Natural Gas Pipeline Network Research Articles

Operation optimization of large-scale natural gas pipeline networks based on intelligent algorithm

With the expansion of natural gas pipelines into larger networks, there is a growing concern regarding energy consumption in the operations of pipeline systems. However, the intricate network structure and hydraulic properties pose challenges for operation optimization. In this paper, a Mixed Integer Nonlinear Programming model is proposed to optimize the steady-state operation of natural gas pipeline network, aiming to minimize the energy consumption of compressor units. The model incorporates constraints related to flow direction, flow balance, pressure drop in pipeline sections, and pressure increase at compressor stations. To solve the complex nonlinear model efficiently, a stochastic optimization algorithm that integrates particle swarm optimization and high-fidelity simulation is proposed. The case study is conducted on a large-scale natural gas pipeline network consisting of forty-three pipeline sections and four compressor stations. The optimal operation scheme is calculated, and the outlet pressures of each compressor are determined. The results demonstrate that the stochastic optimization algorithm proposed in this paper can reduce energy consumption by 21.23 % at most and 19.77 % on average during pipeline operation, which can provide guidance for the operation management of large-scale natural gas pipeline network.

Pipeline leakage identification method based on DPR-net and distributed optical fiber acoustic sensing technology

Real-time monitoring of natural gas pipeline network can ensure the life and health of human beings and property safety in the surrounding area of the pipeline. Therefore, how to realize the rapid identification of pipeline leakage signal when leakage occurs is extremely important. Distributed acoustic sensing (DAS) technology is widely used in the field of pipeline leakage monitoring because of its advantages of wide coverage and high sensitivity. In this paper, a pipeline leak identification method based on DAS and one dimensional DPR-net (DAS pipeline leakage recognition network) are proposed. Pipeline leakage signal samples are collected under different working conditions (leakage aperture, leakage pressure, leakage direction). In test, the recognition accuracy of this method reached over 99%. There are reasons to believe that this method will provide an important technical means for DAS to detect pipeline leakage.

Hydrogen embrittlement effects on remaining life and fatigue crack growth rate in API 5L X52 steel pipelines under cyclic pressure loading

Transporting hydrogen gas through the existing natural gas pipeline network offers an efficient solution for energy storage and conveyance. Hydrogen generated from excess renewable electricity can be conveyed through the API 5L steel-made pipelines that already exist. In recent years, there has been a growing demand for the transportation of hydrogen through existing gas pipelines. Therefore, numerical and experimental tests are required to verify and ensure the mechanical integrity of the API 5L steel pipelines that will be used for pressurized hydrogen transportation. Internal pressure loading is likely to accelerate hydrogen diffusion through the internal pipe wall and consequently accentuate the hydrogen embrittlement of steel pipelines. Furthermore, pre-cracked pipelines are susceptible to quick failure mainly under a time-dependent cyclic pressure loading that drives fatigue crack propagation. Meanwhile, after several loading cycles, the initial cracks will propagate to a critical size. At this point, the remaining service life of the pipeline can be estimated, and inspection intervals can be determined. This paper focuses on the hydrogen embrittlement of API 5L steel-made pipeline under cyclic pressure loading. Pressurized hydrogen gas is transported through a network of pipelines where demands at consumption nodes vary periodically. The resulting pressure profile over time is considered a cyclic loading on the internal wall of a pre-cracked pipeline made of API 5L steel-grade material. Numerical modeling has allowed the prediction of fatigue crack evolution and estimation of the remaining service life of the pipeline. The developed methodology presented in this paper is based on the ASME B31.12 standard, which outlines the guidelines for hydrogen pipelines with reference to the ASME BPVC Section VIII, Division 3, Article KD-10.

Automatic response framework for large complex natural gas pipeline operation optimization based on data-mechanism hybrid-driven

In recent years, the scale of gas transmission networks has been continuously expanding, and the operational conditions are becoming increasingly complex. This poses higher requirements for the centralized control of the pipeline network operation. Relying solely on the experience of scheduling personnel may not comprehensively address the operational issues within the network. There is an urgent need for efficient automatic response methods (ARM) to assist in formulating operation schemes and ensuring the safe and stable operation of the pipeline network. Therefore, this paper proposes an automatic response framework of large complex natural gas pipeline operation optimization based on data-mechanism coupling to provide operation schemes that ensure safety, stability, and economic benefits. First, two ARM is proposed, namely the Data-Based ARM using operation scheme database, and the Opti-Model ARM based on optimization modeling. Subsequently, the rapid response features of Data-Based ARM and the optimal response characteristics of Opti-Model ARM are combined to establish the Integrated ARM. Finally, these three ARMs are compared and analyzed through a regional natural gas pipeline network in China. The result indicates that the Data-Based ARM can quickly produce a variety of matched solutions but cannot ensure economic optimality. Response solutions obtained through Opti-Model ARM reduce the compressor energy costs by 4.6–10.8 % compared to on-site operational schemes, but they take longer in response time. In contrast, the economic attributes of solutions derived from the Integrated ARM are on par with Opti-Model ARM, but with a 58.7 % improvement in response speed. The proposed Integrated ARM can swiftly and accurately offer economically viable operation schemes tailored to the varying needs of pipeline operators, which can help to address the energy demand challenges of the future, fostering sustainable development.

Optimization research on energy consumption and carbon emissions in hydrogen-blended natural gas pipeline networks considering compressor performance - A case study of the west-east gas pipeline (line 1)

The blending of hydrogen into natural gas can utilize existing natural gas pipeline infrastructure to achieve long-distance, large-scale, and cost-effective hydrogen transportation. However, the introduction of hydrogen poses a series of new technical and safety challenges to the operation of natural gas pipelines. Addressing these issues, this paper focuses on minimizing compressor station energy consumption and carbon emissions as objective functions, conducting a comprehensive analysis of station operation modes. Incorporating the characteristics of the model, the soft frost search strategy, the hard frost penetration mechanism, and the positive greedy selection mechanism are introduced to propose the IRIME algorithm. Comparisons are made with well-performing optimization algorithms using classical test functions to evaluate algorithm performance. To further validate the algorithm's accuracy, the West-East Gas Pipeline (Line 1) is considered, comparing the convergence speed and precision of the IRIME algorithm, leading to its selection for solving the model. Furthermore, consider analyzing the impact of different hydrogen blending ratios on the performance curves and operating points of compressors. Results indicate that compared to conditions without hydrogen blending, the compressor outlet temperature and pressure drop increase for hydrogen blending ratios of 5%, 10%, 15%, and 20%; as the hydrogen blending ratio increases, the efficiency of fuel-driven compressors, efficiency of electrically driven compressors, and average efficiency of compressor units decrease; with an increase in hydrogen blending ratio, carbon emissions from fuel-driven compressors and electric-driven compressors both decrease. In conclusion, with an increasing hydrogen blending ratio, total energy consumption increases by 3.14%, 5.69%, 8.68%, and 10.90%, while total carbon emissions decrease by 2.99%, 5.36%, 8.32%, and 10.68%. These findings provide valuable insights for operational guidance in the field.

Performance analysis of coaxial shear static mixer for hydrogen blending into natural gas

Blending a specific proportion of hydrogen into a natural gas (NG) pipeline network is an effective strategy for achieving long-distance, large-scale, and cost-effective hydrogen transport. Static mixers played a crucial role in this process. In this study, a coaxial shear static mixer with ring-shaped structures instead of turbulence elements is proposed. The mixer exhibited favorable mixing performance and low pressure loss. The flow characteristics of NG and hydrogen within the mixer were investigated with computational fluid dynamics (CFD) methods. The effects of the number of cavities, hydrogen pipe diameter, hydrogen blending ratio and pressure on the mixer performances were investigated, taking into account both mixing uniformity and pressure loss. When the number of cavities in the coaxial shear mixer increases to 48, the mixing uniformity reaches 95.43% (SMX is 95%), and the pressure loss is 67.02 Pa (SMX is 500 Pa).

Development of a sectionalizing method for simulation of large-scale complicated natural gas pipeline networks

By 2025, the total mileage of natural gas pipelines in China is expected to reach 163,000 km, placing urgent demands on the simulation technology for increasingly large-scale and more complicated pipeline networks. This paper describes the development of a new sectionalizing method, which is based on optimization strategy, for simulating large-scale and complicated natural gas pipeline networks. Based on analysis of the topological structures, the entire pipeline networks are decomposed into multiple sub-networks according to the connecting nodes between the adjoined pipelines. The sectionalizing method is then implemented by minimizing the residuals of conservation for continuity and momentum at the connecting nodes in isothermal mode. The hydraulic variables in each sub-network are obtained after the hydraulic variables at connecting nodes are updated. The calculation accuracy and efficiency of this sectionalizing method are demonstrated by comparison with a commercial software through three different test cases. It is shown that the maximum relative deviation of pressure of the method developed is within 2.5% of that calculated using the commercial software. In a 5 × 104 km test case with variable spatial step sizes, the computational efficiency is 2.1 to 3.2 times of that of the commercial software. The results of the three case studies suggest that this sectionalizing method is promising and suitable for application to large-scale complicate natural gas network simulation.

Unsupervised gas pipeline network leakage detection method based on improved graph deviation network

Historical data has shown that the natural gas pipeline network, as a critical urban lifeline system, is susceptible to disasters such as earthquakes resulting in leakage. Graph neural network modeling provides frontier rapid detection solutions for pipeline leakage; however, the challenges of collecting gas network anomaly data for training limit the precision and robustness of current model. This research proposes an unsupervised gas leakage detection and localization method based on a contained preprocessing process, with a graph deviation model that combines a structural learning approach with a graph neural network to model the spatial dependence of the sensors based on an attention mechanism, and variational inference models the posterior distributions of the hyper-parameters to optimize the model and improve the model precision. Meanwhile, in the preprocessing stage, the automatic optimization strategy of Northern Goshawk Optimization (NGO) for the best parameters K and ɑ in the Variable Mode Decomposition (VMD) efficiently extracts the valid signals and ensures that the model gives full play to the detection and localization effectiveness. The gas pipeline network dataset constructed by Pipeline Studio was used for comparing the performance of the model in this study with other frontier models. The results demonstrate that the model in this research has competitive detection Precision (93.31%), Recall (70.82%), and F1-score (0.81), and the posterior distribution of the model parameters strengthens the gas leakage localization precision, which provides a comprehensive solution for subsequent decision-making and reduces the hidden hazard of leakage effectively.

Numerical analysis of the effect of hydrogen doping ratio on gas transmission in low-pressure pipeline network

In the context of a global shift towards clean energy, the integration of hydrogen into existing natural gas pipeline networks is essential for facilitating the energy transition. Specifically, low-pressure natural gas pipeline networks are crucial for transporting gas efficiently and with minimal losses from the source to end-users in nearby cities. The physical properties of hydrogen differ significantly from those of natural gas, which implies that introducing hydrogen into the pipeline network will modify operational parameters and impact the safety and efficiency of gas transmission. Therefore, this study concentrates on the efficiency of transporting and scheduling hydrogen-blended natural gas through existing low-pressure direct pipelines. Utilizing the BWRS (Benedict-Webb-Rubin-Starling) equation of state, mathematical models were developed to calculate gas properties and to simulate both the steady and transient states of hydrogen-blended natural gas networks. These models were then validated with TGNET software. This study examines a low-pressure natural gas transmission and distribution network that transports gas directly from a production site in Sichuan to urban areas. It conducts simulations of hydrogen blending and analyzes the impact of various hydrogen blend ratios on the transport and scheduling responses of the network. Research suggests that maintaining the hydrogen blend below 30% ensures the safe operation of low-pressure gas pipelines and prevents the transmission pressure from exceeding 3 MPa. Additionally, under a fixed energy flow output, blending hydrogen intensifies the challenges associated with pressure drops and temperature increases due to high flows in small diameter pipes, and further complicates the management of interruptions resulting from faults. Therefore, it is recommended that the hydrogen blend ratio be maintained at no more than 30%, and that accident handling procedures be established in advance to control pressure variations following a shutdown.

Evaluating hydrogen embrittlement susceptibility of operated natural gas pipeline steel intended for hydrogen service

Green hydrogen produced by renewable energy sources is expected to play an important role as a decarbonized energy carrier. It can be transported cost-effectively over long distances by pipelines. Hydrogen transport through existing natural gas pipeline networks is supposed to be prospective. However, a possible degradation of gas pipeline steels as a result of their long-term operation should be taken into account in assessing the prospects of using the existing gas network for hydrogen transportation safely. In this study, hydrogen embrittlement susceptibility of low-carbon pipeline steel in the as-received state and after long-term operation is investigated. The influence of long-term operation on the microstructure, mechanical properties, and fracture mechanism of steel is assessed, considering the direction of cutting the specimens relative to the pipe axis. The electrolytic hydrogen pre-charging process with different intensities is used to analyze the influence of absorbed hydrogen on the mechanical behaviour of steel by tensile tests of uncharged and hydrogen-charged specimens. The as-delivered steel is not prone to hydrogen embrittlement after moderate hydrogen charging, while the operated one is sensitive to it. Metallographic and fractographic analyses revealed a crucial role of non-metallic inclusions in the hydrogen embrittlement of steel, which depended on its technical state and hydrogen charging conditions. Moderate hydrogen charging led to intergranular embrittlement of steel, while intensive − to transgranular embrittlement, indicating different mechanisms of transport of hydrogen absorbed by the metal.

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.

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.

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.

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.

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.

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.

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.