxiliary node are output.

[0027] Furthermore, the generation of the control commands includes:

[0028] Input the difference between the target wind speed and the current wind speed at the auxiliary node into the PID controller;

[0029] Output control signals to the indoor unit fan inverter.

[0030] A building air conditioning control system based on Internet of Things (IoT) joint drive, the control system includes an information acquisition module, a simulation diffusion module, a zone division module, a data acquisition module, and a coordinated adjustment module;

[0031] The information acquisition module is used to obtain the floor plan information of each floor and the installation location information of each indoor unit on that floor;

[0032] The simulation diffusion module constructs a wind field diffusion model to simulate the diffusion range of the airflow from each indoor unit based on the plan view information and the indoor unit installation location information.

[0033] The area division module is used to divide the airflow adjustment area corresponding to each indoor unit according to the simulation results;

[0034] The data acquisition module is used to collect the temperature and wind speed of the airflow adjustment area corresponding to the target node and the auxiliary node; wherein a certain indoor unit is selected as the target node, and at least one other indoor unit that is adjacent to or has an overlapping area with the airflow adjustment area of ​​the target node is marked as an auxiliary node;

[0035] The coordinated adjustment module is used to input the current wind speed of the target node and the current wind speed of the auxiliary node into the wind speed coordinated adjustment model, and output the target adjusted wind speed for the auxiliary node.

[0036] Furthermore, the data acquisition module includes a sensor unit and a tagging unit;

[0037] The sensor unit is used to collect the temperature and wind speed in the airflow regulation area;

[0038] The marking unit is used to divide the target node and the auxiliary node. The process is as follows: obtain the current air supply parameters of the indoor unit and obtain the airflow adjustment area of ​​the indoor unit corresponding to the current air supply parameters. With the radius of the airflow adjustment area as the direction, set a number of temperature sensors extending outward from the center of the circle, set the interval distance, and measure the temperature of the airflow adjustment area at different radii.

[0039] Obtain the set air supply temperature of each indoor unit. If two indoor units with adjacent or overlapping airflow adjustment areas have different set air supply temperatures, mark the indoor unit with the higher set air supply temperature as the target node and the other indoor unit with the lower set air supply temperature as the auxiliary node.

[0040] Furthermore, the collaborative adjustment module includes determining whether the wind speed of the auxiliary node needs to be adjusted. The determination process is as follows: the target node and the auxiliary node are taken as two endpoints and connected by an auxiliary line. The temperatures corresponding to different radii are marked on the auxiliary line. Starting from the target node, the temperature values ​​are arranged sequentially towards the auxiliary node, and the temperature values ​​in the sequential arrangement gradually decrease. The radius corresponding to the last temperature data in the arrangement is obtained as the temperature radius. The radius of the airflow adjustment area of ​​the target node is taken as the adjustment radius. If the temperature radius is greater than the adjustment radius, it is determined that the wind speed of the auxiliary node needs to be adjusted.

[0041] Compared with the prior art, the beneficial effects of the present invention are:

[0042] 1. By dynamically dividing the airflow adjustment area through the wind field diffusion model, accurately identifying the coupling relationship between target nodes and auxiliary nodes, and combining the multi-objective constrained wind speed collaborative adjustment model, energy consumption can be reduced while ensuring comfort. Furthermore, based on temperature changes, the air outlet speed of two adjacent indoor units can be automatically adjusted to break down information silos between devices and achieve true collaborative effect. Attached Figure Description

[0043] Figure 1 This is a flowchart illustrating a building air conditioning control method based on Internet of Things (IoT) joint drive according to the present invention. Detailed Implementation

[0044] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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.

[0045] Example: Figure 1 As shown, this invention provides a building air conditioning control method based on Internet of Things (IoT) joint drive, the control method specifically including the following steps:

[0046] S1. Obtain the floor plan information of each floor and the installation location information of each indoor unit on that floor;

[0047] S2. Based on the floor plan information and the indoor unit installation location information, construct an air field diffusion model to simulate the airflow diffusion range of each indoor unit, and divide the airflow adjustment area corresponding to each indoor unit according to the simulation results.

[0048] The wind field diffusion model is constructed based on computational fluid dynamics simulation. By simulating the airflow trajectory under different indoor unit air supply parameters, the airflow regulation zone corresponding to each indoor unit is divided. The division process is as follows:

[0049] A circular diffusion range is preset with the indoor unit's air outlet as the center;

[0050] Simulate the gas flow trajectory of the indoor unit under different air supply parameters to form an airflow diffusion path;

[0051] Obtain the wind speed for gas diffusion at different radii;

[0052] The boundary range where the wind speed decreases to a set threshold is marked as the simulated coverage area, forming the airflow regulation zone of the indoor unit.

[0053] S3. Select an indoor unit as the target node, and mark at least one other indoor unit that is adjacent to or has an overlapping area with the airflow adjustment area of ​​the target node as an auxiliary node. Determine whether the wind speed of the auxiliary node needs to be adjusted. If it is determined that adjustment is needed, proceed to step S4.

[0054] In step S3

[0055] Obtain the current air supply parameters of the indoor unit and the airflow adjustment area of ​​the indoor unit corresponding to the current air supply parameters. With the radius of the airflow adjustment area as the direction, set several temperature sensors extending outward from the center, set the interval distance, and measure the temperature of the airflow adjustment area at different radii.

[0056] Obtain the set air supply temperature of each indoor unit. If the set air supply temperatures of two indoor units that are adjacent to each other or have overlapping areas are different, mark the indoor unit with the higher set air supply temperature as the target node and mark the other indoor unit with the lower set air supply temperature as the auxiliary node.

[0057] Connect the target node and the auxiliary node as two endpoints with an auxiliary line. Mark the temperatures corresponding to different radii on the auxiliary line. Starting from the target node, arrange the temperature values ​​sequentially towards the auxiliary node, with the temperature values ​​decreasing gradually in sequence. Obtain the radius corresponding to the last temperature data in the arrangement as the temperature radius. Use the radius of the airflow adjustment area of ​​the target node as the adjustment radius. If the temperature radius is greater than the adjustment radius, it is determined that the wind speed of the auxiliary node needs to be adjusted.

[0058] The overlapping area is defined as follows: if the overlapping area of ​​the airflow adjustment areas of two indoor units exceeds the set percentage of the area of ​​either area, then it is determined that there is an overlapping area.

[0059] S4. The current wind speed of the target node and the current wind speed of the auxiliary node are obtained in real time through the Internet of Things sensor network.

[0060] S5. Establish a wind speed coordinated adjustment model. Input the current wind speed of the target node and the current wind speed of the auxiliary node into the wind speed coordinated adjustment model, and output the target adjusted wind speed for the auxiliary node. The objective function of the wind speed coordinated adjustment model in S5 is to minimize the wind speed fluctuation variance between the target node and the auxiliary node, while constraining the energy consumption increase to not exceed 10%.

[0061] The process of establishing the wind speed coordinated regulation model includes:

[0062] Collect historical operational data and construct a training set with the target node wind speed and auxiliary node wind speed as inputs and the comfort level after target node adjustment as output;

[0063] A wind speed coordinated regulation model is generated by fitting the mapping relationship between input and output through machine learning algorithms.

[0064] The auxiliary node's supply air temperature is input into the wind speed collaborative regulation model, and the target regulation wind speed and recommended supply air temperature of the auxiliary node are output.

[0065] The generation of the control commands includes:

[0066] Input the difference between the target wind speed and the current wind speed at the auxiliary node into the PID controller;

[0067] Output control signals to the indoor unit fan inverter.

[0068] S6. Adjust the wind speed according to the target, generate control commands and send them to the indoor unit actuator of the auxiliary node to adjust the actual air supply speed of the auxiliary node.

[0069] Example 2: A building air conditioning control system based on Internet of Things (IoT) joint drive, the control system includes an information acquisition module, a simulation diffusion module, a zone division module, a data acquisition module, and a collaborative adjustment module;

[0070] The information acquisition module is used to obtain the floor plan information of each floor and the installation location information of each indoor unit on that floor;

[0071] The simulation diffusion module constructs a wind field diffusion model to simulate the diffusion range of the airflow from each indoor unit based on the plan view information and the indoor unit installation location information.

[0072] The area division module is used to divide the airflow adjustment area corresponding to each indoor unit according to the simulation results;

[0073] The data acquisition module is used to collect the temperature and wind speed of the airflow adjustment area corresponding to the target node and the auxiliary node; wherein a certain indoor unit is selected as the target node, and at least one other indoor unit that is adjacent to or has an overlapping area with the airflow adjustment area of ​​the target node is marked as an auxiliary node;

[0074] The coordinated adjustment module is used to input the current wind speed of the target node and the current wind speed of the auxiliary node into the wind speed coordinated adjustment model, and output the target adjusted wind speed for the auxiliary node.

[0075] The data acquisition module includes a sensor unit and a tagging unit;

[0076] The sensor unit is used to collect the temperature and wind speed in the airflow regulation area;

[0077] The marking unit is used to divide the target node and the auxiliary node. The process is as follows: obtain the current air supply parameters of the indoor unit and obtain the airflow adjustment area of ​​the indoor unit corresponding to the current air supply parameters. With the radius of the airflow adjustment area as the direction, set a number of temperature sensors extending outward from the center of the circle, set the interval distance, and measure the temperature of the airflow adjustment area at different radii.

[0078] Obtain the set air supply temperature of each indoor unit. If two indoor units with adjacent or overlapping airflow adjustment areas have different set air supply temperatures, mark the indoor unit with the higher set air supply temperature as the target node and the other indoor unit with the lower set air supply temperature as the auxiliary node.

[0079] The coordinated adjustment module includes determining whether the wind speed of the auxiliary node needs to be adjusted. The determination process is as follows: the target node and the auxiliary node are taken as two endpoints and connected by an auxiliary line. The temperatures corresponding to different radii are marked on the auxiliary line. Starting from the target node, the temperature values ​​are arranged sequentially towards the auxiliary node, and the temperature values ​​in the sequential arrangement gradually decrease. The radius corresponding to the last temperature data in the arrangement is obtained as the temperature radius. The radius of the airflow adjustment area of ​​the target node is taken as the adjustment radius. If the temperature radius is greater than the adjustment radius, it is determined that the wind speed of the auxiliary node needs to be adjusted.

[0080] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A building air conditioning control method based on Internet of Things (IoT) joint drive, characterized in that: The control method specifically includes the following steps: S1. Obtain the floor plan information of each floor and the installation location information of each indoor unit on that floor; S2. Based on the floor plan information and the indoor unit installation location information, construct an air field diffusion model to simulate the airflow diffusion range of each indoor unit, and divide the airflow adjustment area corresponding to each indoor unit according to the simulation results. S3. Select an indoor unit as the target node, and mark at least one other indoor unit that is adjacent to or has an overlapping area with the airflow adjustment area of ​​the target node as an auxiliary node. Determine whether the wind speed of the auxiliary node needs to be adjusted. If it is determined that adjustment is needed, proceed to step S4. S4. The current wind speed of the target node and the current wind speed of the auxiliary node are obtained in real time through the Internet of Things sensor network. S5. Establish a wind speed coordinated adjustment model, input the current wind speed of the target node and the current wind speed of the auxiliary node into the wind speed coordinated adjustment model, and output the target adjusted wind speed for the auxiliary node. S6. Adjust the wind speed according to the target, generate control commands and send them to the indoor unit actuator of the auxiliary node to adjust the actual air supply speed of the auxiliary node; In step S3 Obtain the current air supply parameters of the indoor unit and the airflow adjustment area of ​​the indoor unit corresponding to the current air supply parameters. With the radius of the airflow adjustment area as the direction, set several temperature sensors extending outward from the center, set the interval distance, and measure the temperature of the airflow adjustment area at different radii. Obtain the set air supply temperature of each indoor unit. If the set air supply temperatures of two indoor units that are adjacent to each other or have overlapping areas are different, mark the indoor unit with the higher set air supply temperature as the target node and mark the other indoor unit with the lower set air supply temperature as the auxiliary node. Connect the target node and the auxiliary node as two endpoints with an auxiliary line. Mark the temperatures corresponding to different radii on the auxiliary line. Starting from the target node, arrange the temperature values ​​sequentially towards the auxiliary node, with the temperature values ​​decreasing gradually in the order of arrangement. Obtain the radius corresponding to the last temperature data in the arrangement as the temperature radius. Use the radius of the airflow adjustment area of ​​the target node as the adjustment radius. If the temperature radius is greater than the adjustment radius, it is determined that the wind speed of the auxiliary node needs to be adjusted. The process of establishing the wind speed coordinated regulation model includes: Collect historical operational data and construct a training set with the target node wind speed and auxiliary node wind speed as inputs and the comfort level after target node adjustment as output; A wind speed coordinated regulation model is generated by fitting the mapping relationship between input and output through machine learning algorithms. The auxiliary node's supply air temperature is input into the wind speed collaborative regulation model, and the target regulation wind speed and recommended supply air temperature of the auxiliary node are output.

2. The building air conditioning control method based on IoT joint drive according to claim 1, characterized in that: The wind field diffusion model is constructed based on computational fluid dynamics simulation. By simulating the airflow trajectory under different indoor unit air supply parameters, the airflow regulation zone corresponding to each indoor unit is divided. The division process is as follows: A circular diffusion range is preset with the indoor unit's air outlet as the center; Simulate the gas flow trajectory of the indoor unit under different air supply parameters to form an airflow diffusion path; Obtain the wind speed for gas diffusion at different radii; The boundary range where the wind speed decreases to a set threshold is marked as the simulated coverage area, forming the airflow regulation zone of the indoor unit.

3. The building air conditioning control method based on IoT joint drive according to claim 1, characterized in that: The overlapping area is defined as follows: if the overlapping area of ​​the airflow adjustment areas of two indoor units exceeds the set percentage of the area of ​​either area, then it is determined that there is an overlapping area.

4. The building air conditioning control method based on IoT joint drive according to claim 1, characterized in that: The generation of the control commands includes: Input the difference between the target wind speed and the current wind speed at the auxiliary node into the PID controller; Output control signals to the indoor unit fan inverter.

5. A building air conditioning control system based on Internet of Things (IoT) joint drive, applied to the building air conditioning control method based on IoT joint drive as described in any one of claims 1-4, characterized in that: The control system includes an information acquisition module, a simulation diffusion module, a region division module, a data acquisition module, and a coordinated adjustment module; The information acquisition module is used to obtain the floor plan information of each floor and the installation location information of each indoor unit on that floor; The simulation diffusion module constructs a wind field diffusion model to simulate the diffusion range of the airflow from each indoor unit based on the plan view information and the indoor unit installation location information. The area division module is used to divide the airflow adjustment area corresponding to each indoor unit according to the simulation results; The data acquisition module is used to collect the temperature and wind speed of the airflow regulation area corresponding to the target node and the auxiliary node; One indoor unit is selected as the target node, and at least one other indoor unit that is adjacent to or has an overlapping area with the airflow adjustment area of ​​the target node is marked as an auxiliary node. The coordinated adjustment module is used to input the current wind speed of the target node and the current wind speed of the auxiliary node into the wind speed coordinated adjustment model, and output the target adjusted wind speed for the auxiliary node.

6. The building air conditioning control system based on IoT joint drive according to claim 5, characterized in that: The data acquisition module includes a sensor unit and a tagging unit; The sensor unit is used to collect the temperature and wind speed in the airflow regulation area; The marking unit is used to divide the target node and the auxiliary node. The process is as follows: obtain the current air supply parameters of the indoor unit and obtain the airflow adjustment area of ​​the indoor unit corresponding to the current air supply parameters. With the radius of the airflow adjustment area as the direction, set a number of temperature sensors extending outward from the center of the circle, set the interval distance, and measure the temperature of the airflow adjustment area at different radii. Obtain the set air supply temperature of each indoor unit. If two indoor units with adjacent or overlapping airflow adjustment areas have different set air supply temperatures, mark the indoor unit with the higher set air supply temperature as the target node and the other indoor unit with the lower set air supply temperature as the auxiliary node.

7. The building air conditioning control system based on IoT joint drive according to claim 5, characterized in that: The coordinated adjustment module includes determining whether the wind speed of the auxiliary node needs to be adjusted. The determination process is as follows: the target node and the auxiliary node are taken as two endpoints and connected by an auxiliary line. The temperatures corresponding to different radii are marked on the auxiliary line. Starting from the target node, the temperature values ​​are arranged sequentially towards the auxiliary node, and the temperature values ​​in the sequential arrangement gradually decrease. The radius corresponding to the last temperature data in the arrangement is obtained as the temperature radius. The radius of the airflow adjustment area of ​​the target node is taken as the adjustment radius. If the temperature radius is greater than the adjustment radius, it is determined that the wind speed of the auxiliary node needs to be adjusted.

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