An optimization method for total energy consumption of air compression system

Abstract

The present application relates to a kind of air compression system operation total energy consumption optimization method, comprising: the expression of the density of matter and the viscosity of matter required for building air compression system digital twin model;The pipe network part in air compression system is modeled, wherein, first, single pipe model is established, data-oriented programming method is used, single pipe model is regarded as the structure body of data storage, then the structure body is decoupled with function function;Based on the single pipe model constructed, the structure body and function function of compressor are constructed;Air compression system model is constructed, and the optimal operating parameter is obtained based on the air compression system model, and the operation control of air compression system is controlled.Compared with prior art, the present application is optimized in parallel to pipe network pressure drop calculation by the way of layer interlayer series-layer parallel, and the time complexity is reduced from O (layer number log (layer number) to O (layer number).In energy consumption calculation, by parallel computing, the system energy consumption calculation time complexity is reduced from O (air compressor number) to O (1).

Description

Technical Field

[0001] This invention relates to the field of compressed air system design and optimization, and in particular to a method for optimizing the total energy consumption of a compressed air system. Background Technology

[0002] Compressed air systems account for approximately 25% of a company's total electricity consumption in industrial production, and their operation and maintenance costs can account for 75% of their total costs throughout their entire lifecycle. The operation and maintenance process for compressed air systems typically involves establishing a digital twin model of the system and using optimization algorithms to calculate the optimal power of the air compressors, thereby reducing the overall energy consumption of the system. However, current modeling methods for compressed air systems have several problems: 1) The calculation of the physical properties of compressed air systems relies too heavily on foreign commercial physical property calculation software; 2) Modeling compressed air systems generates thousands of variables to be optimized, which leads to excessively slow optimization speeds, unsatisfactory optimization results, and limited practical application value.

[0003] Therefore, there is an urgent need to develop and construct a high-performance air compressor system modeling and optimization method to maximize and most efficiently reduce the total energy consumption of air compressor system operation. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a method for optimizing the total energy consumption of an air compressor system. By using parallel computing and data-oriented process programming, the optimization speed of the air compressor system is greatly accelerated.

[0005] The objective of this invention can be achieved through the following technical solutions: This invention provides a method for optimizing the total energy consumption of an air compressor system, comprising the following steps: S1: Expressions for the density and viscosity of the material required to construct a digital twin model of the compressed air system; S2: Model the pipeline network in the air compressor system. First, a single-pipe model is established. Using a data-oriented programming method, the single-pipe model is regarded as a data storage structure. Then, the structure is decoupled from the functional functions to speed up the calculation. S3: Based on the constructed single-pipe model, construct the compressor structure and functional functions; S4: Based on the single-pipe structure and the compressor structure, construct an air compressor system model, obtain the optimal operating parameters based on the air compressor system model, and control the operation of the air compressor system.

[0006] Furthermore, in S1, the calculation process for the density of the substance includes: The dimensional Sutherland formula is used to calculate the viscosity required for the digital twin model of the air compressor system. : in, This is the Sutherland constant; each gas has a corresponding Sutherland constant. At 1 atmosphere, viscosity coefficient at that time It is 273.16K, that is The corresponding Kelvin temperature scale; The calculation process for the viscosity of the substance includes: Obtained from the ideal gas equation : p is the pressure, R is the gas constant, T is the temperature, and V is the specific volume.

[0007] Furthermore, in S2, the process of establishing the single-tube model includes: A single-pipe structure is constructed using a data-oriented programming approach. The structure contains pipe length Pipe inner diameter Absolute height difference Pipe roughness Local drag coefficient mass flow Volumetric flow rate Absolute pressure at the intake end Inlet temperature Inlet density Intake end dynamic viscosity Absolute pressure at the outlet outlet temperature Density at the outlet Dynamic viscosity at the outlet end .

[0008] Furthermore, in S2, the process of decoupling the structure from the functional functions includes: 1) Set the property setting function for the air inlet end of the pipeline. Its function is to reset the absolute pressure at the air inlet of the pipeline. ,temperature And recalculate the material density at the inlet of the pipeline based on the updated pressure and temperature. With dynamic viscosity ; 2) Set the property setting function at the gas outlet of the pipeline. Its function is to reset the absolute pressure at the outlet of the pipeline. ,temperature And recalculate the material density at the outlet of the pipeline based on the updated pressure and temperature. With dynamic viscosity ; 3) Set the pipeline mass flow rate setting function Its function is to reset the mass flow rate of the pipeline. ; 4) Set up the pipeline pressure drop calculation function Its function is to calculate the pipeline pressure drop based on the single-pipe total pressure drop calculation model, and then calculate the pressure at the pipeline outlet.

[0009] Furthermore, in S2, the calculation model for the total pressure drop of the single tube is as follows: in, Mass flow rate for a single-tube structure; For a single-pipe structure, the pipe's inner diameter is a parameter. For single-tube structural parameters, the inlet density is used. For gas velocity; The inlet dynamic viscosity is a parameter of a single-tube structure. It is the Reynolds number; This is scientific notation, representing 10 to the power of 6; The local resistance coefficient is a parameter of a single-tube structure. For single-tube structural parameters, the internal roughness of the tube is required. This refers to the absolute height difference of the single-tube structure parameters; Let be the gravitational constant, and take it as 9.8.

[0010] Furthermore, in S3, the process of constructing the compressor structure includes: The compressor structure is constructed using a data-oriented programming approach. The structure contains mass flow rate Volumetric flow rate Power consumption isentropic efficiency Absolute pressure on the import side Inlet temperature Import end density viscosity at the inlet end Absolute pressure on the export side outlet temperature Export end density Viscosity at the outlet .

[0011] Furthermore, in S3, the process of constructing the compressor function includes: 1) Set the compressor inlet property setting function Its function is to reset the absolute pressure at the compressor inlet. ,temperature And recalculate the material density at the compressor inlet based on the updated pressure and temperature. With dynamic viscosity ; 2) Set the property setting function at the compressor outlet. Its function is to reset the absolute pressure at the compressor outlet. ,temperature And recalculate the material density at the compressor outlet based on the updated pressure and temperature. With dynamic viscosity ; 3) Set the compressor mass flow rate setting function Its function is to reset the compressor's mass flow rate. ; 4) Set the system energy consumption calculation function Its function is to determine the mass flow rate of the compressor structure. Absolute pressure on the import side Inlet temperature Absolute pressure on the export side isentropic efficiency The compressor energy consumption is calculated based on the isentropic compression model and isentropic efficiency.

[0012] Furthermore, in S3, the isentropic compression model is as follows: Substituting the following equation into the isentropic compression model We can obtain: The compressor power consumption can be obtained using formula (8); in For compressor power consumption, Let be the adiabatic coefficient, taken as 1.4 for air, and R be the gas constant, taken as 287 for air. Air mass flow rate, For the inlet temperature, Due to export pressure, For the inlet pressure, take 0.1 kPa. For isentropic compression efficiency, we take 0.8.

[0013] Furthermore, in S4, the process of constructing the compressed air system model includes: Establish a pipeline network model, label each pipeline in the compressed air system network, name the pipeline according to the label, and initialize each pipeline with the pipeline inner diameter D, pipe length L, pipe roughness k, absolute height difference delta_H, and local resistance coefficient zeta according to the function ResetNodeIn_Pipeclass(). Establish a compressor model within the air compressor system, name each compressor, and initialize the mass flow rate Q_m, isentropic efficiency eta_s, inlet absolute pressure nodein_P, inlet temperature nodein_T, and outlet absolute pressure nodeout_P of each compressor using the function ResetNodeIn_Compressor().

[0014] Furthermore, in S4, the process of constructing the compressed air system model also includes constructing a function for the compressed air system model, specifically: 1) Set the voltage drop calculation function According to the pipeline sequence, in the direction of compressor to gas consumption, call... Calculate the pressure drop of each pipe; 2) Energy consumption calculation function based on parallel computing Based on the mass flow rate of each compressor's own structure Absolute pressure on the import side Inlet temperature Absolute pressure on the export side isentropic efficiency and call The power consumption of each compressor is calculated, and the total power consumption of the air compressor system is obtained by summing the power consumption of all compressors. Based on a data-parallel computing model, new threads are created according to the number of compressors, and each thread executes its own compressor power consumption calculation function. By using parallel computing, the time complexity is reduced from Reduce to ; Use air end pressure lookup function In the system voltage drop calculation function After the calculation is completed, iterate through and query the absolute pressure at the outlet of the gas-consuming pipeline. And return the minimum value among them, specifically: the absolute pressure at the outlet of each gas-consuming pipe. A thread is provided. In each round of comparison, the pressure at the gas consumption end is compared with the pressure at the previous end, and the smaller pressure is retained for the next round of comparison, until the final round determines the absolute pressure at the gas consumption end outlet. This reduces the time complexity of finding the minimum value from Reduce to .

[0015] Compared with the prior art, the present invention has the following technical advantages: 1) This invention employs the dimensional Sutherland formula to calculate the viscosity required for the digital twin model of the compressed air system, and uses formula derivation based on the ideal gas equation to calculate the density required for the digital twin model of the compressed air system. Tables 2 and 3 demonstrate the correctness of this invention's use of the dimensional Sutherland formula and the formula derivation based on the ideal gas equation to calculate viscosity and density. Furthermore, this method can improve the calculation speed of the model; verification shows that it can improve the calculation speed by 30% in the calculation of total system energy consumption in a single operation. This invention avoids relying on foreign CoolProp / RefProp programs for property calculations by using the dimensional Sutherland formula and the formula derivation based on the ideal gas equation to calculate viscosity and density, thus enhancing the invention's autonomy and avoiding the "bottleneck" problem.

[0016] 2) This invention employs a data-oriented programming approach. Unlike object-oriented programming, which treats objects as collections of data and functions, this invention considers data-carrying structures as the smallest programming elements, decoupling data from functions. Data is represented by immutable data structures: PipeClass, CompressorClass, and AirCompressionClass. This avoids the code bloat caused by the layers of abstraction in object-oriented programming, which leads to reduced efficiency in the air compression model. By dividing the air compression system structure into compressor and pipe structures, hot and cold data partitioning is achieved, optimizing CPU cache usage and reducing memory boundary occurrences. Furthermore, this method naturally provides a foundation for parallel computing, fully utilizing multi-core CPUs to achieve better parallel acceleration and reduce CPU performance boundaries.

[0017] 3) This invention proposes to optimize the modeling of the air compressor system based on parallel computing. During the system initialization phase, parallel computing reduces the time complexity from O(number of air compressors + number of pipes) to O(1). For the calculation of system pipe pressure drop, the invention proposes to layer the pipe network according to the topology, and to perform parallel optimization of the pipe network pressure drop calculation through a serial inter-layer and parallel intra-layer approach, reducing the time complexity from O(number of layers log(number of layers)) to O(number of layers). For energy consumption calculation, parallel computing reduces the time complexity of system energy consumption calculation from O(number of air compressors) to O(1). Attached Figure Description

[0018] Figure 1 This is a schematic diagram of parallel-serial calculation of pipeline pressure drop in this invention; Figure 2This is a schematic diagram of the pipeline node structure in Application Example 1 of the present invention. Detailed Implementation

[0019] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. Any structural / module names, control modes, algorithms, processes, or composition ratios not explicitly described in this technical solution are considered common technical features disclosed in the prior art.

[0020] Example 1 S1: Establishing a digital twin model of an air compressor system requires calculating the density and viscosity of the substances within the system.

[0021] This invention employs the dimensional Sutherland formula to calculate the viscosity required for a digital twin model of an air compressor system. The Sutherland formula calculates an approximate value for gas viscosity using a correlation between temperature and pressure, based on an idealized intermolecular force potential. The Sutherland formula is shown below: in, This is the Sutherland constant; each gas has a corresponding Sutherland constant. At 1 atmosphere, viscosity coefficient at that time It is 273.16K, that is The corresponding Kelvin temperature scales. Table 1 shows the corresponding Kelvin temperature scales for each gas. , , Numerical value.

[0022] Table 1. Gas Parameter Table for Sutherland's Formula It should be noted that Sutherland's formula is only valid for single-phase gas flow under low pressure. Since air is mainly composed of nitrogen and oxygen, which have very similar properties, Sutherland's formula applies to air with very similar properties.

[0023] This invention calculates the material density required for a digital twin model of an air compression system by deriving a formula based on the ideal gas equation. The specific process is as follows: In fluid mechanics, the ideal gas equation is: in, For pressure, The gas constant is For temperature. For specific volume, it is the reciprocal of the density of the substance: From the ideal gas equation, we can obtain: The two equations are equal: The density of the substance can then be obtained: The accuracy of the viscosity and density simulated by formulas (1) and (2) was verified using CoolProp software as a comparison reference. The gas used was air. The error calculation formula is as follows: in, The viscosity and density of the substance calculated using formulas (1) and (2) are the same as the viscosity and density of the substance shown in Tables 2 and 3. The density and viscosity of the substances calculated by CoolProp software under the same conditions are the software values ​​in Tables 2 and 3. It is an absolute value function.

[0024] The comparison results are shown below: Table 2. Comparison of physical property calculations at 500 kPa Table 3. Comparison of physical property calculations at 1000 kPa The average errors in Tables 2 and 3 are all less than 1%, which is within an acceptable range, proving that formulas (1) and (2) can be used in the modeling of compressed air systems.

[0025] S2: After accelerating the physical property calculations, the piping network portion of the compressed air system can be modeled. First, a single-pipe model is established. This invention employs a data-oriented programming approach; unlike object-oriented programming, the single-pipe model is treated as a data storage structure, decoupling the structure from the functional modules to speed up computation.

[0026] Constructing a single-tube structure The structure contains pipe length Pipe inner diameter Absolute height difference Pipe roughness Local drag coefficient mass flow Volumetric flow rate Absolute pressure at the intake end Inlet temperature Inlet density Intake end dynamic viscosity Absolute pressure at the outlet outlet temperature Density at the outlet Dynamic viscosity at the outlet end .

[0027] Construct single-pipe function functions, including inlet property setting function, outlet property setting function, mass flow rate setting function, and pipeline pressure drop calculation function.

[0028] 1) Function for setting the physical properties of the air inlet end of the pipeline Its function is to reset the absolute pressure at the air inlet of the pipeline. ,temperature And recalculate the material density at the inlet of the pipeline based on the updated pressure and temperature. With dynamic viscosity .

[0029] 2) Function for setting the physical properties of the gas outlet end of the pipeline The function is to reset the absolute pressure at the outlet of the pipeline. ,temperature And recalculate the material density at the outlet of the pipeline based on the updated pressure and temperature. With dynamic viscosity .

[0030] 3) Pipeline mass flow rate setting function The function is to reset the mass flow rate of the pipeline. .

[0031] 4) Pipeline pressure drop calculation function The function is to calculate the pipeline pressure drop based on the total pressure drop calculation model, and then use this to calculate the pressure at the pipeline outlet. The single-pipe total pressure drop calculation model is as follows: in, For the mass flow rate of a single-tube structure, For single-pipe structural parameters, the pipe's inner diameter is... For single-tube structure parameters, the inlet end density is... For gas velocity, The inlet dynamic viscosity is a parameter of the single-tube structure. Let Reynolds number be 1. This is scientific notation, representing 10 to the power of 6. The local drag coefficient is a parameter of a single-tube structure. For single-tube structural parameters, the internal roughness of the tube is... For the absolute height difference of the single-tube structure parameters, Let be the gravitational constant, and take it as 9.8.

[0032] Since the implementations of each function are not contained within the structure, the single-pipe structure needs to be passed as a parameter to the function. Here, we choose to reference the parameter to save memory and speed up the calculation. Taking the function for setting the physical properties of the pipe inlet end as an example: in, This is a reference to a single-tube structure. The values ​​required by each function are, here representing the absolute pressure at the inlet end of the pipeline. ,temperature .

[0033] S3: This paper uses a single-pipe structure and function as an example to illustrate data-oriented programming. Similarly, it constructs a compressor structure and function based on data-oriented programming.

[0034] Constructing the compressor structure The structure contains mass flow rate Volumetric flow rate Power consumption isentropic efficiency Absolute pressure on the import side Inlet temperature Import end density viscosity at the inlet end Absolute pressure on the export side outlet temperature Export end density Viscosity at the outlet .

[0035] The compressor function functions include inlet property setting function, outlet property setting function, mass flow rate setting function, and system energy consumption calculation function.

[0036] 1) Compressor inlet property setting function The function is to reset the absolute pressure at the compressor inlet. ,temperature And recalculate the material density at the compressor inlet based on the updated pressure and temperature. With dynamic viscosity .

[0037] 2) Compressor outlet property setting function The function is to reset the absolute pressure at the compressor outlet. ,temperature And recalculate the material density at the compressor outlet based on the updated pressure and temperature. With dynamic viscosity .

[0038] 3) Compressor mass flow rate setting function The function is to reset the compressor's mass flow rate. .

[0039] 4) System energy consumption calculation function Its function is to determine the mass flow rate of the compressor structure. Absolute pressure on the import side Inlet temperature Absolute pressure on the export side isentropic efficiency The compressor energy consumption is calculated based on the isentropic compression model and isentropic efficiency. The isentropic compression model is shown below: Substituting the following equation into the isentropic compression model We can obtain: The compressor power consumption can be obtained using formula (8).

[0040] S4: After the single-pipe structure and compressor structure are constructed, the air compressor system model can be built. First, establish a pipeline network model, label each pipe in the compressed air system network, and name the pipes according to the labels, for example... ,according to Its pipe inner diameter Manager Pipe roughness Absolute height difference Local drag coefficient Initialize each pipe. Construct compressor models within the air compressor system, naming them according to the number of compressors, for example... ,according to For the compressor mass flow rate isentropic efficiency Absolute pressure on the import side Inlet temperature Absolute pressure on the export side Perform initialization.

[0041] The system constructs functional functions for the compressed air system model, including functions for calculating pressure drop, energy consumption, and querying the pressure at the air consumption end.

[0042] 1) Pressure drop calculation function According to the pipeline sequence, in the direction of compressor to gas consumption, call... Calculate the pressure drop of each pipe. The pressure drop calculation of the compressed air system pipeline network adopts a hybrid serial-parallel calculation method. The pipeline network is divided into layers, with those not related by sequence forming a parallel layer. Parallel calculations are performed within each layer, while serial calculations are performed between layers.

[0043] like Figure 1 As shown, the pump station is level 1, nodes 1 and 2 are level 2, and nodes 3, 4, 5, and 6 are level 3. Parallel computation is performed within each level. For example, in level 2, two new threads are created to execute the computation. , .

[0044] 2) Energy consumption calculation function based on parallel computing Based on the mass flow rate of each compressor's own structure Absolute pressure on the import side Inlet temperature Absolute pressure on the export side isentropic efficiency Call Calculate the power consumption of each compressor. The sum of the power consumption of all compressors is the total power consumption of the air compressor system. Based on a data-parallel computing model, create new threads according to the number of compressors, and have each thread execute its own compressor power consumption calculation function. By using parallel computing, the time complexity is reduced from... Reduce to .

[0045] 3) Use the air end pressure lookup function In the system voltage drop calculation function After the calculation is completed, iterate through and query the absolute pressure at the outlet of the gas-consuming pipeline. Calculate and return the minimum value among them. Implement a function to query the gas end pressure. The purpose is to facilitate the optimization algorithm in calculating its fitness value. Once it is found that the minimum pressure at the gas consumption end is less than the required value, it is considered an optimization failure.

[0046] Use air end pressure lookup function The implementation employs a parallel computing model, specifically Parallel Random Access Machine (PRAM), a shared-memory SIMD model. In the implementation, the absolute pressure at the outlet of each gas-consuming pipeline is... A thread is provided. In each round of comparison, the pressure at the gas consumption end is compared with the pressure at the previous end, and the smaller pressure is retained for the next round of comparison, until the final round determines the absolute pressure at the gas consumption end outlet. By using parallel computing, the time complexity of finding the minimum value can be reduced from... Reduce to .

[0047] Application Example 1 S1: Based on formulas (1) and (2), the viscosity and density calculation functions for the compressed air system are derived. The viscosity calculation function is as follows: The density calculation function is .

[0048] S2: The pipeline structure is realized according to technical solution S2. The pseudocode for the function is shown below: S3: The compressor structure is realized according to technical solution S3. The pseudocode for the function is shown below: S4: A schematic diagram of the specific implementation plan is shown below. Figure 2 As shown. The air compressor system is implemented according to technical solution S4. As shown in the figure, the number of nodes is named according to their sequence. There is one compressor, named... The six pipes are named according to their tail node numbers. , , , , , .like Figure 1 As shown, the pipeline network can be divided into two levels for pressure drop calculation. The initialization of the pipeline network can be optimized using parallel computing, as shown in the pseudocode below: The first line creates 6 new threads, the second line performs parallel computation on the 6 threads, and the third line initializes the pipeline in parallel.

[0049] The pseudocode for each function is shown below: Rows 1-3 are parallel computations at level 1, rows 4-6 are parallel computations at level 2, and rows 2-3 are parallel computations within level 1. and Pressure drop, 5-6 lines of parallel computation within level 2 , , , The pressure drop, in pseudocode, reflects serial communication between layers and parallel communication within layers. in, The first line represents the number of compressors; the second and third lines represent the number of new threads created, with the number of compressors as the number of threads. The third and fourth lines represent the total energy consumption for parallel calculations. That is, total energy consumption. Since there are 4 gas-consuming terminals, the first line indicates the creation of 4 new threads, and lines 2-3 represent the first round of parallel comparisons, respectively. and The smaller value is named... , and The smaller value is named... The 4th and 5th lines compare the results of the previous round in parallel, and the minimum value is the result.

[0050] S5: S1-S4 have completed the modeling of the air compressor system according to the technical solution, and testing is required to verify the effectiveness of parallel computing.

[0051] The test environment is as follows: The testing method involves performing 100 tests per experiment, with system initialization and system voltage drop calculation performed each time. System power consumption calculation - Use the air end pressure lookup function Record the total running time. Each experiment was tested 100 times, and the average value was taken as the test result.

[0052] The comparison results between the high-performance air compressor system model and the ordinary air compressor system model are as follows: The results show that the high-performance compressed air system model based on data-oriented and parallel computing significantly improves runtime.

[0053] The above description of the embodiments is provided to enable those skilled in the art to understand and use the invention. It will be apparent to those skilled in the art that various modifications can be made to these embodiments, and the general principles described herein can be applied to other embodiments without inventive effort. Therefore, the present invention is not limited to the above embodiments, and any improvements and modifications made by those skilled in the art based on the disclosure of the present invention without departing from the scope of the invention should be within the protection scope of the present invention.

Claims

1. A method for optimizing the total energy consumption of an air compressor system, characterized in that, Includes the following steps: S1: Expressions for the density and viscosity of the material required to construct a digital twin model of the compressed air system; S2: Model the pipeline network in the air compressor system. First, a single-pipe model is established. Using a data-oriented programming method, the single-pipe model is regarded as a data storage structure. Then, the structure is decoupled from the functional functions to speed up the calculation. S3: Based on the constructed single-pipe model, construct the compressor structure and functional functions; S4: Based on the single-pipe structure and the compressor structure, construct an air compressor system model, obtain the optimal operating parameters based on the air compressor system model, and control the operation of the air compressor system. In S2, the process of establishing the single-tube model includes: A single-pipe structure is constructed using a data-oriented programming approach. The structure contains pipe length The unit is Pipe inner diameter The unit is Absolute height difference The unit is Pipe roughness The unit is Local drag coefficient mass flow The unit is Volumetric flow rate The unit is Absolute pressure at the intake end The unit is Inlet temperature The unit is Inlet density The unit is Intake end dynamic viscosity The unit is Absolute pressure at the outlet The unit is outlet temperature The unit is Density at the outlet The unit is Dynamic viscosity at the outlet end The unit is ; In S2, the process of decoupling the structure from the functional functions includes: 1) Set the property setting function for the air inlet end of the pipeline. Its function is to reset the absolute pressure at the air inlet of the pipeline. ,temperature And recalculate the material density at the inlet of the pipeline based on the updated pressure and temperature. With dynamic viscosity ; 2) Set the property setting function at the gas outlet of the pipeline. Its function is to reset the absolute pressure at the outlet of the pipeline. ,temperature And recalculate the material density at the outlet of the pipeline based on the updated pressure and temperature. With dynamic viscosity ; 3) Set the pipeline mass flow rate setting function Its function is to reset the mass flow rate of the pipeline. ; 4) Set up the pipeline pressure drop calculation function Its function is to calculate the pressure drop of the pipeline based on the single-pipe total pressure drop calculation model, and then calculate the pressure at the outlet end of the pipeline. In S2, the calculation model for the total pressure drop of a single tube is as follows: in, Q m Mass flow rate for a single-tube structure; For a single-pipe structure, the pipe's inner diameter is a parameter. For single-tube structural parameters, the inlet density is used. For gas velocity; nodein mu The inlet dynamic viscosity is a parameter of a single-tube structure. It is the Reynolds number; This is scientific notation, representing 10 to the power of 6; The local resistance coefficient is a parameter of a single-tube structure. For single-tube structural parameters, the internal roughness of the tube is required. This refers to the absolute height difference of the single-tube structure parameters; Let be the gravitational constant, and take it as 9.

8.

2. The method for optimizing the total energy consumption of an air compressor system according to claim 1, characterized in that, In S1, the calculation process for the density of the substance includes: The dimensional Sutherland formula is used to calculate the viscosity required for the digital twin model of the air compressor system. : in, This is the Sutherland constant; each gas has a corresponding Sutherland constant. At 1 atmosphere, viscosity coefficient at that time It is 273.16K, that is The corresponding Kelvin temperature scale; The calculation process for the viscosity of the substance includes: Obtained from the ideal gas equation : p is the pressure, R is the gas constant, T is the temperature, and V is the specific volume.

3. The method for optimizing the total energy consumption of an air compressor system according to claim 1, characterized in that, In S3, the process of constructing the compressor structure includes: The compressor structure is constructed using a data-oriented programming approach. The structure contains mass flow rate The unit is Volumetric flow rate The unit is Power consumption The unit is isentropic efficiency Absolute pressure on the import side The unit is Inlet temperature , Import end density The unit is viscosity at the inlet end The unit is Absolute pressure on the export side The unit is outlet temperature The unit is Export end density The unit is Viscosity at the outlet The unit is .

4. The method for optimizing the total energy consumption of an air compressor system according to claim 3, characterized in that, In S3, the process of constructing the compressor function includes: 1) Set the compressor inlet property setting function Its function is to reset the absolute pressure at the compressor inlet. ,temperature And recalculate the material density at the compressor inlet based on the updated pressure and temperature. With dynamic viscosity ; 2) Set the property setting function at the compressor outlet. Its function is to reset the absolute pressure at the compressor outlet. ,temperature And recalculate the material density at the compressor outlet based on the updated pressure and temperature. With dynamic viscosity ; 3) Set the compressor mass flow rate setting function Its function is to reset the compressor's mass flow rate. ; 4) Set the system energy consumption calculation function Its function is to determine the mass flow rate of the compressor structure. Absolute pressure on the import side The unit is Inlet temperature The unit is Absolute pressure on the export side The unit is isentropic efficiency The compressor energy consumption is calculated based on the isentropic compression model and isentropic efficiency.

5. The method for optimizing the total energy consumption of an air compressor system according to claim 4, characterized in that, In S3, the isentropic compression model is as follows: Substituting the following equation into the isentropic compression model We can obtain: The compressor power consumption can then be calculated. in For compressor power consumption, Let be the adiabatic coefficient, taken as 1.4 for air, and R be the gas constant, taken as 287 for air. Air mass flow rate, For the inlet temperature, Due to export pressure, For the inlet pressure, take 0.1 kPa. For isentropic compression efficiency, we take 0.

8.

6. The method for optimizing the total energy consumption of an air compressor system according to claim 1, characterized in that, In S4, the process of constructing the compressed air system model includes: Establish a pipeline network model, label each pipeline in the compressed air system network, name the pipeline according to the label, and initialize each pipeline with the pipeline inner diameter D, pipe length L, pipe roughness k, absolute height difference delta_H, and local resistance coefficient zeta according to the function ResetNodeIn_Pipeclass(). Establish a compressor model within the air compressor system, name each compressor, and initialize the mass flow rate Q_m, isentropic efficiency eta_s, inlet absolute pressure nodein_P, inlet temperature nodein_T, and outlet absolute pressure nodeout_P of each compressor using the function ResetNodeIn_Compressor().

7. The method for optimizing the total energy consumption of an air compressor system according to claim 6, characterized in that, In S4, the process of constructing the compressed air system model also includes constructing the compressed air system model function, specifically: 1) Set the voltage drop calculation function According to the pipeline sequence, in the direction of compressor to gas consumption, call... Calculate the pressure drop of each pipe; 2) Energy consumption calculation function based on parallel computing Based on the mass flow rate of each compressor's own structure Absolute pressure on the import side The unit is Inlet temperature The unit is Absolute pressure on the export side The unit is isentropic efficiency and call The power consumption of each compressor is calculated, and the total power consumption of the air compressor system is obtained by summing the power consumption of all compressors. Based on a data-parallel computing model, new threads are created according to the number of compressors, and each thread executes its own compressor power consumption calculation function. By using parallel computing, the time complexity is reduced from a level proportional to the number of air compressors to a constant level; Use air end pressure lookup function In the system voltage drop calculation function After the calculation is completed, iterate through and query the absolute pressure at the outlet of the gas-consuming pipeline. And return the minimum value among them, specifically: the absolute pressure at the outlet of each gas-consuming pipe. A thread is provided. In each round of comparison, the pressure at the gas consumption end is compared with the pressure at the previous end, and the smaller pressure is retained for the next round of comparison, until the final round determines the absolute pressure at the gas consumption end outlet. By setting the operating parameters at this point as the optimal operating parameters, the time complexity of finding the minimum value is reduced from a level proportional to the number of gas-consuming terminals to a level proportional to the logarithm of the number of gas-consuming terminals.

Images