Natural Gas Transportation Research Articles

Green villages by Wind + Solar + Hydrogen

This paper describes 5 steps on the move to cost-effective green villages, powered mainly by Solar, Wind and Hydrogen. In Britain, there are around 6000 villages comprising almost half the total population. These village dwellers wish to reduce their expensive energy bills, achievable by profitably going green with local Wind and Solar generation of electricity plus Hydrogen energy storage. The first step is to measure the total energy usage in the village. This defines the size of the required renewable private wire energy installations. The second step calculates savings on grid bills for electricity, natural gas and petroleum transport products, to ensure rapid payback for the renewables to be installed. A third concern is the planning permission for Wind/Solar installations that may take months to approve. Perhaps the most important requirement is to attract investment in the fourth step. Finally, the fifth step is to procure and commission the equipment needed in the village to prove that local energy can beat the present centralized grid energy systems, using Hydrogen as the vital energy storage molecule to fill gaps in Wind/Solar supply.

A Comparative Analysis of Collaborative Models between Government and Business Entity in National Asset Management: Case Study of the Cisem-1 Gas Transmission Pipelines

Developing infrastructure for natural gas transportation requires substantial investment. The high standards of safety in its equipment material, workmanship, design, and construction methods are the reason for this. Consequently, investment in natural gas infrastructure entails significant risk when supply and demand situations are variable and immature. The Cirebon-Semarang Gas Transmission Pipeline project, awarded to Rekind in 2006, has had delays from the beginning. Following Rekind’s resignation, the Government continues the project to regard the Cisem Pipeline as strategic, capable of fostering economic and industrial growth in Java, especially in Central Java. The government utilized the APBN to assume control of the Cisem project, initiating the first phase, designated as Cisem-1, in 2022. Following the completion of the Cisem-1 project in 2023, Lemigas, as the designated asset manager and user, is required to seek a partnership with a business entity that possesses the requisite capabilities and adheres to regulations governing gas transportation operations. This study proposes alternative partnership models between the government, represented by Lemigas, and the business entity, PT Pertamina Gas (Pertagas). This study evaluates and analyzes the most suitable partnership model between Lemigas and Pertagas, taking into account operational costs to maintain affordable gas prices for customers, as well as processing time for partner selection and operatorship alignment with project timelines to ensure the MEMR that the asset is utilized and not abandoned. The KSP (Kerja Sama Pemanfaatan) of BMN (Barang Milik Negara) scheme has been identified as the most suitable option.

Simulation study on hydrogen concentration distribution in hydrogen blended natural gas transportation pipeline.

Hydrogen is a clean energy source, and blending it with natural gas in existing pipeline networks is a key transition solution for transportation cost reduction. However, during the transportation process, a non-uniform distribution of hydrogen concentration occurs in the pipeline due to gravity. Therefore, it is necessary to study the hydrogen concentration distribution law of hydrogen-blended natural gas in pipelines. The undulation and ball valve pipelines, which are common in transport pipelines, were constructed in this study. The effects of the undulation angle, height, pipeline diameter, ball valve opening, and temperature on the distribution of the hydrogen concentration were investigated using computational fluid dynamic (CFD) methods. The results indicated that the hydrogen concentration gradient changed gently with the larger diameter of the undulating pipeline, minimizing hydrogen accumulation. Higher undulation angle and smaller height differences reduces the hydrogen accumulation risk. Increasing vertical height difference of the pipeline from 5 m to 15 m increased the hydrogen volume fraction gradient by1.3 times. In the ball valve pipeline, the velocity fluctuation decreased as the ball valve opening increased. However, the hydrogen accumulation phenomenon was obvious. The opening increased from 25% to 100% and the hydrogen volume fraction gradient increased more than two times. Selecting delivery conditions with low hydrogen blending ratios, high temperatures, low pressures, and high flow rates reduces the occurrence of hydrogen buildup in the pipeline.

Locational marginal pricing of energy in pipeline transport of natural gas and hydrogen with carbon offset incentives

We propose an optimization formulation for locational pricing of energy transported through a pipeline network that carries mixtures of natural gas and hydrogen from distributed sources to consumers. The objective includes the economic value provided by the pipeline to consumers of energy and suppliers of natural gas and green hydrogen, as well as incentives to lower carbon emissions by consuming the latter instead of the former. The optimization is subject to the physics of gas flow and mixing in the pipeline network as well as engineering limits. In addition to formulating this mathematical program, we synthesize the Lagrangian and derive analytical expressions for the dual variables. We propose that the dual solution can be used to derive locational marginal prices of natural gas, hydrogen, and energy, as well as the decarbonization premium paid by consumers that receive hydrogen. We derive several properties of solutions obtained using the proposed market mechanism, and demonstrate them using case studies for standard 8-node and 40-node pipeline test networks. Finally, we show that optimization-based analysis of the type proposed here is critical for making sound decisions about economic policy and infrastructure expansion for blending green hydrogen into existing natural gas pipelines.

Examination of a Surge Suppression System Designed for a Centrifugal Compressor System

Centrifugal compressors are used in many areas of industry, for example from natural gas transportation to superchargers of internal combustion engines and compressor stages of aircraft engines to the air compression equipment of the rapidly expanding fuel cell powered systems. With regards to each field of usage of compressors, reliable operation is an important criteria for the operation of the compressor, in addition for ensuring a continuous and adequate medium supply. This process is easier to implement if the equipment is used in terrestrial applications, where these engines can be operated in closely stationary conditions, because there isn’t any sudden change in environmental parameters, so these engines could be well optimized by their geometrical design for reaching its maximum efficiency. In vehicle industry, but especially in the case of aerial applications, the task is much more complicated, because the operation of the compressor is determined by the current operating states of the engine, but here at least the conditions of the air supply are almost the same. In the case of aircraft, the operation of the compressor is determined not only by the current operating state of the gas turbine engine, but also by the attitude of the aircraft. For this reason it is necessary to investigate the unstable operating conditions of centrifugal compressors and to develop equipment which is suitable for eliminating these affects.

Study for Hydrogen Migration Characteristics in the Elbow of a Hydrogen-Doped Natural Gas Pipeline under Normal Transport and Shutdown Conditions.

During the transportation of hydrogen-doped natural gas (HCNG), there is a risk of uneven distribution of hydrogen at the elbow, causing hydrogen damage to the pipeline. Therefore, based on the basic principles of computational fluid dynamics, this paper uses a hybrid model to describe the flow process of HCNG in an elbow. The results show that under normal transportation, the hydrogen volume fraction varies within 0.2% with the influence of pressure, flow velocity, temperature, hydrogen volume fraction, and undulating angle, and the uneven distribution of hydrogen in the elbow can be ignored. However, in the shutdown state, the hydrogen slip rate gradually slows down, the hydrogen volume fraction is distributed in a horizontal concentration gradient along the vertical direction, and it gradually accumulates at the height of the undulating tube. The difference in hydrogen volume fraction reaches 50%, and the stratification phenomenon is obvious.

Stable heterometallic metal-organic frameworks and pellet composites for low-temperature natural gas storage

Liquefied natural gas coupled with adsorbed natural gas charging (LNG-ANG) offers an efficient solution for recycling boil-off gas, providing a promising strategy for the competent storage and transportation of natural gas. The key challenge in LNG-ANG coupling systems is identifying adsorbents that exhibit superior methane adsorption performance and excellent stability under cryogenic conditions (∼159 K). In this work, we systematically investigated the methane adsorption performance of a stable metal–organic framework, PCN-250-Fe2Ni, under LNG-ANG related conditions. The results demonstrated that PCN-250-Fe2Ni exhibited a high methane capacity of 286 cm3 (standard temperature and pressure, STP) cm−3 (0.227 g g−1) at 6 bar/159 K. Furthermore, the pellet composite of PCN-250-Fe2Ni and polyvinyl butyral also displayed a high methane adsorption capacity with excellent cycling stability. Combined with grand canonical Monte Carlo simulations, our findings revealed that the cage-type pores serve as initial methane adsorption sites, followed by the channel-type pores, both of which contribute to the framework’s high low-temperature methane storage performance at saturation.

A rapid method for composition tracking in hydrogen-blended pipeline using Fourier neural operator

Blending hydrogen into natural gas for transportation is a crucial approach for achieving the widespread utilization of hydrogen. Tracking the concentration of the hydrogen within the pipeline is important for monitoring gas quality and managing pipeline operations. This study develops a rapid computational model to predict the hydrogen and natural gas concentrations within the pipeline during transportation based on the Fourier Neural Operator (FNO), an operator neural network capable of learning the differential operator in the partial differential equation. In the proposed model, the numerical method is employed to generate datasets, with the spline interpolation used to enhance data smoothness. The initial and boundary conditions are taken as the inputs to accommodate varying transportation scenarios. Comparison results indicate that the proposed model can notably reduce the time needed to predict the hydrogen and natural gas concentrations while maintaining prediction accuracy. The accuracy of the proposed model is validated by comparing its calculated results with the analytical solution and the concentrations of hydrogen and natural gas within the pipeline under two transportation scenarios, with relative errors of 0.49%, 0.31%, and 0.45%, respectively. Notably, the trained model demonstrates strong grid invariance, a type of model generalization. Trained on data generated from a coarse grid of 101 × 41 spatial-temporal resolution, the proposed model can accurately predict results on a fine grid of 401 × 81 spatial-temporal resolution with a relative error of only 0.38%. Regarding the prediction efficiency, the proposed model achieves an average 17.7-fold speedup compared to the numerical method. The positive results indicate that the proposed model can serve as a rapid and accurate solver for the composition transport equation.

CONCESSÃO DO SERVIÇO DE GÁS CANALIZADO: ASPECTOS JURÍDICOS, REGULATÓRIOS E ECONÔMICOS

The concession of natural gas services in Brazil is regulated by the Federal Constitution, the Concessions Law (Law No. 8,987/1995) and the Gas Law (Law No. 14,134/2021), which regulates the transportation and commercialization of natural gas. With the approval of the New Gas Law (Law No. 14,134/2021), the sector underwent significant changes, aiming to promote competition and attract new private investments. The legislation seeks to guarantee the economic-financial balance of contracts, free access to infrastructure and reasonable tariffs. The gas distribution service is the responsibility of the States, and supervision is carried out by regulatory agencies. Recent jurisprudence from the Superior Court of Justice (STJ) has reaffirmed the need for efficiency and continuity in service, in addition to ensuring respect for consumer rights and balance between concessionaires and the granting authority. The evolution of the gas regulatory framework is an important step towards the country’s sustainable and energy development.

A novel optimization framework for natural gas transportation pipeline networks based on deep reinforcement learning

Natural gas is an emerging and reliable energy source in transition to a low-carbon economy. The natural gas transportation pipeline network systems are crucial when transporting natural gas from the production endpoints to processing or consuming endpoints. Optimizing the operational efficiency of compressor stations within pipeline networks is an effective way to reduce energy consumption and carbon emissions during transportation. This paper proposes an optimization framework for natural gas transportation pipeline networks based on deep reinforcement learning (DRL). The mathematical simulation model is derived from mass balance, hydrodynamics principles of gas flow, and compressor characteristics. The optimization control problem in steady state is formulated into a one-step Markov decision process (MDP) and solved by DRL. The decision variables are selected as the discharge ratio of each compressor. By the comprehensive comparison with dynamic programming (DP) and genetic algorithm (GA) in three typical element topologies (a linear topology with gun-barrel structure, a linear topology with branch structure, and a tree topology), the proposed method can obtain 4.60% lower power consumption than GA, and the time consumption is reduced by 97.5% compared with DP. The proposed framework could be further utilized for future large-scale network optimization practices.

An equivalent average shear stress yield criterion based on Simpson's numerical integration rule and its application in burst pressure analysis of thin-walled pipelines

Pipelines are a crucial transportation infrastructure for the long-distance transport of natural gas, oil, and other hydrocarbons, typically conducted through thin-walled pipes (D/t≥20). Accurate prediction of the burst pressure of thin-walled pipelines is essential for their safe and reliable operation. To enhance the prediction accuracy of the burst pressure for defect-free, straight, thin-walled pipes, a new numerical integration yield criterion was proposed between the Tresca and Mises criteria, using the mean value of Simpson's numerical integration (MSI) as the equivalent shear stress. A new burst pressure prediction formula was then constructed using the MSI yield criterion. The burst pressure predictions based on different yield criteria were compared with experimental data. Additionally, the burst pressure curves of the new prediction formula were plotted, and the relative errors between the new prediction formula and four existing prediction formulas were analyzed and compared. The results indicate that the new burst pressure prediction formula using the MSI yield criterion closely matches the experimental data, with the best relative error result within a confidence interval of ±1.3 %. The Lord parameter curve and plane stress curve of the MSI yield criterion exhibit good consistency with the experimental data of various ductile metal materials. The new burst pressure formula established by incorporating the MSI criterion provides a safe, economical, and reliable theoretical foundation for the design, manufacture, inspection, and safety assessment of thin-walled pipelines in production practice.

Transportation of Liquefied Natural Gas (LNG) via Long-Distance Low-Temperature Pipeline and Cascade Utilization of Cold Energy

In addition to methane, liquefied natural gas (LNG) typically contains valuable light hydrocarbons such as ethane, propane, and butane. Establishing LNG receiving stations for imported LNG can effectively alleviate regional energy supply-demand conflicts, optimize energy consumption structures, promote sustainable regional economic development, and improve ecological environments. The technology for long-distance low-temperature pipeline transportation of LNG facilitates the efficient transfer and cascading utilization of the cold energy contained in LNG, allowing for deep coupling with cold networks and natural gas pipelines, thereby promoting the integrated development of LNG, cold energy, and natural gas transportation. This paper systematically summarizes the current status of LNG long-distance low-temperature pipeline transportation technology, cold energy cascading utilization technology, pipeline regulation technology, and multi-network integration technology. It analyzes the key challenges these technologies face under new strategies and looks ahead to future development trends, aiming to provide scientific insights and directions for the application of LNG long-distance low-temperature transportation and multi-network integration in China.

Investigation on the methane emissions from permeation of urban gas polyethylene pipes under the background of hydrogen-mixed natural gas transportation

Methane, a more potent greenhouse gas than carbon dioxide, aggravates the greenhouse effect of ecological environment through its emissions. When transporting hydrogen-mixed natural gas through urban polyethylene pipes, methane will be emitted due to the permeation characteristic of polyethylene pipe material. Therefore, it is crucial to pay attention to the methane emissions from permeation of polyethylene pipes for protecting the environment and climate. In this paper, the solubility and diffusion coefficients of methane within hydrogen-mixed natural gas in polyethylene pipe materials are calculated through the Monte Carlo method and molecular dynamics simulation to determine the permeation coefficient of methane. Simultaneously, the methane emissions and equivalent carbon dioxide emissions of the hydrogen-mixed natural gas in polyethylene pipes are investigated. Results indicate the methane solubility coefficient decreases with increasing temperature and hydrogen mixing ratio. The methane diffusion and permeation coefficients increase with the rising temperature and pressure, and decreasing hydrogen mixing ratio. The pressure exerts minor influence while the temperature and hydrogen mixing ratio have more significant impact. That is, the lower the temperature and the higher the hydrogen mixing ratio, the less methane emissions caused by permeation. Therefore, the effective reduction of methane emissions can be achieved by adding the insulation layer to mitigate the impact of high temperature and increasing the hydrogen mixing ratio. For example, for the polyethylene pipe with the operating pressure of 4 bar and the size specification of SDR11, when the temperature drops from 300 K to 260 K, the methane emissions of hydrogen-mixed natural gas with hydrogen mixing ratios of 0 vol%, 20 vol%, 50 vol% and 80 vol% will be drastically reduced by 73.3%, 74.4%, 77.2% and 78.5% respectively, and when 20 vol%∼80 vol% hydrogen are mixed in the natural gas at 260 K, 300 K and 310 K, the methane emissions will be effectively reduced by 26.7%–85.6%, 23.3%–82.1% and 23.9%–82.4% respectively. The findings of this study can serve as guidance for reducing the methane emissions from permeation of polyethylene pipes transporting hydrogen-mixed natural gas.

Hydrate formation and its influence on natural gas pipeline: Simulation study

Natural gas transportation is plagued with the twin problem of hydrate and corrosion that occurs when a hydrate prone gas is conveyed in such a manner that the pipeline operating conditions fall within hydrate formation region of the hydrate phase envelop. This study simultaneously studied this twin problem, establishing their interdependent using gas sample from Niger Delta that was meticulously simulated and analysed for hydrate formation possibilities with the aid of Unism software. CO2 corrosion was simulated using NORSOK M-506 standard model in matlab. Major factors considered are the relationship between corrosion rate and temperature, corrosion rate and PH, corrosion-temperature relationship for varying CO2 mole percent, and PH values. The result from this study established that both type I and type II hydrates could form at the operating conditions of 5OC and 60 bar. Rate of corrosion decreases and increases with increase in PH and temperature respectively to a certain temperature of approximately 78 OC, then a dip in rate of corrosion. Corrosion-temperature relationship for varying PH and CO2 mole percent shows a decrease in corrosion rate with an in increase in PH, and an increase with increase in CO2 mole percent, with a rise as high as 5,7 mm/year at a 3 mole percent. This value and trend portray a bad omen for the affected pipeline. This study recommends that natural gas to be transported by pipeline should be sweetened and processed to remove H2S, CO2 and mercaptans if present and also to satisfy maximum dew point specification.

Identification of gas-liquid two-phase flow patterns based on flexible ultrasound array and machine learning

Ultrasound technology has been recognized as the mainstream approach for the identification of gas-liquid two-phase flow patterns, which holds great value in engineering domain. However, commercial rigid probes are bulky, limiting their adaptability to curved surfaces. Here, we propose a strategy for autonomous identification of flow patterns based on flexible ultrasound array and machine learning. The array features high-performance 1–3 piezoelectric composite material, stretchable serpentine wires, soft Eco-flex layers and a polydimethylsiloxane (PDMS) adhesive layer. The resulting ultrasound array exhibits excellent electromechanical characteristics and offers a large stretchability for an intimate interfacial contact to curved surface without the need of ultrasound coupling agents. We demonstrated that the flexible ultrasound array combined with machine learning can accurately identify gas-liquid two-phase flow patterns, in a circular pipeline. This work presents an effective tool for recognizing gas-liquid two-phase flow patterns, offering engineering opportunities in petroleum extraction and natural gas transportation.

Prediction of wellbore gas hydrate generation based on temperature-pressure coupling model in deepwater testing

With the advancement of oil and gas exploration and development technology, the development of the world's oil and gas resources is gradually advancing from land and shallow waters to deep waters. During the development of gas wells in deepwater regions, the temperature of the wellbore decreases from the bottom of the well to the wellhead, and therefore, common well conditions of high pressure, low temperature, and the presence of free water are encountered, which can lead to gas hydrate plugging of the pipeline and affect the transportation of natural gas. Simulation of temperature and pressure along the wellbore and identification of gas hydrate-generating zones in the wellbore can be used to take timely preventive measures and minimize losses. In this study, a wellbore gas hydrate generation and prediction model is developed by combining the mass, momentum, and energy conservation equations, and the model is solved by the fourth-order Runge-Kutta method, taking into account the temperature-pressure coupling in the wellbore. The effects of gas production, specific heat capacity, thermal conductivity, tubing size, test duration, and ground temperature gradient on the location of gas hydrate generation and the amount of inhibitor used were analyzed in a case study well in the South China Sea. Some suggestions for practical engineering operations, such as increasing the gas production in moderation and choosing smaller tubing sizes within the acceptable range, were given. The study's results can provide a theoretical basis for flow assurance for hydrocarbon production in the wellbore of deepwater gas wells.

Issues of the Russian liquefied natural gas market in the context of sanctions pressure and ways to solve them

Liquefied natural gas export is currently a rather promising sector of the Russian fuel and energy complex. Gas transportation by special gas carriers makes it possible to supply the resource independently of the pipeline system. In recent years, the liquefied natural gas market role has been significant for the Russian economy. This industry has not been subject to significant export restrictions by other countries, unlike pipeline gas exports. However, under the conditions of sanctions imposed by “unfriendly” countries on the supply of technologies and equipment required for liquefied natural gas production and transportation, not only the industry development, but also implementation of the Energy Strategy of the Russian Federation for the period up to 2035 is threatened, especially major projects implementation on the Arctic coast of the country. All of the above speaks for the relevance of the study, the objectives of which are to assess the Russian market of liquefied natural gas in the context of the introduced technological restrictions, to identify the key problems arising as a result of this unfavorable situation and to determine the directions for the industry further development.

Modeling and assessment of hydrogen-blended natural gas releases from buried pipeline

Blending hydrogen into natural gas pipelines for transportation reduces costs but increases safety risks. The main objective of this work is to explore the evolution of leakage hazards in hydrogen-blended natural gas pipelines and quantify these risks. To achieve this, multi-stage coupling numerical models are developed to explore the leakage hazards in hydrogen-blended natural gas transportation. The results show that the proposed model accurately predicts leakage rates of hydrogen-blended natural gas pipelines in various soil types. The gas diffusion pattern shifts from spherical to hemispherical, with the hazardous volume increasing linearly overall. The influence of pressure on leakage is amplified in the soil, while the impact of the leakage aperture is diminished. Although increasing the hydrogen blending ratio reduces the leakage rate, it also enhances the hazard evolution. Burial depth primarily affects alarm time, while an increase in leakage angle within 90–180° significantly delays the hazard evolution. Moreover, higher soil resistance not only mitigates the leakage diffusion but also reduces the pressure differential. The leakage aperture exhibits the highest correlation with the hazard evolution.

Investigation into the Simulation and Mechanisms of Metal-Organic Framework Membrane for Natural Gas Dehydration.

Natural gas dehydration is a critical process in natural gas extraction and transportation, and the membrane separation method is the most suitable technology for gas dehydration. In this paper, based on molecular dynamics theory, we investigate the performance of a metal-organic composite membrane (ZIF-90 membrane) in natural gas dehydration. The paper elucidates the adsorption, diffusion, permeation, and separation mechanisms of water and methane with the ZIF-90 membrane, and clarifies the influence of temperature on gas separation. The results show that (1) the diffusion energy barrier and pore size are the primary factors in achieving the separation of water and methane. The diffusion energy barriers for the two molecules (CH4 and H2O) are ΔE(CH4) = 155.5 meV and ΔE(H2O) = 50.1 meV, respectively. (2) The ZIF-90 is more selective of H2O, which is mainly due to the strong interaction between the H2O molecule and the polar functional groups (such as aldehyde groups) within the ZIF-90. (3) A higher temperature accelerates the gas separation process. The higher the temperature is, the faster the separation process is. (4) The pore radius is identified as the intrinsic mechanism enabling the separation of water and methane in ZIF-90 membranes.

Prediction of hydrate formation boundaries in pure water and salt/alcohol containing systems based on prior knowledge and artificial intelligence

As an efficient and clean energy source, natural gas plays a crucial role in optimizing the global energy consumption structure. However, the formation and accumulation of hydrates in pipelines during the exploitation and transportation of natural gas greatly jeopardize the production safety. Accurately predicting hydrate formation boundaries remains challenging due to the complex interation among various influencing factors. Although mechanistic models provide insights, they often fall short in accuracy. Conversely, machine learning models, while promising, may face limitations related to small sample sizes and a lack of physical interpretability. To overcome these limitations, this study proposed a physically guided neural network (PGNN) based on the Chen-Guo model, which integrated thermodynamic mechanisms with a neural network framework. This proposed model utilized pressure calculated from the Chen-Guo model as an input variable and incorporates physical inconsistencies into its loss function. A comparative analysis using literature data that PGNN achieved superior prediction accuracy, with an R2 value of 0.9768 for gas hydrate formation pressure prediction. The integration of thermodynamic mechanisms enhanced the prediction accuracy, as evidenced by an increase in the R2 value by 0.036, and a reduction in the MSE value by 5.56. Furthermore, the PGNN maintained a high level of prediction accuracy, ranging from 0.96 to 0.98, even with limited sample sizes, thus confirming its applicability and stability. This study validated the feasibility of PGNN for predicting gas hydrate formation conditions and offered insights into hydrate-based applications and hydrate management strategies.