Liquefied natural gas storage and transportation optimization system based on artificial intelligence

Abstract

The invention relates to the technical field of natural gas storage and transportation, and discloses a liquefied natural gas storage and transportation optimization system based on artificial intelligence. The system comprises a sensor and data acquisition module, a data processing and storage module, a machine learning and deep learning module, a decision support and optimization module, a user interface and interaction module, a safety and fault monitoring module, an environment monitoring and prediction module and a visual analysis and virtual simulation module. The sensor and the data acquisition module provide real-time data as a basis for analysis, optimization and decision making of other modules of the system, and the data processing and storage module stores the processed data in an accessible database for other parts of the system to use. Through real-time evaluation of environmental risks, safe operation of the liquefied natural gas system is ensured, and meanwhile, the visual analysis and virtual simulation module optimizes an operation strategy and provides decision support by utilizing data display and model establishment, so that the transportation efficiency and the overall response capability of the system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of natural gas storage and transportation, and in particular to an artificial intelligence-based liquefied natural gas storage and transportation optimization system. Background Art

[0002] The liquefied natural gas (LNG) storage and transportation optimization system is a system specially designed to manage and optimize each link of LNG in the supply chain. The liquefied natural gas storage and transportation optimization system plays a vital role in the LNG industry, especially in the context of globalization and growing energy demand. It not only improves the overall efficiency and reliability of the supply chain, but also ensures the safe transportation and storage of LNG. The application scope of this system covers all links from LNG production facilities to end users, providing accurate and reliable technical support for various enterprises and institutions.

[0003] Although the existing system can collect environmental data in real time, the accuracy of sensors is sometimes not high, or there are delays in the data transmission process, which will affect the system's ability to accurately assess and respond to environmental risks in a timely manner. At the same time, the system's comprehensive analysis capabilities for multiple environmental parameters are limited, and it lacks an in-depth understanding of the interrelationships of complex environmental factors, which hinders its ability to comprehensively assess and predict environmental impacts. Secondly, the authenticity and accuracy of virtual simulation models are not enough to fully reflect the complexity of the actual operating environment. Establishing and updating simulation models requires a lot of data and time, resulting in deviations between the model and actual operation. Finally, although visual analysis provides an intuitive understanding of the system status, it is still insufficient in providing comprehensive decision support, especially under dynamic market and environmental conditions. The system requires more advanced analytical tools to predict future trends and formulate long-term strategies to better support management's decision-making process. Summary of the invention

[0004] In view of the deficiencies of the prior art, the present invention provides an artificial intelligence-based liquefied natural gas storage and transportation optimization system, which solves the problems of insufficient data accuracy and real-time performance in the prior art.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an artificial intelligence-based liquefied natural gas storage and transportation optimization system, including a sensor and data acquisition module, a data processing and storage module, a machine learning and deep learning module, a decision support and optimization module, a user interface and interaction module, a safety and fault monitoring module, an environmental monitoring and prediction module, and a visual analysis and virtual simulation module;

[0006] The sensors and data acquisition modules provide real-time data as the basis for analysis, optimization and decision-making of other modules in the system;

[0007] The data processing and storage module stores the processed data in an accessible database for use by other parts of the system;

[0008] The machine learning and deep learning modules provide intelligent decision support, optimize route scheduling, tank filling and discharge strategies, and achieve predictive maintenance;

[0009] The decision support and optimization module helps operators and managers develop the best operating strategies to maximize efficiency and safety;

[0010] The user interface and interactive module enable the operator to intuitively understand the system operation status and perform necessary operations and adjustments;

[0011] The safety and fault monitoring module promptly detects and handles potential safety risks and equipment failures to ensure the safety and reliability of system operation;

[0012] The environmental monitoring and prediction module assesses environmental risks, formulates corresponding emergency response plans, and ensures the safe operation of the system under complex environmental conditions;

[0013] The visualization analysis and virtual simulation module helps management optimize operational strategies and decisions through visualization interfaces and simulation models, thereby improving the overall efficiency and responsiveness of the system.

[0014] Preferably, the sensor and data acquisition module comprises a temperature sensor unit and a pressure sensor unit;

[0015] The temperature sensor unit monitors temperature changes in the LNG storage tank and pipeline;

[0016] The pressure sensor unit monitors the pressure changes of pipelines and equipment in real time.

[0017] Preferably, the sensor and data acquisition module further includes a flow sensor unit and a liquid level sensor unit;

[0018] The flow sensor unit measures the flow rate of LNG in the pipeline;

[0019] The liquid level sensor unit measures the height of liquid LNG in the LNG storage tank.

[0020] Preferably, the data processing and storage module includes a data cleaning and conversion unit and a data storage and management unit;

[0021] The data cleaning and conversion unit cleans the noise and outliers in the data and converts it into a standard format for analysis;

[0022] The data storage and management unit uses an efficient database management system to ensure secure storage and fast access to real-time and historical data.

[0023] Preferably, the machine learning and deep learning module includes a supply and demand prediction model unit and a fault prediction model unit;

[0024] The supply and demand forecasting model unit forecasts the supply and demand of LNG based on historical data and market trends;

[0025] The fault prediction model unit uses monitoring data to predict faults or performance degradation of equipment.

[0026] Preferably, the decision support and optimization module includes an optimization algorithm unit and a decision evaluation unit;

[0027] The optimization algorithm unit uses an optimization algorithm to analyze multiple variables and constraints to generate an optimal decision-making solution;

[0028] The decision evaluation unit evaluates the impact of various decisions on system performance and safety.

[0029] Preferably, the user interface and interaction module include a real-time monitoring interface unit and an operation control unit;

[0030] The real-time monitoring interface unit displays system status, alarm information and key indicators in an intuitive manner;

[0031] The operating control unit allows an operator to manually intervene and adjust system parameters.

[0032] Preferably, the safety and fault monitoring module includes a safety alarm unit and an equipment health monitoring unit;

[0033] The safety alarm unit monitors the safety indicators in the system and issues an alarm when they exceed a set range;

[0034] The equipment health monitoring unit uses data analysis technology to monitor equipment status in real time and predict failures.

[0035] Preferably, the environmental monitoring and prediction module includes an environmental sensor unit and an environmental data analysis unit;

[0036] The environmental sensor unit monitors air quality, wind speed and wind direction environmental parameters;

[0037] The environmental data analysis unit analyzes environmental monitoring data and predicts environmental factors that may affect system operation.

[0038] Preferably, the visualization analysis and virtual simulation module includes a real-time data visualization unit and a virtual simulation model unit;

[0039] The real-time data visualization unit displays the processed data in the form of charts and maps to help users understand the system operation status;

[0040] The virtual simulation model unit establishes a virtual simulation model of the system to simulate the operating effects under different operating and environmental conditions.

[0041] The present invention provides an artificial intelligence-based liquefied natural gas storage and transportation optimization system, which has the following beneficial effects:

[0042] 1. The present invention monitors environmental parameters such as air quality and wind speed and direction in real time through the environmental monitoring and prediction module, and can accurately assess the environmental risks during the transportation and storage of liquefied natural gas. By identifying potential environmental problems in advance, such as weather changes or pollution incidents, the system can provide key basic data and early warning information for operational decisions, ensuring the safe operation of the system under complex environmental conditions.

[0043] 2. The present invention supports the optimization of operation strategies and scientific support for decision-making through the visualization of real-time data of the visual analysis and virtual simulation modules and the establishment of a virtual simulation model of the system. Operators and management can intuitively understand the operating status of the system and the impact of different strategies on efficiency and safety. This capability enables management to respond quickly to changes, optimize operation strategies, and make accurate decisions, thereby improving the overall efficiency and reliability of the liquefied natural gas storage and transportation system. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 is a system architecture diagram of the present invention;

[0045] Figure 2 It is a schematic diagram of the structure of the sensor and data acquisition module of the present invention;

[0046] Figure 3 It is a schematic diagram of the structure of the data processing and storage module of the present invention;

[0047] Figure 4 This is a schematic diagram of the structure of the machine learning and deep learning modules of the present invention;

[0048] Figure 5 It is a schematic diagram of the structure of the decision support and optimization module of the present invention;

[0049] Figure 6 It is a schematic diagram of the structure of the user interface and the interaction module of the present invention;

[0050] Figure 7 It is a schematic diagram of the structure of the safety and fault monitoring module of the present invention;

[0051] Figure 8 It is a schematic diagram of the structure of the environmental monitoring and prediction module of the present invention;

[0052] Fig. 9 It is a schematic diagram of the structure of the visualization analysis and virtual simulation module of the present invention. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the specification of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] Example:

[0055] Please refer to the attached Figure 1 - Attachment Fig. 9 The embodiment of the present invention provides an artificial intelligence-based liquefied natural gas storage and transportation optimization system, including a sensor and data acquisition module, a data processing and storage module, a machine learning and deep learning module, a decision support and optimization module, a user interface and interaction module, a safety and fault monitoring module, an environmental monitoring and prediction module, and a visualization analysis and virtual simulation module; the sensor and data acquisition module provides real-time data as the basis for analysis, optimization, and decision-making of other modules of the system; the data processing and storage module stores the processed data in an accessible database for use by other parts of the system; the machine learning and deep learning module provides intelligent decision support, optimizes route scheduling, tank filling and discharge strategies, and implements The system can realize predictive maintenance; the decision support and optimization module helps operators and managers to formulate the best operation strategy to maximize efficiency and safety; the user interface and interaction module enable operators to intuitively understand the system operation status and make necessary operations and adjustments; the safety and fault monitoring module timely discovers and handles potential safety risks and equipment failures to ensure the safety and reliability of system operation; the environmental monitoring and prediction module assesses environmental risks, formulates corresponding emergency response plans, and ensures the safe operation of the system under complex environmental conditions; the visual analysis and virtual simulation module helps management optimize operation strategies and decisions through visual interfaces and simulation models, and improves the overall efficiency and responsiveness of the system.

[0056] Please refer to the attached Figure 2The sensor and data acquisition module provides real-time data as the basis for analysis, optimization and decision-making of other modules of the system, and monitors key parameters in the LNG storage and transportation process, such as temperature, pressure, flow, liquid level, etc. in real time; the sensor and data acquisition module includes a temperature sensor unit and a pressure sensor unit. The temperature sensor unit monitors the temperature changes in the LNG storage tank and pipeline. The pressure sensor unit monitors the pressure changes in the pipeline and equipment in real time, and collects real-time environmental data for subsequent data processing and decision support. The sensor and data acquisition module also includes a flow sensor unit and a liquid level sensor unit. The flow sensor unit measures the flow rate of LNG in the pipeline, and the liquid level sensor unit measures the height of liquid LNG in the LNG storage tank, and processes and stores a large amount of real-time data from the sensor.

[0057] Please refer to the attached Figure 3 The data processing and storage module stores the processed data in an accessible database for use by other parts of the system, and cleans, converts and standardizes the raw data collected by the sensor; the data processing and storage module includes a data cleaning and conversion unit and a data storage and management unit. The data cleaning and conversion unit cleans the noise and outliers in the data and converts it into a standard format for analysis. The data storage and management unit uses an efficient database management system to ensure the secure storage and fast access of real-time and historical data, and uses machine learning and deep learning algorithms to process big data and extract patterns and insights.

[0058] Please refer to the attached Figure 4 , machine learning and deep learning modules provide intelligent decision support, optimize route scheduling, tank filling and discharge strategies, and realize predictive maintenance, use historical data and real-time data for pattern recognition, predict market supply and demand, optimize transportation strategies, etc.; machine learning and deep learning modules, including supply and demand prediction model units and fault prediction model units. The supply and demand prediction model unit predicts the supply and demand of LNG based on historical data and market trends. The fault prediction model unit uses monitoring data to predict equipment failures or performance degradation, and uses optimization algorithms to analyze multiple variables and constraints to generate the best decision plan.

[0059] Please refer to the attached Figure 5 The decision support and optimization module helps operators and managers develop optimal operating strategies to maximize efficiency and safety, and provides optimization suggestions and decision support based on the output of machine learning and deep learning models; the decision support and optimization module includes an optimization algorithm unit and a decision evaluation unit. The optimization algorithm unit uses an optimization algorithm to analyze multiple variables and constraints to generate the best decision plan. The decision evaluation unit evaluates the impact of various decisions on system performance and safety, and provides a user-friendly graphical interface and operation methods.

[0060] Please refer to the attached Figure 6The user interface and interactive module enable the operator to intuitively understand the system operation status and perform necessary operations and adjustments, provide a graphical interface, monitor the system status in real time, receive alarm information, and perform necessary manual intervention; the user interface and interactive module include a real-time monitoring interface unit and an operation control unit. The real-time monitoring interface unit displays the system status, alarm information and key indicators in an intuitive manner. The operation control unit allows the operator to manually intervene and adjust system parameters to ensure the safety of system operation and the reliability of equipment.

[0061] Please refer to the attached Figure 7 The safety and fault monitoring module promptly detects and handles potential safety risks and equipment failures, ensures the safety and reliability of system operation, monitors safety indicators such as pressure and temperature anomalies, and predicts equipment failures; the safety and fault monitoring module includes a safety alarm unit and an equipment health monitoring unit. The safety alarm unit monitors safety indicators in the system and issues an alarm when they exceed the set range. The equipment health monitoring unit uses data analysis technology to monitor the equipment status in real time and predict failures, assess environmental risks, and formulate corresponding response measures.

[0062] Please refer to the attached Figure 8 The environmental monitoring and prediction module evaluates environmental risks, formulates corresponding emergency response plans, ensures the safe operation of the system under complex environmental conditions, monitors environmental parameters such as air quality, wind speed and direction, and predicts the impact of environmental factors on system operation; the environmental monitoring and prediction module includes an environmental sensor unit and an environmental data analysis unit. The environmental sensor unit monitors air quality and wind speed and direction environmental parameters. The environmental data analysis unit analyzes environmental monitoring data, predicts environmental factors that affect system operation, evaluates environmental risks, and formulates corresponding response measures.

[0063] Please refer to the attached Fig. 9 The visualization analysis and virtual simulation module helps management optimize operational strategies and decisions through visualization interfaces and simulation models, improves the overall efficiency and responsiveness of the system, and provides real-time data visualization, system simulation analysis, and decision support tools; the visualization analysis and virtual simulation module includes a real-time data visualization unit and a virtual simulation model unit. The real-time data visualization unit displays the processed data in the form of charts and maps to help users understand the system operation status. The virtual simulation model unit establishes a virtual simulation model of the system to simulate the operation effects under different operating and environmental conditions, and optimizes system design and operation strategies through visualization and simulation.

[0064] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. The liquefied natural gas storage and transportation optimization system based on artificial intelligence is characterized by: Including sensor and data acquisition module, data processing and storage module, machine learning and deep learning module, decision support and optimization module, user interface and interaction module, safety and fault monitoring module, environmental monitoring and prediction module and visual analysis and virtual simulation module; The sensors and data acquisition modules provide real-time data as the basis for analysis, optimization and decision-making of other modules in the system; The data processing and storage module stores the processed data in an accessible database for use by other parts of the system; The machine learning and deep learning modules provide intelligent decision support, optimize route scheduling, tank filling and discharge strategies, and achieve predictive maintenance; The decision support and optimization module helps operators and managers develop the best operating strategies to maximize efficiency and safety; The user interface and interactive module enable the operator to intuitively understand the system operation status and perform necessary operations and adjustments; The safety and fault monitoring module promptly detects and handles potential safety risks and equipment failures to ensure the safety and reliability of system operation; The environmental monitoring and prediction module assesses environmental risks, formulates corresponding emergency response plans, and ensures the safe operation of the system under complex environmental conditions; The visualization analysis and virtual simulation module helps management optimize operational strategies and decisions through visualization interfaces and simulation models, thereby improving the overall efficiency and responsiveness of the system.

2. The liquefied natural gas storage and transportation optimization system based on artificial intelligence according to claim 1 is characterized in that: The sensor and data acquisition module includes a temperature sensor unit and a pressure sensor unit; The temperature sensor unit monitors temperature changes in the LNG storage tank and pipeline; The pressure sensor unit monitors the pressure changes of pipelines and equipment in real time.

3. The liquefied natural gas storage and transportation optimization system based on artificial intelligence according to claim 1 is characterized in that: The sensor and data acquisition module also includes a flow sensor unit and a liquid level sensor unit; The flow sensor unit measures the flow rate of LNG in the pipeline; The liquid level sensor unit measures the height of liquid LNG in the LNG storage tank.

4. The liquefied natural gas storage and transportation optimization system based on artificial intelligence according to claim 1 is characterized in that: The data processing and storage module includes a data cleaning and conversion unit and a data storage and management unit; The data cleaning and conversion unit cleans the noise and outliers in the data and converts it into a standard format for analysis; The data storage and management unit uses an efficient database management system to ensure secure storage and fast access to real-time and historical data.

5. The liquefied natural gas storage and transportation optimization system based on artificial intelligence according to claim 1 is characterized in that: The machine learning and deep learning module includes a supply and demand prediction model unit and a fault prediction model unit; The supply and demand forecasting model unit forecasts the supply and demand of LNG based on historical data and market trends; The fault prediction model unit uses monitoring data to predict faults or performance degradation of equipment.

6. The liquefied natural gas storage and transportation optimization system based on artificial intelligence according to claim 1 is characterized in that: The decision support and optimization module includes an optimization algorithm unit and a decision evaluation unit; The optimization algorithm unit uses an optimization algorithm to analyze multiple variables and constraints to generate an optimal decision-making solution; The decision evaluation unit evaluates the impact of various decisions on system performance and safety.

7. The liquefied natural gas storage and transportation optimization system based on artificial intelligence according to claim 1 is characterized in that: The user interface and interaction module includes a real-time monitoring interface unit and an operation control unit; The real-time monitoring interface unit displays system status, alarm information and key indicators in an intuitive manner; The operating control unit allows an operator to manually intervene and adjust system parameters.

8. The liquefied natural gas storage and transportation optimization system based on artificial intelligence according to claim 1 is characterized in that: The safety and fault monitoring module includes a safety alarm unit and an equipment health monitoring unit; The safety alarm unit monitors the safety indicators in the system and issues an alarm when they exceed a set range; The equipment health monitoring unit uses data analysis technology to monitor equipment status in real time and predict failures.

9. The liquefied natural gas storage and transportation optimization system based on artificial intelligence according to claim 1 is characterized in that: The environmental monitoring and prediction module includes an environmental sensor unit and an environmental data analysis unit; The environmental sensor unit monitors air quality, wind speed and wind direction environmental parameters; The environmental data analysis unit analyzes environmental monitoring data and predicts environmental factors that may affect system operation.

10. The liquefied natural gas storage and transportation optimization system based on artificial intelligence according to claim 1 is characterized in that: The visualization analysis and virtual simulation module includes a real-time data visualization unit and a virtual simulation model unit; The real-time data visualization unit displays the processed data in the form of charts and maps to help users understand the system operation status; The virtual simulation model unit establishes a virtual simulation model of the system to simulate the operating effects under different operating and environmental conditions.

Images