Pipeline management system

Abstract

A pipeline management system according to an embodiment of the present invention for monitoring a pipeline that supplies a gas to an end user has: a pipeline system to which gas is supplied; and a control system for controlling the pipeline system. The pipeline system has: a gas source; a pipe that is connected to the gas source; a gas separation device that is connected to the pipe and separates the gas supplied from the gas source into a plurality of gas flows; a first flow rate sensor that measures the flow rate of the gas supplied to a main supply pipe of the pipeline; a second flow rate sensor that measures the flow rate of a generated gas flowing out from the gas separation device; and a first concentration sensor that measures the concentration of the generated gas. The control system has: a recording unit that records measurement data of the first and second flow rate sensors and the first concentration sensor; and a calculation unit that calculates, in accordance with mass balance, the concentration of the gas flow at a position along the supply gas supplied to the gas separation device, and the flow rate and the concentration of the gas flow at a position which is downstream of a return gas returned from the gas separation device to the main supply pipe, on the basis of the measurement results of the first and second flow rate sensors and the first concentration sensor.

Description

Pipeline Management System

[0001] The present invention relates to a pipeline management system that monitors fluid composition and flow rate in a pipeline.

[0002] Hydrogen plays an important role in accelerating decarbonization. One implementation strategy for hydrogen is to reuse existing natural gas pipelines as hydrogen pipelines. In particular, Patent Document 1 discloses a method for monitoring hydrogen supply pipelines that is useful for this strategy. However, natural gas is expected to remain an important energy source in the future to maintain energy security. Therefore, rather than completely reusing natural gas pipelines for hydrogen transportation, a more attractive option is to inject hydrogen into natural gas pipelines and mix the two.

[0003] The resulting mixture of hydrogen and natural gas is transported through pipelines to various end users such as homes, factories, institutions, etc. Some end users require hydrogen-rich fuel while others require natural gas-rich fuel, which ultimately requires the installation of gas separators in the pipelines to separate the mixed gases.

[0004] Monitoring gas composition upstream and downstream of gas separation units is important to ensure the required gas quality is delivered to end users, but given the size of existing pipelines, the significant installation and maintenance costs incurred by additional concentration sensors are a concern.

[0005] JP 2023-044745 A JP 2022-015364 A

[0006] Patent Document 2 discloses a method for monitoring the composition of a mixed fluid by installing flow sensors upstream and downstream of a gas mixing point. Instead of installing a concentration sensor, the disclosed method calculates the composition using the measured output of the flow sensors.

[0007] The method disclosed in Patent Document 2 can reduce monitoring costs in pipelines with a mixing process, but since the document focuses only on determining the composition for gas mixing, it does not disclose monitoring the concentration for separating gases through a gas separation device.

[0008] The present invention has been made in view of the above problems, and an object of the present invention is to provide a means capable of monitoring the gas composition in a gas separation device with a small number of installed sensors.

[0009] The pipeline management system of this embodiment is a pipeline management system for monitoring a pipeline that supplies gas to an end user, comprising: a pipeline system through which gas is supplied; and a control system for controlling the pipeline system. The pipeline system comprises a gas source; a pipe connected to the gas source; a gas separation device connected to the pipe and separating the gas supplied from the gas source into multiple gas streams; a first flow sensor for measuring the flow rate of gas supplied to a main supply pipe of the pipeline; a second flow sensor for measuring the flow rate of product gas flowing out from the gas separation device; and a first concentration sensor for measuring the concentration of the product gas. The control system comprises a recording unit for recording measurement data of the first and second flow sensors and the first concentration sensor; and a calculation unit for calculating, based on the measurement results of the first and second flow sensors and the first concentration sensor, the concentration of the gas flow at a position along the supply gas supplied to the gas separation device, and the flow rate and concentration of the gas flow at a downstream position of the return gas returned from the gas separation device to the main supply pipe according to mass balance.

[0010] According to the present invention, by calculating the composition at unmeasured points, it is possible to monitor the gas composition using a gas separation device with a small number of sensors. Further features related to the present invention will become apparent from the description of this specification and the accompanying drawings. Problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments.

[0011] Figure 1 shows an example of a system 1 for monitoring a pipeline 2. Figure 2 shows a block diagram of an example of applying a mass balance in a pipeline 2. Figure 3 shows a display of the output of the system 1 monitoring a pipeline 2. Figure 4 shows an example of a pipeline 2c monitored by system 1. Figure 5 shows an example of a system 1b monitoring a pipeline 2b. Figure 6 shows the output of a system 1b for detecting an anomalous measurement of a flow sensor. Figure 7 shows the output of a system 1b for detecting an anomalous measurement of a concentration sensor. Figure 8 shows a diagram of time delay in a pipeline. Figure 9 shows the output of a system 1b for detecting an anomalous measurement of a flow sensor taking time delay into account. Figure 10 shows an example of a display output classifying confidence levels. Figure 11 shows an example of a pipeline with a compressor and a turbine monitored by system 1b.

[0012] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0013] Example 1 FIG. 1 is a diagram showing an example of the configuration of a system 1 for monitoring the gas flow rate and composition (concentration) in a pipeline 2 equipped with a plurality of gas separation devices 5.

[0014] (Pipeline 2) In this embodiment, the pipeline management system includes a pipeline 2 supplied with gas and a system 1 for controlling the pipeline 2. The pipeline 2 includes a first gas source (Gas 1) and a second gas source (Gas 2), pipes connected to the gas sources, and multiple gas separation devices 5 connected to the pipes and separating the gas stream supplied from the gas source into multiple gas streams. The pipeline 2 supplies gas to end users 3 through a network of pipes. In this specification, an end user refers to a person or organization that consumes gas at the gas supply destination. In the diagram, the pipes are represented by lines with arrows indicating the direction of gas flow. Gas 1 and Gas 2 are mixed and supplied to each gas separation device 5 through a main supply pipe 4. Gas 1 and Gas 2 have different compositions and are known in composition. For example, Gas 1 can be natural gas, and Gas 2 can be pure hydrogen. This embodiment also applies to a pipeline 2 that has an additional source of gas with a known composition. The additional gas source can be, for example, a natural gas extraction plant, a hydrogen production plant, a methanation plant, etc.

[0015] (Gas Separation Apparatus 5) As described above, the pipeline 2 is equipped with a plurality of gas separation apparatuses 5 (hereinafter also simply referred to as separation apparatuses) including the first gas separation apparatus M_1, the second gas separation apparatus M_2, the third gas separation apparatus M_3, and the Nth gas separation apparatus M_N. In this example, the first separation apparatus M_1 is supplied with the gas flow flowing through the main supply pipe 4, and the separation apparatuses M_2 to M_N are supplied with the product gas 51 flowing out from the separation apparatus M_1. However, the present invention is not limited to this supply form, and for example, the gas flow flowing through the main supply pipe 4 may be supplied to a plurality of separation apparatuses.

[0016] Generally, the gas separation device 5 separates the mixed gas supply into two gas streams with different purities. For example, the first gas stream is enriched in Gas 1, and the second gas stream is enriched in Gas 2. Furthermore, the first gas stream is returned to the pipe network, and the second gas stream is supplied to an end user 3 or consumed by being supplied to another separation device 5. The first gas stream returned to the upstream pipe network from one gas separation device 5 is hereinafter referred to as return gas 52. The second gas stream flowing downstream from the gas separation device 5 is hereinafter referred to as product gas 51, and the mixed gas supplied to the separation device 5 is hereinafter referred to as feed gas 50. It should be noted that each separation device 5 is supplied with a different feed gas 50. The product gas 51 and return gas 52 all have different flow rates and concentrations.

[0017] (Sensors) The pipeline 2 also includes a plurality of flow rate sensors and concentration sensors. The flow rate sensors measure the flow rate of gas through differential pressure, thermal properties, or other known methods. The concentration sensors can measure gas concentration using gas chromatography, calorimetry, or other known methods. Specifically, as shown in FIG. 1, the pipeline 2 is provided with a flow rate sensor Fs that measures the flow rate of gas supplied from the gas source to the main supply pipe 4.

[0018] The pipeline 2 is also provided with a flow rate sensor Fs1 that measures the flow rate of the produced gas 51 flowing out of each gas separation device 5. The pipeline 2 is also provided with a concentration sensor Cs1 that measures the concentration of the produced gas 51. The above-mentioned sensors are included in the elements that make up the pipeline system, including the pipelines to which the gas flow is supplied. Note that, since the composition of Gas 1 or Gas 2, which is the gas source, is known as described above, no concentration sensor is required for Gas 1 or Gas 2.

[0019] (System 1) To meet end-user gas quality requirements, multiple gas separation units 5 in a pipeline 2 must be controlled to produce a product gas 51 that specifically meets a target level of gas purity. Monitoring the gas flow rate and concentration of the feed gas 50 and the product gas 51 is particularly important in controlling the gas separation units 5.

[0020] As described above, the system 1 monitors the gas and composition in the pipeline 2. The system 1 is connected to the pipeline 2 via a wireless or wired network and includes a calculation unit 11 consisting of a CPU (Central Processing Unit) and a recording unit 12 consisting of a memory. The system 1 can receive and record measurement data from the flow rate sensors Fs, Fs1 and the concentration sensor Cs1 installed in the pipeline 2 via the recording unit 12. The system 1 can visually display the stored measurement data of the flow rate and concentration sensors on a display 14, allowing a user of this embodiment to monitor the gas flow rate and concentration of the gas supplied to the main supply pipe 4 and the product gas 51 of each gas separation device 5. The system 1 also allows calculation of the gas flow rate and concentration at points 111a and 111b upstream of the gas separation device 5 via the calculation unit 11. Instead of using sensors, a user of this embodiment can also monitor the gas flow rate and concentration at points 111a and 111b based on calculated conditions.

[0021] (Calculation Unit 11) Specifically, the calculation unit 11 uses the law of conservation of mass or simply mass balance to calculate the concentration at point 111a and the flow rate and concentration at point 111b for each gas separation device 5. The positions of points 111a and 111b on the pipeline 2 are represented by black circles in the figure. Point 111a is located on the pipe through which the supply gas 50 flows. Therefore, the flow rate calculated at point 111a can be used to monitor the flow of the supply gas 50 in the separation device 5. Point 111b is located downstream from the position of the pipe through which the return gas 52 is returned. Therefore, the flow rate and concentration calculated at point 111b can be used to monitor the flow rate and concentration of the gas downstream of the return gas 52 in the separation device 5. Here, each separation device 5 has a corresponding point 111a and point 111b.

[0022] The calculation unit 11 also calculates the concentration and flow rate at point 111c, which is located downstream of the mixing point of gas 1 and gas 2. The calculation unit 11 calculates the gas flow rates and concentrations at points 111a, 111b, and 111c in order from the most upstream point to the most downstream point. Therefore, in this example, the calculation unit 11 performs calculations sequentially from point 111c, which is located downstream of the confluence of gas 1 and gas 2, to point 111b of the separation device M_N. Generally, calculations at downstream points require calculation data at upstream points, so it is useful to perform the calculations in this order. A common method for evaluating the mass balance is to define a control volume 6 (see FIG. 2). The static overall mass balance of the control volume 6 can be evaluated using equation (1): ΣΣmin = Σmout (1) where min (kg / s) is the flow rate at the inlet of the control volume 6, and mout (kg / s) is the flow rate at the outlet of the control volume 6. Since there may be multiple inlets and multiple outlets, equation (1) includes a summation operation (Σ).

[0023] Furthermore, the static mass balance of gas component A in control volume 6 can be defined by equation (2): ΣCin min = ΣCout mout (2) where Cin (kg / kg) is the concentration of gas component A in the inlet stream and Cout (kg / kg) is the concentration of gas component A in the outlet stream. In this example, the components of the inlet or outlet stream can be Gas 1 only, Gas 2 only, or a mixture of Gas 1 and Gas 2.

[0024] FIG. 2 is a block diagram illustrating the evaluation of the mass balance to calculate the conditions at points 111b and 111c.

[0025] (Point 111c) To calculate the flow rate and concentration at point 111c, the calculation unit 11 can define control volume 6 so that point 111c is located on the outlet side and the inlet flow is a gas source of gas 1 and gas 2. In this example, control volume 6 (V_0) is defined. By calculating equation (1) for control volume 6 (V_0) and using the measurement data of flow sensors Fs for gas 1 and gas 2 as input data, the calculation unit 11 can calculate the flow rate at point 111c. Furthermore, the calculation unit 11 can calculate the concentration at point 111c using equation (2) based on the measurement data of flow sensors Fs for gas 1 and gas 2 and the concentration information for gas 1 and gas 2. As described above, the concentrations of gas 1 and gas 2 are known values ​​and are stored in advance in the recording unit 12.

[0026] (Point 111b) To calculate the condition at point 111b of the separation device 5, the calculation unit 11 can define a control volume 6 that surrounds only one separation device 5 and that is located on the outlet side of the separation device 5. In this example, the calculation unit 11 can define control volumes 6(V_1), 6(V_2), and 6(V_3) to calculate the flow rate and concentration at point 111b of the separation devices M_1, M_2, and M_3, respectively. Although examples of control volumes 6 defined for the other points 111b are not shown, the same principle applies. The calculation unit 11 calculates equations (1) and (2) for the control volume 6(V_1) and uses the measurement data of the flow rate sensor Fs1 and the concentration sensor Cs1 that monitor the product gas 51 of the separation device M_1 and the flow rate and concentration calculated at point 111c as input data, thereby being able to calculate the flow rate and concentration at point 111b of the separation device M_1.

[0027] The calculation unit 11 calculates the control volume 6 (V_2) using equations (1) and (2) and the measurement data of the flow sensor Fs1 and the concentration sensor Cs1 that monitor the product gas 51 of the separation device M_2 and the separation device M_1 located upstream of the separation device M_2 as input data, thereby being able to calculate the flow rate and concentration at point 111b of the separation device M_2. Furthermore, the calculation unit 11 calculates the control volume 6 (V_3) using the measurement data of the flow sensor Fs1 and the concentration sensor Cs1 that monitor the product gas 51 of the separation device M_3 and the calculation conditions at point 111b of the upstream separation device M_2 as input data, thereby being able to calculate the flow rate and concentration at point 111b of the separation device M_3.

[0028] The calculation of the flow rate and concentration at point 111b of separation devices M_4 to M_N is similar to the calculation described for point 111b of separation device M_3, and therefore further description will be omitted. Except for the calculation of the flow rate and concentration at point 111b of separation device M_2, the calculation of the conditions at point 111b of separation device M_5 requires calculation data of upstream points as input data (measurement data from flow sensor Fs1 and concentration sensor Cs1 monitoring product gas 51 of separation device M_1 are used as input data for the calculation of the flow rate and concentration at point 111b of separation device M_2). This relationship emphasizes the importance of the order in which calculations are performed by calculation unit 11, i.e., from the most upstream point to the most downstream point.

[0029] (Point 111a) The production of feed gas 50 is the result of simple branching of pipe 4 and does not involve mixing or separation of gas components. Therefore, based on mass balance, the gas concentration at point 111a is the same as the upstream gas concentration. This can be mathematically expressed in equation (3): C １１１ａ = C ｕｐｓｔｒｅａｍ (3) Here, C １１１ａ (kg / kg) is the gas concentration at point 111a, C ｕｐｓｔｒｅａｍ is the gas concentration upstream of point 111a.

[0030] To define the gas concentration upstream of point 111a, calculation unit 11 can use measured data or previously calculated data. As a first example, calculation unit 11 can use the calculated concentration at point 111c to calculate equation (3) for calculating the concentration at point 111a of separation device M_1. ｕｐｓｔｒｅａｍ As a second example, when calculating Equation (3) for calculating the concentration at point 111a of separation device M_2, calculation unit 11 may use measurement data of concentration sensor Cs1 that monitors product gas 51 of separation device M_1 to define C ｕｐｓｔｒｅａｍ As a third example, when calculating Equation (3) for calculating the concentration at point 111a of separation device M_3, calculation unit 11 may use the calculated concentration at point 111b of separation device M_2 on the upstream side to define C ｕｐｓｔｒｅａｍ The calculation of the equation (3) for calculating the concentration at point 111a of the subsequent separation devices M_4 to M_N is similar to the calculation of the concentration at point 111a for separation device M_3, and therefore further explanation will be omitted. Note that the measurement data used to calculate the conditions at points 111a, 111b, and 111c during these calculations is collected by the recording unit 12.

[0031] Overall, by evaluating an equation that takes mass balance into account through the calculation unit 11, i.e., an equation that assumes that the mass of the gas flowing into a given gas inlet point is equal to the mass of the gas flowing out of that point, and using the measurement outputs of sensors Fs, Fs1, and Cs1 in the pipeline 2 as input data, the system 1 allows the user of this embodiment to monitor the composition (concentration) of the feed gas 50 without installing concentration sensors corresponding to the feed gas 50 supplied to each separation device. Again, it should be emphasized that the calculated concentration in the feed gas can serve as a guide for the user of this embodiment in controlling the operation of the separation device. Similarly, the user of this embodiment can also monitor the flow rate and concentration of the gas downstream of the return gas 52 from the separation device 5 without installing concentration and flow rate sensors corresponding to the pipeline 2. Such information can also be useful for controlling the separation device. In summary, the system 1 can monitor multiple separation devices in a pipeline using a fewer number of sensors. This also means that the system 1 can monitor the pipeline 2 with reduced installation and maintenance costs.

[0032] Monitoring the Output of System 1 Figure 3 shows an example of a display output by system 1 for monitoring the flow rate and concentration of gas in pipeline 2. The display output may include a window 100 that visually indicates the location of monitoring points in pipeline 2, as shown in Figure 3(a). Window 100 is displayed on display 14 shown in Figure 1. The monitoring points are represented by black circles that include points 111a, 111b, and the locations of sensors Fs, Fs1, and Cs1.

[0033] Through window 100, a user of this embodiment can distinguish whether a monitored point provides measured or calculated data. Additionally, a user of this embodiment can identify whether the data provided by the monitored point is gas flow rate or concentration. In this example, a user can identify that a monitored point provides flow rate information if connected to the letter F and concentration information if connected to the letter C. Furthermore, a user can know that a monitored point provides measured information if the letter F or C is surrounded by a light gray box with a thin outline (e.g., the box designated A), and can know that a monitored point provides calculated information if the letter F or C is surrounded by a light gray box with a thick outline (e.g., the box designated B).

[0034] As shown in FIG. 3( b), visualization of gas flow rates and concentrations at monitoring points is displayed in window 200. In this embodiment, the concentration of the feed gas 50 in the separation device 5 (M_2) is displayed as an example. In particular, window 200 provides multiple time-series plots of measured or calculated gas flow rates and concentrations. The measurement information displayed by system 1 includes at least the time-series flow rates of the gas sources (Gas 1 and Gas 2) and the time-series gas flow rate and composition of the product gas 51. The calculated flow rates and concentrations displayed in window 200 can be collected by system 1 from calculations by calculation unit 11. Again, these include at least the calculated concentration of the feed gas 50 (point 111 a) of the separation device 5 and the downstream flow rate and composition of the return gas (point 111 b). This embodiment also applies to a pipeline 2 in which pressure sensors are located at the same positions as the flow sensors Fs and Fs1.

[0035] Example 2 The gas pipeline may also include a compressor to maintain the required gas flow in the pipe and a turbine to power the compressor. The turbine uses gas from the pipeline as fuel. These components were not considered in the previous example. In this example, system 1 is used to control a pipeline 2c that further includes a compressor and a turbine for the above-mentioned purposes. This example will be described focusing only on the differences from example 1.

[0036] 4 shows an example of a pipeline 2c monitored by the system 1. Here, the pipeline 2c is based on the pipeline 2, which further includes a number of compressors 7 and a number of turbines 8. A compressor 7 is always paired with a turbine 8, because, as mentioned above, the compressor 7 is powered by the turbine 8.

[0037] A flow rate sensor Fs3 and a concentration sensor Cs3 are connected to the inlet of each turbine 8 to measure the gas flow rate and concentration, respectively. These sensors are necessary for the safe operation and control of the turbine 8. Furthermore, the recording unit 12 can receive and store data measured by these sensors. The turbine 8 uses gas from the pipeline 2c as fuel and finally discharges spent gas. This process changes the mass balance of the pipeline 2c compared to a pipeline without the turbine 8 and compressor 7. More specifically, the flow upstream and downstream of the turbine 8 and compressor 7 pair changes.

[0038] Taking into account changes in mass balance due to the addition of the turbine 8 and the compressor 7, the calculation unit 11 additionally calculates, by mass balance, flow rates and concentrations at a plurality of points 111d located downstream of the compressor 7. This also means that the series of calculations performed by the calculation unit 11 additionally includes calculation of the flow rate and concentration at point 111d.

[0039] (Point 111d) To calculate the flow rate and concentration at point 111d, the calculation unit 11 can define a control volume 6 that surrounds a pair of turbines 8 and compressors 7, with point 111d located on the outlet side. This defines a control volume 6 (V_4) for each pair of turbines 8 and compressors 7. The calculation unit 11 can calculate equation (1) for control volume 6 (V_4) and calculate the flow rate at point 111d using the measurement data of flow sensor Fs3 and the calculated flow rate at upstream point 111b. It should also be noted that due to mass balance, the gas flow rate flowing into the turbine 8 is equal to the gas flow rate flowing out of the turbine 8.

[0040] For compressor 7 and turbine 8, no mixing or separation process of gas components is involved. Therefore, due to mass balance, the gas concentration at point 111d is the same as the upstream gas concentration. This can be mathematically expressed in equation (3a): C １１１ｄ = C ｕｐｓｔｒｅａｍ (3a) where C １１１ｄ (kg / kg) is the gas concentration at point 111d, C ｕｐｓｔｒｅａｍ is the gas concentration upstream of point 111d. To define the gas concentration upstream of point 111a, calculation unit 11 can use measured data or previously calculated data. In this example, evaluation of equation (3a) can use the calculated concentration at upstream point 111b. The explanation given above also applies to pipeline 2b with pressure sensors co-located with flow sensors Fs, Fs1, and Fs3.

[0041] Example 3 The measured and calculated information provided by the system 1 depends on the measurement outputs of the flow sensor Fs1 and the concentration sensor Cs1. However, sensors are generally susceptible to damage, which can result in erroneous measurements. If left undetected, such measurement anomalies can reduce the reliability of the system 1. This problem is addressed in this example. Figure 5 shows a system 1b monitoring a pipeline 2b. In this example, the pipeline 2b further comprises a plurality of flow sensors Fs2 that measure the gas flow rate supplied to end users 3. The flow sensors Fs2 correspond to gas meters installed in homes to measure personal gas consumption and calculate gas consumption charges.

[0042] The description of this embodiment can also be applied to the pipeline 2b equipped with the compressor 7 and turbine 8 described in embodiment 2. The recording unit 12 further receives and records data measured by the flow rate sensor Fs2. The system 1b further includes an abnormality detection unit 13 for detecting abnormal sensor measurement values ​​in the pipeline 2b.

[0043] (Abnormality Detection Unit 13) The abnormality detection unit 13 detects abnormal measurements by the flow rate sensor Fs1 and concentration sensor Cs1 that monitor the produced gas 51 supplied to the end user 3. This means that for pipeline 2b, the abnormality detection range of the abnormality detection unit 13 extends from separation devices M_2 to M_N. First, the details of detection of abnormal measurements by the flow rate sensor Fs1 will be described, and then the details of detection of abnormal measurements by the concentration sensor Cs1 will be described.

[0044] (Abnormality in Flow Sensor Fs1) Due to mass balance, it is assumed that the amount of generated gas 51 flowing out from separation device 5 is the same as the amount of gas supplied to end user 3 connected to separation device 5. Based on this principle, abnormality detection unit 13 detects an abnormality in flow sensor Fs1 using error E1, which indicates the error in the measurement data of flow sensor Fs1 compared with the measurement data of flow sensor Fs2 connected to end user 3. Next, a specific example of processing for detecting an abnormality in Fs1 using error E1 will be described.

[0045] First, the anomaly detection unit 13 calculates the error E1 of the flow sensor Fs1. The anomaly detection unit 13 can calculate the error E1 (%) at time t, for example, by calculating the absolute percentage error, treating the flow to the end user as the actual value. This can be expressed as equation (4): E1t = (|mpg,t - Σmend,t| / Σmend,t) * 100 (4) where mpg,t (kg / s) is the flow measured by the flow sensor Fs1 at time t, and Σmend,t (kg / s) is the sum of the flows measured by the flow sensor Fs2 at the same time t. To simplify the calculation, equation (4) only uses the measurement data of the flow sensor Fs2 of the end user 3, which receives the same product gas 51 monitored by the flow sensor Fs1.

[0046] The abnormality detection unit 13 then determines whether the measurement data from the flow sensor Fs1 is abnormal based on whether the calculated error E1 exceeds a threshold value 122 (see FIG. 6B). Specifically, if the error E1 exceeds the threshold value 122, the abnormality detection unit 13 determines that the measurement data is abnormal. In other cases, the abnormality detection unit 13 determines that the measurement data is not abnormal. The threshold value 122 can be defined in advance by the user of this embodiment.

[0047] Finally, the anomaly detection unit 13 can generate a display output to guide the user about the generated determination. An example of this display output will be described with reference to FIG. 6 . The display output includes plot 300 and plot 400. One plot 300 and one plot 400 are generated for one determined flow rate sensor Fs1. In this example, plot 300 and plot 400 show the display output of the anomaly detection unit 13 generated after repeated anomaly determinations have been made in accordance with the trend of the flow rate sensor Fs1 of the separation device M_2 since time t0.

[0048] Plot 300 in Figure 6(a) shows gas flow rate on the y-axis and time on the x-axis. Graph 120 shows the trend of the measured data from flow sensor Fs1. Graph 121 shows the trend of the total measured flow rate from flow sensor Fs2 (which is equal to Σmend,t in equation (4)). Meanwhile, plot 400 in Figure 6(b) shows the calculated error E1 from flow sensor Fs1. Plot 400 also shows a plot of threshold 122.

[0049] During the period from t0 to time t1, the error E1 does not exceed the threshold value 122. Therefore, during that period, the abnormality detection unit 13 determines that there is no abnormality in the measurement data of the flow sensor Fs1. On the other hand, after time t1, the calculated error E1 exceeds the threshold value 122. Therefore, the abnormality detection unit 13 determines that the measurement data of the flow sensor Fs1 is abnormal after time t1. The calculated error E1, Σmend, and the determination result by the abnormality detection unit 13 are saved in the recording unit 12.

[0050] (Anomaly in Concentration Sensor Cs1 for Produced Gas Supplied to End User) Next, details of the detection of a measurement anomaly by the concentration sensor Cs1 from the separation device 5 supplying gas to the end user 3 will be described. First, the anomaly detection unit 13 generates a correlation plot of flow rate and concentration using the end user's past flow rate and concentration data. The past flow rate and concentration data of the end user 3 can be stored and updated in advance by the user or vendor of this embodiment using the recording unit 12. The generated correlation plot shows various ranges of gas flow rate for various concentration ranges. An example of the generated correlation between flow rate and concentration will be described later using FIG. 7.

[0051] Next, the anomaly detection unit 13 collects the calculated total gas flow rate (=Σmend,t) to the end user 3 at time t, which was previously calculated and stored in the recording unit 12 (for clarity, said end user is the end user to which the product gas 51 monitored by the concentration sensor Cs1 is supplied).

[0052] Next, the anomaly detection unit 13 estimates the expected range of the concentration measured by the concentration sensor Cs1 at time t. Specifically, the anomaly detection unit 13 uses the generated correlation plot and the collected total gas flow rate to the end user to estimate the expected range of the concentration measured by the concentration sensor Cs1. An example of this estimation process will also be described later with reference to FIG. 7.

[0053] Finally, the abnormality detection unit 13 determines whether the measurement data obtained by the concentration sensor Cs1 is abnormal. Specifically, if the measured concentration is within the expected concentration range, the abnormality detection unit 13 determines that the measurement data is not abnormal. Otherwise, the abnormality detection unit 13 determines that the measurement data is abnormal.

[0054] If the measured concentration is determined to be abnormal, the anomaly detection unit 13 can calculate an error E2 of the concentration sensor Cs1, which indicates the error of the measurement data by the concentration sensor Cs1 compared to the expected range of concentrations. The error E2 (%) at time t can be calculated, for example, by treating the average of the expected concentration range as the actual value and calculating the absolute percentage error. This is mathematically expressed in equation (5): E2t = (|Cpg,t - Cexpected,t| / Cexpected,t) * 100 (5) where Cpg,t (kg / kg) is the concentration measured by the concentration sensor Cs1, and Cexpected,t (kg / kg) is the average of the expected concentration range at time t. The calculated error E2 is also stored in the recording unit 12. Finally, the anomaly detection unit 13 generates a display output to guide the user through the generated determination.

[0055] FIG. 7 shows an example of a display output by the anomaly detection unit 13 for detecting an anomaly in the concentration sensor Cs1. The display output may include plot 500 in FIG. 7(a), plot 600 in FIG. 7(b), and plot 700 in FIG. 7(c). One plot 500, one plot 600, and one plot 700 may be generated for one determined concentration sensor Cs1. Plot 500 shows gas flow rate on the y-axis and time on the x-axis. The generated correlation plots of flow rate and concentration are represented by graphs 123a and 124a and regions 123 and 124.

[0056] In this example, graph 123a shows historical gas flow rate data consumed by an end user when the gas concentration of Gas 2 in the mixed gas is very high, i.e., when the Gas 2 concentration is [90%, 100%]. On the other hand, graph 124a shows historical flow rate data consumed by an end user when the gas concentration of Gas 2 is low, i.e., when the Gas 2 concentration is [70%, 90%]. Based on the maximum and minimum gas flow rates in graph 123a, the anomaly detection unit 13 can generate and display region 123, which indicates a flow boundary of high Gas 2 concentration. Similarly, region 124 is generated and displayed by the anomaly detection unit 13 based on graph 124a, which indicates a flow boundary of low Gas 2 concentration. By visualizing the generated correlation plot of flow rate and concentration, a user of this example can understand the historical time series trend of gas flow rate at different Gas 2 concentration levels. The correlation plot may include additional regions, such as the gas flow rate trend when the Gas 2 concentration is [60%, 70%].

[0057] Plot 500 also includes graph 121', which is a trend of the calculated total gas flow rate of product gas 51 to the end user (which is similar to graph 121 in FIG. 6). By observing plot 500, a user of this example can recognize the expected range of concentrations measured by concentration sensor Cs1. For example, if graph 121' is within region 123, the expected concentration range of Gas 2 measured by concentration sensor Cs1 is within [90%, 100%]. If graph 121' is within region 124, the expected Gas 2 concentration range of product gas 51 is within [70, 90%].

[0058] On the other hand, plot 600 shows the concentration value of Gas 2 on the y-axis and time on the x-axis, and further includes graph 125 which is the trend of Gas 2 concentration based on measurement data from concentration sensor Cs1.

[0059] From time t0 to time t2, graph 125 is below the 90% gas 2 concentration line. However, plot 500 shows that graph 121' is within region 123 from time t0 to time t2. This indicates that the expected gas 2 concentration range is within [90%, 100%]. Because the measured gas 2 concentration by concentration sensor Cs1 is outside the expected gas 2 concentration range, the abnormality detection unit 13 determines that the measured gas 2 concentration by concentration sensor Cs1 is abnormal. On the other hand, after time t2, graph 125 is above the 90% gas 2 concentration line, which is within the expected concentration range. Therefore, the abnormality detection unit 13 determines that the measurement data by concentration sensor Cs1 from time t2 onward is not abnormal. In this way, the correlation plot between generated flow rate and concentration is explained based on the concentration of gas 2. However, the correlation plot can also be based on gas 1 (or other gas components of the generated gas 51).

[0060] On the other hand, plot 700 shows the error E2 calculated for concentration sensor Cs1. Note that because error E2 is calculated only when the measurement data of concentration sensor Cs1 is determined to be abnormal, values ​​after time t2 are not displayed. By visualizing this plot, a user of this embodiment can evaluate the error in the measurement data from concentration sensor Cs1.

[0061] To summarize this embodiment, by displaying the plots 500 and 600, the user of this embodiment can understand the determination made by the abnormality detection unit 13 regarding the concentration sensor Cs.

[0062] Example 4 As already explained, the amount of product gas 51 flowing out of the separation device 5 is expected to be the same as the amount of gas supplied to the end user 3 connected to the separation device 5 due to mass balance. This means that if an increase in product gas 51 flowing out of the separation device 5 is observed at time t, a similar increase in the amount of gas flowing to the end user 3 is expected to be observed at the same time. However, due to the distance between the separation device 5 and the end user 3, the increase in the amount of gas flowing to the end user 3 may be observed later than the increase in product gas 51 flowing out of the separation device 5. This phenomenon is a time delay and can be particularly significant in large pipelines.

[0063] 8A shows an example where there is a time delay in the monitored pipeline, where graph 120a in FIG. 8A(a) shows the trend of the measurement data from flow sensor Fs1, and graph 121a shows the trend of the total flow measured by flow sensor Fs2.

[0064] At time t3, graph 120a shows a peak in gas flow, indicating an increase and subsequent decrease in gas flowing in product gas 51. Due to mass balance, gas flowing to the end user should follow a similar trend, and graph 121a is expected to show a similar peak at the same time t3. However, due to pipeline time delays, graph 121a shows an expected peak in gas flow at time t4, later than t3.

[0065] In the above-described embodiment, the determination by the anomaly detection unit 13 did not take time delay into consideration. This could result in a large error E1 exceeding the threshold value 122, as seen from time t5 to time t3 in FIG. 8A(b). As a result, the anomaly detection unit 13 could erroneously determine that the measurement data of the generated gas 51 measured by the flow rate sensor Fs is abnormal. However, the large error E1 exceeding the threshold value 122 from time t5 to time t3 is actually caused by a time delay and is not a measurement abnormality.

[0066] In this embodiment, the abnormality detection unit 13 can also calculate the error E1 at time t according to equation (4b): E1t = (|mpg,t - Σmend,t + tlay| / Σmend,t + tdelay) * 100 (4b) where Σmend,t + tlay (kg / s) is the sum of the flow rates measured by the flow sensor Fs2 at time t + tlay. Furthermore, the abnormality detection unit 13 can calculate tdelay (s), for example, using equation (4c): tdelay = L / v (4c) where L is the distance between the flow sensor Fs1 and the flow sensor Fs2, and v is the average velocity of the gas pipe. Information necessary to evaluate equation (4c) can be stored in advance in the recording unit 12.

[0067] FIG. 8B shows an example of a display output by the anomaly detection unit 13 taking time delay into consideration. In FIG. 8B(a), graph 120a shows the trend of measurement data by flow sensor Fs1 for the generated gas 51. Graph 121b shows the trend of measurement data by flow sensor Fs2 for the end user connected to the generated gas 51, taking the calculated time delay into consideration. At time t3, the peaks of graphs 120a and 121b coincide, indicating that the time delay has been eliminated. Furthermore, as shown in FIG. 8B(b), the error E1 calculated from time t5 to t3 is below threshold 122, and therefore no anomaly is determined to exist. Therefore, inaccurate determinations by the anomaly detection unit 13 due to time delays are avoided.

[0068] [Example 5] Measurement anomalies can be very severe or minor. Severe anomalies result in significantly lower reliability of monitoring than minor anomalies. Furthermore, the maintenance work performed by the user of this example may vary depending on the magnitude of the anomaly. By visualizing the errors E1 and E2, the user of this example can assess the magnitude of the sensor anomaly in the monitored pipeline. However, displaying all plots of the errors E1 and E2 may place a significant load on the CPU. Furthermore, the previous example did not evaluate the impact of sensor measurement anomalies on the data calculated by the calculation unit 11. This example addresses these issues. The following description of this example will focus on the differences from the previous example.

[0069] In this example, the anomaly detection unit 13 based on Example 3 or Example 4 further classifies the reliability levels of the sensors and the data calculated by the calculation unit 11 based on the calculated errors E1 and E2. Specifically, the anomaly detection unit 13 calculates a weighted error Ew based on the errors E1 and E2, thereby classifying the reliability of the measurements at the sensors Fs1 and Cs1 and the points 111a and 111b.

[0070] More specifically, the abnormality detection unit 13 calculates the weighted errors Ew (%) of the flow rate sensor Fs1 and the concentration sensor Cs1 using equations (6a) and (6b), respectively: Ew_Fs1 = wE1 (6a) Ew_Cs1 = wE2 (6b) where E1 is the calculation error E1 of Fs1, E2 (%) is the calculation error E2 of Cs1, and w is the weight assigned to the error E1 or E2. In equations (6a) and (6b), w is set to 1.

[0071] The anomaly detection unit 13 also calculates the weighted error Ew (%) of the calculated flow rate at point 111b using equation (6c): Ew_F = ΣwEw_Fs1 (6c) where Ew_Fs1 (%) is the weighted error Ew calculated for the flow rate sensor Fs1 located upstream of the calculation point 111b, while w is the weight portion assigned to Ew_Fs1.

[0072] Furthermore, the abnormality detection unit 13 calculates the weighted error Ew (%) of the calculated concentration at point 111a or 111b using equation (6d): Ew_C = ΣwεEw_Fs1 - ΣwEw_Cs1 (6d) where Ew_Fs1 / Ew_Cs1 (%) is the weighted error Ew calculated for the flow sensor Fs1 / concentration sensor Cs1 located upstream of point 111a or 111b, and w is the weight portion assigned to the error Ew_Fs1 / Ew_Cs1.

[0073] In equations (6c) and (6d), the weight portion w is assigned so that the errors used to evaluate the equations have equal weights. For example, if four Ew values ​​are used to evaluate equation (6c) (or (6d)), w is assigned as 0.25.

[0074] Overall, a larger weighted error Ew indicates a larger anomaly and lower reliability. Next, the anomaly detection unit 13 uses the calculated Ew to classify the reliability level of the monitoring point in the pipeline 2b. Specifically, the anomaly detection unit 13 classifies the reliability level as either "high," "medium," or "low."

[0075] For example, if the calculated weighted error Ew is within a low error range a, the confidence level is classified as high, if the calculated weighted error Ew is within a medium error range b, the confidence level is classified as medium, and if the calculated weighted error Ew is within a high error range c, the confidence level is classified as low.

[0076] The error ranges a, b, and c are defined so as not to overlap with each other. This allows the reliability levels to be clearly classified as high, medium, or low. For example, the error range a can be defined as [0%, 10%], the error range b as [10%, 30%], and the error range c as [30%, 100%]. The values ​​of the ranges a, b, and c can be defined in advance by the user or vendor of this embodiment. The anomaly detection unit 13 further generates a display output to inform the user of this embodiment of the results of the reliability level classification.

[0077] 9 shows an example of a display output of the anomaly detection unit 13 that visualizes the reliability classification at time t. The display output includes a window 100b displayed on the display 14 (see FIG. 1, etc.). The components of the display output are the same as the components of the window 100 described with reference to FIG. 3.

[0078] The difference between window 100 and window 100b is that window 100b adds a visualization of a confidence scale divided into high, medium, and low. The confidence scale is designed with different colors for high, medium, and low. In this example, "high" confidence is represented by vertical hatching, "medium" confidence by horizontal hatching, and "low" confidence by diagonal hatching. Also displayed are error range values ​​for the high, medium, and low confidence levels.

[0079] By observing this display output, a user of this embodiment can quickly assess the current reliability level of the measured data of the sensors in pipeline 2b and the calculated data by the calculation unit 11. For example, if a monitoring point is connected to a hatched rectangle, the user can assess that the current reliability of the measured / calculated flow rate / concentration at that monitoring point is low, with a weighted error of 30-100%. As a result, the user can plan maintenance or control actions to address the low reliability at the monitoring point. Furthermore, the user can determine which data to trust when monitoring pipeline 2b. For monitoring points with unclassified reliability, the rectangle is shaded.

[0080] Example 6 As described above, the system 1b can also be used to monitor a pipeline 2b equipped with a compressor 7 and a turbine 8. Fig. 10 shows an example of such a pipeline. In this example, the anomaly detection unit 13 further uses measurement data from a concentration sensor Cs3 connected upstream of the turbine 8 to detect measurement anomalies and classify the reliability level. This is expected to improve the accuracy of anomaly detection and reliability classification.

[0081] Due to mass balance around control volume V_5 ( FIG. 10 ), the gas concentration at point 111b should be the same as the gas concentration supplied to turbine 8. This means that the calculated concentration at point 111b should be the same as the measured concentration. Using this relationship, the anomaly detection unit 13 further calculates an error E3 at point 111b. Error E3 indicates the error of the calculated concentration at point 111b compared to the measurement data of concentration sensor Cs3 monitoring turbine 8 downstream of point 111b. The anomaly detection unit can calculate error E3 (%) at point 111b using an absolute percentage error, taking the measurement data of concentration sensor Cs3 as the actual measurement value.

[0082] (Abnormality Detection) Hereinafter, details of additionally using the error E3 to detect an abnormality in the flow sensor Fs1 will be described. In the above-described embodiment, the abnormality detection unit 13 determined whether the measurement data from the flow sensor Fs1 was abnormal by checking whether the calculated error E1 exceeded the threshold value 122. In this embodiment, the abnormality detection unit 13 further determines whether the measurement data from the flow sensor Fs1 is abnormal by checking whether the error E3 at the upstream point 111b of the flow sensor Fs1 exceeds the threshold value 122b. Specifically, the abnormality detection unit 13 determines that the measurement data from the flow sensor Fs1 is abnormal when the error E1 exceeds the threshold value 122 or when the error E3 at the upstream point 111b of the flow sensor Fs1 exceeds the threshold value 122b. In all other cases, the abnormality detection unit 13 determines that the measurement data is not abnormal.

[0083] In the above-described embodiment, the abnormality detection unit 13 determines whether the measurement data of the concentration sensor Cs1 is abnormal based on whether the measurement data of the concentration sensor Cs1 exceeds the expected concentration range. In this embodiment, the abnormality detection unit 13 further determines whether the measurement data of the concentration sensor Cs1 is abnormal by checking whether the error E3 at the point 111b upstream of the concentration sensor Cs1 exceeds the threshold value 122c. Specifically, the abnormality detection unit 13 determines that the measurement data of the concentration sensor Cs1 is abnormal if the measurement data of the concentration sensor Cs1 exceeds the expected concentration range or if the error E3 at any point 111b upstream of the concentration sensor Cs1 exceeds the threshold value 122c. In all other cases, the abnormality detection unit 13 determines that the measurement data is not abnormal. The threshold values ​​122b and 122c can be defined in advance by the user in this embodiment.

[0084] By adding the error E3, the anomaly detection unit 13 can detect measurement anomalies that could not be detected using only the error E1 or the flow rate / concentration correlation plot. Furthermore, in the above-described embodiment, the anomaly detection unit 13 can detect only anomalies in the flow rate sensor Fs1 and concentration sensor Cs1 that monitor the generated gas 51 supplied to the end user 3. This limits the anomaly detection for the separation devices M_2 to M_N. By using the error E3 for anomaly detection, the anomaly detection unit 13 can detect anomalies in the flow rate sensor Fs1 and concentration sensor Cs1 even for the separation device M_1.

[0085] (Reliability Level) In calculating the weighted error Ew of the flow sensor Fs1 and the concentration sensor Cs1, the error E3 is also taken into consideration. Therefore, the weighted error Ew of the flow sensor Fs1 and the concentration sensor Cs1 is calculated using equations (7a) and (7b), respectively. Ew_Fs1 = wE1 + ΣwE3ε (7a) Ew_Cs1 = wE2 + ΣwE3ε (7b) Here, E3 (%) is the error E3 at point 111b upstream of the flow sensor Fs1 or the concentration sensor Cs1. Because there may be multiple points 111b upstream of the flow sensor Fs1 or the concentration sensor Cs1, an addition operation is performed on the error E3. Adding the error E3 can improve the accuracy of the reliability classification. Furthermore, the classification range of the reliability level can also be widened.

[0086] The above-described embodiments of the present invention provide the following advantageous effects: (1) A pipeline management system according to the present invention is a pipeline management system for monitoring a pipeline that supplies gas to an end user, the pipeline management system comprising: a pipeline system to which gas is supplied; and a control system for controlling the pipeline system, the pipeline system comprising: a gas source; a pipe connected to the gas source; a gas separation device connected to the pipe and separating the gas supplied from the gas source into multiple gas streams; a first flow rate sensor for measuring the flow rate of gas supplied to a main supply pipe of the pipeline; a second flow rate sensor for measuring the flow rate of product gas flowing out from the gas separation device; and a first concentration sensor for measuring the concentration of the product gas, the control system comprising: a recording unit for recording measurement data of the first and second flow rate sensors and the first concentration sensor; and a calculation unit for calculating, based on the measurement results of the first and second flow rate sensors and the first concentration sensor, the concentration of the gas stream at a position along the supply gas supplied to the gas separation device and the flow rate and concentration of the gas stream at a downstream position of return gas returned from the gas separation device to the main supply pipe according to mass balance.

[0087] With the above configuration, by calculating the composition at unmeasured points, it becomes possible to monitor the gas composition in the gas separation device with a small number of installed sensors.

[0088] (2) The pipeline system further includes a compressor for maintaining a gas flow in the pipeline, a turbine for supplying power to the compressor, and a third flow rate sensor and a second concentration sensor for measuring the flow rate and concentration of the gas supplied to the turbine, the recording unit being further configured to record measurement data from the third flow rate sensor and the second concentration sensor, and the calculation unit being further configured to calculate the flow rate and concentration of the gas flow downstream of the compressor based on the measurement results of the third flow rate sensor and the second concentration sensor. In this way, compressors and turbines are often installed in pipelines, and by applying the present invention, it is possible to monitor the gas composition without increasing the number of installed sensors even if the number of compressors and turbines increases.

[0089] (3) The pipeline system further includes a pressure sensor at the same position as the first flow sensor and / or the second flow sensor, and the recording unit is further configured to record measurement data of the pressure sensor, thereby enabling more accurate measurement of the gas composition using the measurement data of the pressure sensor as well.

[0090] (4) The control system further includes an anomaly detection unit that detects an anomaly in the gas flow flowing through the pipeline, the pipeline system further including a fourth flow sensor that measures the gas flow rate of the product gas at the end user, and the recording unit is further configured to record measurement data of the fourth flow sensor. The anomaly detection unit determines a measurement anomaly by a second flow sensor that measures the flow rate of the product gas based on whether a first error of the measurement data of the second flow sensor compared to a sum of measurement data of a fourth flow sensor that measures the flow rate of the same product gas at the end user exceeds a threshold value. The anomaly detection unit determines a measurement anomaly by a first concentration sensor that measures the flow rate of the product gas from the gas separation device by generating a correlation plot of flow rate and concentration based on past gas flow rate and concentration data of the end user, estimating an expected concentration range of the product gas using the generated correlation plot and a sum of measurement data of a fourth flow sensor that measures the flow rate of the same product gas at the end user, and determining whether the measurement data of the first concentration sensor is outside the expected concentration range. This allows accurate prediction of the sensor measurement error based on data already obtained by calculation or on data actually obtained in the past.

[0091] (5) The anomaly detection unit is further configured to calculate a time delay of the pipeline, and the calculated time delay is further used in calculating the first error for anomaly detection. As the length of the pipeline increases, the distance between the sensors also increases, and time delay becomes an issue. Therefore, it is necessary to perform error calculation taking time delay into account in this way.

[0092] (6) The anomaly detection unit is further configured to classify the reliability levels of the measurement data of the first, second, and third flow rate sensors and the first concentration sensor in the pipeline and the calculation data by the calculation unit based on the first error. This makes it possible to determine the reliability based on the error and appropriately select maintenance measures, etc., according to the reliability.

[0093] (7) The pipeline system further includes a compressor for maintaining a gas flow in the pipeline, a turbine for powering the compressor, and a third flow rate sensor and a second concentration sensor for measuring the flow rate and concentration of the gas supplied to the turbine, and the anomaly detection unit further calculates a third error calculated downstream of the return gas compared with measurement data of a second concentration sensor of the turbine located downstream of the return gas, and classifies the reliability level based on the third error in addition to the first error. This increases the number of criteria for judgment, enabling more accurate reliability judgment.

[0094] It should be noted that the present invention is not limited to the above-described embodiments, and various modifications are possible. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to embodiments that include all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment. It is also possible to add the configuration of another embodiment to the configuration of one embodiment. It is also possible to delete part of the configuration of each embodiment, or to add or replace other configurations.

[0095] 1 Pipeline management system, 2 Pipeline, 4 Main supply pipe, 5 Gas separation device, 7 Compressor, 8 Turbine, 11 Calculation unit, 12 Recording unit, 13 Abnormality detection unit, Fs, Fs1, Fs2, Fs3 Flow rate sensors, Cs1, Cs3 Concentration sensors

Claims

1. A pipeline management system for monitoring a pipeline supplying gas to an end user, comprising: a pipeline system through which gas is supplied; and a control system for controlling the pipeline system, wherein the pipeline system comprises a gas source, a pipe connected to the gas source, a gas separation device connected to the pipe for separating the gas supplied from the gas source into a plurality of gas streams, a first flow sensor for measuring the flow rate of gas supplied to a main supply pipe of the pipeline, a second flow sensor for measuring the flow rate of a product gas flowing out of the gas separation device, and a first concentration sensor for measuring a concentration of the product gas, wherein the control system comprises: a recording unit for recording measurement data of the first and second flow sensors and the first concentration sensor, and a calculation unit for calculating, based on the measurement results of the first and second flow sensors and the first concentration sensor, the concentration of the gas stream at a position along the supply gas supplied to the gas separation device, and the flow rate and concentration of the gas stream at a position downstream of the return gas returned from the gas separation device to the main supply pipe according to mass balance.

2. A pipeline management system according to claim 1, further comprising: a compressor for maintaining a flow of a gas stream in the pipeline; a turbine for powering the compressor; and a third flow rate sensor and a second concentration sensor for measuring the flow rate and concentration of gas supplied to the turbine; the recording unit is further configured to record measurement data of the third flow rate sensor and the second concentration sensor; and the calculation unit is further configured to calculate the flow rate and concentration of the gas stream downstream of the compressor based on the measurement results of the third flow rate sensor and the second concentration sensor.

3. A pipeline management system as claimed in claim 1, characterized in that the pipeline system further comprises a pressure sensor at the same position as the first flow sensor and / or the second flow sensor, and the recording unit is further configured to record measurement data of the pressure sensor.

4. A pipeline management system according to claim 1, wherein the control system further comprises an anomaly detection unit for detecting an anomaly in the gas flow flowing through the pipeline, the pipeline system further comprises a fourth flow sensor for measuring a gas flow rate of the produced gas at an end user, and the recording unit is further configured to record measurement data of the fourth flow sensor, and the anomaly detection unit determines a measurement anomaly by the second flow sensor measuring the flow rate of the produced gas based on whether a first error of measurement data of the second flow sensor compared with a sum of measurement data of the fourth flow sensor measuring the flow rate of the same produced gas at the end user exceeds a threshold value, and determines a measurement anomaly by the first concentration sensor measuring the flow rate of the produced gas from the gas separation device by generating a correlation plot of flow rate and concentration based on past gas flow rate and concentration data of the end user, estimating an expected concentration range of the produced gas using the generated correlation plot and a sum of measurement data of the fourth flow sensor measuring the flow rate of the same produced gas at the end user, and determining whether the measurement data of the first concentration sensor is outside the expected concentration range, and calculating a second error of the measurement data of the first concentration sensor compared to an expected concentration range of the concentration sensor measuring the product gas flow from the gas separation device.

5. A pipeline management system according to claim 4, characterized in that the anomaly detection unit is further configured to calculate a time delay of the pipeline, and the calculated time delay is further used in the calculation of the first error for anomaly detection.

6. A pipeline management system as described in claim 4, characterized in that the anomaly detection unit is further configured to classify the reliability levels of the measurement data of the first / second / third flow rate sensors and the first concentration sensor in the pipeline and the calculation data by the calculation unit based on the first error.

7. A pipeline management system according to claim 6, further comprising: a compressor for maintaining a flow of gas in the pipeline; a turbine for powering the compressor; and a third flow rate sensor and a second concentration sensor for measuring the flow rate and concentration of gas supplied to the turbine; and the abnormality detection unit further calculates a third calculated error in the downstream of the return gas compared with measurement data of the second concentration sensor of the turbine located downstream of the return gas, and classifies the reliability level based on the third error in addition to the first error.

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