Gas Pipeline Network Research Articles

A transient gas pipeline network simulation model for decoupling the hydraulic-thermal process and the component tracking process

The metering mode is gradually changing from volumetric metering to energy metering under the open-access operation of gas pipelines. The gas component tracking by operating simulation is an effective method to realize the energy metering of gas networks. In this paper, coupling and decoupling transient component tracking models of gas networks are proposed. The pipeline governing equations, compressor equations, valve equations, and node relationship equations are considered in the proposed models. The implicit central difference method and the damped Newtonian method are adopted to solve the models. The coupling model considers the component tracking part and hydraulic-thermal simulation as a whole, while the decoupling model splits the whole process into the gas component tracking part, the parameters calculation part, and the hydraulic-thermal simulation part. In the component tracking part, the spatiotemporal variation of the gas mass fraction and density can be obtained through the input velocity of each node. Then, the parameters in the gas state equation can be solved, the hydraulic-thermal simulation can be performed, and the new velocity of each node can be calculated. The iteration for each time step ends if the deviation of flow velocity in the component tracking process and the hydraulic-thermal process satisfies the requirements. Two cases are studied to verify the effectiveness of the proposed models, and the boundary condition adaptability of the transient simulation models is analyzed. The proposed models can efficiently simulate the spatiotemporal variation of the operating variables and gas components, providing a reference in the operation of natural gas pipeline networks.

Three-layer and robust planning models to evaluate the strategies of defense layer, attack layer, and operation layer for optimal protection in natural gas pipeline network

Using game theory techniques, a three-layer planning model (THLPM) for the defense, attack, and operational layers has been established to address malicious damage to pipelines. A robust planning model was developed for situations with uncertain attack resources. In this model, the defense layer protects critical infrastructure within the network to minimize losses. The attack layer targets unprotected facilities based on the defensive strategy. The operational layer formulates the optimal pipeline transmission strategy based on the decisions of the defense and attack layers. By utilizing the duality theorem, the THLPM is transformed into a two-layer planning problem, which is then linearized and solved using a decomposition algorithm. Taking a specific ring-shaped pipeline network as an example, the study analyzes the significant role of backup pipelines in enhancing system resilience and evaluates the offensive and defensive strategies of THLPM. The effectiveness of THLPM in protecting the network was assessed, showing that when defense and attack resources are invested at levels 3 and 10, respectively, operational costs of the network are reduced by 54.2 % compared to a scenario without any defenses. The methods proposed in this paper are applicable to other pipeline systems.

Research on the vibration response characteristics of PE gas pipeline aimed for third-party damage monitoring

Third-party damage (TPD) incidents account for over 73% in China, becoming the primary cause of urban buried gas pipeline disruption. Therefore, real-time monitoring of TPD holds significance. This passage introduces a novel method for third-party damage monitoring of urban gas pipeline networks without excavation. The approach involves installing acoustic sensors in the pipeline to detect abnormal signals caused by construction activities. While the effectiveness of this method has been confirmed for buried steel pipelines, the propagation patterns, frequency characteristics, and the impact of fluid flow within PE pipelines remain unclear. To this end, this study explores these issues through experiments and simulations. According to the research, sound waves are the primary mode of signal propagation. The impact of gas pressure can be disregarded, but if the flow is reversed, the signal will weaken by 26%. The signal energy is concentrated in the 0–2 kHz range, decreasing exponentially as the distance increases. Moreover, a positive linear correlation exists between the signal energy and the load size to the power of 0.1. This research provides theoretical support for studying third-party damage monitoring technology and identifying and localizing damage types.

A probabilistic analysis method for evaluating the safety & resilience of urban gas pipeline network

Urban gas pipeline networks (UGPN) provide important support for high-quality urbanization. Therefore, it is imperative to analyze and assess the potential failures of UGPN. A novel probabilistic analysis method is proposed for assessing the safety and resilience of UGPN. Firstly, Bow-Tie analysis is used to identify faults. Then, a four-dimensional resilience assessment network is developed. Bayesian network is utilized to model the relationship between the variables, while dynamic Bayesian network is used to consider the dynamic nature of the system. The results of the study show that the proposed model can accurately estimate faults, consequences, and influence paths. Furthermore, the resilience analysis shows that monitoring the objective conditions is crucial and that the initial failure probability of the UGPN decreases from 0.03767 % to 0.01435 % when connected to a resilience network, indicating that considering resilience can effectively improve the reliability and safety of the UGPN. Two application examples are presented in the paper to validate the functionality of the proposed model. The proposed model can be used to set the state of UGPN to predict the probability of occurrence of a specific event and its consequences and to simulate the improvement trend of UGPN based on the direction of focus of future work.

Optimal Scheduling of Integrated Energy System Considering Hydrogen Blending Gas and Demand Response

In the context of carbon neutrality and carbon peaking, in order to achieve low carbon emissions and promote the efficient utilization of wind energy, hydrogen energy as an important energy carrier is proposed to mix hydrogen and natural gas to form hydrogen-enriched compressed natural gas (HCNG). It is also injected into the natural gas pipeline network to achieve the transmission and utilization of hydrogen energy. At the same time, the participation of demand response is considered, the load’s peak and trough periods are adjusted, and the large-scale consumption of renewable energy and the reduction in carbon emissions are achieved. First of all, a fine model of hydrogen production and hydrogen use equipment is established to analyze the impact of adding hydrogen mixing on the economy and the low-carbon property of the system. With green certificates and demand response, the utilization rate of hydrogen energy is improved to further explore the energy utilization rate and emission reduction capacity of the system. Secondly, on the basis of modeling, the optimal scheduling strategy is proposed with the sum of energy purchase cost, equipment operation cost, carbon emission cost, wind curtailment cost, and green certificate income as the lowest objective function. Considering the constraints such as hydrogen blending ratio and flexible load ratio of the pipeline network, a low-carbon economic scheduling model of hydrogen mixed natural gas was established. The model was linearized and solved by using MATLAB 2021a and CPLEX solver. By comparing different scenarios, the superiority of the model and the effectiveness of the strategy are verified.

Interdependent Expansion Planning for Resilient Electricity and Natural Gas Networks

This study explores enhancing the resilience of electric and natural gas networks against extreme events like windstorms and wildfires by integrating parts of the electric power transmissions into the natural gas pipeline network, which is less vulnerable. We propose a novel integrated energy system planning strategy that can enhance the systems’ ability to respond to such events. Our strategy unfolds in two stages. Initially, we devise expansion strategies for the interdependent networks through a detailed tri-level planning model, including transmission, generation, and market dynamics within a deregulated electricity market setting, formulated as a mixed-integer linear programming (MILP) problem. Subsequently, we assess the impact of extreme events through worst-case scenarios, applying previously determined network configurations. Finally, the integrated expansion planning strategies are evaluated using real-world test systems.

Robust pressure prediction of oil and gas pipeline networks based on equipment embedding neural network

Currently, extensive pipeline networks are developed in response to the demands of the oil and gas industry. The accurate estimation of the hydraulic condition of pipeline networks holds significant importance in the fields of pipeline design and safety management. Nevertheless, predicting the pressure of oil and gas pipeline networks with different equipment and structures remains challenging. To meet this challenge, a novel pressure prediction model for the oil and gas pipeline networks based on the equipment embedding neural network (EENN) is proposed in this study. The proposed model embeds different equipment models into the neural network model. The neural network in this model is used to focus on learning the connection characteristics of the pipeline network to achieve higher prediction accuracy. The present study first explores different embedding combinations of the EENN model to estimate the pressure in an oil pipeline network system that involves a non-isothermal batch transportation process. Then, the trained model is applied to predict the pressure in a gas pipeline network. The optimal EENN exhibits an average prediction error of 18.5% for oil pipelines and 0.36% for gas pipelines, which is lower than 20.8% and 3.57% under the neural network. The findings of this study demonstrate the efficacy of the proposed EENN in accurately forecasting pressures in diverse oil and gas pipeline networks by reducing the complexity of the learning process.

New Approach to SCADA System Screen Configuration Based on the Model of Oil and Gas Pipeline Network

INTRODUCTION： With the continuous progress of science and technology, the monitoring and control of oil and gas pipeline networks have become more and more critical; SCADA systems, as a kind of technology widely used in industrial control, play a key role. The screen configuration of the SCADA system is the core part of its user interface, which is directly related to the operator's mastery of the status of the pipeline network. In order to improve the monitoring efficiency and reduce the operation risk, this study is devoted to exploring a new method of SCADA system screen configuration based on the oil and gas pipeline network model.PURPOSE: The purpose of this study is to develop an innovative SCADA system screen configuration method to present the operating status of the oil and gas pipeline network more intuitively and efficiently. The design based on the pipeline network model aims to enhance the operators' understanding of essential information, such as pipeline network topology, fluid flow, etc., so as to make monitoring and control more intelligent.METHODS: The study adopts a new method of SCADA system screen configuration based on the oil and gas pipeline network model. First, the topology, sensor data, and control nodes of the oil and gas pipeline network are comprehensively modelled. Then, through the design principle of human-computer interaction, the modelling results are integrated into the screen configuration of the SCADA system to realize the intuitive presentation of information. At the same time, advanced visualization technology is introduced so that the operators can understand the real-time changes in the pipe network status more clearly.RESULTS: After experimental verification, the new method shows significant advantages in oil and gas pipeline network monitoring. The operators can recognize the abnormalities of the pipeline network more quickly and accurately through the SCADA system screen configuration, which improves the efficiency of troubleshooting and treatment. The visualized interface design makes the operation more intuitive and reduces the possibility of operating errors, thus improving the safety and reliability of the pipeline network.CONCLUSION: The new method of SCADA system screen configuration based on the oil and gas pipeline network model has achieved significant results in improving monitoring efficiency and reducing operational risks. Through a more intuitive and intelligent interface design, operators can have a more comprehensive understanding of the operating status of the pipeline network, which provides practical support for rapid response and decision-making. This approach introduces new ideas to the field of oil and gas pipeline network monitoring, which is of positive significance for improving the overall performance of the system. Future work can be carried out to optimize the interface design further and expand the applicable scenarios.

OPC UA Application Study in Oil and Gas Pipeline Network Monitoring Data Forwarding

INTRODUCTION： With the continuous development of oil and gas pipeline network monitoring and control technology, the need for data transmission and communication is becoming more and more prominent. In this context, OPC UA has attracted wide attention. This study aims to explore the application of OPC UA in data forwarding for oil and gas pipeline network monitoring in order to improve the efficiency, reliability and security of data transmission.PURPOSE: The purpose of this study is to evaluate the applicability of OPC UA in oil and gas pipeline network monitoring and to verify its performance in data forwarding through empirical studies. By gaining an in-depth understanding of the characteristics of OPC UA, it aims to provide a more advanced and efficient monitoring data transfer solution for the oil and gas industry.METHOD: The study adopts a combination of field monitoring and laboratory simulation. First, the essential characteristics and requirements of monitoring data in oil and gas pipeline networks were collected. Subsequently, a monitoring system with OPC UA as the communication protocol was established and field tested. In the laboratory environment, data transmission scenarios under different working conditions were simulated, and the performance of OPC UA under different conditions was analyzed.RESULT: The field monitoring results show that the data transmission efficiency is significantly improved by using OPC UA as the communication protocol for data forwarding in oil and gas pipeline network monitoring. Meanwhile, the system performs well in different environments with high reliability and security. The laboratory simulation results further verify the stability and adaptability of OPC UA under complex working conditions.CONCLUSION: OPC UA is an effective communication protocol that can meet the data transmission requirements for oil and gas pipeline network monitoring. Its efficient, reliable, and secure characteristics make it an ideal choice for improving the communication performance of monitoring systems in the oil and gas industry. The empirical results of this study provide reliable technical support for the oil and gas industry in the field of data transmission and a vital reference for the optimization and upgrading of monitoring systems in the future.

GIS-BASED REAL-TIME GAS LEAK DETECTION SYSTEM AT BASKENT NATURAL GAS DISTRIBUTION COMPANY

Abstract. Natural gas has been used for heating and production purposes in Turkey since 1987, and every passing year, the natural gas pipeline network continues to expand with investments. The distribution of natural gas within urban areas is achieved through a complex network structure formed by the joining of Polyethylene (PE) and Steel (ST) pipes using various connection elements. This complex structure is susceptible to deformation over time due to various reasons such as corrosion in steel lines, manufacturing errors in connection elements in PE lines, and other factors. As a result, natural gas leaks occasionally occur in these pipelines. The leakage control process in natural gas pipelines is carried out using specially designed equipment and vehicles equipped for this purpose. However, while these systems may be sufficient for collecting the necessary data for leak detection, the complex structure of the distribution network and the necessary data for leak detection, the complex structure of the distribution network and the necessity of performing this process with multiple teams bring about many challenges in terms of tracking, management, and reliability of the operation. At this point, the advancement of GIS (Geographic Information System), mobile, and communication technologies has made it possible to overcome these challenges. In this study, a real-time GIS-supported leak detection system developed using these technologies for Başkent Natural Gas Distrubition Inc. (Başkentgaz), which provides natural gas distribution services in Ankara, has been described. The study discusses the benefits brought by this system to the natural gas leak detection process.

Study on the Physical Properties of Hydrogen-Doped Natural Gas Based on Equation of State

As a zero-emission green clean energy, hydrogen energy is an important means to achieve the strategic goal of carbon neutrality and an important part of the energy Internet. Hydrogen-doped natural gas transportation is an economical and feasible scheme to realize long-distance transportation of hydrogen by using the existing natural gas pipeline network. However, the addition of hydrogen to natural gas will cause obvious changes in the physical properties of the transport medium, which will have a certain impact on the transport characteristics and flow measurement of the pipeline. The main problem is that we need to understand the changes of physical properties after natural gas mixed with hydrogen to ensure the safe operation of natural gas pipe network mixed with hydrogen. Based on this situation, this paper takes BWRS equation as the theoretical basis, selects typical natural gas temperament, calculates and solves the physical parameters of natural gas under different hydrogen blending ratios, and compares them with the standard physical reference values. After verification, the results are used to explore the physical properties of hydrogen-doped natural gas with hydrogen blending ratio, temperature and pressure as variables. The relative average absolute value error (RAAD) of the calculated physical properties of hydrogen-doped natural gas in this paper is less than 2% compared with the reference value of standard physical properties, which can provide theoretical data basis for studying hydrogen-doped pipeline transportation, ensuring pipeline transportation safety and hydrogen-doped natural gas metering.

Design Improvement Using Topology Optimization for the Structural Frame Design of a 40 Ft LNG ISO Container Tank

LNG ISO tank containers are a solution for bulk liquefied natural gas (LNG) delivery to the outer islands of Indonesia that are not connected to the gas pipeline network. The design of an ISO tank frame must consider two critical parameters, strength/rigidity and weight saving, which affect the operational performance of the distribution process. The current investigation aims to numerically optimize the design of the structural frame of a 40 ft LNG ISO tank for a mini LNG carrier operation using a topology optimization framework. Two design solutions are used in the topology optimization framework: reducing the strain energy and mass retained. Mass retained was selected as the objective function to be minimized, which was assumed to be 60–80%. The proposed frame design is tested using three operational loading scenarios, including racking, lifting, and stacking tests based on the ISO 1496 standard. The convergence mesh tests were initially evaluated to obtain the appropriate mesh density in the finite element analysis (FEA). The simulation findings show that the topology optimization method of the frame design resulted in an improved design, with an increase in the strength-to-weight saving ratio. A promising result from the optimization scenario demonstrates weight savings of about 18.4–37.3%, with experienced stress below the limit criteria. It is found that decreasing mass retained causes a significant stress increase in the structural frame and ISO corner castings, especially in the stacking load. The critical recommendation in the frame design of the LNG ISO tank can be improved by eliminating the saddle support and bottom frame and increasing the thickness of the vertical frame.

Crack detection in metallic materials using a mobile robot

Cracks and flaws are typical failure modes in mechanical structures such as oil and gas pipeline networks, buildings, aircraft fuselages, and spacecraft. Early detection of these failures is critical for safety, timely replacement of damaged or corroded parts, accident prevention, and resource and cost savings. This requires low-cost, easy-to-implement, non-destructive, and reliable testing. For this purpose, we developed an embedded system in a Zumo 32U4 mobile robot for the magnetic detection of cracks in metal plates. Two AVR microcontrollers were used. One controls the magnetic sensing, signal processing, and data acquisition, and the other controls the robot’s displacement. A graphical user interface (GUI) was also implemented. Low-cost commercial magnetoresistive sensors (Sparkfun MAG3110) were used to monitor the variations of the 3D magnetic field around the cracks. Our detection method is based on the magnetic memory method, where local magnetic distortions are expected around a crack in a metallic material. Such distortions are due to the breaking of the symmetry of the crystal in the region where cracks appear. Experimental tests were carried out on a steel plate with machine-induced cracks of depth and width variations. The magnetic field changes associated with these cracks were analyzed and compared. This crack detection method could be used for structural health monitoring of mechanical infrastructure.

Allocation of transportation capacity for complex natural gas pipeline network under fair opening

China has formed a national natural gas pipeline network, and reasonable and accurate pipeline capacity allocation scheme has important significance for improving the utilization rate of pipeline network, improving the income of pipeline network operators and ensuring the gas consumption of downstream users, which poses greater challenges to the formulation of pipeline capacity allocation rules and mechanisms. This paper takes the natural gas pipeline network system as the research object, and studies the rules and mechanisms of pipeline capacity allocation. A capacity allocation model of natural gas pipeline network is proposed with the net present value of pipeline network operator's income as the goal, considering the gas consumption characteristics of downstream users, the dynamic change of gas source node capacity, pipeline hydraulic characteristics, pipeline flow direction, compressor and other constraints. Based on the simulation of the actual pipeline network by the proposed model, seven allocation rules and one mechanism are proposed. Specifically, the user priority of non-interruptible type, the pipeline path adjustable type and the gas source node adjustable type is higher than the corresponding comparison type. In the pipeline capacity allocation mechanism, the amount compensation mechanism for pipeline capacity transactions is as follows: When the pipeline capacity transaction occurs between users, the transaction information is submitted to the pipeline network operator. The pipeline network operator proposes the corresponding amount compensation according to the transaction information, and the transaction parties negotiate the proportion of the amount compensation and submit it to the pipeline network operator. In addition, it is recommended that pipeline network operators vigorously develop LNG receiving stations and downstream interruptible and compressible users in the future.

Influence of hydrogen blending on the operation of natural gas pipeline network considering the compressor power optimization

Blending hydrogen into the existing natural gas pipeline network is regarded as the most potential transportation mode on the utility-scale. However, the impact of hydrogen on the operation performance of the pipeline remained unclear. This paper analyzes the economic and environmental performance of natural gas pipeline under different hydrogen blending ratios and different hydraulic boundary conditions. In order to reduce the operation costs and carbon emissions in each condition, this paper establish a non-linear optimization model to get the new operation plan of the pipeline system. Further, in order to characterize different boundary conditions of the system, four scenarios, namely, the baseline scenario (BS), the setpoint of flow rate scenario (SF), the setpoint of pressure (SP), and the setpoint of heat flow rate (SH) are proposed in this paper. Two studied cases demonstrated that: (1) the original compressor for natural gas can adapt to a hydrogen blending without change the type of compressor. (2) The optimization model has significant potential in reducing the economic cost and carbon emissions of the system with an average decrease of 11.48%. (3) For every 1% of hydrogen added, the annual operating cost of the system is reduced by $0.73 million (3.29%) in SF, 0.017 million (0.08%) in SP, or increased by $1.67 million (7.50%) in SH. Moreover, the annual carbon emission is reduced by 0.38 kt (3.53%) in SF, 0.047 kt (0.44%) in SP, or increased by 0.76 kt (7.14%) in SH. However, when the hydrogen mixing ratio is more than 8%, the contrary trend may occur. (4) The maximum blending ratio at different points of the multi-source pipeline network are physically interdependent. The paper proposed an optimization model for the 2-E analysis of the pipeline and can provide theoretical guidance for the further application of this transportation mode.

Frequency stability control method for multi-energy system considering storage characteristics and transmission inertia of hot and gas pipeline network

The grid-connected capacity of renewable energy generation in multi-energy microgrid is increasing. This leads to a decrease in the inertia level in the microgrid, which has a great impact on the frequency stabilization control. This article proposes an adaptive control method for frequency control of inertia in multi-energy microgrids. Firstly, the system frequency fluctuation problem is addressed. Analyze the response characteristics of virtual inertia and the influence of physical inertia of rotating equipment on system frequency dynamics in multi-energy microgrid. Secondly, study the energy transfer characteristics of electric, thermal and gas systems in multi-energy microgrids. The energy coupling model between the subsystems in the multi-energy microgrid is established. And according to the difference of energy transmission time inertia of electric, heat and gas subsystems, the microgrid inertia response time model of different energy systems is established. Then, according to the energy balance stability criterion of multi-energy microgrid, combined with the current operating state of the system and the state of the higher-level distribution network, the fast response adaptive over-compensation control of multi-energy microgrid cluster is carried out to realize the inertia allocation in multi-energy microgrids. Finally, the proposed advanced frequency control method of multi-energy microgrid considering inertia demand is verified by simulation.

Extraction and Association Analysis of Risk Factors in Gas Pipeline Network Emergencies Through Fusing Expert Knowledge and Pre-Trained Model

Extraction and Association Analysis of Risk Factors in Gas Pipeline Network Emergencies Through Fusing Expert Knowledge and Pre-Trained Model

Simultaneous multi-objective framework of natural gas pipeline network operations

The optimization of gas transportation networks is essential as natural gas demand increases. Conflicting objectives, such as maximizing delivery flow rate, minimizing power consumption, and maximizing line pack, pose challenges in this context. To address these complexities, a novel multi-objective optimization method based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is proposed. The method generates a diverse set of Pareto optimal solutions, empowering decision-makers to select the most suitable solution for gas transportation networks. Three case studies validate the approach's effectiveness, showcasing its advantages in yielding more economical networks and enhancing the cost-effectiveness of natural gas transmission networks. The proposed method's versatility allows application to various gas transportation network scenarios. Decision-makers benefit from a range of Pareto optimal solutions, providing valuable insights. Moreover, the seamless integration of the proposed method into existing gas transportation network optimization frameworks further enhances performance. In conclusion, the study presents a robust multi-objective optimization method based on TOPSIS for gas transportation network optimization. It offers cost-effective solutions and improves the efficiency of natural gas transmission networks. The provision of diverse Pareto optimal solutions enables well-informed decision-making, contributing to sustainable energy solutions in the face of increasing natural gas demand.

Low Carbon Operation Control Technology for Smart Parks Combined with Intelligent Optimization Algorithms

Abstract This paper first calculates carbon emissions based on the carbon emission factor method and other methods and constructs a linear programming model for low-carbon operation of smart parks with economy, independence, and carbon emissions as objective functions, and constrains them from four aspects: power grid, natural gas pipeline network, equipment output, and energy storage battery limit. The problem can be solved using the sparrow optimization algorithm. Finally, the carbon emissions, power dispatching, and power consumption of the sample parks under the low-carbon operation control mode were analyzed. The results show that the carbon emissions of the park are reduced by 2035.93kg, and the total operating cost is reduced by 1680.11 yuan during the typical daily operation in summer after the intelligent optimization algorithm is used. The park’s carbon emissions decreased by 1686.53kg, and the total operating cost decreased by 1582.42 yuan during the typical daily operation in winter. The importance of this study lies in the low-carbon and modernization of smart parks.

Enhancing Real-Time Simulation of the Complexity Natural Gas Pipeline Network Through MLP-Newton Algorithm for High Precision and Reliability

Enhancing Real-Time Simulation of the Complexity Natural Gas Pipeline Network Through MLP-Newton Algorithm for High Precision and Reliability