An intelligent management system applied to a digital energy nitrogen station

Abstract

This invention relates to the field of nitrogen station technology, and more particularly to an intelligent management system for digital energy nitrogen stations. The system uses a nitrogen booster control module to start, stop, and adjust the power of the boosters, flexibly responding to real-time changes in nitrogen demand and thus reducing energy consumption. The first and second pipeline modules precisely regulate nitrogen pressure and flow rate by controlling valve opening and closing, achieving efficient nitrogen delivery. The first pipeline stores nitrogen at a higher pressure, providing a continuous nitrogen supply to the second pipeline; the second pipeline then delivers nitrogen directly to the point of use at a lower pressure. This system optimizes nitrogen energy distribution through gradient pressure control, reducing energy loss during delivery. By predicting the fluctuation range of the total flow rate, it determines the number of nitrogen boosters to operate and the operating range of the first and second pipelines, thereby improving the system's responsiveness to demand changes and ensuring the stability of nitrogen supply while reducing energy consumption.

Description

Technical Field

[0001] This invention relates to the field of nitrogen station technology, and more particularly to an intelligent management system applied to digital energy nitrogen stations. Background Technology

[0002] The integration of digital and intelligent technologies has become a crucial means for various industries to improve efficiency, reduce costs, and enhance system reliability and flexibility. Particularly in the field of energy management, with the continuous increase in energy demand and growing pressure for energy conservation and emission reduction, how to manage energy efficiently and intelligently has become a problem to be solved. As a key link in industrial gas supply, the operational efficiency and stability of digital energy nitrogen stations directly affect the continuity and safety of downstream industrial production.

[0003] Traditional nitrogen station management relies heavily on experience-based operation and manual control. This is not only labor-intensive but also difficult to adapt to complex and changing needs and environments. Especially when nitrogen demand fluctuates, multiple nitrogen boosters need to be controlled to increase or decrease pressure. This is difficult to adjust accurately in real time, and higher pressures result in greater power consumption, leading to significant electricity waste. In reality, the information on increasing and decreasing power is delayed, causing multiple nitrogen boosters to be idle multiple times during the process of controlling the stored nitrogen pressure, resulting in resource waste. Summary of the Invention

[0004] To address the above problems, this invention provides an intelligent management system for digital energy nitrogen stations.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] An intelligent management system for a digital energy nitrogen station includes: a nitrogen booster control module, a first pipeline module, a second pipeline module, and an intelligent management module, wherein the nitrogen booster control module, the first pipeline module, and the second pipeline module are respectively connected to the intelligent management module;

[0007] The nitrogen booster control module is used to control the start-up, shutdown, and operating power of all nitrogen boosters in the digital energy nitrogen station; the nitrogen booster is used to output nitrogen pressure to the first pipeline network;

[0008] The first pipeline module is used to control the opening and closing degree of all connected valves in the first pipeline and to output nitrogen pressure to the second pipeline. The first pipeline is used to store nitrogen at a first gradient pressure. The second pipeline module is used to control the opening and closing degree of all connected valves in the second pipeline and to output nitrogen to several output ports. The second pipeline is used to store nitrogen at a second gradient pressure. The first gradient pressure is greater than the second gradient pressure.

[0009] The intelligent management module is used to obtain the total flow rate of all output ports, determine the number of nitrogen boosters to be turned on and the operating range of the first and second pipelines based on the predicted fluctuation range of the total flow rate; and control the opening and closing of valves in the first and second pipelines and adjust the operating power of the nitrogen boosters in real time based on the nitrogen pressure and fluctuation stability range of the second pipeline.

[0010] Furthermore, the first pipeline network and the second pipeline network each include a number of nitrogen pipelines connected by connecting pipes and connecting valves.

[0011] Furthermore, the operating range of the second pipeline network is determined through the following steps:

[0012] Monitor the total nitrogen flow rate at all output ports of the digital energy nitrogen station and collect total flow rate data at different time points;

[0013] Based on historical total flow velocity data, time series analysis algorithms are applied to predict the predicted fluctuation range of total flow velocity in future time periods.

[0014] The default operating range of the second pipeline is preset, and the pressure fluctuation range of the second pipeline is calculated based on the operating range of the second pipeline and the second gradient air pressure under the predicted fluctuation range of the total flow velocity.

[0015] The operating range of the second pipeline is adjusted with the pressure fluctuation range of the second pipeline as the starting value and the preset fluctuation stability range as the target value.

[0016] Furthermore, the application of time series analysis algorithm to predict the predicted fluctuation range of total flow velocity in future time periods includes the following steps:

[0017] Based on historical total flow velocity data, seasonal fluctuations, trend changes, and periodic fluctuations are separated.

[0018] The total nitrogen flow rate in the future time period is predicted by using an autoregressive integral moving average model. The maximum and minimum values ​​of the total nitrogen flow rate in the future are output to obtain the predicted fluctuation range.

[0019] Furthermore, the operating range of the first pipeline network is determined through the following steps:

[0020] The pressure fluctuation range of the first pipeline under the first gradient pressure is calculated based on the pressure fluctuation range of the second pipeline and the second gradient pressure.

[0021] The operating range of the first pipeline is adjusted with the pressure fluctuation range of the first pipeline as the starting value and the fluctuation stability range as the target value.

[0022] Furthermore, determining the number of nitrogen booster compressors to be turned on includes the following steps:

[0023] The average time-period supply required by the nitrogen booster is calculated based on the operating range of the first pipeline network, the first gradient gas pressure calculation, and the fluctuation stability range.

[0024] The number of nitrogen boosters to be activated is calculated based on the average supply during the time period and the ramp-up power consumption of the nitrogen booster.

[0025] Furthermore, the real-time control of valve opening and closing in the first and second pipelines based on the nitrogen pressure and fluctuation stability range of the second pipeline includes:

[0026] If the nitrogen pressure in the second pipeline is lower than the stable fluctuation range, then control the nitrogen pressure output from the first pipeline to the second pipeline.

[0027] If the nitrogen pressure in the second pipeline is greater than the stable fluctuation range, then control the pressure output from the first pipeline to the second pipeline to be reduced.

[0028] If the nitrogen pressure in the second pipeline is within a stable fluctuation range, then the real-time output strategy from the first pipeline to the second pipeline is maintained.

[0029] Furthermore, the adjustment of the operating power of the nitrogen booster includes adjusting the operating power of the nitrogen booster based on the predicted fluctuation range of the total flow rate and the nitrogen pressure data of the first and second pipeline networks.

[0030] The beneficial effects of this invention are as follows: This invention controls the start-up, stop, and operating power of the nitrogen booster through a nitrogen booster control module, directly responding to real-time changes in nitrogen demand, making nitrogen pressure output more flexible and reducing energy consumption caused by unnecessary high-power operation. The first and second pipeline modules achieve fine adjustment of nitrogen pressure and flow rate by controlling the opening and closing of valves within their respective networks. The first pipeline stores nitrogen at a higher pressure than the second pipeline, while the second pipeline is closer to the point of use and stores nitrogen at a lower pressure. This gradient pressure control allows for control of the output from the first pipeline to the second pipeline when demand fluctuates, without frequent adjustments to the nitrogen booster power. This not only meets different pressure requirements but also optimizes energy distribution, reduces energy loss during transportation, and improves the resilience of the first and second pipelines to demand changes by determining the number of nitrogen boosters to operate and the operating range of the first and second pipelines based on the predicted fluctuation range of the total flow rate, effectively increasing the stability of nitrogen supply. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of an intelligent management system applied to a digital energy nitrogen station according to the present invention.

[0032] Figure 2 This is a flowchart of the steps for determining the operating range of the second pipeline network in this invention. Detailed Implementation

[0033] Please see Figure 1-2 As shown, the present invention relates to an intelligent management system for a digital energy nitrogen station, comprising: a nitrogen booster control module, a first pipeline module, a second pipeline module, and an intelligent management module, wherein the nitrogen booster control module, the first pipeline module, and the second pipeline module are respectively connected to the intelligent management module;

[0034] The nitrogen booster control module is used to control the start-up, shutdown, and operating power of all nitrogen boosters in the digital energy nitrogen station; the nitrogen booster is used to output nitrogen pressure to the first pipeline network;

[0035] The first pipeline module is used to control the opening and closing degree of all connected valves in the first pipeline and to output nitrogen pressure to the second pipeline. The first pipeline is used to store nitrogen at a first gradient pressure. The second pipeline module is used to control the opening and closing degree of all connected valves in the second pipeline and to output nitrogen to several output ports. The second pipeline is used to store nitrogen at a second gradient pressure. The first gradient pressure is greater than the second gradient pressure.

[0036] The intelligent management module is used to obtain the total flow rate of all output ports, determine the number of nitrogen boosters to be turned on and the operating range of the first and second pipelines based on the predicted fluctuation range of the total flow rate; and control the opening and closing of valves in the first and second pipelines and adjust the operating power of the nitrogen boosters in real time based on the nitrogen pressure and fluctuation stability range of the second pipeline.

[0037] It should be noted that the nitrogen booster control module is responsible for managing the start-up, shutdown, and power adjustment of all nitrogen boosters within the nitrogen station. This module automatically adjusts its operating parameters by monitoring the booster's operating status and output pressure in real time to adapt to constantly changing nitrogen demand. For example, when it detects that the first pipeline network needs to supply more nitrogen to the second pipeline network to meet increased demand, the module will instruct the corresponding booster to increase its operating power, thereby increasing the output nitrogen pressure. The first and second pipeline network modules are responsible for managing nitrogen flow within their respective networks. By controlling the opening and closing of valves within the networks, these two modules can precisely regulate the nitrogen flow rate and pressure, ensuring that nitrogen is efficiently delivered from the booster to the point of use. In practice, if the demand in the second pipeline network increases, the first pipeline network module will correspondingly increase the nitrogen pressure output to the second pipeline network, while the second pipeline network module adjusts its internal valve status to ensure that each output port receives an appropriate nitrogen supply. The intelligent management module, as the core of the system, integrates data acquisition, processing, and decision support functions. By collecting total flow rate data from each output port in real time and combining it with historical data using time series analysis and machine learning algorithms, the intelligent management module can predict the fluctuation trend of nitrogen demand. Based on these predictions, the system automatically adjusts the number of booster compressors started and their operating power, as well as the valve status of the first and second pipeline networks, to achieve real-time optimization of nitrogen supply. For example, if a significant increase in nitrogen demand is predicted in the future, the system will increase the number of booster compressors started in advance and adjust the pipeline valves to ensure that the increased demand is met without causing insufficient supply or energy waste.

[0038] Furthermore, the first pipeline network and the second pipeline network each include a number of nitrogen pipelines connected by connecting pipes and connecting valves.

[0039] Specifically, the first pipeline network primarily serves to deliver nitrogen from the booster to various branch points. It typically maintains a high pressure rating to ensure efficient nitrogen delivery. By incorporating precisely controlled valves within the first network, the system can adjust the pressure and rate of nitrogen flow to the second pipeline network based on real-time demand, ensuring flexibility and responsiveness in nitrogen supply. The second pipeline network, on the other hand, distributes nitrogen from the first network to specific usage points, such as production lines and laboratories. The pressure in the second pipeline network is generally lower than that of the first network to allow for more precise control of the final nitrogen delivery pressure, meeting the specific needs of different usage points. The opening and closing of valves within the second pipeline network are also adjusted by the intelligent management system based on real-time changes in nitrogen demand, achieving precise control of nitrogen supply to each output port. For example, if a production line suddenly increases its nitrogen demand, the system will immediately detect this change and increase the nitrogen flow from the first network to the branch in the second pipeline network containing that production line by adjusting the opening of relevant valves, while ensuring that the nitrogen supply to other branches remains unaffected. This highly automated and intelligent pipeline management not only greatly improves the efficiency of nitrogen use, but also ensures the stability and safety of nitrogen supply.

[0040] Furthermore, the operating range of the second pipeline network is determined through the following steps:

[0041] Monitor the total nitrogen flow rate at all output ports of the digital energy nitrogen station and collect total flow rate data at different time points;

[0042] Based on historical total flow velocity data, time series analysis algorithms are applied to predict the predicted fluctuation range of total flow velocity in future time periods.

[0043] The default operating range of the second pipeline is preset, and the pressure fluctuation range of the second pipeline is calculated based on the operating range of the second pipeline and the second gradient air pressure under the predicted fluctuation range of the total flow velocity.

[0044] The operating range of the second pipeline is adjusted with the pressure fluctuation range of the second pipeline as the starting value and the preset fluctuation stability range as the target value.

[0045] In some embodiments, the total nitrogen flow rate at all output ports is comprehensively monitored, and flow rate data at key time points is collected. By tracking the nitrogen flow in real time, the system can capture instantaneous changes in nitrogen demand. Next, the system uses the collected historical flow rate data and time series analysis algorithms to predict the fluctuation range of the total nitrogen flow rate over a future period. This step predicts possible changes in future nitrogen flow rate by analyzing patterns and trends in historical data, thereby enabling foresight of future demand fluctuations. For example, advanced statistical methods such as the Autoregressive Integrated Moving Average (ARI MA) model can be used to analyze seasonal fluctuations, trend changes, and periodic fluctuations in the data, thereby obtaining accurate predictions of future flow rate changes. Based on these predictions, the system will preset the default operating range of the second pipeline network and calculate the pressure fluctuation range within the predicted total flow rate fluctuation range according to the design operating range of the second pipeline network and the second gradient pressure. This means that the system will pre-set the second pipeline network's ability to cope with demand changes at a certain pressure level based on future demand predictions, ensuring the continuity and stability of nitrogen supply. Finally, the system will dynamically adjust its operating range based on the actual fluctuation range of the secondary pipeline pressure to match the preset stable fluctuation range. This dynamic adjustment strategy enables the secondary pipeline to flexibly respond to actual changes in nitrogen demand, ensuring optimal operating efficiency and gas supply quality under various operating conditions. For example, if an increase in nitrogen demand is predicted during a certain period, the system will adjust the pipeline parameters in advance to increase the nitrogen supply to that area, thereby avoiding supply shortages.

[0046] Furthermore, the application of time series analysis algorithm to predict the predicted fluctuation range of total flow velocity in future time periods includes the following steps:

[0047] Based on historical total flow velocity data, seasonal fluctuations, trend changes, and periodic fluctuations are separated.

[0048] The total nitrogen flow rate in the future time period is predicted by using an autoregressive integral moving average model. The maximum and minimum values ​​of the total nitrogen flow rate in the future are output to obtain the predicted fluctuation range.

[0049] In some embodiments, total nitrogen flow rate data is first collected over a period of time, including flow rate records at various time points. Statistical analysis of this data can reveal clear seasonal fluctuation patterns, such as increases or decreases in nitrogen demand during specific seasons or months, which are often closely related to seasonal variations in industrial production activities. Simultaneously, trend analysis helps identify long-term growth or decline trends, while periodic fluctuation analysis reveals recurring patterns of change beyond seasonality. Next, these analytical insights are applied to construct a predictive model. The Autoregressive Integral Moving Average (ARI MA) model combines the autoregressive properties of time series, the stationarity of differencing, and the moving average process, comprehensively considering information from historical data to predict future total nitrogen flow rates. By adjusting model parameters, such as the seasonal differencing order, the order of the autoregressive term, and the moving average term, the model best fits the fluctuation patterns identified in the historical data. Finally, the model outputs a prediction range for future total nitrogen flow rates, encompassing the maximum and minimum values ​​that nitrogen flow rates may reach within the prediction period. For example, if the forecast shows that the maximum total nitrogen flow rate will be 10,000 cubic meters per hour and the minimum will be 8,000 cubic meters per hour in the next three months, the intelligent management system will adjust the operation strategy of the booster and the regulation plan of the pipeline network according to this predicted fluctuation range, so as to ensure that the nitrogen supply can meet the maximum demand without causing waste.

[0050] Furthermore, the operating range of the first pipeline network is determined through the following steps:

[0051] The pressure fluctuation range of the first pipeline under the first gradient pressure is calculated based on the pressure fluctuation range of the second pipeline and the second gradient pressure.

[0052] The operating range of the first pipeline is adjusted with the pressure fluctuation range of the first pipeline as the starting value and the fluctuation stability range as the target value.

[0053] In some embodiments, the system monitors and analyzes the pressure fluctuation range of the second pipeline network based on its actual operation. For example, if the second pipeline network primarily supplies an industrial area requiring large amounts of nitrogen, its pressure fluctuations may be significant, necessitating greater flexibility and responsiveness from the first pipeline network to cope with such fluctuations. The system collects relevant data, including nitrogen usage, time distribution, and pressure changes, to assess the pressure performance of the second pipeline network under different operating conditions. Next, using the collected data and considering the characteristics of the second gradient pressure, the system calculates the pressure fluctuation range that the first pipeline network should maintain under the first gradient pressure. This calculation considers not only current usage demands but also predicts future demand changes, ensuring that the first pipeline network's operating strategy meets current needs while flexibly responding to potential future changes. Based on the calculated pressure fluctuation range of the first pipeline network, the system sets this range as the starting value for operation and adjusts it according to a preset fluctuation stability range. This means that the system dynamically adjusts the operating parameters of the first pipeline network based on predictions and real-time data, such as adjusting valve openings and changing the operating mode of the booster compressor, to ensure that the pressure of the first pipeline network remains within the optimal operating range. For example, if it is predicted that the nitrogen demand of the second pipeline will increase in a certain period of time in the future, the system may increase the pressure output of the first pipeline in advance to prevent insufficient nitrogen supply during peak demand.

[0054] Furthermore, determining the number of nitrogen booster compressors to be turned on includes the following steps:

[0055] The average time-period supply required by the nitrogen booster is calculated based on the operating range of the first pipeline network, the first gradient gas pressure calculation, and the fluctuation stability range.

[0056] The number of nitrogen boosters to be activated is calculated based on the average supply during the time period and the ramp-up power consumption of the nitrogen booster.

[0057] In some embodiments, the system first assesses the operating range of the first pipeline network, which includes accurately calculating the nitrogen demand at the first gradient pressure. This step is typically based on historical data analysis, current usage trends, and future demand forecasts. By integrating this information, the system can determine the nitrogen supply that the first pipeline network should maintain during a specific time period to ensure that sufficient nitrogen is safely and efficiently transmitted through the network. Next, the system calculates the number of nitrogen booster compressors required to be activated based on the determined average time-period supply. This calculation takes into account the ramp-up power consumption of each compressor under different operating conditions, i.e., the energy consumed to reach a specified pressure level from a static position. By accurately calculating the optimal number of booster compressors required to activate at a specific supply level, the system can optimize the operating configuration, ensuring both energy economy and efficiency while meeting nitrogen supply demands. For example, if predictive analysis shows that the first pipeline network requires additional nitrogen supply to meet sudden increases in demand during peak periods, the system will automatically calculate how many additional booster compressors need to be activated to maintain a stable supply at the existing first gradient pressure. If the calculation results indicate that two additional booster compressors are needed, the system will automatically adjust and start these two booster compressors, while taking into account the impact of each booster compressor's start-up and operation on the total energy consumption, in order to achieve the optimal energy efficiency ratio.

[0058] Furthermore, the real-time control of valve opening and closing in the first and second pipelines based on the nitrogen pressure and fluctuation stability range of the second pipeline includes:

[0059] If the nitrogen pressure in the second pipeline is lower than the stable fluctuation range, then control the nitrogen pressure output from the first pipeline to the second pipeline.

[0060] If the nitrogen pressure in the second pipeline is greater than the stable fluctuation range, then control the pressure output from the first pipeline to the second pipeline to be reduced.

[0061] If the nitrogen pressure in the second pipeline is within a stable fluctuation range, then the real-time output strategy from the first pipeline to the second pipeline is maintained.

[0062] First, the system monitors the nitrogen pressure in the second pipeline network in real time using a pressure sensor and compares it with a predetermined stable pressure range. This stable pressure range is a pressure range pre-set based on long-term nitrogen usage data, nitrogen supply and demand patterns, and system safety operating parameters, designed to ensure efficient and safe system operation. When the nitrogen pressure in the second pipeline network is detected to be below this stable pressure range, the system determines that nitrogen demand has increased or supply is insufficient. At this point, the intelligent management system immediately responds, instructing the first pipeline network to increase nitrogen pressure output to the second pipeline network. This can be achieved by increasing the operating power of the booster compressor or adjusting the opening of relevant valves, thereby quickly replenishing the nitrogen supply to the second pipeline network to ensure that increased demand is met. Conversely, if the nitrogen pressure in the second pipeline network exceeds the stable pressure range, the system identifies it as nitrogen oversupply or decreased usage. To prevent nitrogen waste and potential damage to the pipeline network from excessive pressure, the intelligent management system adjusts the first pipeline network to reduce nitrogen output to the second pipeline network. This is typically achieved by reducing the power of the booster compressor or decreasing the valve opening to optimize nitrogen supply and avoid unnecessary energy waste. When the nitrogen pressure in the second pipeline network remains within a stable fluctuation range, it indicates that the nitrogen supply and demand are in balance. At this time, the intelligent management system will maintain the current valve opening and closing strategy to ensure stable nitrogen delivery to both the first and second pipeline networks, while continuing to monitor changes in nitrogen pressure to respond quickly to any sudden changes in demand.

[0063] Furthermore, the adjustment of the operating power of the nitrogen booster includes adjusting the operating power of the nitrogen booster based on the predicted fluctuation range of the total flow rate and the nitrogen pressure data of the first and second pipeline networks.

[0064] In some embodiments, the nitrogen pressure in the first and second pipeline networks is monitored in real time, combined with total nitrogen flow rate prediction data. This includes analyzing historical flow rate data and applying advanced prediction models to estimate changes in nitrogen demand over a future period. Then, based on the predicted total flow rate fluctuation range, the system assesses whether the current operating status of the nitrogen booster compressor can meet future nitrogen demand. If the prediction indicates that future nitrogen demand will increase, and the current booster compressor power setting cannot meet this increase, the system automatically increases the booster compressor's operating power to ensure sufficient nitrogen output. This adjustment process may involve increasing the booster compressor's rotational speed or adjusting the compression ratio to increase nitrogen compression and delivery capacity. Conversely, if the prediction indicates that nitrogen demand will decrease over a future period, the system appropriately reduces the nitrogen booster compressor's operating power to avoid unnecessary energy consumption and reduce operating costs. This may be achieved by reducing the rotational speed, adjusting the duty cycle, or enabling a more efficient operating mode to reduce energy consumption while meeting demand. Actual measured values ​​of nitrogen pressure in the first and second pipeline networks are considered to ensure that power adjustments do not cause system pressure to exceed the optimal range for safety or efficiency. For example, if the pressure in the second pipeline is already close to the maximum allowable value of the system, the system will control the extent to which the booster power is increased even if demand increases, in order to avoid excessive pressure causing safety risks or equipment damage.

[0065] The above embodiments are merely descriptions of preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. An intelligent management system for digital energy nitrogen stations, characterized in that, include: The system includes a nitrogen booster control module, a first pipeline module, a second pipeline module, and an intelligent management module, wherein the nitrogen booster control module, the first pipeline module, and the second pipeline module are respectively connected to the intelligent management module; The nitrogen booster control module is used to control the start-up, shutdown, and operating power of all nitrogen boosters in the digital energy nitrogen station; the nitrogen booster is used to output nitrogen pressure to the first pipeline network; The first pipeline module is used to control the opening and closing degree of all connected valves in the first pipeline and to output nitrogen pressure to the second pipeline. The first pipeline is used to store nitrogen at a first gradient pressure. The second pipeline module is used to control the opening and closing degree of all connected valves in the second pipeline and to output nitrogen to several output ports. The second pipeline is used to store nitrogen at a second gradient pressure. The first gradient pressure is greater than the second gradient pressure. The intelligent management module is used to obtain the total flow rate of all output ports, determine the number of nitrogen boosters to be turned on and the operating range of the first and second pipelines based on the predicted fluctuation range of the total flow rate; and control the opening and closing of valves in the first and second pipelines and adjust the operating power of the nitrogen boosters in real time based on the nitrogen pressure and fluctuation stability range of the second pipeline. The operating range of the second pipeline network is determined through the following steps: Monitor the total nitrogen flow rate at all output ports of the digital energy nitrogen station and collect total flow rate data at different time points; Based on historical total flow velocity data, time series analysis algorithms are applied to predict the predicted fluctuation range of total flow velocity in future time periods. The default operating range of the second pipeline is preset, and the pressure fluctuation range of the second pipeline is calculated based on the operating range of the second pipeline and the second gradient air pressure under the predicted fluctuation range of the total flow velocity. The operating range of the second pipeline is adjusted with the pressure fluctuation range of the second pipeline as the starting value and the preset fluctuation stability range as the target value. The operating range of the first pipeline network is determined through the following steps: The pressure fluctuation range of the first pipeline under the first gradient pressure is calculated based on the pressure fluctuation range of the second pipeline and the second gradient pressure. The operating range of the first pipeline is adjusted with the pressure fluctuation range of the first pipeline as the starting value and the fluctuation stability range as the target value.

2. The intelligent management system for a digital energy nitrogen station according to claim 1, characterized in that, The first pipeline network and the second pipeline network each include several nitrogen pipelines connected by connecting pipes and connecting valves.

3. The intelligent management system for a digital energy nitrogen station according to claim 1, characterized in that, The application of time series analysis algorithm to predict the predicted fluctuation range of total flow velocity in future time periods includes the following steps: Based on historical total flow velocity data, we separate trend changes from periodic fluctuations; The total nitrogen flow rate in the future time period is predicted by using an autoregressive integral moving average model. The maximum and minimum values ​​of the total nitrogen flow rate in the future are output to obtain the predicted fluctuation range.

4. The intelligent management system for a digital energy nitrogen station according to claim 1, characterized in that, Determining the number of nitrogen boosters to be turned on includes the following steps: Based on the operating range of the first pipeline network, the first gradient gas pressure, and the stable fluctuation range, calculate the average time-period supply required by the nitrogen booster. The number of nitrogen boosters to be turned on is calculated based on the average supply during the time period and the ramp-up power consumption of the nitrogen booster; ramp-up power consumption is the energy consumed by the nitrogen booster to reach the specified pressure level from a static position.

5. The intelligent management system for a digital energy nitrogen station according to claim 1, characterized in that, The real-time control of valve opening and closing in the first and second pipelines based on the nitrogen pressure and fluctuation stability range of the second pipeline includes: If the nitrogen pressure in the second pipeline is lower than the stable fluctuation range, then control the nitrogen pressure output from the first pipeline to the second pipeline. If the nitrogen pressure in the second pipeline is greater than the stable fluctuation range, then control the pressure output from the first pipeline to the second pipeline to be reduced. If the nitrogen pressure in the second pipeline is within a stable fluctuation range, then the real-time output strategy from the first pipeline to the second pipeline is maintained.

6. The intelligent management system for a digital energy nitrogen station according to claim 1, characterized in that, The adjustment of the operating power of the nitrogen booster includes adjusting the operating power of the nitrogen booster based on the predicted fluctuation range of the total flow rate and the nitrogen pressure data of the first and second pipeline networks.

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