Method and device for establishing simulation model of heating, ventilation and temperature control system of underground powerhouse

Abstract

The invention relates to the technical field of underground powerhouse heating and ventilation temperature control, and discloses an underground powerhouse heating and ventilation temperature control system simulation model establishment method and device, and the method comprises the steps: obtaining the operation data of equipment in an underground powerhouse, and building an underground powerhouse equipment model based on the operation data of the equipment in the underground powerhouse; the underground powerhouse equipment model comprises a cooler model, a water pump model, a heat exchanger model, a pipeline air duct model, a fan model and a room airflow agent model; and acquiring a pipeline topology and an air duct space structure, and integrating and connecting the underground powerhouse equipment models according to the pipeline topology and the air duct space structure to obtain the simulation model of the underground powerhouse heating, ventilation and temperature control system. According to the method, the simulation model of the heating, ventilation and temperature control system of the underground powerhouse is accurately constructed, and the operation optimization of the heating, ventilation and temperature control system of the underground powerhouse is ensured.

Description

Technical Field

[0001] The invention relates to the technical field of HVAC temperature control of underground plant buildings, and in particular to a method and device for establishing a simulation model of a HVAC temperature control system of an underground plant building. Background Art

[0002] As society's demand for sustainable development and security continues to increase, the development of underground space has become an important trend in infrastructure construction. The application of underground space not only effectively saves precious ground land resources, but also provides higher security and environmental adaptability for key infrastructure. By cleverly utilizing the advantages of terrain and combining advanced engineering technology, these underground facilities can achieve efficient operation and strong protection capabilities to better serve modern society.

[0003] Therefore, it is particularly important to optimize the internal environmental control system of underground workshops. The HVAC temperature control system is one of the key links to ensure the safety and comfort of underground workplaces, and it is also an important factor affecting the energy consumption of the entire facility.

[0004] However, underground factories have a large number of equipment and complex and diverse spaces. The design method of the HVAC temperature control system is difficult to achieve the requirements of real-time prediction of the status of the HVAC temperature control system, and thus it is impossible to optimize the control of the HVAC temperature control system. Summary of the invention

[0005] In view of this, the present invention provides a method and device for establishing a simulation model of a HVAC temperature control system of an underground plant, so as to solve the problem that the HVAC temperature control system cannot be optimally controlled.

[0006] In a first aspect, the present invention provides a method for establishing a simulation model of a HVAC temperature control system of an underground plant, the method comprising:

[0007] Obtain the equipment operation data in the underground plant, and establish an underground plant equipment model based on the equipment operation data in the underground plant; the underground plant equipment model includes a chiller model, a water pump model, a heat exchanger model, a pipeline duct model, a fan model and a room airflow proxy model;

[0008] The pipeline topology and air duct space structure are obtained, and the underground plant equipment model is integrated and connected according to the pipeline topology and air duct space structure to obtain the simulation model of the underground plant HVAC temperature control system.

[0009] The present embodiment provides a method for establishing a simulation model of an underground plant HVAC temperature control system. The method establishes an underground plant equipment model based on the equipment operation data in the underground plant; the underground plant equipment model is integrated and connected according to the pipeline topology and the air duct space structure to obtain a simulation model of the underground plant HVAC temperature control system; wherein, by classifying the underground plant HVAC temperature control system, a model is constructed for each component to obtain a chiller model, a water pump model, a heat exchanger model, a pipeline air duct model, a fan model and a room airflow proxy model, thereby realizing the refinement of the underground plant HVAC temperature control system, and according to the The underground plant equipment models are integrated and connected according to the pipeline topology and duct space structure, realizing the accurate construction of the simulation model of the underground plant HVAC temperature control system. The simulation model of the underground plant HVAC temperature control system can quickly calculate the temperature rise in the room and the energy consumption of each equipment according to the different temperature and flow conditions of the chiller cooling water and chilled water when the heat sources in different rooms generate heat. It can further optimize the operation of the underground plant HVAC temperature control system and realize real-time prediction of the status of the HVAC temperature control system, ensuring the maximum energy utilization efficiency while meeting the requirements of environmental comfort.

[0010] In an optional implementation, establishing an underground plant equipment model based on the equipment operation data in the underground plant includes:

[0011] The equipment operation data in the underground plant is used to fit the parameters of the efficiency polynomial regression model and obtain the chiller model.

[0012] The water pump model is obtained by fitting the parameters of the power flow polynomial model using the equipment operation data in the underground powerhouse.

[0013] The heat exchanger model was obtained by fitting the equipment operation data in the underground powerhouse using the effective heat transfer unit method model.

[0014] The power flow cubic relationship model is used to fit the equipment operation data in the underground powerhouse to obtain the fan model;

[0015] A thermal resistance model was established and the data of the equipment operation in the underground plant was used to verify the thermal resistance model and obtain the pipeline air duct model;

[0016] Based on the equipment operation data in the underground plant, the room airflow proxy model was constructed using the orthogonal decomposition method and artificial neural network.

[0017] The present embodiment provides a method for establishing a simulation model of an underground factory HVAC temperature control system. An analytical model is used to describe the equipment, pipes and air ducts in the underground factory. The analytical model has good generalization ability, can adapt to a variety of working conditions, and has a low demand for training data, thereby effectively reducing the computational burden in the model construction process. For three-dimensional room spaces with more complex structures, since it is difficult to achieve sufficient accuracy through analytical models, a mathematical model based on actual data is used to ensure the accuracy and efficiency of the simulation results.

[0018] In an optional implementation, a thermal resistance model is established, and the thermal resistance model is verified using the equipment operation data in the underground plant to obtain a pipeline air duct model, including:

[0019] Determine the inlet temperature, flow rate and outlet temperature of the pipeline duct, as well as the total thermal resistance from the fluid to the outside world based on the equipment operation data in the underground plant;

[0020] A thermal resistance model is established based on the inlet temperature, flow rate and outlet temperature of the pipeline air duct, as well as the total thermal resistance from the fluid to the outside world;

[0021] The measured data of heat loss is obtained, and the thermal resistance model is verified by using the measured data of heat loss to obtain the pipeline air duct model.

[0022] The present embodiment provides a method for establishing a simulation model of an underground factory building HVAC temperature control system. By establishing a thermal resistance model for analyzing the difference between the inlet temperature, flow rate and outlet temperature of the pipeline and air duct, an accurate description of the heat loss in the pipeline and air duct is achieved. The thermal resistance model is verified through actual measured data of heat loss, thereby ensuring the accuracy of the pipeline and air duct model.

[0023] In an optional implementation, based on the equipment operation data in the underground plant, the room airflow proxy model is constructed by using the orthogonal decomposition method and artificial neural network, including:

[0024] Establishing a CFD simulation model, verifying the CFD simulation model, and obtaining a verified CFD simulation model;

[0025] A data sample group is obtained, and based on the data sample group, a CFD simulation result is generated using a verified CFD simulation model; wherein the data sample group includes multiple sets of equipment inlet and outlet air boundary conditions and heat source heat generation;

[0026] The orthogonal decomposition method is used to reduce the dimension of the CFD simulation results, and the CFD simulation results after the dimension reduction are used as the training data of the artificial neural network, and the training data is used to train the artificial neural network;

[0027] Map the prediction results corresponding to the trained artificial neural network to the physical space to obtain the reconstructed temperature field structure;

[0028] A room airflow proxy model is constructed based on the CFD simulation results and the reconstructed temperature field structure.

[0029] This embodiment provides a method for establishing a simulation model of an underground factory building HVAC temperature control system. When processing the data model of a three-dimensional room, a verified CFD simulation model is first used to generate a detailed data set. Subsequently, a method combining orthogonal decomposition technology with an artificial neural network is used to construct the model. The above method not only ensures the richness of the data set and the accuracy of the model, but also reduces the dimension of the original CFD data through orthogonal decomposition, further reduces the number of artificial neural network layers and parameters required, significantly improves the computational efficiency of the model and simplifies the overall complexity.

[0030] In an optional implementation, the underground plant equipment model is integrated and connected according to the pipeline topology and the air duct space structure to obtain a simulation model of the HVAC temperature control system of the underground plant, including:

[0031] Use pipeline topology to connect the chiller model, water pump model, heat exchanger model and pipeline duct model to build a water system model;

[0032] The fan model, the pipe duct model and the room airflow proxy model are connected by using the air duct space structure to construct the wind system model;

[0033] A simulation model of the HVAC temperature control system of the underground plant is constructed based on the water system model, heat exchanger model and wind system model.

[0034] This embodiment provides a method for establishing a simulation model of an underground factory building HVAC temperature control system. By constructing a water system model and a wind system model, the two subsystem models responsible for air flow and water circulation are integrated, and the two subsystems responsible for air flow and water circulation are connected through a heat exchanger model to ensure that the heat exchange process of the HVAC temperature control system is correctly simulated.

[0035] In an optional implementation, it also includes:

[0036] The simulation model of the HVAC temperature control system of the underground plant is used to predict the status of the HVAC temperature control system, and the status of the HVAC temperature control system is used to optimize the control of the HVAC temperature control system of the underground plant.

[0037] In a second aspect, the present invention provides a device for establishing a simulation model of a HVAC temperature control system of an underground plant, the device comprising:

[0038] Establish a module for obtaining the equipment operation data in the underground plant, and establish an underground plant equipment model based on the equipment operation data in the underground plant; the underground plant equipment model includes a chiller model, a water pump model, a heat exchanger model, a pipeline duct model, a fan model and a room airflow proxy model;

[0039] The integration module is used to obtain the pipeline topology and air duct space structure, integrate and connect the underground plant equipment model according to the pipeline topology and air duct space structure, and obtain the simulation model of the underground plant HVAC temperature control system.

[0040] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for establishing a simulation model of an underground factory HVAC temperature control system according to the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0041] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute a method for establishing a simulation model of an underground factory building HVAC temperature control system according to the first aspect or any corresponding embodiment thereof.

[0042] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions, which are used to enable a computer to execute the method for establishing a simulation model of an underground plant HVAC temperature control system according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 It is a flow chart of a method for establishing a simulation model of a HVAC temperature control system of an underground plant according to an embodiment of the present invention;

[0045] Figure 2 is a flow chart of another method for establishing a simulation model of a HVAC temperature control system of an underground plant according to an embodiment of the present invention;

[0046] Figure 3 is a schematic diagram of establishing an underground plant equipment model according to an embodiment of the present invention;

[0047] Figure 4It is a flowchart of another method for establishing a simulation model of a HVAC temperature control system of an underground plant according to an embodiment of the present invention;

[0048] Figure 5 is a schematic structural diagram of a water system model according to an embodiment of the present invention;

[0049] Figure 6 is a schematic structural diagram of a wind system model according to an embodiment of the present invention;

[0050] Figure 7 is a schematic diagram of connecting a water system model and a wind system model in series through a heat exchanger model according to an embodiment of the present invention;

[0051] Figure 8 is a structural schematic diagram of a simulation model of a HVAC temperature control system for an underground plant according to an embodiment of the present invention;

[0052] Fig. 9 It is a structural block diagram of a device for establishing a simulation model of a HVAC temperature control system of an underground plant according to an embodiment of the present invention;

[0053] Fig.10 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0055] During the design phase, HVAC temperature control systems usually focus on simulation verification under a small number of working conditions to ensure basic functions; but in the face of increasing pressure from safety standards and "dual carbon" goals, more attention is paid to refined management during system operation. Therefore, it is necessary to accurately predict and adjust the status of the HVAC temperature control system in real time to achieve the goal of energy conservation and emission reduction.

[0056] However, underground powerhouses have numerous equipment and complex and diverse spaces. Design methods for HVAC temperature control systems, such as computational fluid dynamics (CFD) simulation or scaled experiments, are difficult to meet the needs of real-time prediction, let alone further optimization control. Therefore, a new method is needed to improve the speed and accuracy of simulation and to be able to make dynamic adjustments based on actual operating conditions.

[0057] In order to solve the above technical problems, an embodiment of the present invention provides a method for establishing a simulation model of an underground plant HVAC temperature control system. The method establishes a simulation model of an underground plant HVAC temperature control system based on the unique conditions of the underground environment. Under the condition of the heat source heat output in a given room and different chiller cooling water temperature flow rates and chiller freezing water temperature flow rates, the temperature rise of the heat source in the room and the energy consumption of each device are quickly calculated, which solves the problem that it is difficult to meet the real-time prediction requirements by using CFD simulation or scaled experiments. It can be used as a real-time calculation basis for refined operation, and further combined with optimization algorithms and automatic control to achieve the purpose of optimized operation.

[0058] The embodiment of the present invention provides a method for establishing a simulation model of a HVAC temperature control system of an underground factory building. It should be noted that the method for establishing a simulation model of a HVAC temperature control system of an underground factory building provided by the embodiment of the present invention may be executed by a device for establishing a simulation model of a HVAC temperature control system of an underground factory building. The device for establishing a simulation model of a HVAC temperature control system of an underground factory building may be implemented as part or all of an electronic device through software, hardware, or a combination of software and hardware. The electronic device may be a server or a terminal. The server in the embodiment of the present application may be a single server or a server cluster composed of multiple servers. The terminal in the embodiment of the present application may be a smart phone, a personal computer, a tablet computer, a wearable device, an intelligent robot, or other intelligent hardware devices. In the following method embodiments, the execution subject is an electronic device as an example for explanation.

[0059] According to an embodiment of the present invention, an embodiment of a method for establishing a simulation model of an underground plant HVAC temperature control system is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0060] In this embodiment, a method for establishing a simulation model of a HVAC temperature control system of an underground plant is provided, which can be used for the above-mentioned electronic equipment. Figure 1 FIG. 1 is a flow chart of a method for establishing a simulation model of a HVAC temperature control system of an underground plant according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0061] Step S101, obtain the equipment operation data in the underground plant, and establish an underground plant equipment model based on the equipment operation data in the underground plant; the underground plant equipment model includes a chiller model, a water pump model, a heat exchanger model, a pipeline duct model, a fan model and a room airflow proxy model.

[0062] Specifically, the equipment in the underground plant is divided into six categories: chillers, water pumps, heat exchangers, fans, pipeline ducts and rooms, and the corresponding model is selected for each type of equipment for description and prediction.

[0063] Step S102, obtaining the pipeline topology and the air duct space structure, integrating and connecting the underground plant equipment model according to the pipeline topology and the air duct space structure, and obtaining a simulation model of the HVAC temperature control system of the underground plant.

[0064] Specifically, the HVAC temperature control system simulation model of the underground plant is used to predict the state of the HVAC temperature control system, and the HVAC temperature control system state is used to optimize the control of the HVAC temperature control system of the underground plant.

[0065] Furthermore, since the composition of the simulation model of the HVAC temperature control system of the underground factory is based on the analytical model and the data model, the temperature rise of the heat source in the room and the energy consumption of each device can be quickly calculated under the conditions of a given heat source heat value in the underground factory room and different chiller cooling water temperature flow rates and chiller freezing water temperature flow rates, and then the HVAC temperature control system of the underground factory can be optimized and controlled based on the calculated temperature rise of the heat source in the room and the energy consumption of each device.

[0066] The present embodiment provides a method for establishing a simulation model of an underground plant HVAC temperature control system. The method establishes an underground plant equipment model based on the equipment operation data in the underground plant; the underground plant equipment model is integrated and connected according to the pipeline topology and the air duct space structure to obtain a simulation model of the underground plant HVAC temperature control system; wherein, by classifying the underground plant HVAC temperature control system, a model is constructed for each component to obtain a chiller model, a water pump model, a heat exchanger model, a pipeline air duct model, a fan model and a room airflow proxy model, thereby realizing the refinement of the underground plant HVAC temperature control system, and according to the The underground plant equipment models are integrated and connected according to the pipeline topology and duct space structure, realizing the accurate construction of the simulation model of the underground plant HVAC temperature control system. The simulation model of the underground plant HVAC temperature control system can quickly calculate the temperature rise in the room and the energy consumption of each equipment according to the different temperature and flow conditions of the chiller cooling water and chilled water when the heat sources in different rooms generate heat. It can further optimize the operation of the underground plant HVAC temperature control system and realize real-time prediction of the status of the HVAC temperature control system, ensuring the maximum energy utilization efficiency while meeting the requirements of environmental comfort.

[0067] In this embodiment, a method for establishing a simulation model of a HVAC temperature control system of an underground plant is provided, which can be used for the above-mentioned electronic equipment. Figure 2 FIG. 1 is a flow chart of a method for establishing a simulation model of a HVAC temperature control system of an underground plant according to an embodiment of the present invention. Figure 2 As shown, the process includes the following steps:

[0068] Step S201, obtain the equipment operation data in the underground plant, and establish an underground plant equipment model based on the equipment operation data in the underground plant; the underground plant equipment model includes a chiller model, a water pump model, a heat exchanger model, a pipeline duct model, a fan model and a room airflow proxy model.

[0069] Specifically, Figure 3 As shown, the above step S201 includes:

[0070] Step S2011, using the equipment operation data in the underground plant to perform parameter fitting on the efficiency polynomial regression model to obtain a chiller model.

[0071] Specifically, the chiller efficiency is expressed by a polynomial regression model, which is fitted based on operating data and reflects the complex relationship between energy efficiency and cooling water inlet / outlet temperature, chilled water inlet / outlet temperature, cooling water flow rate, chilled water flow rate and chiller power.

[0072] Furthermore, the efficiency polynomial regression model of the chiller is used to describe the COP (Cooling Performance Ratio, energy efficiency ratio), cooling water inlet temperature t ci , Cooling water outlet temperature t co , Cooling water flow m c , Chilled water inlet temperature t ei , Chilled water outlet temperature t eo , Chilled water flow m e And the power of the cooling machine P l The relationship between them, where the calculation formula of the intermediate quantity is as follows:

[0073] COP = a 1 +a 2 Q e +a 3 ·t ei +a 4 ·t ci +a 5 Q e 2 +a 6 ·t ei 2 +a 7 ·t ci 2 +a 8 Q e ·t ei +a 9 Q e ·t ci +a 10 ·t ei ·t ci (1)

[0074] P l =Q e / COP (2)

[0075] t eo =t ei -Q e / m e C p (3)

[0076] t co =t ci +(Q e +P l ) / m c C p (4)

[0077] Among them, a 1 -a 10 All are unknown coefficients, Q e is the cooling capacity, C p is the heat capacity of water.

[0078] Furthermore, the linear regression method was used to analyze the equipment operation data in the underground powerhouse. 1 -a 10 The fitting was performed to determine the refrigeration machine model with the relative error between the predicted result and the actual data within ±5%.

[0079] Step S2012, using the equipment operation data in the underground powerhouse to perform parameter fitting on the power flow polynomial model to obtain a water pump model.

[0080] Specifically, the water pump performance adopts a power-flow polynomial model, which is fitted by the equipment operation data in the underground powerhouse to describe the characteristics of the water pump power changing with flow under different working conditions.

[0081] Furthermore, the pump uses a power-flow polynomial to describe the rated power P s And pump flow m s The relationship between , the expression of the water pump model is as follows:

[0082]

[0083] Among them, P rate1 and m rate1 They are the rated power and rated flow of the pump respectively.

[0084] Furthermore, the linear regression method was used to analyze the b 1 -b 4 The fitting was performed to determine the water pump model with the relative error between the predicted result and the actual data within ±5%.

[0085] Step S2013, using the effective heat transfer unit method model to fit the equipment operation data in the underground powerhouse to obtain a heat exchanger model.

[0086] Specifically, the heat exchanger adopts the efficiency-heat transfer unit method model to describe the relationship between the inlet and outlet temperatures and flow rates at both ends of the heat exchanger; for example, the heat exchanger is a water-to-air cooling coil heat exchanger with a countercurrent flow and an inlet water temperature t wi , water outlet temperature t wo , water flow m w And the inlet air temperature t ai , outlet air temperature t ao 、Air volume m a The relationship between them is:

[0087]

[0088] Q=εC a,p (t wi -t ai ) (8)

[0089] t wo =t wi -Q / C w,p (9)

[0090] t ao =t ai +Q / C w,p (10)

[0091] Where NTU is the number of heat transfer units, K is the average heat transfer coefficient, and A is the heat transfer area C. a,p and C w,p are the specific heat capacities of air and water respectively, ε is the efficiency, and Q is the heat transfer capacity.

[0092] Step S2014, using the power flow cubic relationship model to fit the equipment operation data in the underground powerhouse to obtain a fan model.

[0093] Specifically, the working state of the fan is simulated using a power-flow cubic relationship model to reflect the energy consumption of the fan under different air volumes.

[0094] Furthermore, the fan adopts a power-flow cubic relationship model to describe the fan power P f And fan air volume m f The relationship between , the expression of the fan model is as follows:

[0095]

[0096] Among them, P rate2 and m rate2are the rated power and rated flow of the fan respectively.

[0097] Step S2015, establishing a thermal resistance model, using the equipment operation data in the underground plant to verify the thermal resistance model, and obtaining a pipeline air duct model.

[0098] Specifically, the heat loss in the pipes and ducts was evaluated by calculating the thermal resistance, and a relationship model was established to analyze the difference between the inlet temperature, flow rate and outlet temperature. This model was verified by measured data.

[0099] In some optional implementations, the above step S2012 includes:

[0100] Step a1, determining the inlet temperature, flow rate and outlet temperature of the pipeline air duct, and the total thermal resistance from the fluid to the outside based on the equipment operation data in the underground plant.

[0101] Step a2, establishing a thermal resistance model based on the inlet temperature, flow rate and outlet temperature of the pipeline air duct, and the total thermal resistance from the fluid to the outside.

[0102] Specifically, the heat loss in the pipes and ducts is evaluated by calculating the thermal resistance. A relationship model that can be used to analyze the difference between the inlet temperature, flow rate and outlet temperature is established. That is, the heat loss model of all pipes and ducts is calculated by thermal resistance, and the model of the inlet and outlet temperature difference Δt (i.e., thermal resistance model) is established. Its expression is as follows:

[0103] Δt=(T in +Δt / 2-T a ) / (R total mxD p ) (12)

[0104] Among them, R total is the total thermal resistance between the fluid and the outside world, m is the flow rate of the pipeline duct, T a is the ambient temperature of the pipeline air duct, T in is the inlet temperature of the pipe duct.

[0105] Step a3, obtaining the measured data of heat loss, using the measured data of heat loss to verify the thermal resistance model, and obtaining the pipeline air duct model.

[0106] Step S2016, based on the equipment operation data in the underground plant, the room airflow proxy model is constructed using the orthogonal decomposition method and artificial neural network.

[0107] Specifically, the thermodynamic behavior inside the room is constructed with the help of computational fluid dynamics (CFD) simulation combined with proper orthogonal decomposition (POD) technology and artificial neural network (ANN) to build a data-driven model (i.e., room airflow proxy model): first, create a detailed CFD simulation model, taking into account the specific structure and heat source conditions of the room; second, use a systematic sampling method to generate a variety of boundary conditions and heat source input combinations to form a training data set; finally, use POD to reduce the dimension of the CFD results and use this as the training set of the ANN. The trained ANN prediction results are then inversely transformed through POD to obtain the temperature field structure of the physical space, ultimately achieving fast and accurate prediction of indoor temperature distribution.

[0108] In some optional implementations, the above step S2016 includes:

[0109] Step b1, establishing a CFD simulation model, verifying the CFD simulation model, and obtaining a verified CFD simulation model.

[0110] Specifically, a CFD simulation model of two rooms in the underground factory building is established. The CFD simulation model is modeled separately according to the structure of the two rooms and the design conditions of the heat source. The inlet and outlet air boundary conditions of the design conditions and the heating value of the heat source are verified using measured data. The verified CFD simulation model is used to generate a data set for the training data model.

[0111] Step b2, obtaining a data sample group, and generating CFD simulation results based on the data sample group using the verified CFD simulation model; wherein the data sample group includes multiple sets of equipment inlet and outlet air boundary conditions and heat source heating values.

[0112] Specifically, the system's data sample group has an inlet air volume ranging from 0 to 720,000 cubic meters per hour, the outlet air volume is equal to the inlet air volume, the inlet air temperature is between 15 degrees Celsius and 30 degrees Celsius, and the total heat output of multiple devices is between 0 and 4340 kW. The system's data samples are sampled to generate data sample groups of various inlet and outlet air boundary conditions and heat source heat output. There are a total of 300 data sample groups, and the above data sample groups are used as setting parameters for CFD simulation. The verified CFD simulation model is used to generate a series of CFD simulation results, and the temperature field data in the CFD simulation results under different setting parameters are extracted as a training data set.

[0113] Step b3, using orthogonal decomposition method to perform dimensionality reduction processing on the CFD simulation results, and using the CFD simulation results after dimensionality reduction processing as training data of the artificial neural network, and using the training data to train the artificial neural network.

[0114] Specifically, the eigenorthogonal decomposition is used to reduce the order of all CFD simulation results to generate orthogonal basis matrices and POD coefficients, and the reduced POD coefficients are used as training data for the artificial neural network.

[0115] Furthermore, the specific steps of reducing the order of all CFD simulation results by using eigenorthogonal decomposition include: sorting the CFD simulation results to obtain the original data matrix; calculating the covariance matrix of the original data matrix; performing eigenvalue decomposition on the covariance matrix to obtain the eigenvector matrix; sorting the eigenvalues ​​from large to small and selecting the first k principal components; projecting the CFD simulation results onto the selected first k principal components to obtain the POD coefficients and orthogonal basis matrix after dimensionality reduction.

[0116] Step b4, mapping the prediction results corresponding to the trained artificial neural network to the physical space to obtain the reconstructed temperature field structure.

[0117] Specifically, the prediction results of the trained artificial neural network, that is, the predicted orthogonal basis matrix, are mapped back to the physical space, the temperature results are reconstructed, and the reconstructed temperature field structure is obtained.

[0118] Step b5, constructing a room airflow proxy model based on the CFD simulation results and the reconstructed temperature field structure.

[0119] Specifically, the reconstructed temperature field structure is re-input into the intrinsic orthogonal decomposition-artificial neural network for training, and the trained intrinsic orthogonal decomposition-artificial neural network is used as the room airflow proxy model.

[0120] Among them, assuming that the number of artificial neural network layers is 3, it only takes 9 seconds for the trained appropriate orthogonal decomposition-artificial neural network to predict the temperature field of a room under a set of inlet and outlet air boundary conditions and heat source heat.

[0121] Step S202, obtain the pipeline topology and air duct space structure, integrate and connect the underground plant equipment model according to the pipeline topology and air duct space structure, and obtain the underground plant HVAC temperature control system simulation model. Figure 1 Step S102 of the illustrated embodiment will not be described in detail here.

[0122] The present embodiment provides a method for establishing a simulation model of an underground factory HVAC temperature control system. An analytical model is used to describe the equipment, pipes and air ducts in the underground factory. The analytical model has good generalization ability, can adapt to a variety of working conditions, and has a low demand for training data, thereby effectively reducing the computational burden in the model construction process. For three-dimensional room spaces with more complex structures, since it is difficult to achieve sufficient accuracy through analytical models, a mathematical model based on actual data is used to ensure the accuracy and efficiency of the simulation results.

[0123] In this embodiment, a method for establishing a simulation model of a HVAC temperature control system of an underground plant is provided, which can be used for the above-mentioned electronic equipment. Figure 4 FIG. 1 is a flow chart of a method for establishing a simulation model of a HVAC temperature control system of an underground plant according to an embodiment of the present invention. Figure 4 As shown, the process includes the following steps:

[0124] Step S401, obtain the equipment operation data in the underground plant, and establish the underground plant equipment model based on the equipment operation data in the underground plant; the underground plant equipment model includes a chiller model, a water pump model, a heat exchanger model, a pipeline duct model, a fan model and a room airflow proxy model. For details, please refer to Figure 2 Step S201 of the illustrated embodiment will not be described in detail here.

[0125] Step S402, obtaining the pipeline topology and the air duct space structure, integrating and connecting the underground plant equipment model according to the pipeline topology and the air duct space structure, and obtaining a simulation model of the HVAC temperature control system of the underground plant.

[0126] Specifically, the above step S402 includes:

[0127] Step S4021, using the pipeline topology to connect the chiller model, the water pump model, the heat exchanger model and the pipeline air duct model to build a water system model.

[0128] Step S4022, using the air duct space structure to connect the fan model, the pipeline air duct model and the room airflow proxy model to construct a wind system model.

[0129] Specifically, Figure 5-6 As shown, after establishing models for the six types of equipment and spaces involved in the factory, based on the pipeline topology and air duct space structure, all equipment and spaces are connected in series to establish subsystem models to obtain water system models and wind system models.

[0130] Step S4023, constructing a simulation model of the HVAC temperature control system of the underground plant based on the water system model, the heat exchanger model and the wind system model.

[0131] Specifically, the water system model and the wind system model are connected using the heat exchanger model, and the heat exchanger inlet and outlet water temperature flow and the heat exchanger inlet and outlet wind temperature flow are associated using the heat exchanger model to obtain the simulation model of the underground plant HVAC temperature control system.

[0132] Furthermore, if Figure 7 As shown, the two subsystem models are connected in series through the heat exchanger model responsible for the heat exchange of the air duct and the pipeline, and the inlet and outlet water temperature flow and the inlet and outlet air temperature flow of the heat exchanger are associated through the heat exchanger model; wherein, the two subsystem models responsible for air flow and water flow circulation are connected through the heat exchanger model to ensure that the heat exchange process of the entire HVAC temperature control system is correctly simulated.

[0133] This embodiment provides a method for establishing a simulation model of an underground factory building HVAC temperature control system. By constructing a water system model and a wind system model, the two subsystem models responsible for air flow and water circulation are integrated, and the two subsystems responsible for air flow and water circulation are connected through a heat exchanger model to ensure that the heat exchange process of the HVAC temperature control system is correctly simulated.

[0134] The following is a specific example to illustrate the specific steps of a method for establishing a simulation model of an underground plant HVAC temperature control system.

[0135] Embodiment 1:

[0136] like Figure 8 As shown, it is assumed that the underground plant is a hydropower station plant. The underground plant system takes water from a water source and cools plant room 1 and plant room 2 through a water-air cooling system composed of a chiller, a water pump, a heat exchanger, and a fan. In plant room 1, there are generator sets, excitation cabinets, speed control cabinets, and lighting as heating equipment, and in plant room 2, there are busbars, generator outer cylinders, and lighting as heating equipment.

[0137] The underground plant equipment and space are divided into six categories, namely, chillers, water pumps, heat exchangers, fans, pipeline ducts and rooms. The specific steps of the method for establishing the simulation model of the HVAC temperature control system of the underground plant include:

[0138] The chiller efficiency is expressed by a polynomial regression model, which is fitted based on the operating data and reflects the complex relationship between energy efficiency and cooling water inlet / outlet temperature, chilled water inlet / outlet temperature, cooling water flow rate, chilled water flow rate and chiller power.

[0139] The pump performance adopts a power-flow polynomial model, which is also fitted by actual operating data to describe the characteristics of the pump power changing with flow under different working conditions.

[0140] For the heat exchanger, the efficiency-heat transfer unit method model is applied, which describes the relationship between the water temperature and wind temperature at the inlet and outlet ports and their corresponding flow rates.

[0141] The working state of the fan is simulated using the power-flow cubic relationship model to reflect the energy consumption of the fan under different air volumes.

[0142] Heat losses in pipes and ducts were evaluated by calculating thermal resistance, and a relationship model was established to analyze the difference between inlet temperature, flow rate and outlet temperature. This model was verified by measured data.

[0143] The thermodynamic behavior inside the room is simulated with computational fluid dynamics combined with intrinsic orthogonal decomposition technology and artificial neural networks to build a data-driven model: first, a detailed CFD simulation model is created, taking into account the specific structure and heat source conditions of the room; second, a systematic sampling method is used to generate a variety of boundary conditions and heat source input combinations to form a training data set; finally, POD is used to reduce the dimension of the CFD results and use this as the training set of the ANN. The trained ANN prediction results are then inversely transformed through POD to obtain the temperature field structure of the physical space, ultimately achieving fast and accurate prediction of indoor temperature distribution.

[0144] After establishing models for the six types of equipment and spaces involved in the factory, all equipment and spaces are connected in series to establish a subsystem model based on the pipeline topology and duct space structure; the two subsystem models are connected in series through the heat exchanger model responsible for heat exchange in the duct and pipeline, and the inlet and outlet water temperature flow and the inlet and outlet air temperature flow of the heat exchanger are associated through the heat exchanger model to obtain the simulation model of the HVAC temperature control system of the underground factory.

[0145] The flow and temperature at the inlet and outlet of the chiller correspond to the flow and water temperature of the corresponding pipeline, which are water temperature T1, T2, T3, T4 and flow m1 and m2 respectively. The flow of the water pump corresponds to the flow of the pipeline, that is, the rated flow of the two pumps is m1 and m2. The inlet and outlet temperature and flow of the heat exchanger correspond to the flow and water and wind temperatures of the corresponding pipelines and ducts, which are temperature T5, T6, T7, T8 and flow m2 and m3 respectively. The air volume of the fan corresponds to the air volume of the duct, which is m 3, m4, m5, for the room, the flow rate and wind temperature of the corresponding air duct at its inlet and outlet, the flow rate of plant room 1 is m3, m4 and the inlet wind temperature is T8, the flow rate of plant room 2 is m3, m4 and the inlet wind temperature is T9, the heating value of the heat source in the room is used as the input parameter of the wind system, plant room 1 is H1, plant room 2 is H2, the temperatures in the room are t1 and t2 respectively, the difference between T4 and T5 and between T3 and T6 is the inlet and outlet temperature difference of the corresponding pipeline.

[0146] After completing the combination of the underground plant HVAC temperature control system simulation model, since the composition of the underground plant HVAC temperature control system simulation model is based on analytical models and data models, under the given heat source heat in the room, under different chiller cooling water temperature flow rates and chiller freezing water temperature flow rates, the temperature rise of the heat source in the room and the energy consumption of each equipment can be quickly calculated.

[0147] In the above-mentioned embodiment 1, the simulation model of the HVAC temperature control system of the underground plant can quickly calculate the temperature rise in the room and the energy consumption of each equipment according to the different temperature and flow conditions of the cooling water and chilled water of the chiller when the heat sources in different rooms generate heat. The method for establishing the simulation model of the HVAC temperature control system of the underground plant overcomes the limitations of computational fluid dynamics simulation or scaled experiments in real-time prediction, and provides instant calculation support for refined operations; secondly, combined with optimization algorithms and automatic control technology, the simulation model of the HVAC temperature control system of the underground plant can further realize the optimization of system operation, ensure the maximization of energy utilization efficiency while meeting the requirements of environmental comfort.

[0148] In this embodiment, a device for establishing a simulation model of a HVAC temperature control system of an underground plant is also provided, and the device is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0149] This embodiment provides a device for establishing a simulation model of a HVAC temperature control system of an underground plant. Fig. 9 As shown, including:

[0150] Establishing module 901, for obtaining the equipment operation data in the underground plant, and establishing the underground plant equipment model based on the equipment operation data in the underground plant; the underground plant equipment model includes a chiller model, a water pump model, a heat exchanger model, a pipeline air duct model, a fan model and a room airflow proxy model;

[0151] The integration module 902 is used to obtain the pipeline topology and the air duct space structure, integrate and connect the underground plant equipment model according to the pipeline topology and the air duct space structure, and obtain the simulation model of the underground plant HVAC temperature control system.

[0152] In some optional implementations, the establishing module 901 includes:

[0153] The first establishment unit is used to perform parameter fitting on the efficiency polynomial regression model using the equipment operation data in the underground plant to obtain a chiller model;

[0154] The second establishment unit is used to perform parameter fitting on the power flow polynomial model using the equipment operation data in the underground powerhouse to obtain a water pump model;

[0155] The third establishment unit is used to fit the equipment operation data in the underground powerhouse using the efficiency heat transfer unit method model to obtain a heat exchanger model;

[0156] The fourth establishment unit is used to fit the equipment operation data in the underground powerhouse using the power flow cubic relationship model to obtain a fan model;

[0157] The fifth establishment unit is used to establish a thermal resistance model, and use the equipment operation data in the underground plant to verify the thermal resistance model to obtain a pipeline air duct model;

[0158] The sixth establishment unit is used to construct a room airflow proxy model based on the equipment operation data in the underground plant by using the orthogonal decomposition method and artificial neural network.

[0159] In some optional implementations, the fifth establishing unit includes:

[0160] A determination subunit is used to determine the inlet temperature, flow rate and outlet temperature of the pipeline air duct, and the total thermal resistance from the fluid to the outside based on the equipment operation data in the underground powerhouse;

[0161] Establish subunits to establish a thermal resistance model based on the inlet temperature, flow rate and outlet temperature of the pipeline duct, and the total thermal resistance from the fluid to the outside;

[0162] The first verification subunit is used to obtain the actual measured data of heat loss, and use the actual measured data of heat loss to perform data verification on the thermal resistance model to obtain the pipeline air duct model.

[0163] In some optional implementations, the sixth establishing unit includes:

[0164] The second verification subunit is used to establish a CFD simulation model, verify the CFD simulation model, and obtain a verified CFD simulation model;

[0165] A generation subunit is used to obtain a data sample group, and based on the data sample group, generate a CFD simulation result using a verified CFD simulation model; wherein the data sample group includes multiple sets of equipment inlet and outlet air boundary conditions and heat source heat generation;

[0166] A dimension reduction subunit is used to perform dimension reduction processing on the CFD simulation results by using the orthogonal decomposition method, and use the CFD simulation results after the dimension reduction processing as training data of the artificial neural network, and use the training data to train the artificial neural network;

[0167] A mapping subunit is used to map the prediction results corresponding to the trained artificial neural network to the physical space to obtain the reconstructed temperature field structure;

[0168] Construct subunits for building room airflow proxy models based on CFD simulation results and reconstructed temperature field structures.

[0169] In some optional implementations, the integration module 902 includes:

[0170] The first construction unit is used to connect the chiller model, the water pump model, the heat exchanger model and the pipeline air duct model by using the pipeline topology to construct a water system model;

[0171] The second construction unit is used to connect the fan model, the pipeline duct model and the room airflow proxy model by using the duct space structure to construct a wind system model;

[0172] The third construction unit is used to construct a simulation model of the HVAC temperature control system of the underground plant based on the water system model, the heat exchanger model and the wind system model.

[0173] In some optional embodiments, it also includes:

[0174] The optimization control module is used to use the simulation model of the HVAC temperature control system of the underground plant to predict the state of the HVAC temperature control system, and use the state of the HVAC temperature control system to optimize the control of the HVAC temperature control system of the underground plant.

[0175] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0176] In this embodiment, a device for establishing a simulation model of an underground factory HVAC temperature control system is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above-mentioned functions.

[0177] The embodiment of the present invention also provides a computer device having the above Fig. 9 A device for establishing a simulation model of an underground plant HVAC temperature control system is shown.

[0178] See also Fig.10 , Fig.10 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Fig.10As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Fig.10 A processor 10 is taken as an example.

[0179] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0180] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0181] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0182] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0183] The computer device also includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Fig.10 The example of connecting through bus is taken in the following.

[0184] The input device 30 can receive input digital or character information, and generate key signal input related to the user settings and function control of the computer device, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, an indicator bar, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 may include a display device, an auxiliary lighting device (e.g., an LED) and a tactile feedback device (e.g., a vibration motor), etc. The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display and a plasma display. In some optional embodiments, the display device can be a touch screen.

[0185] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0186] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0187] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for establishing a simulation model of an underground plant HVAC temperature control system, characterized in that: The method comprises: Acquire equipment operation data in the underground plant, and establish an underground plant equipment model based on the equipment operation data in the underground plant; the underground plant equipment model includes a chiller model, a water pump model, a heat exchanger model, a pipeline air duct model, a fan model and a room airflow proxy model; The pipeline topology and the air duct space structure are obtained, and the underground plant equipment model is integrated and connected according to the pipeline topology and the air duct space structure to obtain a simulation model of the underground plant HVAC temperature control system.

2. The method according to claim 1, characterized in that The establishing of the underground plant equipment model based on the equipment operation data in the underground plant includes: Using the equipment operation data in the underground plant to perform parameter fitting on the efficiency polynomial regression model, the refrigeration machine model is obtained; Using the equipment operation data in the underground powerhouse to perform parameter fitting on a power flow polynomial model, to obtain the water pump model; Using the effective heat transfer unit method model to fit the equipment operation data in the underground powerhouse, the heat exchanger model is obtained; The power flow cubic relationship model is used to fit the equipment operation data in the underground powerhouse to obtain the fan model; Establishing a thermal resistance model, and using the equipment operation data in the underground plant to verify the thermal resistance model, to obtain the pipeline air duct model; Based on the equipment operation data in the underground plant, the room airflow proxy model is constructed using orthogonal decomposition method and artificial neural network.

3. The method according to claim 2, characterized in that The step of establishing a thermal resistance model and verifying the thermal resistance model using the equipment operation data in the underground plant to obtain the pipeline air duct model includes: Determine the inlet temperature, flow rate and outlet temperature of the pipeline air duct, and the total thermal resistance from the fluid to the outside based on the equipment operation data in the underground plant; Establishing the thermal resistance model based on the inlet temperature, flow rate and outlet temperature of the pipeline air duct and the total thermal resistance from the fluid to the outside; Acquire heat loss measured data, use the heat loss measured data to perform data verification on the thermal resistance model, and obtain the pipeline air duct model.

4. The method according to claim 2, characterized in that: The room airflow proxy model is constructed based on the equipment operation data in the underground plant using the orthogonal decomposition method and artificial neural network, including: Establishing a CFD simulation model, verifying the CFD simulation model, and obtaining a verified CFD simulation model; Acquire a data sample group, and based on the data sample group, generate a CFD simulation result using the verified CFD simulation model; wherein the data sample group includes multiple sets of equipment inlet and outlet air boundary conditions and heat source heat generation; The CFD simulation results are subjected to dimensionality reduction processing by using an orthogonal decomposition method, and the CFD simulation results after dimensionality reduction processing are used as training data of an artificial neural network, and the artificial neural network is trained by using the training data; Map the prediction results corresponding to the trained artificial neural network to the physical space to obtain the reconstructed temperature field structure; The room airflow proxy model is constructed based on the CFD simulation results and the reconstructed temperature field structure.

5. The method according to claim 2, characterized in that: The underground plant equipment model is integrated and connected according to the pipeline topology and the air duct space structure to obtain a simulation model of the HVAC temperature control system of the underground plant, including: The chiller model, the water pump model, the heat exchanger model and the pipeline air duct model are connected by using the pipeline topology to construct a water system model; The fan model, the pipe duct model and the room airflow proxy model are connected by using the duct space structure to construct a wind system model; A simulation model of the HVAC temperature control system of the underground plant is constructed based on the water system model, the heat exchanger model and the wind system model.

6. The method according to claim 1, characterized in that Also includes: The HVAC temperature control system simulation model of the underground powerhouse is used to predict the state of the HVAC temperature control system, and the HVAC temperature control system state is used to optimize and control the HVAC temperature control system of the underground powerhouse.

7. A device for establishing a simulation model of a HVAC temperature control system of an underground plant, characterized in that: The device comprises: Establish a module for obtaining equipment operation data in the underground plant, and establish an underground plant equipment model based on the equipment operation data in the underground plant; the underground plant equipment model includes a chiller model, a water pump model, a heat exchanger model, a pipeline duct model, a fan model and a room airflow proxy model; The integration module is used to obtain the pipeline topology and the air duct space structure, integrate and connect the underground plant equipment model according to the pipeline topology and the air duct space structure, and obtain a simulation model of the underground plant HVAC temperature control system.

8. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for establishing a simulation model of an underground plant HVAC temperature control system according to any one of claims 1 to 6 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method for establishing a simulation model of an underground plant HVAC temperature control system according to any one of claims 1 to 6.

10. A computer program product, characterized in that It includes computer instructions, and the computer instructions are used to enable a computer to execute the method for establishing a simulation model of an underground plant HVAC temperature control system according to any one of claims 1 to 6.

Images