Air conditioner temperature intelligent adjusting design system based on BIM technology

Abstract

The invention discloses an air conditioner temperature intelligent adjustment design system based on a BIM technology, and belongs to the technical field of air conditioner temperature adjustment, and the system comprises a data obtaining module which obtains air conditioner data and environment data, builds a BIM model in combination with the air conditioner data, and simulates the adjustment state of an air conditioner in the environment; the output instruction module outputs a starting instruction when the user load changes or the central air-conditioning system operates under the same operation parameter combination to reach the time condition, 3D model output is formed through BIM simulation, visual air-conditioning management is achieved, and intelligent temperature adjustment in a target space is achieved in combination with an air-conditioning refrigeration / heating scene. And the adaptation degree of temperature adjustment and the target space is improved, and then the air conditioner control quality is improved.

Description

Technical Field

[0001] This invention belongs to the field of air conditioning temperature control technology, specifically relating to an intelligent air conditioning temperature control design system based on BIM technology. Background Technology

[0002] With social development and the improvement of people's living standards, air conditioners have become an indispensable appliance in people's daily lives. In order to pursue a larger market share, many manufacturers have been committed to developing smarter air conditioners.

[0003] Currently, most smart air conditioners primarily employ the following technologies: 1) Using built-in temperature sensors to detect temperature changes in the vicinity of the air conditioner and adjust its operating status, achieving energy savings to some extent; 2) Using infrared temperature measurement chips combined with motion scanning devices to determine the approximate temperature distribution of the external environment; 3) Using scene analysis methods based on visible light cameras, by embedding visible light cameras in the air conditioner, human detection and recognition technologies can detect human targets and roughly locate their distances, enabling intelligent directional airflow. However, the built-in temperature sensors lack information on the overall environmental temperature distribution and the presence of human targets, resulting in a poor user experience; infrared temperature measurement chips can only collect temperature information at a single point, and their working distance is limited by the power of the reflective module, making it difficult to solve problems such as obstruction and to achieve global analysis of the entire environmental temperature field distribution; while scene analysis methods based on visible light cameras cannot obtain accurate temperature information, and installing visible light cameras on air conditioners can also cause psychological resistance from users. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and provide an intelligent air conditioning temperature control design system based on BIM technology, comprising: The data acquisition module acquires air conditioning data and environmental data, and combines the air conditioning data to build a BIM model to simulate the air conditioning's regulation state in the environment; The output command module outputs a start command when the user load changes or when the central air conditioning system reaches the time condition under the same combination of operating parameters.

[0005] The parameter adjustment module handles the operating parameters, including the operating frequency and number of cooling water pumps, and the operating speed and number of cooling tower fans. The operating frequency and number of chilled water pumps are adaptively adjusted based on the user load. Upon receiving a signal from the central control station of the central air conditioning system indicating a decrease in chilled water flow, the module confirms a change in user load. When the central air conditioning system operates continuously under a certain operating parameter combination for a preset time threshold, the module confirms that the central air conditioning system has met the time requirement under that same operating parameter combination. If either of these two conditions is met, a start command is output.

[0006] The test module responds to the start command by outputting a test command to select the system's operating mode; in response to the test command, it selects a combination of operating parameters from the preset database and sends a test request to the central air conditioning system based on that combination of operating parameters.

[0007] Furthermore, the combination of operating parameters in the database is divided into multiple groups, with each user load corresponding to a group. There is a one-to-one correspondence between groups and user loads, and each combination of operating parameters in each group corresponds to a historical energy efficiency value obtained from historical data.

[0008] Furthermore, the historical energy efficiency value obtained from historical data refers to the average of the energy efficiency values ​​obtained each time the user load is the same, using a combination of operating parameters within the group. The average value is the historical energy efficiency value corresponding to that combination of operating parameters in the group.

[0009] Furthermore, before the first round of testing begins, the highest historical energy efficiency value of the operating parameter combination is selected from the corresponding group based on the current user load, and a test request for this round is issued. If the highest historical energy efficiency value corresponds to multiple operating parameter combinations, then one of these operating parameter combinations is selected.

[0010] Furthermore, it receives the energy efficiency test results obtained from the operation of the central air conditioning system in response to the test request, and outputs the next round of test instructions based on the mapping relationship table in the preset test mechanism.

[0011] Furthermore, the test is repeated multiple times. When the number of operating parameter combinations that have been run reaches a set proportion of the total number of operating parameter combinations in the database, the operating parameter combination with the highest energy efficiency is output as the final test result and the final test result is configured into the central air conditioning system.

[0012] Furthermore, the system obtains the cooling tower outlet water temperature setpoint that enables the energy-saving optimization control system to achieve the highest efficiency, and increases or decreases the number of operating cooling towers and adjusts the operating frequency of the cooling towers based on the cooling tower outlet water temperature setpoint.

[0013] The beneficial effects of this invention include: This invention provides a BIM-based intelligent temperature control design system for air conditioning, comprising: a data acquisition module for acquiring air conditioning data and environmental data, and establishing a BIM model based on the air conditioning data to simulate the air conditioning's adjustment state in the environment; and an output command module for outputting a start command when the user load changes or when the central air conditioning system operates under the same combination of operating parameters for a certain period of time. The system utilizes BIM simulation to generate a 3D model output, enabling visualized air conditioning management. Combined with air conditioning cooling / heating scenarios, the system intelligently adjusts the temperature in the target space, improving the adaptability of temperature control to the target space and thus enhancing the technical effect of air conditioning management quality. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a schematic diagram of the structure of an intelligent air conditioning temperature control design system based on BIM technology in an embodiment of the present invention; Figure 2 This is a temperature control flowchart of an intelligent air conditioning temperature regulation design system based on BIM technology according to the present invention. Figure 3 This is a construction layout diagram of an intelligent air conditioning temperature control design system based on BIM technology according to the present invention. Detailed Implementation

[0016] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0017] This invention discloses an intelligent air conditioning temperature control design system based on BIM technology, comprising: The data acquisition module acquires air conditioning data and environmental data, and combines the air conditioning data to build a BIM model to simulate the air conditioning's regulation state in the environment; The output command module outputs a start command when the user load changes or when the central air conditioning system reaches the time condition under the same combination of operating parameters.

[0018] The parameter adjustment module handles the operating parameters, including the operating frequency and number of cooling water pumps, and the operating speed and number of cooling tower fans. The operating frequency and number of chilled water pumps are adaptively adjusted based on user load. Upon receiving a signal from the central control station of the central air conditioning system indicating a decrease in chilled water flow, the module confirms a change in user load. When the central air conditioning system operates continuously under a certain operating parameter combination for a preset time threshold, the module confirms that the system has met the time requirement under that parameter combination and performs temperature compensation. The data processing module acquires an indoor temperature distribution image, calculates the compensation temperature, and determines whether the compensation temperature exceeds the specified range. If it does, temperature compensation is performed; otherwise, the compensation temperature is output. A start command is output when either of the above two conditions is met.

[0019] The test module responds to the start command by outputting a test command to select the system's operating mode; in response to the test command, it selects a combination of operating parameters from the preset database and sends a test request to the central air conditioning system based on that combination of operating parameters.

[0020] The database's operating parameter combinations are divided into multiple groups, with each user load corresponding to one group. There is a one-to-one correspondence between groups and user loads, and each operating parameter combination within a group corresponds to a historical energy efficiency value obtained from historical data. This historical energy efficiency value is calculated by averaging the energy efficiency values ​​obtained each time a single operating parameter combination within a group is run, assuming the same user load. Before the first round of testing, the operating parameter combination with the highest historical energy efficiency value within the corresponding group is selected based on the current user load, and a test request for this round is issued. If the highest historical energy efficiency value corresponds to multiple operating parameter combinations, one of these combinations is randomly selected.

[0021] Receive the energy efficiency test results obtained from the operation of the central air conditioning system in response to the test request, and output the next round of test instructions based on the mapping relationship table between the energy efficiency test results and the preset test mechanism.

[0022] Repeat the test multiple times. When the number of operating parameter combinations that have been run reaches the set proportion of the total number of operating parameter combinations in the database, output the operating parameter combination with the highest energy efficiency as the final test result and configure the final test result into the central air conditioning system.

[0023] The system obtains the cooling tower outlet water temperature setpoint that enables the energy-saving optimization control system to achieve the highest efficiency, and increases or decreases the number of operating cooling towers and adjusts the operating frequency of the cooling towers based on the cooling tower outlet water temperature setpoint.

[0024] The control algorithm is as follows:

[0025] Where CPE is the energy efficiency ratio of the central air conditioning system, Qcooling is the cooling capacity of the central air conditioning system, and WChiller is the chilled water capacity. The power consumption of the unit is as follows: WChille dpum is the power consumption of the chilled water pump, WCooling pump is the power consumption of the cooling water pump, and WCoolingTower is the power consumption of the cooling tower.

[0026] Wherein, SCOP is the overall cooling performance coefficient of the central air conditioning system, COP is the performance coefficient of the central air conditioning system, and WSYS is the power consumption of the energy-saving optimization control system.

[0027] Coefficient of Performance (COP) The Comprehensive Coefficient of Performance (SCOP) is the Seasonal Coefficient of Performance. Based on the COP / SCOP results, the optimal operating scheme is selected. When Qcooling is constant, the CPE function in the control algorithm can be transformed into the power and Pk of each energy-consuming component:

[0028] Where Pk is the total power consumption of each energy-consuming component in the k-th time period.

[0029] The process involves acquiring air conditioning and environmental data, and then using this data to build a BIM model that simulates the air conditioning system's regulation state within the environment. Specifically: acquiring air conditioning engineering design information and construction environment information; analyzing these information to determine modeling complexity; analyzing the air conditioning engineering design information to obtain construction area, piping layout design information, and component processing efficiency; performing engineering complexity analysis based on the construction area, piping layout design information, and component processing efficiency to obtain an engineering complexity threshold; analyzing the construction environment information to obtain construction space constraints and environmentally acceptable piping paths; performing environmental complexity analysis based on construction space constraints and environmentally acceptable piping paths to obtain an environmental complexity threshold; and finally, using both the engineering complexity threshold and the environmental complexity threshold, determining the modeling complexity. Based on the modeling complexity, configure the control parameter set for the data acquisition device's acquisition terminal; import the control parameter set into the control function, and through the data acquisition device's acquisition terminal, carry the control function to control the data acquisition device to collect modeling data, acquiring engineering modeling data; transmit the engineering modeling data to the BIM simulation system for simulation modeling (the engineering modeling data is on-site data; transmitting the engineering modeling data to the BIM simulation system ensures the model's fidelity), obtaining the first visualization model; connect the BIM simulation system's terminal to the GIS positioning system's terminal (the BIM simulation system's terminal and the GIS positioning system's terminal establish a communication connection; simply put, the communication connection is achieved through signal transmission). The communication network between the BIM simulation system terminal and the GIS positioning system terminal is defined as a model calibration platform. The model calibration platform is used to perform scene overlay calibration on the first visualization model to obtain a second visualization model. Based on the second visualization model, visualized air conditioning management is performed. For efficient control of the air conditioning system, BIM software technology can significantly shorten calculation time and greatly improve the accuracy and efficiency of the obtained data. Furthermore, BIM software allows for adjustments to the design of prefabricated buildings, making intelligent temperature regulation within the building safer and more effective.

[0030] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A BIM technology-based air conditioning temperature intelligent adjustment design system, characterized in that, Comprise: Data acquisition module, get air conditioning data and environmental data, and combined with air conditioning data to establish BIM model, simulate air conditioning in the environment in the adjustment state; Output instruction module, when the user load changes or the central air conditioning system runs under the same operating parameter combination to reach the time condition, output the start instruction; Parameter adjustment module, the operating parameter combination here includes the running frequency and number of cooling water pump, and the running speed and number of cooling tower fan; The running frequency and number of chilled water pump will be adjusted adaptively according to the user load; After receiving the signal that the chilled water flow of the central control station of the central air conditioning system is smaller, it is confirmed that the user load changes; When the central air conditioning system runs under a certain operating parameter combination for a predetermined time threshold, it is confirmed that the central air conditioning system runs under the same operating parameter combination to reach the time condition; When one of the above two conditions is met, output the start instruction; Test module, response start instruction output selection system operation mode test instruction; Response test instruction in the preset database to select an operating parameter combination, and according to the operating parameter combination to the central air conditioning system to issue this round of test request.

2. The air conditioning temperature intelligent adjustment design system based on BIM technology according to claim 1, wherein The operating parameter combination in the database is divided into multiple groups, each user load corresponds to a group, and each group corresponds to a user load and each operating parameter combination in each group corresponds to a historical energy efficiency value obtained from historical data.

3. The BIM technology-based air conditioning temperature intelligent adjustment design system of claim 2, wherein, The historical energy efficiency value obtained from the historical data is that: under the premise of the same user load, the energy efficiency value obtained by each operating parameter combination in the group is averaged, and the average value is the historical energy efficiency value corresponding to the operating parameter combination in the corresponding group.

4. The air conditioning temperature intelligent regulation design system based on BIM technology according to claim 3, characterized in that, Before the first round of test starts, first select a historical energy efficiency value highest operating parameter combination in the corresponding group according to the current user load, and issue this round of test request, if the highest historical energy efficiency value corresponds to multiple operating parameter combinations, select one of them.

5. The BIM technology-based air conditioning temperature intelligent adjustment design system of claim 4, wherein, Receive the energy efficiency detection result obtained by the central air conditioning system in response to the test request, and output the next round of test instruction based on the mapping relationship table in the preset detection mechanism.

6. The BIM technology-based air conditioning temperature intelligent adjustment design system of claim 5, wherein, Repeat multiple rounds of test, when the number of operating parameter combinations that have been run reaches the set proportion of the total number of all operating parameter combinations in the database, output the operating parameter combination with the highest energy efficiency as the final detection result and configure the final detection result to the central air conditioning system.

7. The BIM technology-based air conditioning temperature intelligent adjustment design system of claim 6, wherein, Get the cooling tower outlet water temperature set value that can make the energy saving optimization control system efficiency reach the highest, increase or decrease the number of operating cooling towers and adjust the operating frequency of the cooling tower according to the cooling tower outlet water temperature set value.

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