Effect-increasing conveying system based on natural gas pipeline

Abstract

The invention relates to the technical field of natural gas conveying, in particular to an efficiency-increasing conveying system based on a natural gas pipeline. Suction and exhaust parameters of a compressor unit are collected through a state sensing module, and a thermodynamic rigidity index representing the nonlinear coupling degree of fluid medium pressure and temperature is constructed through a rigidity observation module; an efficiency correction mechanism is introduced to eliminate mechanical interference; the feature mapping module calculates a map distortion factor according to the static performance map, and executes coordinate system affine transformation on the static performance map to generate a dynamic map; the boundary control module reconstructs a safety boundary based on the dynamic atlas and adjusts a reflux valve; according to the method, the problem of space-time mismatching of the anti-surge control boundary and the physical working condition due to dependence on a static map under the variable component working condition of natural gas hydrogen doping and the like in the prior art is solved, self-adaptive dynamic reconstruction of the safety boundary is achieved, ineffective energy consumption is remarkably reduced on the premise that the equipment safety is guaranteed, and the pipe network conveying efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of natural gas transportation technology, and in particular to an efficient transportation system based on natural gas pipelines. Background Technology

[0002] The efficiency improvement transmission system based on natural gas pipelines mainly involves centrifugal compressor units and their energy efficiency control technology in long-distance natural gas pipeline networks. In the existing natural gas transmission process, the compressor unit is the core power source, and its operating energy efficiency is directly related to the operating cost of the entire pipeline network. In order to ensure the safe and stable operation of the unit, it is usually equipped with an anti-surge control system. The working principle of this system is based on the performance spectrum calibrated at the factory, which monitors the unit's operating parameters in real time, and prevents the unit's operating point from falling into the unstable surge region by adjusting the opening of the anti-surge return valve.

[0003] However, in the actual operation of current pipeline networks, complex scenarios involving changes in the composition of the transported medium are frequently encountered, such as the alternating transport of different gas sources and the application of hydrogen-blended natural gas transport technology. Under these conditions, the thermodynamic properties of the fluid medium no longer remain constant. Traditional control systems typically employ fixed control logic, relying strictly on pre-set static performance profiles based on a single design component to define safety boundaries. Existing systems struggle to detect in real time whether the thermodynamic stiffness of the fluid medium within the pipeline has shifted during actual compression. Summary of the Invention

[0004] The main objective of this invention is to provide an efficient transportation system based on natural gas pipelines, which aims to solve the problem of thermodynamic stiffness drift in the process of efficient natural gas transportation in the prior art.

[0005] To achieve the above objectives, the present invention provides an efficiency-enhancing transportation system based on a natural gas pipeline, the system comprising: A status sensing module is used to acquire the status parameters of the compressor unit on the intake and exhaust sides. The status parameters include at least intake pressure, intake temperature, exhaust pressure, exhaust temperature, and compressor speed. A stiffness observation module is used to construct a thermodynamic stiffness index of the fluid medium in the natural gas pipeline based on the state parameters. The thermodynamic stiffness index is used to characterize the degree of nonlinear coupling between the pressure rise rate and the temperature rise rate of the fluid medium during actual compression. The feature mapping module is used to obtain the spectrum distortion factor according to the thermodynamic stiffness index, and to perform an affine transformation of the coordinate system on the compressor performance spectrum in the pre-existing system according to the spectrum distortion factor, so as to obtain a dynamic performance spectrum that matches the current fluid medium composition characteristics. A boundary control module is used to obtain a safety control boundary based on the dynamic performance spectrum and generate a control signal based on the safety control boundary, so as to adjust the opening degree of the reflux valve or the speed of the drive motor according to the control signal.

[0006] To achieve the above objectives, the present invention also provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program and the processor executes the computer program to implement the above-described method.

[0007] To achieve the above objectives, the present invention also provides a computer-readable storage medium storing a computer program, wherein a processor executes the computer program to implement the above-described method.

[0008] The beneficial effects that this invention can achieve are as follows: This invention solves the technical problem of existing control systems facing variable composition conditions such as natural gas blending with hydrogen or multiple gas source switching. This is because the inability to detect fluid thermodynamic characteristic drift in real time leads to a mismatch between the anti-surge control boundary and the physical conditions, forcing excessive safety margins and resulting in low energy efficiency. Specifically, this invention achieves millisecond-level sensing of the compression response characteristics of the fluid medium within the pipe and decoupling from mechanical losses. It does so by constructing a thermodynamic stiffness observation model including an efficiency correction factor and utilizing a graph distortion factor to perform coordinate system affine transformation on the static performance graph. The system accurately captures thermodynamic stiffness fluctuations caused by changes in fluid composition and uses an affine transformation mechanism to correct the static design spectrum in real time into a dynamic spectrum that adapts to the current medium. This mechanism enables the anti-surge safety boundary to be dynamically reconstructed adaptively following the fluctuations in medium composition. While ensuring the absolute safety of the unit in the face of transient shocks such as hydrogen addition, it completely eliminates the redundant safety margin that was forced to be reserved due to the lack of a reference system. This allows the compressor operating point to always approach the true thermodynamic efficiency optimum region under variable composition conditions, thereby significantly reducing ineffective backflow energy consumption and achieving the ultimate improvement in energy efficiency and inherent safety of the entire pipeline network. Attached Figure Description

[0009] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0010] Figure 1 This is a structural block diagram of the system in Embodiment 1 of the present invention; The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0011] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0012] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a specific posture. If the specific posture changes, the directional indication will also change accordingly.

[0013] In this invention, unless otherwise explicitly specified and limited, the terms "connection," "fixed," etc., should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral part; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0014] Furthermore, if the embodiments of this invention involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the meaning of "and / or" throughout the text includes three parallel solutions; for example, "A and / or B" includes solution A, solution B, or a solution where both A and B are satisfied simultaneously. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0015] Example 1: Reference Figure 1 This embodiment provides an efficiency-enhancing transportation system based on natural gas pipelines, the system comprising: A status sensing module is used to acquire the status parameters of the compressor unit on the intake and exhaust sides. The status parameters include at least intake pressure, intake temperature, exhaust pressure, exhaust temperature, and compressor speed. A stiffness observation module is used to construct a thermodynamic stiffness index of the fluid medium in the natural gas pipeline based on the state parameters. The thermodynamic stiffness index is used to characterize the degree of nonlinear coupling between the pressure rise rate and the temperature rise rate of the fluid medium during actual compression. The feature mapping module is used to obtain the spectrum distortion factor according to the thermodynamic stiffness index, and to perform an affine transformation of the coordinate system on the compressor performance spectrum in the pre-existing system according to the spectrum distortion factor, so as to obtain a dynamic performance spectrum that matches the current fluid medium composition characteristics. A boundary control module is used to obtain a safety control boundary based on the dynamic performance spectrum and generate a control signal based on the safety control boundary, so as to adjust the opening degree of the reflux valve or the speed of the drive motor according to the control signal.

[0016] During the operation of centrifugal compressor units in long-distance natural gas pipelines, the anti-surge control system relies on the static performance profile calibrated at the factory to define the safety boundary. However, when the composition of the transported medium changes dynamically, such as when different gas sources are transported alternately or when natural gas is blended with hydrogen, the thermodynamic properties of the fluid medium drift. This causes the static performance profile, which is based on a single design component, to fail to accurately reflect the pressure-temperature response characteristics during the actual compression process. Furthermore, the system struggles to detect changes in thermodynamic stiffness in real time, causing the safety boundary setting to deviate from the actual operating conditions, thereby affecting the energy efficiency control accuracy and operational stability of the compressor unit.

[0017] To address the aforementioned issues, this embodiment provides an efficiency-enhancing transportation system based on natural gas pipelines. The system primarily focuses on accurately sensing the operating status of the compressor unit, observing the thermodynamic stiffness of the fluid medium, dynamically adjusting the compressor performance profile, and intelligently controlling the operating boundaries. Specifically, the status sensing module, serving as the system's data entry point, is configured to capture the real-time thermodynamic operating trajectory of the compressor unit. High-precision sensors installed on the compressor unit's intake and exhaust manifolds acquire the compressor unit's status parameters on the intake and exhaust sides. These status parameters are the fundamental data source for subsequent thermodynamic model calculations and include at least intake pressure, intake temperature, exhaust pressure, exhaust temperature, and compressor speed. More specifically, the intake and exhaust pressure data are obtained from a high-frequency pressure transmitter; to capture transient fluctuations, the transmitter's sampling frequency is typically set to no less than 50Hz. The intake and exhaust temperature data are obtained from fast-response resistance temperature detectors (RTDs) or thermocouple sensors. The compressor speed data is acquired through a magnetoelectric or photoelectric speed sensor installed on the drive shaft. These analog signals, after analog-to-digital conversion, are sent to the subsequent calculation module.

[0018] The stiffness observation module is one of the core computing units of this system. Connected to the state sensing module, it constructs the thermodynamic stiffness index of the fluid medium within the natural gas pipeline based on the state parameters. Traditional control logic often assumes the gas composition is known and constant, directly using a fixed adiabatic index for calculation. However, this leads to significant errors under variable composition conditions. In this embodiment, the stiffness observation module introduces the concept of a thermodynamic stiffness index, which characterizes the degree of nonlinear coupling between the rate of pressure rise and the rate of temperature rise during the actual compression process of the fluid medium. To accurately quantify this physical quantity, the stiffness observation module executes a specific algorithm. This algorithm first establishes a model containing the ratio of pressure and temperature logarithms, and then introduces an efficiency correction factor to eliminate the interference of mechanical losses.

[0019] Specifically, the stiffness observation module calculates the thermodynamic stiffness exponent according to the following expression: ; In the formula, This represents the thermodynamic stiffness exponent obtained from real-time calculation. It is dimensionless and is calculated and output by the stiffness observation module. This represents the measured absolute pressure on the compressor's exhaust side, expressed in kilopascals (kPa); the data originates from the exhaust pressure collected by the status sensing module. This represents the measured absolute pressure on the compressor's suction side, expressed in kilopascals (kPa); the data originates from the suction pressure collected by the state sensing module. This represents the measured thermodynamic temperature on the compressor exhaust side, in Kelvin (K); the data comes from the exhaust temperature collected by the state sensing module. This represents the measured thermodynamic temperature on the compressor suction side, in Kelvin (K); the data comes from the suction temperature collected by the state sensing module. This represents the variable efficiency estimated based on the current operating conditions, and is dimensionless. This data comes from the efficiency correction unit and is obtained by interpolating the real-time flow coefficient φ onto a pre-stored baseline performance curve.

[0020] In the above expression, the polytropic index n is used to calculate the actual gas compression process. However, the polytropic index n is a mixed variable, encompassing both the gas's inherent physical properties (such as specific heat ratio k) and aerodynamic losses (entropy increase) within the compressor flow path. If n is directly used to guide control, fluctuations in compressor efficiency due to wear or changes in operating conditions may be misinterpreted by the system as changes in gas composition. Therefore, this embodiment introduces a polytropic index n into the expression. This term, acting as a decoupling factor, mathematically eliminates the negative impact of mechanical efficiency on the thermodynamic trajectory by dividing by the estimated efficiency, thus reducing the calculation results to thermodynamic stiffness that is only related to the molecular structure of the fluid medium itself. This design allows the system to sensitively capture changes in the ease of compression caused by hydrogen doping or gas source switching, providing a clean physical property reference for subsequent spectral transformations.

[0021] The feature mapping module is connected to the stiffness observation module and is used to obtain the spectrum distortion factor based on the thermodynamic stiffness index, and then perform an affine transformation of the coordinate system. Since the performance spectrum of the compressor at the factory is calibrated based on a specific design gas (usually pure methane or nitrogen), when the stiffness of the actual operating medium drifts, the original spectrum will no longer be applicable. The feature mapping module calculates a normalized distortion factor to quantify the difference between the current medium and the design medium, and uses this as a basis to mathematically stretch or compress the static spectrum to generate a dynamic performance spectrum that matches the composition characteristics of the current fluid medium.

[0022] Specifically, the feature mapping module calculates the map distortion factor based on the following expression: ; In the formula, This represents the graph distortion factor, which is dimensionless and is calculated and output by the feature mapping module to guide subsequent coordinate transformations. This represents the system's preset reference gas adiabatic index, which is dimensionless and derived from the compressor's factory design manual or calibration report. It is usually a constant (e.g., 1.31 for methane).

[0023] Understandably, the design logic of the above expression is based on the similarity principle of gas dynamics. In fluid mechanics, the term... , The Mach number effect and sound velocity characteristics of gas during expansion or compression within the impeller channel are directly determined. By comparing the real-time observed stiffness term with the stiffness term of the design reference, a dimensionless ratio reflecting the difference in compressibility is constructed. .when A value greater than 1 indicates that the current gas's acoustic characteristics are more active than the design gas (e.g., the addition of hydrogen leads to an increase in sound speed and a decrease in Mach number); conversely, a value less than 1 indicates that the gas is heavier. The technical advantage of this factor is that by condensing complex thermodynamic property changes into a simple scalar, the control system no longer needs to perform complex full-flow field simulations. It can approximate the performance curve under real-world conditions with extremely high accuracy simply by linearly scaling (affine transformation) the coordinate axes of the original spectrum according to this factor, significantly reducing the computational load on the controller and improving response speed.

[0024] The boundary control module, acting as the system's execution decision unit, obtains the safety control boundary based on the dynamic performance graph and generates control signals accordingly. After obtaining the dynamic performance graph after affine transformation, the module redraws the anti-surge control line on the graph. Since the graph has been corrected for real-time gas stiffness, the reconstructed safety boundary closely matches the compressor's physical surge boundary, eliminating the need for a large, blind safety margin as in traditional technologies. The boundary control module compares the real-time operating point (determined by flow rate and pressure ratio) with the reconstructed safety control boundary and generates adjustment commands using a built-in PID control algorithm. When the operating point approaches the safety boundary, the module outputs a signal to adjust the opening of the anti-surge return valve, allowing some gas to flow back to the inlet to increase flow rate; or, in units with speed regulation capabilities, it outputs a signal to adjust the drive motor speed, thereby ensuring the compressor always operates in the optimal energy efficiency region without surging.

[0025] In summary, this embodiment overcomes the technical barrier of traditional control systems relying on hysteresis component detection data by constructing a thermodynamic stiffness observation model that includes an efficiency correction factor. It achieves millisecond-level perception and decoupling of mechanical losses for the compression response characteristics of the fluid medium (especially hydrogen-doped heterogeneous fluid) within the pipe. Based on this, an affine transformation of the coordinate system is performed on the static performance spectrum using a spectrum distortion factor, mathematically eliminating the spatiotemporal mismatch between control logic and physical operating conditions. This allows the anti-surge safety boundary to be adaptively and dynamically reconstructed in response to fluctuations in the medium composition. While ensuring the absolute safety of the compressor unit, it completely eliminates the redundant safety margin that was forced to be reserved due to the lack of a reference frame. This allows the compressor operating point to always approach the true thermodynamic efficiency optimum under variable composition conditions, thereby significantly reducing ineffective backflow energy consumption and achieving a maximum improvement in the overall pipeline network's energy efficiency.

[0026] Example 2: In this embodiment, the stiffness observation module includes: A model building unit is used to establish a ratio relationship model containing pressure and temperature logarithmic terms, which is used to quantify the thermodynamic response characteristics during compression. An efficiency correction unit is used to obtain the estimated efficiency of the current flow coefficient and input the estimated efficiency as a correction factor into the ratio relationship model.

[0027] Understandably, the model building unit is configured to establish a ratio model containing logarithmic terms for pressure and temperature, its physical essence being a logarithmic linearization of the polytropic process equations, used to quantify the thermodynamic response characteristics during compression. In actual natural gas compression, the gas state changes follow polytropic process laws, with a specific power-law relationship between temperature and pressure increases. This relationship is directly controlled by the degrees of freedom of gas molecules (i.e., specific heat ratio) and energy dissipation during compression. To transform this nonlinear power-law relationship into linear or quasi-linear characteristics easily handled by the control system, the model building unit first performs a natural logarithmic operation on the ratio of real-time collected exhaust pressure to intake pressure to extract the pressure response component characterizing the intensity of mechanical work; simultaneously, it performs a natural logarithmic operation on the ratio of exhaust temperature to intake temperature to extract the temperature response component characterizing the intensity of internal energy change. The ratio of these two components profoundly reveals the thermodynamic hardness of the fluid medium when receiving mechanical work, i.e., the tendency of the gas to generate a temperature rise when compressed.

[0028] However, a simple pressure-to-temperature ratio model not only includes gas property information but also inevitably couples with the compressor's own aerodynamic efficiency information. To eliminate the interference of mechanical performance fluctuations (such as efficiency changes caused by flow rate variations) on property observation, the efficiency correction unit is configured to introduce a decoupling mechanism. This unit obtains an estimated efficiency of the current flow coefficient and inputs this estimated efficiency as a correction factor into the ratio model. Specifically, the efficiency correction unit calculates the dimensionless flow coefficient based on the current rotational speed, flow rate, and geometry, and performs interpolation indexing on a pre-stored baseline performance curve to obtain the estimated variable efficiency that should be present at this operating point under standard test conditions. Introducing this efficiency into the calculation model is equivalent to mathematically removing equipment factors, thereby refining the thermodynamic stiffness index that is only related to the composition of the fluid medium itself.

[0029] It should also be noted that the aforementioned polytropic index is a parameter reflecting the compression process path, and its value is determined by two factors: the specific heat ratio of the gas itself (k value, determined by the composition) and the efficiency of the compression process (η, determined by the equipment operating conditions). In the special scenario of natural gas pipeline transportation, especially when hydrogen is involved, because the specific heat ratio of hydrogen (approximately 1.41) is much higher than that of methane (approximately 1.31), even a small amount of hydrogen blending will cause a significant increase in the k value of the mixed gas. However, changes in compressor operating conditions (such as reduced flow rate) will also lead to a decrease in efficiency, thereby altering the polytropic index.

[0030] If the polyvariance index is used directly as the control basis, the system cannot distinguish whether the gas composition has changed or the operating conditions have changed. Therefore, the aforementioned expression performs a normalization operation mathematically by dividing the calculated polyvariance index by the baseline efficiency obtained from a table based on the current operating conditions. Its physical meaning is that, assuming the current efficiency change perfectly matches the baseline curve, after eliminating the efficiency effect, the remaining numerical fluctuations can only be attributed to changes in gas composition (i.e., the k-value). This logical design has strong adaptability and is particularly suitable for pipeline systems lacking online gas chromatographs or with lagging chromatograph data. By utilizing the compressor itself as a large physical property sensor, millisecond-level sensing of changes in fluid medium composition is achieved. It is extremely sensitive to changes in hydrogen concentration and can be used as a feedforward signal to directly drive subsequent spectral coordinate transformations. This allows for adaptive reconstruction of the control boundary before the gas reaches the next station or before the compressor enters a dangerous operating condition, eliminating the risk of response hysteresis and malfunction in traditional control.

[0031] Example 3:

[0032] The model building unit is also used for: Obtain the ratio of exhaust pressure to intake pressure and obtain the logarithmic value of the pressure, so as to use the logarithmic value of the pressure as the pressure response component. Obtain the ratio of exhaust temperature to intake temperature and obtain the logarithmic value of the temperature, so as to use the logarithmic value of the temperature as the temperature response component. The stiffness value is obtained by multiplying the reciprocal of the difference between the pressure response component and the temperature response component by the pressure response component. The efficiency correction unit is also used to obtain the thermodynamic stiffness index based on the stiffness value.

[0033] Understandably, the model building unit first performs data preprocessing and feature extraction. It acquires the ratio of exhaust pressure to intake pressure in real time through the state-aware module and processes this ratio using natural logarithm calculation to obtain the pressure logarithm value. Physically, this process corresponds to linearizing the pressure change term in the polytropic process equation. The resulting value is defined as the pressure response component, representing the intensity of the pressure increase in the fluid medium under the mechanical work of the compressor impeller. Simultaneously, the model building unit acquires the ratio of exhaust temperature to intake temperature and performs natural logarithm calculation to obtain the temperature logarithm value. This value is defined as the temperature response component, whose physical meaning lies in quantifying the intensity of the temperature rise caused by the increase in internal energy of the fluid medium during compression.

[0034] Subsequently, the model building unit enters the basic stiffness calculation stage, executing specific algebraic operation logic: first, it calculates the difference between the pressure response component and the temperature response component, which thermodynamically reflects the degree to which the actual compression path deviates from the isothermal process; then, it calculates the reciprocal of this difference and multiplies it by the pressure response component. The output of this operation is defined as the stiffness value (physically, this value is the polytropic index under the current operating condition). However, this stiffness value is a mixed physical quantity, which not only includes the component characteristics of the fluid medium itself (such as the change in specific heat ratio caused by hydrogen incorporation), but also inevitably couples with the influence of the compressor's current operating efficiency. In order to achieve a pure extraction of the medium's physical properties, the efficiency correction unit intervenes. The efficiency correction unit performs a reverse compensation operation on the stiffness value based on the estimated efficiency obtained from the current flow coefficient, and finally obtains a thermodynamic stiffness index that can truly characterize the component characteristics of the fluid medium.

[0035] Example 4:

[0036] In this embodiment, the efficiency correction unit includes: A curve storage subunit, wherein the curve storage subunit stores a reference performance curve; An interpolation indexing subunit is used to obtain a flow coefficient based on the acquired intake flow rate, rotational speed, and impeller geometry, and to perform interpolation indexing on the baseline performance curve based on the flow coefficient to obtain the estimated efficiency.

[0037] It should be noted that the efficiency correction unit constructs a standardized reference system through the collaborative operation of the curve storage subunit and the interpolation index subunit, ensuring that the final output thermodynamic stiffness index reflects only the compositional characteristics of the fluid medium itself, rather than the mechanical characteristics of the equipment operating efficiency.

[0038] Specifically, the curve storage subunit is configured to store a reference performance curve. This reference performance curve is not a randomly generated universal curve, but rather a dimensionless characteristic relationship fitted based on bench test data of the compressor unit at the time of its delivery or full-condition testing using standard design gas (usually pure methane or natural gas with specific components) during the on-site commissioning phase. The curve constructs a mathematical model describing the aerodynamic performance of the compressor under ideal single-medium conditions, with the flow coefficient as the abscissa and the variable efficiency as the ordinate. The purpose of storing the curve as dimensionless is to isolate the influence of specific speeds and inlet conditions, so that the reference system still has universality under variable speed conditions.

[0039] During actual compressor operation, the interpolation index subunit first obtains real-time suction flow rate and compressor speed from the state sensing module and flow metering system, and calculates the current dimensionless flow coefficient by combining it with the impeller geometry parameters preset in the system. Subsequently, using the calculated real-time flow coefficient as the index key, the subunit performs numerical interpolation (such as linear interpolation or cubic spline interpolation) on the baseline performance curve in the curve storage subunit to obtain the estimated efficiency corresponding to that operating point. This estimated efficiency represents the efficiency value that the compressor should exhibit at this flow rate if the current conveyed medium is the standard design gas.

[0040] The real-time flow coefficient is calculated to satisfy the expression: ; The estimated efficiency satisfies the expression based on the benchmark curve; ; In the formula, The real-time flow coefficient describes the relative flow rate of fluid passing through the compressor impeller, eliminating the influence of speed and machine size. It is the abscissa for determining the aerodynamic operating position of the compressor. The suction side volumetric flow rate is the actual volume of gas flowing through the compressor inlet per unit time (which needs to be converted to the operating flow rate under inlet conditions; it is collected by a flow meter (such as an ultrasonic flow meter or orifice plate flow meter) installed in the compressor inlet pipe section and calculated in combination with suction temperature and pressure). The impeller geometric diameter is the characteristic diameter of the first-stage impeller of a centrifugal compressor (usually referring to the impeller outer diameter, in meters). This refers to the compressor speed; To estimate polytropic efficiency, the theoretical polytropic efficiency value that the compressor should possess under the current flow coefficient, assuming no component drift of the medium, is used as the normalized denominator for subsequent calculation of the stiffness exponent. This is the baseline performance mapping function.

[0041] Example 4: In this embodiment, the feature mapping module includes a factor calculation unit and a transformation execution unit: The factor calculation unit is used to normalize and compare the thermodynamic stiffness index with the system's preset reference gas adiabatic index and the derived terms of the adiabatic index to obtain a value reflecting the degree of drift of the current fluid medium relative to the design medium in terms of sound velocity characteristics and isentropic index. The transformation execution unit is used to keep the origin coordinates of the compressor performance graph unchanged, and apply non-proportional linear stretching or compression operations to the flow coordinate axis and pressure head coordinate axis of the compressor performance graph according to the magnitude of the graph distortion factor, so as to obtain a dynamic performance graph.

[0042] In this embodiment, the feature mapping module further includes: A blocking warning unit is used to obtain the blocking boundary of the compressor based on the spectrum distortion factor.

[0043] Building upon the aforementioned embodiments, this embodiment, after obtaining the spectrum distortion factor, involves the transformation execution unit performing an affine transformation of the coordinate system on the pre-existing static compressor performance spectrum in the system. This performance spectrum typically uses flow rate (or flow coefficient) as the abscissa and pressure head (or pressure ratio) as the ordinate. The transformation execution unit maintains the origin coordinates of the compressor performance spectrum (i.e., the zero flow and zero pressure head point) unchanged, and applies non-proportional linear stretching or compression operations to the flow rate and pressure head axes of the compressor performance spectrum based on the magnitude of the spectrum distortion factor. This means that the characteristic curve originally applicable to pure methane is distorted or corrected in mathematical space, thereby generating a dynamic performance spectrum capable of describing the aerodynamic characteristics of the current mixed gas (such as hydrogen-blended natural gas).

[0044] Specifically, the transformation execution unit performs coordinate transformation on the feature points on the graph according to the following expression: ; ; In the formula, This refers to the dynamic pressure head coefficient. This is the static pressure head coefficient; For dynamic flow coefficients; This is the static flow coefficient.

[0045] The above expression uses a non-proportional affine transformation logic (i.e., the ordinate and...). Inversely proportional, the x-axis is... The inverse relationship is because the increased gas stiffness due to hydrogen doping means that at the same mechanical speed, the pressure ratio that the compressor can provide will decrease (because the gas is more difficult to compress), and at the same time, due to the increase in sound speed, the actual flow range corresponding to the same Mach number will also change.

[0046] This transformation logic ensures that the graph seen by the control system is consistent with the physical reality, dynamically shrinking the high-efficiency zone and surge boundary, preventing the controller from mistakenly believing that the compressor still has a large boost margin and blindly increasing the speed, or mistakenly judging that the current flow is in the safe zone and failing to open the anti-surge valve in time.

[0047] Furthermore, the feature mapping module also includes a blockage warning unit. This unit is used to obtain the compressor's blockage boundary based on the spectrum distortion factor. The blockage condition refers to the limiting state where the fluid velocity at the impeller throat reaches the speed of sound, preventing further flow rate increases. Due to the significant change in the gas speed after hydrogen doping, the blockage boundary will also drift. The blockage warning unit corrects the maximum flow rate boundary in the static spectrum based on the distortion factor, generating a dynamic blockage flow rate threshold.

[0048] The expression for obtaining the dynamic blocking boundary satisfies: ; This is a dynamic blocking traffic threshold; For reference, the blocked traffic.

[0049] Understandably, under the same geometric flow channel constraints, the higher the speed of sound, the larger the allowable limit volumetric flow rate (approximately in the subsonic range). Therefore, the blockage warning unit will push the blockage boundary to the right. It is also understandable that the above expression expands the operability range of the compressor under hydrogen-blended conditions. Traditional control systems may artificially limit the speed before the flow rate reaches the actual blockage point. However, this solution releases the incorrectly locked capacity by accurately calculating the dynamic blockage flow threshold, allowing the system to safely increase the delivery volume under high flow conditions and further tapping the potential for efficiency improvement.

[0050] Example 5:

[0051] In this embodiment, the boundary control module includes: A steady-state reconstruction unit is used to scale the reference surge flow line in the compressor performance graph according to the inverse square root proportionality of the graph distortion factor in order to obtain a safe control boundary. A transient compensation unit is used to obtain the rate of change of the spectrum distortion factor over time. When the rate of change exceeds a preset threshold, a damping gain term positively correlated with the rate of change is generated and the damping gain term is superimposed on the safety control boundary.

[0052] It should be noted that the above content, through the internally integrated steady-state reconstruction unit and transient compensation unit, constructs a dual-layer safety protection mechanism that takes into account both static accuracy and dynamic stability, aiming to solve the fundamental contradiction that a single fixed surge boundary cannot adapt to changes in the physical flow field under variable component operating conditions.

[0053] First, the steady-state reconstruction unit is responsible for correcting the reference boundary. Since the surge phenomenon in a compressor is essentially caused by aerodynamic stall of the fluid within the impeller channel, and the location of the stall point is highly correlated with the fluid's Mach number (the ratio of flow velocity to sound velocity), when hydrogen is added to natural gas, increasing the sound velocity, the actual Mach number of the machine will decrease at the same mechanical rotational speed, causing the surge boundary to drift. Based on the principle of gas dynamics similarity, the steady-state reconstruction unit uses the spectral distortion factor output by the preceding module to scale the coordinates of the reference surge flow line stored in the system. Specifically, this unit is configured to execute computational logic based on the inverse square root relationship to obtain a basic safety control boundary adapted to the current medium characteristics.

[0054] The expression for the basic security control boundary satisfies: ; In the formula, Based on the basic safety control boundary flow rate, the predicted critical volumetric flow rate at which the compressor will surge under the current fluid medium composition and current speed is the static baseline for anti-surge control; The surge flow rate is the surge limit flow rate calibrated at the current speed ω, which is usually stored in the controller in the form of a lookup table or a polynomial fitting curve.

[0055] In centrifugal compressors, there is a specific relationship between the flow coefficient and the Mach number; when hydrogen is added... When the speed is greater than 1, it means that the thermodynamic stiffness of the fluid increases, and the speed of sound increases. With the physical rotational speed remaining constant, the higher speed of sound causes the Mach number of the airflow relative to the blades to decrease. According to compressor characteristics, the surge flow rate at low Mach numbers is usually smaller than the surge flow rate at high Mach numbers (i.e., the surge line shifts to the left). The formula uses... The form is precisely for mathematically simulating this physical phenomenon: when When the value is greater than 1, the product term is less than 1, thus reducing the baseline surge flow rate towards lower flow rates. This logic exhibits excellent adaptability in hydrogen-blended transport scenarios, enabling the control system to identify the true stability margin after the gas becomes lighter and the sound velocity increases. Under hydrogen-blended conditions, the system allows the compressor to operate at a lower flow rate without opening the reflux valve, thereby uncovering a low-flow, high-efficiency operating range that is often obscured by traditional conservative control strategies, significantly reducing the ineffective opening time of the anti-surge valve.

[0056] Secondly, considering the potential for drastic fluctuations in pipeline operating conditions (such as rapid switching of gas source valves or the passage of slug flow), the transient compensation unit is configured to superimpose a dynamic protection layer on top of the steady-state boundary. This unit is used to monitor the rate of change of the spectrum distortion factor over time (i.e., the rate of component change) in real time. When the rate of change exceeds the safety threshold set by the system, it indicates that the fluid composition in the pipe is undergoing a drastic change. At this time, simple steady-state calculation may be risky due to sensor lag or actuator response delay. Therefore, the transient compensation unit generates a damping gain term that is proportional to the rate of change and superimposes this term onto the safety control boundary, thereby temporarily widening the safety margin during the component oscillation period.

[0057] The transient compensation unit calculates the final dynamic safety control boundary based on the following expression: ; In the formula, For ultimate safety control of boundary flow; Basic security control of boundary flows; β is the damping gain coefficient; Rate of change of distortion factor; This is the dead zone threshold for the rate of change.

[0058] During the natural gas transportation process, when When rapid changes occur, it means the fluid properties are extremely unstable. In this case, the steady-state model may have instantaneous calculation errors, and the mechanical action of the return valve may lag behind the airflow changes. By introducing differential terms... During periods of drastic component fluctuations, artificially shifting the surge boundary towards higher flow rates means the anti-surge valve will open prematurely, sacrificing short-term energy efficiency for absolute equipment safety. The adaptability of this logic lies in its effectiveness only in transient situations: once the component changes stabilize and the rate of change reaches zero, the compensation term automatically disappears, and the control boundary immediately reverts to the state determined by... The determined physical limits of high efficiency are thus largely resolved, addressing the paradox of balancing efficiency and safety. It maximizes efficiency in steady state (boundary contraction) and prioritizes survival in transient state (boundary expansion), thereby eliminating unexpected compressor surge shutdowns caused by sudden changes in composition.

[0059] In this embodiment, the boundary control module further includes: A closed-loop control unit is used to acquire the compressor inlet flow rate as a process variable and the safety control boundary as a set value; when the process variable and the set value satisfy the set relationship, the closed-loop control unit drives the reflux valve to open.

[0060] By constructing a high-precision negative feedback control loop, it is ensured that when the compressor's operating point approaches the dynamic surge line reconstructed by the preceding unit, it can intervene with a millisecond-level response speed, while remaining silent when the operating point is in the safe range, thereby achieving a precise balance between energy efficiency and safety.

[0061] Specifically, the closed-loop control unit first acquires the compressor inlet flow rate in real time as a process variable. This flow rate data is not a simple raw differential pressure signal, but a standard volumetric flow rate after temperature and pressure compensation, which can truly reflect the current gas load entering the compressor impeller. Simultaneously, this unit uses the safety control boundary (i.e., the dynamically reconstructed anti-surge flow threshold) generated jointly by the steady-state reconstruction unit and the transient compensation unit as the setpoint of the control system. It is important to note that, unlike the fixed setpoint in traditional control, the setpoint in this scheme is a dynamic target that fluctuates in real time with the fluid thermodynamic stiffness exponent.

[0062] When the process variable (actual flow rate) and the set value (safety boundary) satisfy the set relationship, that is, when the actual flow rate decreases and approaches or attempts to fall below the safety boundary, the closed-loop control unit immediately activates its internal control algorithm, calculates the required valve opening signal, and drives the anti-surge return valve to open. In order to adapt to the characteristics of rapid gas volume fluctuation and large inertia in natural gas transportation, it is understood that the unit preferentially adopts the existing proportional-integral-derivative (PID) control algorithm to generate control commands.

[0063] Example 6: In this embodiment, the state awareness module includes: A high-frequency sampling unit, comprising a pressure sensor and a temperature sensor, wherein the pressure sensor is used to acquire pressure parameters and the temperature sensor is used to acquire state parameters; The trend extraction unit is used to perform moving average filtering on the pressure and temperature signals acquired by the high-frequency sampling unit to filter out random noise components, and transmit the trend component reflecting the evolution of thermodynamic state to the stiffness observation module.

[0064] Understandably, pressure sensors are used to acquire instantaneous fluid pressure parameters on the intake and exhaust sides, while temperature sensors are used to acquire corresponding fluid thermodynamic temperature parameters. To capture potential precursors to rapid surges or pressure waves during gas source switching, the sampling frequency is typically set to a value much higher than the fluid thermodynamic time constant (e.g., 100Hz to 1kHz). However, while this high-frequency sampling ensures information integrity, it also introduces a significant amount of non-thermodynamic noise. In the actual operating environment of a centrifugal compressor, fluid flow within the impeller and diffuser is accompanied by intense turbulent pulsations, vortex shedding, and acoustic standing waves in the pipes. These high-frequency components superimposed on the actual static pressure and temperature signals create substantial random noise. If the raw signal containing this noise is directly fed into the subsequent stiffness observation model involving logarithmic calculations, the calculated thermodynamic stiffness exponent will exhibit severe pseudo-fluctuations due to the differential amplification effect, thus misleading the control system.

[0065] To this end, the trend extraction unit performs digital signal processing on the original signal. The unit adopts a moving average filtering strategy to construct a time-dimensional low-pass filter. The core logic of this filter is to use statistical principles to offset the alternating positive and negative random turbulence noise by arithmetically averaging the data within a continuous sampling window, thereby retaining the low-frequency trend component that reflects the evolution of the thermodynamic state of the fluid medium. The essence of this process is a finite impulse response (FIR) low-pass filter.

[0066] Example 7: In this embodiment, the system further includes a cloud-edge collaboration module, which includes an edge computing unit and a cloud analytics unit; The edge computing unit is used to obtain the thermodynamic stiffness index and upload the thermodynamic stiffness index as component feature data. The cloud-based analysis unit is used to acquire and analyze the component characteristic data uploaded by each node of the pipeline network to draw a component distribution map of the entire pipeline network and send a feedforward early warning signal to the downstream stations.

[0067] Understandably, the edge computing unit, acting as a distributed data preprocessing node, is configured to communicate directly with the stiffness observation module. Unlike traditional SCADA systems that only upload raw temperature and pressure simulations, the edge computing unit performs feature extraction tasks, acquiring the thermodynamic stiffness index calculated by the stiffness observation module in real time. Since the thermodynamic stiffness index has been freed from interference from equipment efficiency and mechanical noise, becoming a pure digital fingerprint characterizing the fluid composition, the edge computing unit packages this index along with timestamps and station geographic information encoding to generate component feature data and uploads it to the cloud.

[0068] The cloud-based analysis unit acts as a virtual flow observer for the entire network, acquiring and analyzing the component characteristic data uploaded by each node in the pipeline network. Internally, this unit runs a hydraulic-thermal coupling simulation model based on the pipeline network topology. Utilizing the component characteristic data uploaded from upstream stations, combined with pipe segment length, pipe diameter, and real-time flow velocity, it deduces the physical movement trajectory of a specific component gas mass (such as a high-concentration hydrogen-doped gas mass) within the pipeline, thereby drawing a component distribution map of the entire pipeline network. Based on this distribution map, the cloud-based analysis unit can accurately calculate the time window for the gas mass to reach the downstream station and generate a feedforward early warning signal to send to the downstream station.

[0069] Furthermore, in one embodiment, the present invention also provides a computer storage medium storing a computer program, which, when executed by a processor, implements the steps of the methods described in the foregoing embodiments.

[0070] In some embodiments, the computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; or it may be a device including one or any combination of the above-mentioned memories. The computer may be a variety of computing devices, including smart terminals and servers.

[0071] In some embodiments, executable instructions may take the form of a program, software, software module, script, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a standalone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0072] As an example, executable instructions may, but do not necessarily, correspond to files in a file system. They may be stored as part of a file that holds other programs or data, for example, in one or more scripts in a Hyper Text Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple collaborating files (e.g., a file that stores one or more modules, subroutines, or code sections).

[0073] As an example, executable instructions can be deployed to execute on a single computing device, or on multiple computing devices located in one location, or on multiple computing devices distributed across multiple locations and interconnected via a communication network.

[0074] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0075] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0076] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory / random access memory, magnetic disk, optical disk) and includes several instructions to cause a multimedia terminal device (which may be a mobile phone, computer, television receiver, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0077] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. An efficiency-enhancing transportation system based on natural gas pipelines, characterized in that, The system includes: A status sensing module is used to acquire the status parameters of the compressor unit on the intake and exhaust sides. The status parameters include at least intake pressure, intake temperature, exhaust pressure, exhaust temperature, and compressor speed. A stiffness observation module is used to construct a thermodynamic stiffness index of the fluid medium in the natural gas pipeline based on the state parameters. The thermodynamic stiffness index is used to characterize the degree of nonlinear coupling between the pressure rise rate and the temperature rise rate of the fluid medium during actual compression. The feature mapping module is used to obtain the spectrum distortion factor according to the thermodynamic stiffness index, and to perform an affine transformation of the coordinate system on the compressor performance spectrum in the pre-existing system according to the spectrum distortion factor, so as to obtain a dynamic performance spectrum that matches the current fluid medium composition characteristics. A boundary control module is used to obtain a safety control boundary based on the dynamic performance spectrum and generate a control signal based on the safety control boundary, so as to adjust the opening degree of the reflux valve or the speed of the drive motor according to the control signal.

2. The efficiency-enhancing transportation system based on natural gas pipelines as described in claim 1, characterized in that, The stiffness observation module includes: A model building unit is used to establish a ratio relationship model containing pressure and temperature logarithmic terms, which is used to quantify the thermodynamic response characteristics during compression. An efficiency correction unit is used to obtain the estimated efficiency of the current flow coefficient and input the estimated efficiency as a correction factor into the ratio relationship model.

3. The efficiency-enhancing transportation system based on a natural gas pipeline as described in claim 2, characterized in that, The model building unit is also used for: Obtain the ratio of exhaust pressure to intake pressure and obtain the logarithmic value of the pressure, so as to use the logarithmic value of the pressure as the pressure response component. Obtain the ratio of exhaust temperature to intake temperature and obtain the logarithmic value of the temperature, so as to use the logarithmic value of the temperature as the temperature response component. The stiffness value is obtained by multiplying the reciprocal of the difference between the pressure response component and the temperature response component by the pressure response component. The efficiency correction unit is also used to obtain the thermodynamic stiffness index based on the stiffness value.

4. The efficiency-enhancing transportation system based on a natural gas pipeline as described in claim 1, characterized in that, The feature mapping module includes a factor calculation unit and a transformation execution unit: The factor calculation unit is used to normalize and compare the thermodynamic stiffness index with the system's preset reference gas adiabatic index and the derived terms of the adiabatic index to obtain a value reflecting the degree of drift of the current fluid medium relative to the design medium in terms of sound velocity characteristics and isentropic index. The transformation execution unit is used to keep the origin coordinates of the compressor performance graph unchanged, and apply non-proportional linear stretching or compression operations to the flow coordinate axis and pressure head coordinate axis of the compressor performance graph according to the magnitude of the graph distortion factor, so as to obtain a dynamic performance graph.

5. The efficiency-enhancing transportation system based on a natural gas pipeline as described in claim 1, characterized in that, The boundary control module includes: A steady-state reconstruction unit is used to scale the reference surge flow line in the compressor performance graph according to the inverse square root proportionality of the graph distortion factor in order to obtain a safe control boundary. A transient compensation unit is used to obtain the rate of change of the spectrum distortion factor over time. When the rate of change exceeds a preset threshold, a damping gain term positively correlated with the rate of change is generated and the damping gain term is superimposed on the safety control boundary.

6. The efficiency-enhancing transportation system based on a natural gas pipeline as described in claim 2, characterized in that, The efficiency correction unit includes: A curve storage subunit, wherein the curve storage subunit stores a reference performance curve; An interpolation indexing subunit is used to obtain a flow coefficient based on the acquired intake flow rate, rotational speed, and impeller geometry, and to perform interpolation indexing on the baseline performance curve based on the flow coefficient to obtain the estimated efficiency.

7. The efficiency-enhancing transportation system based on a natural gas pipeline as described in claim 1, characterized in that, The state awareness module includes: A high-frequency sampling unit, comprising a pressure sensor and a temperature sensor, wherein the pressure sensor is used to acquire pressure parameters and the temperature sensor is used to acquire state parameters; The trend extraction unit is used to perform moving average filtering on the pressure and temperature signals acquired by the high-frequency sampling unit to filter out random noise components, and transmit the trend component reflecting the evolution of thermodynamic state to the stiffness observation module.

8. The efficiency-enhancing transportation system based on a natural gas pipeline as described in claim 5, characterized in that, The boundary control module also includes: A closed-loop control unit is used to acquire the compressor inlet flow rate as a process variable and the safety control boundary as a set value; when the process variable and the set value satisfy the set relationship, the closed-loop control unit drives the reflux valve to open.

9. The efficiency-enhancing transportation system based on a natural gas pipeline as described in claim 4, characterized in that, The feature mapping module further includes: A blocking warning unit is used to obtain the blocking boundary of the compressor based on the spectrum distortion factor.

10. The efficiency-enhancing transportation system based on a natural gas pipeline as described in claim 1, characterized in that, The system also includes a cloud-edge collaboration module, which includes an edge computing unit and a cloud analytics unit. The edge computing unit is used to obtain the thermodynamic stiffness index and upload the thermodynamic stiffness index as component feature data. The cloud-based analysis unit is used to acquire and analyze the component characteristic data uploaded by each node of the pipeline network to draw a component distribution map of the entire pipeline network and send a feedforward early warning signal to the downstream stations.

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