Gas pipeline network intelligent pressure regulating system based on hydrogen doping concentration perception

Abstract

The application discloses a kind of based on hydrogen concentration sensing's gas pipe network intelligent pressure regulating system, it is related to gas pipe network intelligent control technical field.The sensing module, processing module, execution module and feedback module are included;Sensing module acquires upstream pressure, downstream pressure, temperature, flow, valve position, pressure difference and gas component information;Processing module carries out consistency confidence analysis and correction to the volume fraction of multiple source hydrogen, and outputs accurate hydrogen volume fraction;Execution module reconstructs mixed gas property based on the corrected hydrogen volume fraction, calculates feedforward opening degree and combines PID valve control amount to carry out dynamic adjustment to pressure regulating valve;Feedback module extracts steady-state deviation and recovery time based on the adjusted pressure response curve, evaluates pressure regulating result and re-tunes the experience parameter of PID, can adapt to the change of mixed gas property after hydrogen is mixed into natural gas, reduce pressure regulating lag, overshoot and pressure oscillation, improve outlet pressure control precision and operating stability.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology for gas pipeline networks, specifically to an intelligent pressure regulation system for gas pipeline networks based on hydrogen concentration sensing. Background Technology

[0002] Natural gas blending with hydrogen has become an important pathway for the large-scale utilization of hydrogen energy. As a key link connecting long-distance pipelines and urban gas pipeline networks, the operational stability of the pressure regulating system is directly related to the safe transportation of hydrogen-blended gas. However, the significant difference in physical properties between hydrogen and natural gas alters the flow and combustion characteristics of the mixed gas, thus making pressure regulation of gas pipeline networks with hydrogen blending of natural gas of great importance. Most existing pressure regulating models are based on fixed physical properties of natural gas. After hydrogen is added, the calorific value, density, viscosity, sound velocity and other parameters of the mixed gas will change. Traditional pressure regulators still use fixed valve flow coefficients or empirical control curves for adjustment, which cannot accurately match the gas transport characteristics under different hydrogen concentrations. This leads to increased pressure regulation control lag, and in severe cases, it may even cause local pressure oscillations and pipeline network instability. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides an intelligent pressure regulation system for gas pipelines based on hydrogen concentration sensing, which solves the problems mentioned in the background section.

[0004] To achieve the above objectives, the present invention is implemented through the following technical solution: an intelligent pressure regulating system for gas pipeline network based on hydrogen concentration sensing, comprising a sensing module, a processing module, an execution module and a feedback module; The sensing module is used to collect operating parameters in real time through monitoring devices deployed on the upstream and downstream sides of the pressure regulating station and at the pressure regulating valve body; The processing module is used to perform consistency confidence analysis on the hydrogen gas integral counts from different sources collected in real time and output corrected values ​​for the hydrogen gas integral counts. The execution module is used to receive the hydrogen gas integral correction value and dynamically adjust the outlet pressure of the gas pipeline network in combination with the operating parameters; The feedback module is used to verify the pressure response results after valve adjustment in real time, and update the parameters output by the processing module and the execution module based on the verification results.

[0005] Furthermore, the operating parameters include at least upstream pressure, downstream pressure, upstream temperature, downstream temperature, instantaneous flow rate, valve opening, pressure difference across the valve, and gas composition information; the gas composition information includes at least hydrogen volume fraction, methane volume fraction, carbon dioxide volume fraction, and one or more other gas components.

[0006] Furthermore, a consistency confidence analysis is performed on the hydrogen gas integral counts from different sources collected in real time, and corrected values ​​for the hydrogen gas integral counts are output, including: The hydrogen gas integral count at the current moment is obtained in real time, including at least the hydrogen gas integral count directly measured by the gas analyzer, the hydrogen gas integral count obtained by thermal conductivity inversion, the hydrogen gas integral count obtained by density inversion, the hydrogen gas integral count obtained by sound speed inversion, and the hydrogen gas integral count calculated by converting upstream hydrogen injection flow rate and natural gas flow rate. The median of the hydrogen gas integral count from various sources is used as a reference value. The hydrogen gas integrals directly measured by the gas analyzer, the hydrogen gas integrals obtained by thermal conductivity inversion, the hydrogen gas integrals obtained by density inversion, the hydrogen gas integrals obtained by sound velocity inversion, and the hydrogen gas integrals obtained by converting upstream hydrogen injection flow rate and natural gas flow rate are respectively compared with the reference value to calculate the deviation amount for each source. The health status of each source is then assigned a corresponding weight, and the deviation amounts of each source are linearly weighted and fused according to the corresponding weights to obtain the total deviation amount. The total deviation is normalized by dividing the total deviation by the sum of the deviations from each source, resulting in the total deviation degree. The total deviation degree is then used to calculate the consistency confidence degree through the decay relationship. A confidence threshold is preset. If the consistency confidence level is less than the confidence threshold, the source with the largest deviation is removed, and the multi-source weights are recalculated and weighted fusion is performed to obtain the corrected value of the hydrogen gas integral. If the consistency confidence level is greater than or equal to the confidence threshold, there is no need to perform anomaly removal, and the reference value is directly used as the corrected value of the hydrogen gas integral.

[0007] Furthermore, assigning corresponding weights based on the health status from each source specifically includes: Let N be the total number of samples from the i-th source within a preset time window, meaning each source corresponds to N hydrogen gas integrals, where N is a positive integer; where i represents the index of the source type. In this embodiment, the source type is at least one of the following: gas analyzer, thermal conductivity detector, density detector, sound velocity detector, and flow conversion device. These correspond to the hydrogen gas integrals directly measured by the gas analyzer, the hydrogen gas integrals derived from thermal conductivity, the hydrogen gas integrals derived from density, the hydrogen gas integrals derived from sound velocity, and the hydrogen gas integrals converted from upstream hydrogen injection flow and natural gas flow, respectively. The number of samples lost from each source within the time window is counted and calculated using the formula... The sampling continuity factor is calculated, where N i N represents the total number of samples from source i within a preset time window. miss，i This represents the number of lost samples from source i within a preset time window; the sampling continuity factor is used to characterize the continuous stability of the data output from source i. The more complete and stable the sampling, the closer the sampling continuity factor is to 1. Let C be the current integral number of hydrogen gas from the i-th source. i Through formula The consistency deviation factor is calculated, where Cref is the reference value and σ is the standard deviation factor. i ε is the standard deviation of the i-th source within the historical time window, and ε is a very small positive number to prevent the denominator from being zero; the consistency deviation factor is used to characterize the degree of consistency between the source and the multi-source reference results. The smaller the deviation, the larger the consistency deviation factor. Let C be the integral number of hydrogen gas from the i-th source within the preset time window. i (t), through the formula The short-term stability factor is calculated, where t represents the index of the acquisition time within the preset time window, t=1, 2, 3...N; Δ i The short-term stability factor is the maximum average jump threshold allowed for source i. It is used to characterize whether there is significant jitter or abrupt change in the output of source i in a short period of time. The smaller the fluctuation, the larger the short-term stability factor.

[0008] The continuity factor, consistency deviation factor, and short-term stability factor of source i are linearly combined according to preset weights to obtain the health score h of the i-th source. i The weights are summed to one, representing the importance of sampling continuity, consistency bias, and short-term stability in the health score, respectively. These weights can be adjusted by those skilled in the art according to the needs of the actual application scenario. Then, the health scores h from each source i are... i Normalization formula Calculate the weight w corresponding to each source i. i As can be seen from the weighting analysis of the sources mentioned above, the higher the health score of a source, the greater its weight in the calculation of the total deviation; the lower the health score of a source, the smaller its weight.

[0009] Furthermore, the outlet pressure of the gas pipeline network is dynamically adjusted, including: Based on the current hydrogen integral correction value and other gas components, the key physical properties of the current hydrogen-blended gas are calculated in real time using mixing rules. These key physical properties include the molar mass, density, and dynamic viscosity of the mixed gas; specifically: (1) The formula for calculating the molar mass of the mixed gas is as follows: ; Where C H2 C CH4 C NH3 C CO2 These represent the corrected values ​​for the hydrogen gas integral fraction, methane volume fraction, ammonia gas integral fraction, and carbon dioxide volume fraction, respectively. H2 =2.016 g / mol, MCH4 =16.04 g / mol, M NH3 =17.03 g / mol, M CO2 =44.01 g / mol, which are the molar masses of hydrogen, methane, ammonia and carbon dioxide, respectively; (2) The density of the mixed gas is calculated based on the GERG-2008 equation of state, combined with the measured upstream pressure and temperature. The calculation formula is as follows: ; Where P in For upstream pressure, T in Let Z be the upstream temperature, b be the ideal gas constant with a value of 8.314 J / (mol·K), and Z be the upstream temperature. mix The gas compressibility factor of the mixed gas is obtained by iteratively solving the AGA-8 equation; (3) The dynamic viscosity of the mixed gas is calculated using the Herning-Zipperer mixing rule, and the calculation formula is as follows: ; Where y H2 y CH4 y NH3 y CO2 These represent the mole fractions of hydrogen, methane, ammonia, and carbon dioxide, respectively, in μ. H2 μ CH4 μ NH3 μ CO2 Hydrogen, methane, ammonia, and carbon dioxide at upstream temperatures T, respectively. in The viscosity at a given temperature can be obtained by consulting a temperature-viscosity table for each gas or by calculating the relationship between gas viscosity and temperature using the Sutherland empirical formula. It should be noted that changes in the hydrogen integral number in the gas mixture will significantly alter the density, viscosity, and calorific value of the mixture, which directly affects the flow capacity and throttling characteristics of the pressure regulating valve, as well as the stability of downstream combustion equipment. Therefore, real-time reconstruction of physical property parameters based on the hydrogen integral number in the gas mixture is the foundation for subsequent precise control. Based on the density, dynamic viscosity, and instantaneous flow rate of the mixed gas, the calibrated flow coefficient of the pressure regulating valve is dynamically corrected to obtain the equivalent flow coefficient. The target pressure and target flow rate of the current pressure regulating station are dynamically set according to downstream gas demand. The required valve flow coefficient is calculated using the standard valve flow equation. The calculation formula is as follows: ; Where 1.17 is the unit conversion factor, f c Let be the coefficient of thermal expansion, when When <0.5, it is taken as 1; otherwise, it is calculated according to ISO 5167; Q tar For the target traffic, P tar For the target pressure; match the required valve flow coefficient and the equivalent flow coefficient corresponding to the target flow rate, calculate the valve flow demand ratio under the current operating conditions, and use the valve's factory-calibrated opening-flow coefficient characteristic curve to map the valve flow demand ratio into an opening percentage, which is used as the valve's feedforward opening. The reference parameters, including the proportional reference coefficient, were obtained by experimental tuning of the step response under pure natural gas conditions. Integral benchmark coefficient and differential reference coefficients And obtain the proportional coefficient K under the current operating conditions through concentration adaptive mapping. p Integral coefficient K s and differential coefficient K d The concentration adaptive mapping formula is as follows: ; Where β p β s and β d These are empirical coefficients for the proportionality coefficient, integral coefficient, and derivative coefficient, respectively, calibrated through offline hydrogen doping and pressure regulation experiments. In this embodiment, they are set to 0.02, 0.015, and 0.005, respectively, indicating that for every 1% increase in the hydrogen gas integral correction value, the proportionality coefficient K... p Increase by 2%, integral coefficient K s And a decrease of 1.5%, the differential coefficient K d Increase by 0.5%; Subtracting the downstream pressure from the target pressure yields the downstream pressure deviation, denoted as e(N). The current valve opening control quantity u(N) is then calculated using the following formula: ; Where Δt represents the time interval between two sampling times, t represents the index of any time within the preset time window, the time window is from t=1 to t=N, and t=N represents the sequence number of the current sampling time; the feedforward opening degree is superimposed with the valve opening control quantity to obtain the target valve opening degree at the current time, and the target valve opening degree is subjected to amplitude limiting and speed limiting processing, and then the target valve opening degree after amplitude limiting and speed limiting processing is sent as the final valve opening control command to the pressure regulating valve actuator to dynamically adjust the pressure regulating valve opening in real time.

[0010] Furthermore, the calibrated flow coefficient of the pressure regulating valve is dynamically corrected to obtain the equivalent flow coefficient, which includes: The density correction factor is obtained by dividing the reference density of pure natural gas under the same operating conditions by the density of the mixed gas and then taking the square root. Instantaneous flow rate, density of the mixed gas, and dynamic viscosity are expressed using the formula The Reynolds number is calculated, where Q is the instantaneous flow rate and D is the inner diameter of the gas pipeline; if the Reynolds number is less than 4000, then... Calculate the viscosity correction factor; if the Reynolds number is greater than or equal to 4000, the viscosity correction factor is equal to one. Obtain the pressure difference correction factor by analyzing the effect of the pressure difference across the quantizing valve on the gas compressibility. The calculation formula is: ; in This represents the reference pressure drop ratio under pure natural gas operating conditions; The equivalent flow coefficient is then calculated by multiplying the calibrated flow coefficient, density correction coefficient, viscosity correction coefficient, and differential pressure correction coefficient of the pressure regulating valve.

[0011] Furthermore, the pressure response results after valve adjustment are verified in real time, including: After the pressure regulating valve receives the final valve opening control command and completes the action, the operating parameters of the pressure regulating station are continuously collected again, and the downstream pressure is used to construct a pressure response curve according to the collection time series. The steady-state value after the pressure stabilizes is identified by the pressure response curve, and the steady-state deviation is obtained by subtracting the target pressure from it and taking the absolute value. The recovery time is obtained by identifying the time interval from the moment the valve is activated when the downstream pressure re-enters the target pressure allowable deviation zone and remains there for a preset time. The steady-state deviation and recovery time are compared with preset allowable thresholds to obtain the voltage regulation result. If the steady-state deviation is less than or equal to the allowable steady-state deviation threshold and the recovery time is less than or equal to the allowable time threshold, the current voltage regulation result is determined to be valid. Otherwise, the current voltage regulation result is determined to be invalid, and the PID empirical coefficient is retuned.

[0012] Furthermore, PID empirical coefficient retuning includes: The steady-state deviation tuning factor δ1 and the recovery time tuning factor δ2 are calculated based on the steady-state deviation and recovery time, respectively. The empirical coefficients of the proportional coefficient, integral coefficient, and derivative coefficient are then corrected accordingly. The correction formula is as follows: ; Where γ p , λ p These are the adjustment step sizes for the steady-state deviation tuning factor and the recovery time tuning factor within the proportional coefficient range, respectively, γ. s , λ s These are the adjustment step sizes for the steady-state deviation tuning factor and the recovery time tuning factor within the integral coefficients, respectively, γ. dThe adjustment step size of the recovery time tuning factor within the differential coefficient is 0.05-0.2. The corrected empirical coefficient is then fed back to the execution module to recalculate and update the proportional coefficient, integral coefficient, and differential coefficient feedback, and update the valve opening control quantity. This quantity is then superimposed with the feedforward opening and the final valve control command is re-output.

[0013] Furthermore, the feedback module returns to the next round of verification after adjustment. If the adjustment result is still invalid, the operating parameters are updated and fed back to the processing module and execution module for pressure adjustment again until the outlet pressure meets the target control requirements. An alarm is output when the adjustment results of the cumulative preset number of times are invalid.

[0014] The present invention has the following beneficial effects: By applying median reference, deviation calculation, health score weighting, and confidence threshold determination to the hydrogen gas integral count from multiple sources, sensor sampling loss, short-term jitter, and inter-source inconsistency are separated from the original measurement. After filtering out abnormal sources, a more stable and accurate corrected value for the hydrogen gas integral count is obtained. Compared with directly using a single sensor reading, this module significantly reduces the error in identifying hydrogen blending concentration, providing reliable input for subsequent mixed gas property reconstruction, feedforward opening calculation, and pressure closed-loop regulation, thereby improving the adaptability and robustness of the entire pressure regulation system to complex operating conditions. Based on the hydrogen gas integral correction value, the molar mass, density, and dynamic viscosity of the mixed gas are reconstructed in real time, and the equivalent correction is performed on the pressure regulating valve calibration flow coefficient. Then, combined with the downstream gas demand, the feedforward opening and PID valve position control quantity are calculated, and finally, the valve control command after amplitude and speed limiting is generated and sent to the valve regulating mechanism. Compared with the scheme that only relies on the fixed valve flow curve or simple feedback control, this method realizes the linkage adjustment of hydrogen concentration, gas properties, and valve execution characteristics, and realizes the composite control of feedforward preset and feedback fine adjustment. This can significantly reduce pressure regulation lag, overshoot, and pressure oscillation, and improve the dynamic tracking accuracy and stability of outlet pressure. By extracting the pressure response curve after valve action, the steady-state deviation and recovery time are obtained as pressure regulation effect indicators, and it is used to determine whether the current pressure regulation result meets the stability requirements. When the result does not meet the requirements, the empirical parameters of the PID are quantitatively retuned according to the pressure regulation effect indicators, and the valve opening control quantity is recalculated by sending the data back to the execution module. This makes the pressure regulation process no longer a one-time open-loop setting, but a self-correcting and self-iterable closed-loop process. Once multiple adjustments are ineffective, an alarm is triggered and manual intervention is forced, thus balancing control performance and operational safety and improving the long-term reliability of hydrogen-blended gas pipeline networks. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the system module connections of the present invention. Detailed Implementation

[0017] 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 some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Example 1 This embodiment applies to pressure regulating stations between long-distance pipelines and urban gas pipeline networks. In the scenario of natural gas blending with hydrogen, by real-time sensing of the hydrogen concentration in the mixed gas and combining it with the characteristics of changes in the physical properties of the mixed gas, the control quantity of the pressure regulating valve and the outlet pressure setpoint are dynamically corrected, thereby realizing intelligent pressure regulation control of the gas pipeline network; please refer to Figure 1 The present invention provides a technical solution: an intelligent pressure regulating system for gas pipeline network based on hydrogen concentration sensing, comprising a sensing module, a processing module, an execution module and a feedback module; The sensing module collects operating parameters in real time by deploying monitoring devices on the upstream and downstream sides of the pressure regulating station and at the pressure regulating valve body. The operating parameters include at least upstream pressure, downstream pressure, upstream temperature, downstream temperature, instantaneous flow rate, valve opening, pressure difference across the valve, and gas composition information. The gas composition information includes hydrogen integral, methane volume fraction, and carbon dioxide volume fraction. It should be noted that in this embodiment, ammonia is an optional blending component, which is used to adapt to some hydrogen-natural gas-ammonia mixed transmission scenarios. When the gas does not contain ammonia, the corresponding ammonia integral is zero, which does not affect the normal execution of subsequent mixed gas property parameter calculation, pressure regulation control, and feedback adjustment process. Since the online acquisition process is affected by sensor drift, instantaneous disturbance, sampling noise, or sudden changes in operating conditions, directly using the original measurement value can easily lead to deviations in the judgment of hydrogen concentration, which in turn affects the accuracy of subsequent pressure regulation. Therefore, it is necessary to perform confidence analysis correction on the hydrogen concentration in the gas to obtain an accurate hydrogen integral. The processing module performs a consistency confidence analysis based on the real-time collected hydrogen gas integral, specifically including: The hydrogen gas integral count at the current moment is acquired in real time, including at least the hydrogen gas integral count directly measured by the gas analyzer, the hydrogen gas integral count obtained from thermal conductivity inversion, the hydrogen gas integral count obtained from density inversion, the hydrogen gas integral count obtained from sound velocity inversion, and the hydrogen gas integral count calculated from the upstream hydrogen injection flow rate and natural gas flow rate. The median of the hydrogen gas integral counts from these various sources is used as a reference value. The deviation of each source is calculated by comparing the hydrogen gas integral count directly measured by the gas analyzer, the hydrogen gas integral count obtained from thermal conductivity inversion, the hydrogen gas integral count obtained from density inversion, the hydrogen gas integral count obtained from sound velocity inversion, and the hydrogen gas integral count calculated from the upstream hydrogen injection flow rate and natural gas flow rate with the reference value. The health status of each source is then assigned a corresponding weight. Based on the corresponding weights, the deviations of each source are linearly weighted and fused to obtain the total deviation. The total deviation is then normalized by dividing the total deviation by the sum of the deviations of each source to obtain the total deviation degree. Finally, the consistency confidence degree R is calculated by applying the decay relationship formula as follows: ; Where Y is the total deviation and α is the consistency decay number, which is used to control the rate at which the confidence decreases when the deviation of the integral of hydrogen gas from each source increases. In this example, its value is set to 2, and it is adjusted within the range according to the sensor measurement accuracy, the intensity of on-site disturbance and the stability requirements of the voltage regulation control. Furthermore, assigning corresponding weights based on the health status from each source specifically includes: Let N be the total number of samples from the i-th source within a preset time window, meaning each source corresponds to N hydrogen gas integrals, where N is a positive integer; where i represents the index of the source type. In this embodiment, the source type is at least one of the following: gas analyzer, thermal conductivity detector, density detector, sound velocity detector, and flow conversion device. These correspond to the hydrogen gas integrals directly measured by the gas analyzer, the hydrogen gas integrals derived from thermal conductivity, the hydrogen gas integrals derived from density, the hydrogen gas integrals derived from sound velocity, and the hydrogen gas integrals converted from upstream hydrogen injection flow and natural gas flow, respectively. The number of samples lost from each source within the time window is counted and calculated using the formula... The sampling continuity factor is calculated, where N i N represents the total number of samples from source i within a preset time window. miss，i This represents the number of lost samples from source i within a preset time window; the sampling continuity factor is used to characterize the continuous stability of the data output from source i. The more complete and stable the sampling, the closer the sampling continuity factor is to 1. Let C be the current integral number of hydrogen gas from the i-th source. i Through formula The consistency deviation factor is calculated, where Cref is the reference value and σ is the standard deviation factor. i ε is the standard deviation of the i-th source within the historical time window, and ε is a very small positive number to prevent the denominator from being zero; the consistency deviation factor is used to characterize the degree of consistency between the source and the multi-source reference results. The smaller the deviation, the larger the consistency deviation factor. Let C be the integral number of hydrogen gas from the i-th source within the preset time window. i (t), through the formula The short-term stability factor is calculated, where t represents the index of the acquisition time within the preset time window, t=1, 2, 3...N; The short-term stability factor is the maximum average jump threshold allowed for source i. It is used to characterize whether there is significant jitter or abrupt change in the output of source i in a short period of time. The smaller the fluctuation, the larger the short-term stability factor. The continuity factor, consistency deviation factor, and short-term stability factor of source i are linearly combined according to preset weights to obtain the health score h of the i-th source. i The weights are summed to one, representing the importance of sampling continuity, consistency bias, and short-term stability in the health score, respectively. These weights can be adjusted by those skilled in the art according to the needs of the actual application scenario. Then, the health scores h from each source i are... i Normalization formula Calculate the weight w corresponding to each source i. i As shown in the weighting analysis of the sources above, the higher the health score of a source, the greater its weight in the calculation of the total deviation; conversely, the lower the health score of a source, the smaller its weight. It should be noted that... The meaning represented is the sum of health scores from all sources.

[0019] A preset confidence threshold is used to distinguish whether the current multi-source hydrogen gas integral measurement results are within the confidence range. It is usually determined based on the statistical distribution of consistency confidence under historical stable operating conditions, the measurement error range of each source sensor, and the stability requirements of subsequent voltage regulation control. This ensures that the threshold can effectively identify the source of abnormal deviations while avoiding misjudging normal fluctuations as abnormalities. If the consistency confidence is less than the confidence threshold, it indicates that there is a deviation in the current hydrogen gas integral counts from each source. In this case, the source with the largest deviation is removed, and the multi-source weights are recalculated and weighted fusion is performed to obtain the corrected value of the hydrogen gas integral count. If the consistency confidence is greater than or equal to the confidence threshold, it indicates that the consistency between the current hydrogen gas integral counts from each source meets the requirements. There is no need to perform abnormality removal, and the reference value is directly used as the corrected value of the hydrogen gas integral count. The execution module receives the hydrogen gas integral correction value and, in conjunction with other operating parameters collected in real time by the sensing module, dynamically adjusts the outlet pressure of the gas pipeline network. The specific process includes: Based on the current hydrogen integral correction value and other gas components, the key physical properties of the current hydrogen-blended gas are calculated in real time using mixing rules. These key physical properties include the molar mass, density, and dynamic viscosity of the mixed gas; specifically: (1) The formula for calculating the molar mass of the mixed gas is as follows: ; Where C H2 C CH4 C NH3 C CO2 These represent the corrected values ​​for the hydrogen gas integral fraction, methane volume fraction, ammonia gas integral fraction, and carbon dioxide volume fraction, respectively. H2 =2.016 g / mol, M CH4 =16.04 g / mol, M NH3 =17.03 g / mol, M CO2 =44.01 g / mol, which are the molar masses of hydrogen, methane, ammonia and carbon dioxide, respectively; (2) The density of the mixed gas is calculated based on the GERG-2008 equation of state, combined with the measured upstream pressure and temperature. The calculation formula is as follows: ; Where P in For upstream pressure, T in Let Z be the upstream temperature, b be the ideal gas constant with a value of 8.314 J / (mol·K), and Z be the upstream temperature. mix The gas compressibility factor of the mixed gas is obtained by iteratively solving the AGA-8 equation; (3) The dynamic viscosity of the mixed gas is calculated using the Herning-Zipperer mixing rule, and the calculation formula is as follows: ; Where y H2 y CH4 y NH3 y CO2 These represent the mole fractions of hydrogen, methane, ammonia, and carbon dioxide, respectively, in μ. H2 μ CH4 μ NH3 μ CO2 Hydrogen, methane, ammonia, and carbon dioxide at upstream temperatures T, respectively. in The viscosity at a given temperature can be obtained by consulting a temperature-viscosity table for each gas or by calculating the relationship between gas viscosity and temperature using the Sutherland empirical formula. It should be noted that changes in the hydrogen integral number in the gas mixture will significantly alter the density, viscosity, and calorific value of the mixture, which directly affects the flow capacity and throttling characteristics of the pressure regulating valve, as well as the stability of downstream combustion equipment. Therefore, real-time reconstruction of physical property parameters based on the hydrogen integral number in the gas mixture is the foundation for subsequent precise control. Based on the density, dynamic viscosity, and instantaneous flow rate of the mixed gas, the calibrated flow coefficient of the pressure regulating valve is dynamically corrected to obtain the equivalent flow coefficient. The calibrated flow coefficient refers to the inherent flow capacity parameter obtained experimentally before the pressure regulating valve leaves the factory, using pure water or pure natural gas as the test medium, under specified valve opening (usually fully open) and differential pressure conditions. The specific dynamic correction process is as follows: The density correction factor f is obtained by dividing the reference density of pure natural gas under the same operating conditions by the density of the mixed gas and then taking the square root. ρ Through formula The Reynolds number Re is calculated, where Q is the instantaneous flow rate and D is the inner diameter of the gas pipeline. If the Reynolds number Re is less than 4000, it indicates laminar flow or a transition zone, and the viscosity correction factor is used. If the Reynolds number Re is greater than or equal to 4000, it indicates turbulence, and the viscosity correction factor is equal to one. The pressure difference across the valve (i.e., the upstream pressure P) is quantified using the following formula. in and downstream pressure P out The effect of gas compressibility yields a pressure difference correction factor, calculated using the following formula: ; in This represents the reference pressure drop ratio under pure natural gas operating conditions; The equivalent flow coefficient C is then calculated by multiplying the calibrated flow coefficient, density correction coefficient, viscosity correction coefficient, and differential pressure correction coefficient of the pressure regulating valve. eff The formula is as follows: ; Where C0 is the calibrated flow coefficient of the pressure regulating valve; through adaptive correction based on concentration and operating conditions, the valve model is matched with the actual fluid characteristics, avoiding deviations between control commands and execution effects; The target pressure and target flow rate of the pressure regulating station are dynamically set according to downstream gas demand. It should be noted that the target flow rate is usually estimated based on the deviation between the current downstream pressure and the target pressure. Specifically, the target pressure is subtracted from the downstream pressure, the difference is multiplied by the flow-to-pressure conversion coefficient, and then added to the current instantaneous flow rate to obtain the target flow rate. The flow-to-pressure conversion coefficient is obtained through offline calibration based on the characteristics of the gas pipeline network. The required valve flow coefficient C is calculated using the standard valve flow equation. req The calculation formula is as follows: ; Where 1.17 is the unit conversion factor, f c Let be the coefficient of thermal expansion, when When <0.5, it is taken as 1; otherwise, it is calculated according to ISO 5167; Q tar For the target traffic, P tar For target pressure; The required valve flow coefficient corresponding to the target flow rate is matched with the equivalent flow coefficient to calculate the valve flow demand ratio under the current operating condition. That is, the required valve flow coefficient is divided by the equivalent flow coefficient to obtain the valve flow demand ratio, which is used to characterize the relative relationship between the current target flow capacity and the current valve's actual flow capacity. Using the valve's factory-calibrated opening-flow coefficient characteristic curve, the flow demand ratio is mapped to an opening percentage as the valve's feedforward opening. The feedforward opening serves as the basic preset opening of the pressure regulating valve, which is used to quickly adjust the valve to an initial position that matches the current hydrogen-doped operating condition before pressure regulation begins. This avoids relying solely on feedback control to gradually approach the target state from the initial state, thereby reducing pressure regulation response lag and improving the system's dynamic response speed. The reference parameters, including the proportional reference coefficient, were obtained by experimental tuning of the step response under pure natural gas conditions. Integral benchmark coefficient and differential reference coefficients And obtain the proportional coefficient K under the current operating conditions through concentration adaptive mapping. p Integral coefficient K s and differential coefficient K d The concentration adaptive mapping formula is as follows: ; Where β p β s and β d These are empirical coefficients for the proportionality coefficient, integral coefficient, and derivative coefficient, respectively, calibrated through offline hydrogen doping and pressure regulation experiments. In this embodiment, they are set to 0.02, 0.015, and 0.005, respectively, indicating that for every 1% increase in the hydrogen gas integral correction value, the proportionality coefficient K... p Increase by 2%, integral coefficient K s And a decrease of 1.5%, the differential coefficient K d Increase by 0.5%; The target pressure of the current pressure regulating station is dynamically set according to the downstream gas demand. The downstream pressure deviation is then obtained by subtracting the target pressure from the downstream pressure and denoted as e(N). The current valve opening control quantity u(N) is then calculated using the following formula: ; Where Δt represents the time interval between two sampling moments, t represents the index of any moment within the preset time window, the time window is from t=1 to t=N, and t=N represents the sequence number of the current sampling moment; the valve opening control quantity is used to dynamically fine-tune the feedforward opening to compensate for pressure deviations caused by flow fluctuations and changes in operating conditions during actual operation; specifically, the feedforward opening and the valve opening control quantity are superimposed to obtain the target valve opening at the current moment, and the target valve opening is subjected to amplitude limiting and speed limiting processing. Amplitude limiting processing is used to limit the valve opening to be within the allowable control range to avoid the valve being completely closed or over-opened; speed limiting processing is used to limit the amount of change in valve opening per unit time to avoid the valve acting too quickly and causing outlet pressure oscillation or system impact; then the target valve opening after amplitude limiting and speed limiting processing is sent as the final valve opening control command to the pressure regulating valve actuator to dynamically adjust the pressure regulating valve opening in real time to achieve stable control of the gas pipeline outlet pressure. It should be noted that during the pressure regulation process, if the pressure deviation is detected to be continuously increasing, the valve opening correction range is increased; if the downstream pressure is detected to be gradually approaching the target pressure, the valve adjustment step size is reduced, and anti-saturation processing is performed on the integral term to suppress pressure overshoot and oscillation, thereby improving pressure regulation stability and control accuracy; through concentration-adaptive parameter tuning, the overshoot and adjustment time can be significantly reduced, enabling rapid and accurate control of downstream pressure against the target pressure. The feedback module performs real-time verification, effect evaluation, and parameter updates on the pressure regulation results after the execution module completes the valve adjustment, thereby forming a closed-loop control, specifically including: Step 1: After the pressure regulating valve receives the final valve opening control command and completes its action, the operating parameters of the pressure regulating station are immediately and continuously collected again. The downstream pressure is then used to construct a pressure response curve according to the collection time series. The pressure response curve reflects the change trend of the outlet pressure over time after valve regulation, so as to quantify the pressure regulation effect. Specifically, the steady-state value after pressure stabilization is identified through the pressure response curve, and the steady-state deviation is obtained by subtracting the target pressure from it and taking the absolute value. The steady-state deviation is used to characterize the final deviation between the outlet pressure and the target pressure after pressure regulation. The recovery time is obtained by identifying the time interval from the moment the valve is activated when the downstream pressure re-enters the target pressure allowable deviation zone and remains there for a preset duration. Step two: Compare the steady-state deviation and recovery time with preset allowable thresholds to obtain the voltage regulation result. If the steady-state deviation is less than or equal to the allowable steady-state deviation threshold, and the recovery time is less than or equal to the allowable time threshold, the current voltage regulation result is considered valid. If the steady-state deviation is greater than the allowable steady-state deviation threshold, or the recovery time is greater than the allowable time threshold, the current voltage regulation result is considered invalid, indicating that the current PID parameters or feedforward compensation amount still need to be corrected, thus triggering the retuning of the PID empirical coefficients. Step 3: When the steady-state deviation exceeds the preset allowable steady-state deviation threshold or the recovery time exceeds the allowable time threshold, it is determined that the current voltage regulation result simultaneously suffers from excessive overshoot and slow recovery. The corresponding tuning factors are calculated and adjusted using empirical coefficients. Specifically: the steady-state deviation is subtracted from the allowable steady-state deviation threshold, and the non-negative portion is divided by the allowable steady-state deviation threshold to obtain the steady-state deviation tuning factor δ1. Similarly, the recovery time is subtracted from the allowable time threshold, and the non-negative portion is divided by the allowable time threshold to obtain the recovery time tuning factor δ2. This is achieved using the formula... The new empirical coefficients are calculated, where γ p , λ p These are the adjustment step sizes for the steady-state deviation tuning factor and the recovery time tuning factor within the proportional coefficient range, respectively, γ. s , λ s These are the adjustment step sizes for the steady-state deviation tuning factor and the recovery time tuning factor within the integral coefficients, respectively, γ. d The adjustment step size for the recovery time tuning factor within the differential coefficients ranges from 0.05 to 0.2. It should be noted that when the steady-state deviation is too large, the empirical coefficient of the proportional gain should be increased or the empirical coefficient of the integral gain should be decreased. Simultaneously, decreasing the empirical coefficient of the integral gain weakens the integral effect and avoids steady-state oscillations. An excessively large recovery time indicates a slow response speed; decreasing the empirical coefficient of the proportional gain prevents excessive proportional amplification, while increasing the empirical coefficient of the integral gain enhances the ability to eliminate steady-state error. The range of the corrected empirical coefficients should be limited to a reasonable range. Step four: Feed the new empirical parameters of the PID controller to the execution module to update the valve opening control quantity. Superimpose it with the feedforward opening quantity, re-output the final valve control command, and then proceed to step one for the next round of feedback verification. If the adjustment result is still invalid, update the operating parameters and feed them back to the processing module and execution module to correct the valve opening control quantity, feedforward opening mapping relationship, or PID parameters until the outlet pressure meets the target control requirements. If the adjustment result is invalid after 5 cumulative attempts, issue an alarm and force manual intervention.

[0020] Through the above feedback process, not only can the current pressure regulation result be verified in real time, but the actual pressure regulation effect can also be used to correct the PID parameters, thereby forming a closed-loop adaptive pressure regulation mechanism to improve the stability and control accuracy of the outlet pressure of the gas pipeline network under hydrogen blending conditions.

[0021] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A smart pressure regulating system for gas pipeline networks based on hydrogen concentration sensing, comprising a sensing module, wherein the sensing module is used to collect operating parameters in real time through monitoring devices deployed on the upstream side, downstream side, and pressure regulating valve body of the pressure regulating station; characterized in that, Also includes: The processing module is used to perform consistency confidence analysis on the hydrogen gas integral counts from different sources collected in real time and output corrected values ​​for the hydrogen gas integral counts. The execution module is used to receive the hydrogen gas integral correction value and dynamically adjust the outlet pressure of the gas pipeline network in combination with the operating parameters. The feedback module is used to verify the pressure response result after valve adjustment in real time, and update the parameters output by the processing module and the execution module based on the verification result; This includes dynamically adjusting the outlet pressure of the gas pipeline network, including: Based on the current hydrogen gas integral correction value and other gas components, the key physical property parameters of the current hydrogen-blended gas are calculated in real time using the mixing rule; Based on the density, dynamic viscosity, and instantaneous flow rate of the mixed gas, the calibrated flow coefficient of the pressure regulating valve is dynamically corrected to obtain the equivalent flow coefficient. The target pressure and target flow rate of the current pressure regulating station are dynamically set according to the downstream gas demand. The required valve flow coefficient is calculated using the standard valve flow equation. The required valve flow coefficient corresponding to the target flow rate is matched with the equivalent flow coefficient. The valve flow demand ratio under the current operating conditions is calculated. The valve flow demand ratio is mapped to the opening percentage using the valve's factory-calibrated opening-flow coefficient characteristic curve, which serves as the valve's feedforward opening. The reference parameters are obtained by experimental tuning of the step response under pure natural gas conditions. The reference parameters include proportional reference coefficient, integral reference coefficient and differential reference coefficient. The proportional coefficient, integral coefficient and differential coefficient under the current operating conditions are obtained by adaptively mapping them through concentration. The downstream pressure deviation is obtained by subtracting the target pressure from the downstream pressure. This deviation is then used to calculate the current valve opening control quantity using the proportional coefficient, integral coefficient, and derivative coefficient under the current operating conditions. The feedforward opening is then superimposed on the valve opening control quantity to obtain the current target valve opening. The target valve opening is then subjected to amplitude limiting and speed limiting. Finally, the target valve opening after amplitude limiting and speed limiting is sent as the final valve opening control command to the pressure regulating valve actuator to dynamically adjust the pressure regulating valve opening in real time.

2. A smart pressure regulating system for gas pipelines based on hydrogen concentration sensing according to claim 1, characterized in that, The calibrated flow coefficient of the pressure regulating valve is dynamically corrected to obtain the equivalent flow coefficient, which includes: The density correction factor is obtained by dividing the reference density of pure natural gas under the same operating conditions by the density of the mixed gas and then taking the square root. The Reynolds number is calculated using formulas based on instantaneous flow rate, density of mixed gas, and dynamic viscosity. If the Reynolds number is less than a preset value, a viscosity correction factor is further calculated based on the Reynolds number. If the Reynolds number is greater than or equal to the preset value, the viscosity correction factor is equal to one. A pressure difference correction factor is obtained by analyzing the effect of the pressure difference across the quantizing valve on the gas compressibility. The equivalent flow coefficient is then calculated by multiplying the calibrated flow coefficient, density correction coefficient, viscosity correction coefficient, and differential pressure correction coefficient of the pressure regulating valve.

3. A smart pressure regulating system for gas pipelines based on hydrogen concentration sensing according to claim 2, characterized in that, Real-time verification of the pressure response results after valve adjustment, including: After the pressure regulating valve receives the final valve opening control command and completes the action, the operating parameters of the pressure regulating station are continuously collected again, and the downstream pressure is used to construct a pressure response curve according to the collection time series. The steady-state value after the pressure stabilizes is identified by the pressure response curve, and the steady-state deviation is obtained by subtracting the target pressure from it and taking the absolute value. The recovery time is obtained by identifying the time interval from the moment the valve is activated when the downstream pressure re-enters the target pressure allowable deviation zone and remains there for a preset time. The steady-state deviation and recovery time are compared with preset allowable thresholds to obtain the voltage regulation result. If the steady-state deviation is less than or equal to the allowable steady-state deviation threshold and the recovery time is less than or equal to the allowable time threshold, the current voltage regulation result is determined to be valid. Otherwise, the current voltage regulation result is determined to be invalid, and the PID empirical coefficient is retuned.

4. A smart pressure regulating system for gas pipelines based on hydrogen concentration sensing according to claim 3, characterized in that, PID empirical coefficient retuning includes: The steady-state deviation tuning factor and recovery time tuning factor are calculated based on the steady-state deviation and recovery time, respectively. Based on these factors, the empirical coefficients of the proportional coefficient, integral coefficient, and derivative coefficient are corrected. The corrected empirical coefficients are then fed back to the execution module to recalculate and update the proportional coefficient, integral coefficient, and derivative coefficient feedback, and update the valve opening control quantity. This quantity is then superimposed with the feedforward opening quantity, and the final valve control command is re-output.

5. A smart pressure regulating system for gas pipelines based on hydrogen concentration sensing according to claim 4, characterized in that, The feedback module returns to the next round of verification after adjustment. If the adjustment result is still invalid, the operating parameters are updated and fed back to the processing module and execution module for pressure adjustment again until the outlet pressure meets the target control requirements. An alarm is output when the adjustment results are invalid after a cumulative preset number of adjustments.

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