Natural Gas Pipeline Network Research Articles

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

Feature extraction and pattern recognition of gas pipeline flow noise signals in a strong noisy background.

The purpose of this study is to put forward a feature extraction and pattern recognition method for the flow noise signal of natural gas pipelines in view of the complex situation brought by the rapid development and expansion of urban natural gas infrastructure in China, especially in the case that there are active and abandoned pipelines, metal and nonmetal pipelines, and natural gas, water and power pipelines coexist in the underground of the city. Because the underground situation is unknown, gas leakage incidents caused by natural gas pipeline rupture occur from time to time, posing a threat to personal safety. Therefore, the motivation of this study is to provide a feasible method to accelerate the aging, renewal and transformation of urban natural gas pipelines to ensure the safe operation of urban natural gas pipeline network and promote the high-quality development of urban economy. Through the combination of experimental test and numerical simulation, this study establishes a database of urban natural gas pipeline flow noise signals, and uses principal component analysis (PCA) to extract the characteristics of flow noise signals, and develops a mathematical model for feature extraction. Then, a classification and recognition model based on backpropagation neural network (BPNN) is constructed, which realizes the detection and recognition of convective noise signals. The research results show that the theoretical method based on acoustic feature analysis provides guidance for the orderly and safe construction of urban natural gas pipeline network and ensures its safe operation. The research conclusion shows that through the simulation analysis of 75 groups of gas pipeline flow noise under different working conditions. Combined with the experimental verification of ground flow noise signals, the feature extraction and pattern recognition method proposed in this study has a recognition accuracy of up to 97% under strong noise background, which confirms the accuracy of numerical simulation and provides theoretical basis and technical support for the detection and recognition of urban gas pipeline flow noise.

Unit Commitment Considering Long-term Supply Risk of Natural Gas Pipeline Network

As the coupling degree of the natural gas pipeline network (NGPN) and the power system increase, unreliable gas supply risk related to random failures in NGPN has threatened the operation security of the power system. However, present studies seldom discuss the effect of natural gas supply reliability on power system operation. In this manner, a stochastic unit commitment model is presented with the consideration of long-term gas supply risk in NGPN. Firstly, with the combination of the Monte Carlo simulation (MCS) technique and the maximum-flow algorithm, the failure scenario set corresponding to gas supply risk can be obtained. Then, a two-stage model for unit commitment is established considering gas supply uncertainty based on the stochastic optimization model. Finally, case studies have shown that the power operation reliability has been improved with the increased reliability indices.

Permeability measurement theory in case of natural gas and natural gas-hydrogen mixture

Green hydrogen, using renewable electricity that breaks down water molecules into hydrogen and oxygen, holds great promise for meeting global energy demand while contributing to climate policy goals. Interest in green hydrogen production technologies has increased considerably. This is because the potential uses of hydrogen cover many sectors, including power generation, manufacturing processes in steel and cement production, fuel cells for electric vehicles, and power grid stabilization. One possible use of green hydrogen is to blend it with natural gas and deliver it to end-users using existing natural gas pipeline storage and networks, thereby increasing performance and reducing emissions. In the case of underground storage of a hydrogen natural gas mixture, it is important to assess its impact on the reservoir beforehand, which rock permeability studies can do. This article deals with the theory of rock permeability testing for natural gas and natural gas-hydrogen mixtures.

Risk modelling of hydrogen‐enriched natural gas on pipelines and gas‐electric coupled systems

AbstractThe use of natural gas pipeline networks to transmit hydrogen energy is an important form of hydrogen energy utilisation. The coupling of hydrogen‐enriched natural gas pipeline network and power grid involves the energy conversion of electricity‐hydrogen‐electricity, so the assessment is crucial because the system is complex, and the hazards to the system can be identified. This paper proposes a risk assessment method for gas‐electric coupling of hydrogen‐enriched natural gas pipeline networks and a three‐stage risk assessment model to assess the life cycle risk of natural gas pipelines; a material energy‐based risk transfer model considering gas‐electric coupling is proposed to describe the risk transfer process of hydrogen‐enriched natural gas between the gas network and the grid. By comparing and analysing the risk of natural gas blending ratio to the pipeline and the risk of pipeline pressure to the pipeline, the validity of the model is verified, which provides safety support for the connection of the natural gas pipeline system to the grid and ensures the efficient use of hydrogen energy.

Capacity allocation method of hydrogen-blending natural gas pipeline network based on bilevel optimization

Blending hydrogen into the natural gas pipeline network is an efficient approach for storing and delivering renewable energy. However, the variation in gas quality and the diversity of delivery paths can lead to difficulties in pipeline operation management. In this paper, we propose a bilevel optimization model to understand the influence of hydrogen blending on pipeline capacity allocation and gas transmission tariffs. The lower-level model optimizes the best capacity booking of each shipper, and the upper-level model optimizes the best capacity allocation of the transmission system operator. Detailed transmission paths and gas calorific values at each delivery point are taken into account to calculate the actual gas transmission tariffs. The proposed model is solved by the alternating direction multiplier method and validated by a real-world pipeline network. Results show that: (1) the proposed method can facilitate shippers to meet the energy demand under different hydrogen blending cases, (2) a fair-cost sharing is achieved among all parties, (3) when the hydrogen blending ratio reaches 5 %, the pipeline capacity can be optimally utilized to achieve the maximum pipeline capacity allocation. This approach can guide efficient gas pipeline capacity allocation and facilitate the establishment of trading platforms.

New method for the transient simulation of natural gas pipeline networks based on the fracture-dimension-reduction algorithm

The transient simulation technology of natural gas pipeline networks plays an increasingly prominent role in the scheduling management of natural gas pipeline network system. The increasingly large and complex natural gas pipeline network requires more strictly on the calculation efficiency of transient simulation. To this end, this paper proposes a new method for the transient simulation of natural gas pipeline networks based on fracture-dimension-reduction algorithm. Firstly, a pipeline network model is abstracted into a station model, inter-station pipeline network model and connection node model. Secondly, the pressure at the connection node connecting the station and the inter-station pipeline network is used as the basic variable to solve the general solution of the flow rate at the connection node, reconstruct the simulation model of the inter-station pipeline network, and reduce the equation set dimension of the inter-station pipeline network model. Thirdly, the transient simulation model of the natural gas pipeline network system is constructed based on the reconstructed simulation model of the inter-station pipeline network. Finally, the calculation accuracy and efficiency of the proposed algorithm are compared and analyzed for the two working conditions of slow change of compressor speed and rapid shutdown of the compressor. And the following research results are obtained. First, the fracture-dimension-reduction algorithm has a high calculation accuracy, and the relative error of compressor outlet pressure and user pressure is less than 0.1%. Second, the calculation efficiency of the new fracture-dimension-reduction algorithm is high, and compared with the nonlinear equations solving method, the speed-up ratios under the two conditions are high up to 17.3 and 12.2 respectively. Third, the speed-up ratio of the fracture-dimension-reduction algorithm is linearly related to the equation set dimension of the transient simulation model of the pipeline network system. The larger the equation set dimension, the higher the speed-up ratio, which means the more complex the pipeline network model, the more remarkable the calculation speed-up effect. In conclusion, this new method improves the calculation speed while keeping the calculation accuracy, which is of great theoretical value and reference significance for improving the calculation efficiency of the transient simulation of complex natural gas pipeline network systems.

Enhanced Method for Emergency Scheduling of Natural Gas Pipeline Networks Based on Heuristic Optimization

Safety and disturbance issues in system engineering have garnered substantial attention. This study focuses on the analysis of the distinct characteristics of emergency dispatch problems in Natural Gas Pipeline Networks (NGPS). Graph theory serves as a tool to transform the NGPS topology and establish an optimization model for NGPS emergency dispatch. The model also integrates user weights, satisfaction, and reduction factors into the user modeling approach. Its objective is to maximize overall system satisfaction while considering factors such as demand-side requirements and operational constraints. To solve this optimization model, the Particle Swarm Optimization (PSO) method is employed. An in-depth exploration of four unique disturbance scenarios provides solid evidence of the effectiveness and practicality of the PSO method. Compared to other methods, the PSO method consistently boosts overall user satisfaction and aligns more fluidly with the real-time demands of emergency scheduling, regardless of reduced supply capacity, complete supply interruptions, sudden surges in user demand, or pipeline connection failures. The developed emergency scheduling optimization method presents two key advantages. Firstly, it proficiently mitigates potential losses stemming from decreased supply capacity at local or regional levels. By adeptly adjusting natural gas supply strategies, it minimizes economic and production losses while ensuring a steady supply to critical users. Secondly, the method is superior at swiftly reducing the affected area and managing the increased demand for natural gas, thus maintaining NGPS stability. This research underscores the importance of considering user characteristics and demands during emergencies and demonstrates the effectiveness of employing the PSO method to navigate emergency scheduling challenges. By strengthening the resilience of the pipeline network and ensuring a sustainable natural gas supply, this study constitutes a significant contribution to energy security, economic development, and the promotion of clean energy utilization, ultimately propelling the achievement of sustainable development goals.

Operational optimization of large-scale thermal constrained natural gas pipeline networks: A novel iterative decomposition approach

Operation optimization is an effective but quite challenging way to reduce the energy consumption of large-scale pipeline networks. The thermal-hydraulic performance of natural gas, combined with the detailed constraints of compressors, creates many nonlinear constraints that make optimization models difficult to solve. Previous studies aimed at optimizing large-scale natural gas pipeline networks have often simplified multiple compressors into a single compressor station and ignored the operating envelopes of centrifugal compressors. This oversimplification can lead to solutions that deviate from reality. To address this issue, this paper presents an optimization model that is more practical to real-world scenarios. The model incorporates thermal-hydraulic constraints, reverse processes, and detailed constraints of compressors, including the operating envelopes of centrifugal compressors. To solve the Mixed Integer Nonlinear Programming (MINLP) model, an iterative four-stage decomposition algorithm is proposed. The proposed model and algorithm are verified by three large-scale natural gas pipeline networks, demonstrating advantages in solving time and scalability. Specifically, the solving time only requires 9.9 s for a pipeline network containing 406 nodes, even when considering the operating envelopes of centrifugal compressors. These characteristics of the model and algorithm enable them to be portable for similar problems and future research.

Large-scale transient simulation for consequence analysis of hydrogen-doped natural gas leakage and explosion accidents

Transporting blended hydrogen natural gas through existing natural gas pipeline networks is an important strategy for meeting the growing demand for hydrogen energy. However, gas leakage poses a serious safety concern. This study conducts a large-scale simulation of gas leakage and explosion accidents in a hydrogen-doped natural gas station and aims to evaluate the impact of pipeline pressure and leakage direction on the accident consequences. Simulation results indicated that the high pipeline pressure led to more accumulated flammable gas, which caused severer explosion disasters. Within the 100s simulation period, the cumulative volume of the flammable gas cloud reached 2329.80 m3 under 4 MPa pipeline pressure, and the peak explosion overpressure increased by 69.64% compared with the 1 MPa case. Leakage directions also significantly affect the evolution of accidents. Suppose the leakage direction is towards living areas, flammable gas is more likely to accumulate in confined spaces up to 2363.20 m3. The gas explosion will severely damage the building structure with a 17 kPa explosion overpressure and 7 kPa shock wave intensity. Interaction with wind and the disturbance of obstacles also contributed to the flammable gas cloud accumulation, which increased peak values of explosive overpressure.

Investigation on mixing characteristics of hydrogen and natural gas fuel based on SMX static mixer

Hydrogen, as a carbon-free fuel, is significantly for replacing fossil fuels and reaching the ultimate goal of carbon neutrality, and is commonly expected to play a major role in future energy supply. Blending hydrogen into natural gas pipeline networks for end-user consumption as a means of delivering pure hydrogen to the market which not only improves the utilization rate of hydrogen energy, but also reduces the cost of hydrogen transportation. A three-dimensional model of the blending the natural gas and hydrogen with SMX mixing elements is developed to obtain homogeneous mixed gas injected into the natural gas pipeline network. The Reynolds-averaged Navier-Stokes (RANS) method is employed to investigate the flow physics in the static mixer, which was verified by experiments. The numerical results are in good agreement with the experimental data. Based on the static mixer model, the coupling relationship between mixing performance and the crucial parameters including the number of mixing elements, operating conditions and hydrogen blending volume fraction is analyzed in detail, and a compromise design scheme is proposed under the studied conditions to improve the mixing performance of natural gas and hydrogen.

Supply-demand balance of natural gas pipeline network integrating hydraulic and thermal characteristics, energy conservation and carbon reduction

Under the background of “One national network”, the balance between the natural gas supply side and the demand side is prominent. This paper proposes a supply-demand balance method of natural gas pipeline network coupled with the hydraulic and thermal characteristics, and decides the transportation scheme through flow rate allocation. This paper designs a two-stage relaxation optimization algorithm, coupled the thermal process into the hydraulic calculation to improve the hydraulic calculation accuracy, making the natural gas transportation scheme more applicable to engineering. The result shows the feasibility of transportation decision-making and the accuracy of hydro thermal calculation of the proposed model through a real case. The relative error of thermal calculation and TGNET is below 2%, and the hydraulic calculation error of coupled thermal can also be within 10%. After optimization, the carbon emissions decrease from 418,100 tons to 260,000 tons, reducing by about 37.81%. This study also analyzes the impact of hydraulic calculation on carbon emissions calculation, and further illustrates the necessity of coupled thermal characteristics in transportation scheme. This study can provide decision support for the transportation operation and help the natural gas pipeline network to meet the dual carbon requirements and achieve sustainable development.

Computational fluid dynamic analysis of hydrogen‐injected natural gas for mixing and transportation behaviors in pipeline structures

AbstractThe transportation of hydrogen is a weak link in the large‐scale development of the hydrogen energy industry. Injecting hydrogen into the natural gas pipeline network for transportation is an efficient way to achieve the large‐scale, long‐distance, and low‐cost transportation of hydrogen. Hydrogen can lead to hydrogen embrittlement in natural gas pipelines and cause safety incidents if hydrogen and natural gas are not mixed uniformly. Therefore, it is necessary to study the blending process and blending uniformity of hydrogen and natural gas. In this study, a three‐dimensional model of the hydrogen‐injected natural gas pipeline was constructed. The effects of hydrogen injection inlet and turbulator configuration on the mixing process of hydrogen and natural gas were investigated using a computational fluid dynamics approach. The results show that increasing the number of hydrogen injection inlets shortens the distance L98% of uniform mixing of hydrogen and natural gas. Increasing the radial distance r from the initial hydrogen mixing positions to the center of the pipeline will shorten the distance for uniform gas mixing in the pipeline. The addition of turbulator configurations in the pipeline significantly reduces the distance to uniform gas mixing. Changing the distance Lturb from the turbulator to the initial mixing position further shortens the distance between hydrogen and natural gas mixing uniformly. The results of this study provide a reference for the structural design of the hydrogen–natural gas mixing pipeline and the gas distribution state during the mixing process.

A methodology to evaluate gas supply reliability of natural gas pipeline network considering the effects of natural gas resources

In this study, a methodology to evaluate gas supply reliability of the natural gas pipeline network is proposed, and the uncertainty of the gas supply capacity of the natural gas resources is considered. The methodology is composed of four parts. Firstly, the gas supply capacity calculation model of natural gas resources considering its stochastic and time-dependent characteristics is described. Secondly, the gas demand prediction model is developed based on the demand-side analysis. Thirdly, the gas supply calculation model of natural gas pipeline network is proposed considering units failure and hydraulic characteristics. Finally, according to the established gas supply reliability index system, the gas supply reliability indicators are calculated based on N (N is a large number) times of Monte Carlo simulation. Furthermore, a real natural gas pipeline network located in China is applied to confirm the feasibility of the methodology, and the gas supply reliability is evaluated based on quantity and time dimensions, and the results are reduced by about 3.9% and 4.1% compared with the results calculated by the method which ignored the uncertainty of resources. At last, the significance of the natural gas resources in the gas supply reliability is investigated by the sensitivity analysis.

A graph neural network (GNN) method for assigning gas calorific values to natural gas pipeline networks

Calorific value metering offers unique advantages in the natural gas industry. Based on a graph neural network (GNN), this study proposes a method for metering the gas calorific value in natural gas transportation. Graph theory is introduced to consider the effects of physical topology and node properties in natural gas pipeline networks. Inductive inference is performed in conjunction with dynamic graph training mechanisms to improve the accuracy of the prediction models and simulate the corresponding model responses when topological relationships or node properties change. The results show that graph deep learning can accurately capture the spatio-temporal characteristics of mixed gas transport processes in a pipeline network. Compared with a normal deep-learning algorithm, the performance improvement of the proposed GNN algorithm can be as high as 62% in R2 and 50% in mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean squared error (RMSE) metrics, depending on the different scenarios and noises. This model can be applied to various scenarios, such as pipeline extensions and hydrogen blending. Based on all the tests conducted, the generalization ability of the algorithm is better than that of the others, with the accuracies of most cases satisfying the requirements of metering stations.

A multi-objective model for optimizing hydrogen injected-high pressure natural gas pipeline networks

The paper develops a statistical model for optimizing the Hydrogen-injected Natural gas (H-NG) high-pressure pipeline network. Gas hydrodynamic principles are utilized to construct the pipeline and compressor station model. The model developed is implemented on a pipeline grid that is supposed to carry Hydrogen as an energy carrier in a natural gas-carrying pipeline. The paper aims to optimize different objectives using ant colony optimization (ACO). The first objective includes a single objective optimization problem that evaluates the maximum permissible hydrogen amounts blended with natural gas (NG) for a set of pipeline constraints. We also evaluated the variations in operational variables on injecting Hydrogen into the natural gas pipeline networks at varying fractions. The study further develops a multi-objective optimization model that includes bi-objective and tri-objective problems and is optimized using ACO. Traditional studies have focused on single-objective optimization with minimal bi-objective issues. In addition, none of the earlier research has shown the effect of introducing Hydrogen to the NG network using tri-objective function evaluations. The bi-objective and tri-objective functions help evaluate the effect of injecting Hydrogen on different operational parameters. The study further attempts to fill the gap by detailing the modelling equations implemented through a bi-objective and tri-objective function for the H-NG pipeline network and optimized through ACO. Pareto fronts that show the tradeoff between the different objectives for the multi-objective problem have been generated. The primary objective of the bi-objective and tri-objective optimization problems is maximizing hydrogen mole percent in natural gas. The other objective chosen is minimizing compressor fuel consumption and maximizing delivery pressure, throughput, and power delivered at the delivery station. The findings will serve as a roadmap for pipeline operators interested in repurposing natural gas pipeline networks to transport hydrogen and natural gas blend (H-NG) and seeking to reduce carbon intensity per unit of energy-delivered fuel.

Flame Acceleration in Stoichiometric CH4/H2/air Mixtures with Different Hydrogen Blend Ratios in an Obstructed Channel

ABSTRACT Adding a certain percentage of hydrogen into the natural gas pipeline network is regarded as an efficient way to store and transport hydrogen. CH4-H2 binary fuel is also considered to be an important means of hydrogen utilization. In this paper, flame acceleration (FA) in stoichiometric CH4/H2/air mixtures with various hydrogen blend ratios (i.e., Hbr = 0%, 20%, 50%, 80%, and 100%) was studied experimentally and numerically. In the experiments, high-speed photography was used to record the FA process. In the numerical simulations, the two-dimensional, fully-compressible, reactive Navier-Stokes equations were solved using a high-order algorithm on a dynamically adapting mesh. The chemical reaction and diffusive transport of the mixtures were described by a calibrated chemical-diffusive model. The numerical predictions agree reasonably with the experimental measurements. The results show that a larger hydrogen blend ratio leads to a faster FA. The difference in FA due to hydrogen blending mainly depends on the property change of the fuel mixtures, the increase of flame surface area and the interactions between flame and pressure waves, corresponding to three different stages. In addition, the heat loss to the channel walls and obstacle surfaces has an impact on the FA process, especially in the mixtures with low hydrogen blend ratios (i.e., Hbr ≤ 20%). This is related to the weakening of interactions between pressure waves and flame under isothermal boundary condition.

Energy Mutual Networking Establishment Method Based on Hydrogen Production from Water Electrolysis Technology

The new power system has the characteristics of a high proportion of renewable energy power generation and multi-field interconnection. In order to reduce the carbon emission level of the new power system, it is necessary to improve the flexible response capability of the system in the form of different energy carriers. Analyze the feasibility of two hydrogen energy utilization technologies such as water electrolysis for hydrogen production and carbon dioxide hydromethanation, and propose to use hydrogen as an energy carrier to form an energy mutual networking, through the transformation between renewable energy-electricity-hydrogen energy-electricity-chemical energy, the flexible response capability of the new power system can be improved, and the carbon emission level of the new power system can be reduced. The method of building the energy mutual networking on the basis of water electrolysis for hydrogen production technology is as follows: first, use renewable energy for water electrolysis for hydrogen production, and use hydrogen to supplement power generation through fuel cells when the power output is insufficient; then, capture carbon dioxide generated by thermal power generation, use hydrogen to reduce carbon dioxide to produce methane and finally, hydrogen and methane are sent to the natural gas pipeline network for reuse. At the same time, an energy storage system with an appropriate capacity is installed in the new power system to stabilize the volatility of wind-solar hybrid power generation, and the use of wind-solar hybrid energy storage power generation technology can further improve the hydrogen production efficiency of renewable energy.

Multiobjective Gas Distribution Optimization of Natural Gas Pipeline Network Considering User Satisfaction under Shortage Conditions

The management of natural gas user daily designation is taken as the background, the characteristics of users are considered, the distribution mode is integrated, and a multiobjective distribution optimization model of natural gas pipeline network under the insufficient condition is constructed. The decision variable is the actual gas distribution volume of users, aiming to minimize the energy consumption of the compressor station and maximize the user satisfaction under multiple physical constraints. Comparing the solution schemes, when the user satisfaction is the same, scheme 4 solved by the optimization method reduces the compressor energy consumption by 8.6% compared with scheme 1 solved by the manual adjustment method. The three optimization solutions are compared and contrasted, the differences in the operation of the pipeline network are analyzed in different optimization solutions, and the changes of the compressor operating parameters with the increase of user satisfaction are expounded. By analyzing the influence of flow distribution among different types of natural gas users on user satisfaction, it is clarified that the two goals of natural gas user satisfaction and pipeline network operation energy consumption are mutually restrictive.

Research on the dynamic characteristics of natural gas pipeline network with hydrogen injection considering line-pack influence

Hydrogen energy has the advantages of renewable, clean and high energy density, which is considered as the most potential secondary energy in the 21st century. But transportation is a major constraint on development of hydrogen. A possible solution is to inject hydrogen into natural gas network for transport. Due to the obvious differences in the properties of natural gas and hydrogen, it is necessary to establish natural gas pipeline model with hydrogen injection to explore the influence of hydrogen on pipeline. The line-pack of natural gas network can improve the flexibility of the system to deal with uncertainties, and the line-pack has a significant impact on the dynamic characteristics of the natural gas network under the change of external conditions. When hydrogen is injected into the natural gas network, the line-pack is affected by both pressure and hydrogen mixture ratio, and the line-pack influence on the dynamic characteristics of the network is more complicated. In this paper, a natural pipe network with hydrogen injection is established based on the finite difference method, and simulation is carried out under different situations to explore the influence of different line-pack on the dynamic characteristics of the natural gas network. The results show that the response speed of hydrogen mixture ratio is faster under the condition of low line-pack, which is conducive to reducing the risk of hydrogen embrittlement when the hydrogen mixture ratio surges for a short time. However, the pressure loss caused by the increase of flow can be reduced in the high line-pack state.