A method and device for selecting a natural gas compressor

Abstract

The application discloses a natural gas compressor selection method, comprising the following steps: selecting a basic data unit of the compressor; setting a natural gas component; setting ambient environment data; setting a compressor operation parameter input matching function to obtain a compressor type; testing the selected compressor type; and generating a selection report output according to the selected compressor type. The application also provides a natural gas compressor selection device. By setting the basic data unit, the gas component and the ambient environment data, the compressor is matched, and the performance of the compressor under different conditions is simulated, so that the basic selection of the compressor type is ensured, and the defects of the artificial calculation data, such as the lack of accuracy and errors, are solved.

Description

Technical Field

[0001] This invention relates to the field of natural gas compressor selection technology, specifically a method and apparatus for selecting natural gas compressors. Background Technology

[0002] This compressor selection system fills a gap in domestic compressor selection software. Currently, most natural gas compressor selection relies on manual calculations, which are not only inefficient but also prone to errors and even mistakes. This is unacceptable in the industrial resources sector. Summary of the Invention

[0003] This invention addresses the shortcomings of the existing technology by providing a method and apparatus for selecting natural gas compressors. This enables more accurate and rapid compressor feedback schemes to be developed for new natural gas extraction projects, tailored to various local conditions.

[0004] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0005] A method for selecting a natural gas compressor includes the following steps:

[0006] Select the compressor's basic data unit;

[0007] Set the natural gas composition;

[0008] Set the surrounding environment data;

[0009] The compressor type is obtained by setting the compressor operating parameters and inputting them into the matching function.

[0010] Test the selected compressor type;

[0011] A selection report is generated based on the selected compressor type.

[0012] As a further technical solution of the present invention, the compressor type is obtained from the compressor operating parameter input matching function; specifically including:

[0013] The maximum inlet pressure, maximum outlet pressure, maximum inlet temperature, maximum outlet temperature, and maximum flow rate of the compressor are matched based on the gas pressure and temperature when the gas enters the natural gas compressor, the gas pressure and temperature when the gas is discharged, and the flow rate of the compressed gas. This results in a suitable compressor, which is obtained by using the formula W = 22 × (ratio / stage) × (Stages) × MMSCFD × F.

[0014] Where W is the compressor power, ratio is the inlet pressure / outlet pressure, stage is the current compression stage, Stages is the total number of compression stages, MMSCFD is the compressed gas flow rate, and F is a constant at different compression stages.

[0015] As a further technical solution of the present invention, the compressor type is obtained by setting the compressor operating parameters input matching function; the SVR model is used to map the original variables to a high-dimensional feature space through nonlinear transformation to construct a linear classification function to optimize the compressor.

[0016] As a further technical solution of the present invention, the constants for the different compression levels are specifically: the constant for the first level of compression is 1, the constant for the second level of compression is 1.08, and the constant for the third level of compression is 1.1.

[0017] As a further technical solution of the present invention, the setting of surrounding environmental data includes: basic ambient temperature, atmospheric pressure, and inhalation and exhaust temperatures.

[0018] As a further technical solution of the present invention, the test selects the compressor type; specifically, the compressor type is determined and selected based on the compressor's maximum shaft speed, volume ratio, maximum shaft power, maximum discharge temperature, suction pressure, and discharge pressure.

[0019] The present invention also provides a natural gas compressor selection device, comprising:

[0020] The compressor basic data setting module is used to store compressor data information;

[0021] Natural gas composition module, used to set the natural gas composition;

[0022] The compressor surrounding environment setting module is used to set environmental conditions as the operating conditions of the compressor.

[0023] The compressor configuration module is used to determine the specific performance of the compressor and select the compressor type;

[0024] The compressor performance simulation module is used to test the suction pressure, discharge pressure, and power of the selected compressor type.

[0025] The compressor selection report module simulates compressor operation based on the compressor performance simulation module, determines the compressor selection, and generates a selection report.

[0026] As a further technical solution of the present invention, the environmental conditions for the operation of the compressor include: ambient temperature, atmospheric pressure, and intake and exhaust temperatures.

[0027] As a further technical solution of the present invention, the compressor type is specifically determined and selected based on the compressor's maximum shaft speed, volume ratio, maximum shaft power, maximum discharge temperature, suction pressure, and discharge pressure.

[0028] The beneficial effects of this invention are:

[0029] This invention sets basic data units, gas and environmental data, inputs a series of data to match the compressor, selects the compressor model, and performs performance simulations under different conditions. An SVM regression model is used for optimization to calculate whether the compressor's power exceeds its maximum capacity under actual conditions, thus determining whether it can operate normally at different operating points. This invention effectively breaks the current market monopoly of foreign compressor selection software in China. While ensuring basic compressor type selection, it also overcomes the shortcomings of manual calculations, such as lack of accuracy and errors. This further improves the overall practicality of the system. Attached Figure Description

[0030] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0031] Figure 1 This is a flowchart of a natural gas compressor selection method proposed in this invention;

[0032] Figure 2 This is a flowchart illustrating the process of a natural gas compressor selection method proposed in this invention;

[0033] Figure 3 This is a structural diagram of a natural gas compressor selection device proposed in this invention. Detailed Implementation

[0034] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0035] See Figure 1 and Figure 2 This invention provides a method for selecting a natural gas compressor, comprising the following steps:

[0036] Step 101: Select the compressor's basic data unit;

[0037] Step 102, set the natural gas composition;

[0038] Step 103, set the surrounding environment data;

[0039] Step 104: Set the compressor operating parameters and input them into the matching function to obtain the compressor type;

[0040] Step 105, test the selected compressor type;

[0041] Step 106: Generate a selection report output based on the selected compressor type.

[0042] In this embodiment of the invention, basic data units and environmental conditions surrounding the compressor are set. The data required for selecting a natural gas compressor are the natural gas composition, the gas pressure and temperature when entering the compressor, and the gas pressure and temperature when discharging. The natural gas composition can be used to calculate the molar mass, specific gravity, and concentration of the gas. Thus, the gas determines whether the temperature exceeds the maximum temperature that the compressor can withstand when compressed. Secondly, the gas pressure and temperature when entering the compressor, the gas pressure and temperature when discharging, and the flow rate of the compressed gas are also considered.

[0043] In this embodiment of the invention, ambient environmental data is set, including: basic ambient temperature, atmospheric pressure, and intake and exhaust temperatures. The compressor type is selected through testing; specifically, the compressor type is determined and selected based on the compressor's maximum shaft speed, volume ratio, maximum shaft power, maximum exhaust temperature, intake pressure, and exhaust pressure.

[0044] Set basic data units: Set the basic units for the entire system, such as power, gas flow rate, pressure, temperature, etc. For example, power can be set to KW, HP, BTU / sec, BTU / min.

[0045] Setting the natural gas composition: The natural gas composition needs to be entered by the user to calculate various required data such as specific gravity and molar weight. The calculated data is one of the factors in selecting the compressor model.

[0046] The system sets the environmental conditions around the compressor, such as basic air pressure and temperature. Users input inlet and outlet pressure, temperature, compressor flow rate, and other data. The system then inputs the data into a matching function, which directly matches the input data with various compressor data in the database and checks whether the input data falls within the range of the compressor's various data. Finally, it selects the compressor type that meets the requirements.

[0047] In this embodiment of the invention, the compressor type is obtained by setting the compressor operating parameters input matching function. Specifically, this includes matching the compressor's maximum inlet pressure, maximum outlet pressure, maximum inlet temperature, maximum outlet temperature, and maximum flow rate based on the gas pressure and temperature at the time of entry into the natural gas compressor, the gas pressure and temperature at the time of discharge, and the flow rate of the compressed gas, thereby obtaining a matching compressor. The power of various compressors at different operating points is calculated using the formula W = 22 × (ratio / stage) × (Stages) × MMSCFD × F, and the power at this point is compared to see if it exceeds the compressor's maximum power capacity and rated power. Where W is the compressor power, ratio is the inlet pressure / outlet pressure, stage is the current compression stage, Stages is the total number of compression stages, MMSCFD is the compressed gas flow rate, and F is a constant at different compression stages.

[0048] The constants for different compression levels are as follows: the constant for level 1 compression is 1, the constant for level 2 compression is 1.08, and the constant for level 3 compression is 1.1.

[0049] The compressor power calculated by the above formula deviates from the actual power. An SVM algorithm can be used to build a machine learning regression model for this formula. Since the amount of compressor data may be too small, the SVM regression model algorithm is chosen to address the small dataset issue. Here, only the right side of the formula is used as the x-variable, i.e., one-dimensional training, to achieve a match with the actual compressor power. Then, by inputting different operating points, inlet pressures, outlet pressures, and other data, the power calculated by the corrected formula is compared with the maximum power of the model to determine whether it can operate normally under different operating conditions.

[0050] The optimization steps for the nonlinear regression problem regarding formula optimization in the model are as follows:

[0051] 1) Establish a linear regression function in a high-dimensional feature space;

[0052]

[0053] In the formula: It is a nonlinear mapping function;

[0054] 2) Define the ε-linear insensitive loss function;

[0055]

[0056] In the formula: f(x) is the predicted value, y is the corresponding actual value, and if the difference between the predicted value and the actual value is less than or equal to ε, then the loss is 0;

[0057] 3) Introduce slack variable ξ i ,ξ* i Solve for w and b in equation (1);

[0058]

[0059] In the formula: Ф(x) is the nonlinear mapping function, C is the penalty factor, and ε specifies the error requirement of the regression function.

[0060] 4) Introduce the Lagrange multiplier α i α i * After multiple solutions and dual operations, the linear fitting function is obtained as follows:

[0061]

[0062] 5) Select the radial basis kernel function:

[0063] K(x i ,x j )=Φ(x i )Φ(x j (5)

[0064] 6) Substitute the kernel function to solve for the regression function;

[0065]

[0066] In the formula: when the parameter (α) i -α * i When x is not zero, the corresponding x i The system uses support vectors; then, by inputting different operating points, as well as different inlet and outlet pressures, the user calculates the power using an optimized formula and compares it with the maximum power of the machine model to determine whether it can operate normally under different operating points.

[0067] The SVR model obtains the theoretically global optimal solution, avoiding the problem of local optima. The SVR model maps the original variables to a high-dimensional feature space through nonlinear transformation to construct a linear classification function, which can not only ensure the model's good generalization ability, but also solve the problem of the "curse of dimensionality" of vectors.

[0068] See Figure 3 The present invention also provides a natural gas compressor selection device, comprising:

[0069] The compressor basic data setting module 201 is used to store compressor data information;

[0070] Natural gas composition module 202 is used to set the natural gas composition;

[0071] The compressor surrounding environment setting module 203 is used to set environmental conditions as the environmental conditions for compressor operation.

[0072] The compressor configuration module 204 is used to determine the specific performance of the compressor and select the compressor type;

[0073] Compressor performance simulation module 205 is used to test the suction pressure, discharge pressure, and power of the selected compressor type;

[0074] The compressor selection report module 206 simulates the operation of the compressor using the compressor performance simulation module, determines the compressor selection, and generates a selection report.

[0075] In this embodiment of the invention, the environmental conditions for compressor operation include: ambient temperature, atmospheric pressure, and suction and discharge temperatures. Specifically, the compressor type is selected based on its maximum shaft speed, volume ratio, maximum shaft power, maximum discharge temperature, suction pressure, and discharge pressure.

[0076] The compressor data unit module sets various units, the natural gas composition module determines the gas composition, the compressor ambient environment module determines the environmental conditions (including ambient temperature, atmospheric pressure, suction and discharge temperatures, etc.), the compressor configuration module determines the compressor's specific performance (including maximum shaft speed, volume ratio, maximum shaft power, maximum discharge temperature, suction pressure, discharge pressure, etc.) and selects the compressor type, and the compressor performance module determines the suction pressure, discharge pressure, power, etc. under various conditions to simulate whether the compressor can work normally under a series of data changes, and finally generates a compressor selection report.

[0077] This invention enables more convenient and rapid compressor feedback schemes to be developed for new natural gas extraction projects, adapting to various local conditions. While ensuring the basic selection of compressor type, it also overcomes the shortcomings of manual calculation data, such as lack of accuracy and errors. This further improves the overall practicality of the system.

[0078] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for selecting a natural gas compressor, characterized in that, Includes the following steps: Select the compressor's basic data unit; Set the natural gas composition; Set the surrounding environment data; set the compressor operating parameters and obtain the compressor type from the matching function; Test the selected compressor type; Generate a selection report output based on the selected compressor type; The compressor type is obtained from the compressor operating parameter input matching function; Specifically, this involves matching the compressor's maximum inlet pressure, maximum outlet pressure, maximum inlet temperature, maximum outlet temperature, and maximum flow rate based on the gas pressure and temperature at the time of entry into the natural gas compressor, the gas pressure and temperature at the time of discharge, and the compressed gas flow rate. This results in a suitable compressor, determined through a formula. ;in For compressor power, Inlet pressure / outlet pressure This represents the current compression level. This represents the total number of compression levels. The air flow rate of the compressed air cylinder For constants at different compression levels; The compressor type is obtained by setting the compressor operating parameters and inputting them into the matching function; the SVR model is used to map the original variables to a high-dimensional feature space through nonlinear transformation to construct a linear classification function to optimize the compressor; The test selects the compressor type; specifically, the compressor type is determined and selected based on the compressor's maximum shaft speed, volume ratio, maximum shaft power, maximum discharge temperature, suction pressure, and discharge pressure.

2. The method for selecting a natural gas compressor according to claim 1, characterized in that, The constants for the different compression levels are as follows: the constant is 1 for level 1 compression, 1.08 for level 2 compression, and 1.1 for level 3 compression.

3. The method for selecting a natural gas compressor according to claim 1, characterized in that, The set ambient environmental data includes: basic ambient temperature, atmospheric pressure, and inhalation and exhaust temperatures.

4. A natural gas compressor selection device, employing a natural gas compressor selection method as described in any one of claims 1-3, characterized in that, include: The compressor basic data setting module is used to store compressor data information; Natural gas composition module, used to set the natural gas composition; The compressor surrounding environment setting module is used to set environmental conditions as the operating conditions of the compressor. The compressor configuration module is used to determine the specific performance of the compressor and select the compressor type; The compressor performance simulation module is used to test the suction pressure, discharge pressure, and power of the selected compressor type. The compressor selection report module simulates compressor operation based on the compressor performance simulation module, determines the compressor selection, and generates a selection report.

5. A natural gas compressor selection device according to claim 4, characterized in that, The environmental conditions for compressor operation include: ambient temperature, atmospheric pressure, and intake and exhaust temperatures.

6. A natural gas compressor selection device according to claim 4, characterized in that, The selection of compressor type specifically involves determining and selecting the compressor type based on its maximum shaft speed, volume ratio, maximum shaft power, maximum discharge temperature, suction pressure, and discharge pressure.

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