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Changes in gas flow in the pipeline depending on the network foundation in the area
Abstract
The article presents an analysis of the results of overpressure distribution, velocity and gas streams obtained during the simulation of gas flow in the low pressure pipeline network. The calculations were made for the section of an existing gas network and the actual data describing gas consumption from the network by municipal customers and actual weather data characteristic to the specific city. Minimum and maximum overpressure of gas stream entering the network was determined, depending on the size of the network load and the difference in height between the gas station supplying the network and the most distant network connection (parameter ΔH). It was demonstrated that taking into account in the calculation the differences in the height of particular pipelines location in the network affects the selection of overpressure limit values of gas stream supplying the network. Moreover, gas overpressure distributions were compared in particular pipelines in the network for different cases of pipeline location in the area.
... However, few of the existing research studies have focused on the gas pressure problem and taken the high-rise buildings into account in the scheduling of the UMIES. Generally, in a horizontal gas pipeline, the change of natural gas pressure is mainly dependent on the diameter and length of the gas pipeline, the volume flow of the natural gas, and decreases with distance due to pipe loss [13,14]. However, in the case of a network with significant differences in height between the start and end points of the gas pipelines, as in high-rise buildings, additional overpressure may occur when the natural gas is transported from lower floors to higher floors. ...
... According to national regulations, it is recommended for lowpressure gas networks that the gas overpressure in each network connection should be in the range from 1700 to 2500 Pa [14]. Gas overpressure that is either too low or too high may result in lowthermal efficiency, combustion instability, and damage or improper functioning of the equipment powered by gas. ...
... The constraint in (13) is the SOC constraints mentioned above. Constraints (14) and (15) limit the magnitude of voltage and current. Constraints (16) and (17) show that CHP and wind power units will generate active and reactive power when they are plugged into the electricity distribution network through bus e. Constraints (18) and (19) describe that the active and reactive power purchased from the electricity market and transmission network governs the energy flowing from the root bus to the electricity distribution network, as mentioned in the assumptions. ...
Different from conventional low‐rise buildings, in high‐rise buildings, the gas pressure can easily exceed the safe limit, and the hot water cannot be easily transported to the higher floors owing to the effect of gravity. Therefore, overcoming these problems to supply heating for high‐rise buildings remains a great challenge. Accordingly, gas‐hanging stoves are introduced in this study as a provision for decentralised heating supply. To analyse the influence of gas hanging stoves on high‐rise buildings and on the entire urban micro integrated energy system (UMIES), two models were developed: a scenario‐based two‐stage stochastic model for optimal scheduling of the UMIES and a gas overpressure model taking both additional overpressures caused by the frictional resistance and gravity into account. Numerical experiments based on two microgrid test systems show the efficiency of gas hanging stoves with regard to reducing operation costs of the UMIES; moreover, the gas pressure in high‐rise buildings becomes more uniform and concentrated. Thus, the supply of gas and heat to high‐rise buildings can be significantly improved.
Simulation software packages are very useful tools for evaluating hydraulic conditions in gas systems, and therefore for supporting the design process, network maintenance and decisions about rerouting or modernisation of a network. In the range of this paper, a model of a real branched gas network covering 3 towns was created in the GAZNET software. At first, actual hydraulic conditions of gas flow in the pipes were simulated to evaluate distributions of flow velocity and pressure in the pipes. The obtained results indicated meaningful pressure drops and increase in flow velocity in some sections of the model, which not only constitutes a threat to provide required parameters of gas to consumers, but also forecloses connecting new consumers to the network. Thus, two variants of improvements were proposed: (1) expanding the network by building two additional sections or (2) increasing the number of gas sources by building additional pressure reduction and measuring unit. Conducted simulations indicated that changes of the network proposed in both variants clearly improve hydraulic conditions in the network model. However, the first variant was chosen as a better alternative, because distribution of hydraulic parameters in the model was more homogeneous than in the second variant, as well as because of economic considerations.
The paper presents two stages of an analysis of the storage capacity of low-pressure gas network for biomethane with a low value of combustion heat. The subject of the study is up-to-date, since it concerns an important issue of the storage and transport of energy generated from renewable sources. Based on the results of the gas flow simulation in the network in Polish city, the distributions of parameters describing the gas dynamics in the network were analyzed and the weak points of gas mixtures and alternative fuels transport in the network pipelines were indicated. Then, two methods of biomethane introducing and storing in the natural gas or regasified liquid natural gas LNG transported through the network were compared. The advantages and disadvantages of each solution were discussed, and the size of the biomethane stream, which can be introduced into the gas network pipelines and supplied to the recipients together with the gas was quantified. It was demonstrated that the highest volume of biomethane can be stored in the network transporting regasified LNG, and the biomethane stream, regardless of the network load, constitutes 39% of the mixture of biomethane and regasified LNG. In turn, the lowest biomethane volume can be stored in the network in the case of constant over time biomethane stream introducing into the natural gas.
Considering uncertainties from wind power and day-ahead market price, this paper develops a scenario-based two-stage model for the day-ahead scheduling of integrated energy distribution network (IDN) which couples various energy systems such as electricity, heat, and natural gas. However, gas network constraints pose a great challenge to the computation because the piecewise linear approximation (PLA) method linearizes the nonlinear flow-pressure constraints (i.e., Weymouth equations) by adding a large number of additional auxiliary variables and constraints into the model, which increases the complexity of the model. To address this problem, we propose a sufficient condition for identifying redundant gas network constraints. We also develop a bounds tightening strategy that combines Weymouth equation relaxation and optimality-based bounds tightening method to mitigate the conservatism of the proposed sufficient condition. Numerical case studies show that the proposed method can greatly improve the computational performance of the optimization model, which is superior to the conventional PLA method. For a larger-scale test system, the improvement of computational efficiency is more significant.
The paper presents calculation results of stream, velocity and gas overpressure obtained from steady state simulation of gas flow in pipeline network distributing natural gas. The calculations were performed for real section of pipeline network localized in city Szczecin. Total length of pipelines creating network was equal to 4,151 m. This network was filled with 51 m 3 gas with overpressure of approximately 2.4 kPa. Based on simulation results, received for various input data values, corresponding with different hours of the day, it was proved, that both gas flow rate and its velocity in pipeline network depend inter alia on the time of the day.
This research study focuses on the modeling and simulation of a gas distribution pipeline network with a special emphasis on gas ducts. Gas ducts are the most important components of such kind of systems since they define the major dynamic characteristics. Isothermal, unidirectional flow is usually assumed when modeling the gas flow through a gas duct. This paper presents two simplified models derived from the set of partial differential equations governing the dynamics of the process. These models include the inclination term, neglected in most related papers. Moreover, two numerical schemes are presented for the integration of such models. Also, it is shown how the pressure drop along the pipe has a strong dependency with the inclination term. To solve the system dynamics through the proposed numerical schemes a based MATLAB-Simulink library was built. With this library it is possible to simulate the behavior of a gas distribution network from the individual simulation of each component. Finally, the library is tested through three application examples, and results are compared with the existing ones in the literature.
A numerical method is developed to investigate leakage in above-ground and buried urban distribution natural gas pipelines. The main aim is to develop a few equations to estimate leakage form above-ground and buried urban natural gas pipelines. The equations are developed by considering the impact of various parameters such as the pipeline and hole diameters. A computational model for steady, compressible turbulent flow is built to model leakage. The natural gas as working fluid is treated as an ideal gas and soil considered as a porous zone. The results indicate that for holes with small diameters, discharge speed reaches to the sound speed and at the so-called, choking occurs in the flow. Also based on the result, the volumetric flow rate of leaked gas have a linear relation, second order relation and fourth order relation with pressure of initial point, diameter of hole and ratio of the hole diameter to the pipe diameter, respectively. In the case of buried pipes, permeation depth of gas into soil at the small diameter holes is more than large holes but volumetric rate of leaked gas is lower. Also after permeation of natural gas into the soil, and hitting the soil particles and the air moving through soil, a pair of vortex is created inside the soil. Finally two new correlations have been proposed to calculate the natural gas leakage from a small hole located on the lateral surface of the above-ground and buried distribution gas pipelines. Results show that, the percentage of relative error between simulation results and correlation values is below 5% which implies high accuracy of the presented correlations.
Abundant natural gas at low prices has prompted industry and politicians to welcome gas as a ‘bridge fuel’ between today's coal-intensive electric power generation and a future low-carbon grid. We used existing national datasets and publicly available models to investigate the upper limit to the emission benefits of natural gas in the USA power sector. As a limiting case, we analyzed a switch of all USA coal plants to natural gas plants, occurring in 2016. The human health benefits of such a switch are substantial: SO2 emissions are reduced from the baseline (MATS (Mercury and Air Toxics Standard) retrofits by 2016) by more than 90%, and NOX emissions by more than 60%, reducing total national annual health damages by 50 billion annually. While the effect on global temperatures is small out to 2040, the USA power plant fleet's contribution could be changed by as much as −50% to +5% depending on the rate of fugitive CH4 emissions and efficiency of replacement gas plants.
The work presents an example of practical application of gas flow modeling results in the network, that was obtained for the existing gas network and for real data about network load depending on the time of day and air temperature. The gas network load in network connections was estimated based on real data concerning gas consumption by customers and weather data in 2010, based on two-parametric model based on the number of degree-days of heating. The aim of this study was to elaborate a relationship between pressure and gas stream introduced into the gas network. It was demonstrated that practical application of elaborated relationship in gas reduction station allows for the automatic adjustment of gas pressure in the network to the volume of network load and maintenance of gas pressure in the whole network at possibly the lowest level. It was concluded based on the results obtained that such an approach allows to reduce the amount of gas supplied to the network by 0.4% of the annual network load.
The lack of attention to unsteady state condition in pipeline networks results a considerable error for gas researchers. Our work aims to fill this gap for pipeline networks in series, parallel and looped based on unsteady Weymouth equation. For this, we introduced “Gain Coefficient” as the scale of gas flow increases in pipelines. Our results showed the gain coefficient for steady flow in series was a function of diameter and length ratios (D2/D1, L1/L). The value of gain coefficient for unsteady flow closes to steady flow in series until it reaches to 1.97 after 500 h for L1/L = 0.25 and D2/D1 = 2.5. Based on our development, the gain coefficient just was a function of diameter ratio for steady flow in parallel systems. According to our results, the value of gain coefficient for unsteady flow tends towards steady flow in parallel until it reaches to 12.50 for ratio of diameters equal 2.5 after 4000 h. For looped systems, fractions of looping and diameter ratio were main parameters of gain coefficient. Also, for all diameter ratios, a significant growth occurs in gain coefficient for unsteady flow when fraction of looping exceeds from 0.75. Based on our results, for fraction of looping equal to 0.75, gain coefficients for steady and unsteady flows converged to 1.94 for diameter ratio equal to 2.5 after 200 h. From our results, parallel system has a considerable preference in comparison with series and looped systems, but, it needs a large amount of cost. This paper as a basic report tries to help engineers of gas industry to design more accurate gas pipeline networks.
A considerable growth is expected for the natural gas sector and some believe that it will be the leading primary fuel between 2020 and 2030. Different options are available to utilize the natural gas resource. Three processes namely, LNG, GTL, and methanol considered as the most promising utilization options are addressed in this paper to represent a natural gas processing and production network. The objective of this work is to illustrate the importance of incorporating rigorous simulation models in the decision-making process in the gas processing industry. A steady state simulation is carried out for LNG, GTL, and methanol processed to determine mass and energy balances, operating conditions, and equipment specification. The simulations' flowsheet is beneficial in many aspects. For example, accurate yield values can be obtained. Also, both the capital and operating costs can be estimated. Moreover, the environmental impact can be assessed quantitatively. Then, an optimization model is presented that is able to represent the processing and production network over a wide range of forecasted economic changes. The main feature of this work is the usage of an integrated simulation-optimization framework. Although the modeling, simulation and optimization of a single natural gas system have been addressed previously, the simulation and optimization of enterprise-wide natural gas processing has not been addressed to this extent in the literature. Furthermore, besides considering more than one utilization process, namely LNG, GTL, and methanol, this work addresses the preprocessing units of these utilization processes in a comprehensive manner. The results of the optimization are improved by utilizing data from process simulation. Such data are used to tune the optimization model. An illustrative case study is used to show the applicability of formulated optimization model on natural gas processing and production network and show how accurate representations of the plants are obtained from process simulation. The end result is a more highly optimized and sustainable processing and production network.
In this study, the results of forecasting of the gas demand obtained with the use of artificial neural networks are presented. Design and training of MLP (multilayer perceptron model) was carried out using data describing the actual natural gas consumption in Szczecin (Poland). In the model, calendar (month, day of month, day of week, hour) and weather (temperature) factors, which have a pronounced effect on gas consumption by individual consumers and small industry, were considered. The results of forecasts with the use of MLP models differing in the number of neurons in the hidden layer and in the size of the data set used in the training process were compared. MLP networks with the higher quality were used for the preparation of gas consumption forecast for the additional input data, which was not previously used in the training process. It was found that MLP 22-36-1 model can be successfully used to predict gas consumption on any day of the year and any hour of the day.
Pipeline networks transmit gas between the source of natural gas and customers. The high cost of transportation is a challenge that must be addressed to decrease costs. Optimizing transmission operations can decrease energy consumption in compressor stations of the network. Considering significant fuel consumption in network, the present study examined common methods of optimizing fuel consumption in gas transmission networks and then simulated a simple network model using Simone simulation software. The theoretical effects of the methods were then applied to the National Iranian Gas Network, which currently transfers gas using 65 compressor stations and 33,000 km of high pressure pipeline. The methods studied were: use of maximum and balanced capacity of pipelines; adjusting the optimum inlet pressure at city inlets, industries and power plants; use of appropriate connections to assist gas transportation flow and decrease compressor load; and selecting appropriate numbers of in-service compressors to handle the volume of gas transferred. Results indicate that substantial cost savings can be realized from the decrease in gas consumption of turbo-compressors that will also postpone overhaul time by decreasing the hours of operation.
We consider the problem of designing a new natural gas transmission network or expanding an existing network while minimizing the total investment and operating costs. We develop an integrated large-scale mixed-integer nonlinear optimization model to determine pipelines in the network, compressor stations and their capacities, timings of these installations in a multi-period planning horizon, and natural gas purchase and steady-state flow decisions for each period in the network. The model is solvable using state-of-the-art solution methodologies available online.
Employing our modeling and the solution methodology for its solution, we conduct computational studies on various test instances generated using realistic network structure and data based on the natural gas network in Turkey as well as data from literature. Our analysis provides insights into sensitivity of network configuration and operations to the number of periods within the planning horizon and cost parameters as well as into strategic decision making for design and expansion of natural gas networks.
A transient flow simulation for gas pipelines and networks is proposed. The proposed transient flow simulation is based on the state space equations. These equations are derived by the transfer function equations. However, the transfer function model cannot be used for a complicated network. One can easily apply a state space model for a large and complicated network. For a state space model, the equivalent transfer functions of the nonlinear governing equations are derived for different boundary condition types. Next, the state space equations are derived from the transfer functions. To verify the accuracy of the proposed simulation, the results obtained are compared with those of the conventional finite difference schemes (such as total variation diminishing algorithms, method of lines, and other finite difference implicit and explicit schemes). The effect of the flow inertia is incorporated in this simulation. The accuracy and computational efficiency of the proposed method are discussed for a single gas pipeline and a sample gas network; besides for accuracy of this method for different boundary conditions, results for a sample gas pipeline with different boundary conditions are compared.
Pipeline leaks can lead to excessive economical loss as well as posing environmental hazards. Mathematical modeling of the flow in a pipeline with a leak can be used to evaluate the loss caused by a leak and provide a guide for pipeline operation as well as an aid for leak detection. The mathematical expressions describing the flow in a pipeline with a leak have been formulated. A new approach based on the analogy between pipeline and electric circuit has been proposed to solve these equations. In this approach, an equivalent circuit with a certain structure has been used to simulate the leaking pipeline and the flow characteristics of the pipeline end have been treated with approximation. The mathematical model of the pipeline with a leak has been developed with the solution of the equations. The model was verified by using an experimental gas pipeline and a real oil pipeline. The simulated results agreed well with the experimental recordings confirmed the accuracy of the models and the validity and efficiency of the proposed approach.
The paper discusses chosen issues concerning damaged gas pipelines. Attention is paid to modelling the steady-state flow of natural gas in distribution pipelines, and the most commonly applied models of isothermal and adiabatic flow are evaluated for both the ideal and the real gas properties. A method of accounting for a leakage by means of a reference flow equation with a discharge coefficient is presented, and the dependency of the discharge coefficient on pressure is demonstrated both with literature data and the authors' experimental results. A relevant computational study of a pipeline failure is presented for a high- and a medium pressure pipeline. The importance of an appropriate choice of the flow model (isothermal or adiabatic flow of real or ideal gas) is demonstrated by the results of the study. It is shown that accounting for the variability of the discharge coefficient is required if medium pressure pipelines are analysed. However, it is eventually shown that the impact of the discharge coefficient on the predicted outflow rate is of lesser importance than that of the applied flow model.
The pressure in the main natural gas transport pipelines should be reduced for proper consumption in vicinity of cities. A common procedure of reducing pressure in natural gas station (city gate station, CGS) is using expansion valves, which causes the waste of large amount of exergy (availability). In this paper a combined heat and power (CHP) system was used instead which included an expander, gas engines, boilers, a pump and a preheater. A new and relatively quick method for selecting the required number of gas engine/boiler, and determining their nominal power/heating capacity, as well as the expander efficiency are also presented. An objective function named actual annual benefit ($) was defined as the sum of income (from selling electricity) and expenses (such as investment cost, operation and maintenance costs). Subsequently different parts of the objective function were expressed in terms of 9 decision variables. The optimum values of decision variables were obtained by maximizing the objective function using genetic algorithm optimization technique. By applying the above procedure for our case study, it was obtained that two 5.48 (MW) gas engines and one 5.94 (MW) boiler was needed while the payback period was found to be 1.23 (year).
One-dimensional, nonisothermal gas flow model was solved to simulate the slow and fast fluid transients, such as those typically found in high-pressure gas transmission pipelines. The results of the simulation were used to understand the effect of different pipeline thermal models on the flow rate, pressure and temperature in the pipeline. It was found that simplified flow model with steady-state heat transfer term overestimates the amplitude of the temperature fluctuations in the pipeline. This result indicated that unsteady heat transfer model with the effect of heat accumulation in the surroundings of the pipeline should be used to calculate the gas parameters at locations of interest within high-pressure gas transmission pipelines.
Natural gas is rapidly growing in global importance both as a primary energy source and a feedstock for downstream industry. Therefore, needs for natural gas transportation from production zones to consuming areas are ever increasing. Natural Gas transmission through pipeline is the oldest and most common method for high capacity gas transmission. These transmission systems are very capital intensive; therefore, the optimum design for this method of transportation seems indispensable.In this work, the optimum design for gas transmission systems has been investigated from technical and economical points of view. The main optimization criterion has been the minimization of the life cycle cost for the gas transmission system. Considering various factors affecting the life cycle cost of these systems, a comprehensive mathematical model has been established to find the optimum design. In view of the characteristics of the model, comprising continuous and discrete variables, a rank-optimization methodology has been used. Based on the developed optimization method, an optimization program has been compiled. The effect of different variables on the life cycle cost for one of the Iranian Gas Trunk-Lines (IGAT-II) has been investigated.
Rising import dependency, increasing market liberalization and cross-border trade and security of supply fears facilitate investments in natural gas supply infrastructures in Europe. In order to ensure an efficient allocation of capital resources, it is important to identify congestion in the existing system and investment requirements based on economic principles. This paper first outlines an analytical framework for the identification of bottlenecks and the evaluation of transport capacities and the cost of congestion based on nodal prices. Secondly, an infrastructure model of the European gas market with high temporal and spatial granularity which exhibits the characteristics of the theoretical model is introduced. Parameterizing the model with the existing infrastructure and applying a demand and supply scenario for the year 2015, congestion mark-ups between countries in Europe are estimated. This approach indicates potential bottlenecks which might arise within the next five years and quantifies their economic costs. With only some temporary congestion, physical market integration is found to be high in Western Europe. In Eastern Europe, severe bottlenecks are identified and discussed. Implications for efficient investment decisions arising from the findings are examined in the context of the theoretical considerations.
The paper presents a technique for detection of “bottlenecks” in gas transportation networks in emergency situations. The described approach makes it possible to formulate the optimal ways to tackle negative consequences for gas consumers. The technique is based on the “Oil and Gas” software developed at Energy Systems Institute SB RAS and is exemplified with the European gas pipeline network.
Real gas effects exert a significant influence on the hydraulics of natural gas transmission pipelines. In this article the implications of the selection of the equation of state for the pipeline gas flow model are investigated. A non-isothermal transient gas flow model with AGA-8 and SGERG-88 equations of state was studied. Models with Soave-Redlich-Kwong and Benedict-Webb-Rubin equations of state were solved to illustrate the overall gas flow model inaccuracies. The effect of the selection of different equations of state on the flow parameters is demonstrated and discussed.
Traditionally, the governing equations for transient analysis of gas pipeline network involve two partial differential equations, which are normally solved by complex numerical methods. Following the success of its application in the steady analysis of pipeline networks, the electric analogy method is extended by combining resistance and capacitance, which leads to a first order ordinary differential equation and an alternative route to solving the transient problem. Solving the proposed first order ordinary differential equation has been shown to be much simpler than having to solve the set of partial differential equations normally encountered in other transient models. It is found that the results obtained are comparable to those obtained from the traditional methods published in the literature. The proposed method is computationally efficient and is readily applicable as a method for design and control of network systems.
Dynamic simulation models of gas pipeline networks can be used for on-line applications such as state estimation, leak detection, etc. A prime requirement for such models is computational efficiency. In this paper, a transfer function model of a gas pipeline is used as a basis for developing a dynamic simulator for gas pipeline networks. The simulator is incorporated in a data reconciliation framework, which is ideally suited for on-line state estimation based on all available measurements of pressures and flow rates. The American Gas Association (AGA) model is used for making realistic computations of the gas compressibility. Accuracy and computational efficiency of the proposed method are evaluated by comparing our results with those obtained using a fully nonlinear second-order accurate finite difference method. The ability of the proposed approach for obtaining accurate state estimation from noisy measurements is demonstrated through simulations on an example network. We also demonstrate the use of the proposed approach for estimating an unknown demand at any node by exploiting the redundancy in measurements.
Hardy Cross method is common for calculation of loops-like gas distribution networks with known node gas consumptions. This method is given in two forms: original Hardy Cross method-successive substitution methods and improved-simultaneous solution method (Newton-Raphson group of methods). Problem of gas flow in looped network is nonlinear problem; i.e. relation between flow and pressure drop is not linear while relation between electric current and voltage is. Improvement of original method is done by introduction of influence of adjacent contours in Yacobian matrix which is used in calculation and which is in original method strictly diagonal with all zeros in non-diagonal terms. In that way necessary number of iteration in calculations is decreased. If during the design of gas network with loops is anticipated that some of conduits are crossing each other without connection, this sort of network became, so there has to be introduced corrections of third or higher order.
With the start up of West–East Natural Gas Transmission Project, the construction of natural gas-pipeline will enter on a new era in China. The development tendency will be towards large-diameter, high-pressure and long-distance for natural gas-pipelines. Correspondingly, the life cycle cost of natural gas-pipeline networks is increasing gradually. The mainline system is a vital part of natural gas network systems. The investment required for the mainline system is enormous, usually accounting for 80% of the total investment for this system. In general, the investment required for a gas-pipeline depends on its operating parameters. Therefore, based on the characteristics of gas networks, optimization for investment becomes indispensable to gas networks design. A comprehensive and optimal mathematic model of a gas networks system is established in this paper which considers all the factors influencing the total investment of a gas networks system (e.g. pipe diameter, thickness, pressure, length, compression ratio, etc). From the standpoint of the characteristics of a model comprising both continuous and discrete variables, a new methodology, rank-optimization, is presented. On the basis of this model, a simple and visual high-pressure networks optimization program has been compiled. Furthermore, the developed optimization program has been applied to a practical project and the effects of operating parameters on the total investment have been analyzed. The simulation model in this paper is shown to be an effective method to solve optimization on mainline system in high-pressure gas networks.
Europe’s dependency on non-EU countries’ energy supply is sharply increasing. Recently, sudden supply disruption caused by international disputes outside the EU have created serious problems for some EU countries and raised concern in many others. In these situations, it is highly desirable to have a tool to assess possible outcomes of supply disruptions. This paper presents a newly developed model, MC-GENERCIS, aimed to assess the robustness of the EU transnational gas transmission system during both normal and special operating conditions, including high-demand situations and/or a supply shortage. The model has a country-by-country resolution and examines all possible dispatching choices of national TSOs on the basis of a probabilistic MonteCarlo approach. The preliminary validation of the model through its application to the “normal” conditions for the winter 2008–2009 and to the recent supply disruption involving Ukrainian gas transit is also described.
The aim of the present study is the numerical modelling of the dynamic behaviour of high-pressure natural-gas flow in pipelines. The numerical simulation was performed by solving the conservation equations, for one-dimensional compressible flow, using the Runge–Kutta discontinuous Galerkin method, with third-order approximation in space and time. The boundary conditions were imposed using a new weak formulation based on the characteristic variables. The occurrence of pressure oscillations in natural-gas pipelines was studied as a result of the compression wave originated by the rapid closure of downstream shut-off valves. The effect of the partial reflection of pressure waves was also analyzed in the transition between pipes of different cross-sectional areas.
Predictions of the gas temperature and pressure profiles are vital to the design and operation of gas transmission lines. Available analytical methods for the calculation of these profiles are evaluated and a numerical framework for the rigorous calculation has been developed. The predictions from both the analytical and numerical procedure have been compared to field data from the Iranian Gas Trunk-lines (IGAT). These comparisons showed that all the available methods were tuned using data obtained from small to medium diameter pipes extrapolated poorly to large diameter pipelines. In order to improve the predictions for large diameter pipelines, the effect of model parameters such as soil thermal conductivity, pipe relative roughness and velocity profile correction factor has been evaluated. The results show that temperature and pressure profiles at high Reynolds number are sensitive to the Fanning friction factor; however, thermal conductivity and velocity distribution correction factor have almost no effect on the temperature and pressure profiles provided these parameters were set at an average acceptable industry value. Since the pressure profile for large diameter pipes was most sensitive to the Fanning friction factor a parameter optimization method was used to fine-tune the Fanning friction factor as a function of Reynolds number at an average accepted industry relative pipe roughness.
Operative planning in gas distribution networks leads to large-scale mixed-integer optimization problems involving a hyperbolic PDE defined on a graph. We consider the NLP obtained under prescribed combinatorial decisions—or as relaxation in a branch-and-bound framework, addressing in particular the KKT systems arising in primal–dual interior methods. We propose a custom solution algorithm using sparse projections locally in time, based on the KKT systems’ structural properties in space as induced by the discretized gas flow equations in combination with the underlying network topology. The numerical efficiency and accuracy of the algorithm are investigated, and detailed computational comparisons with a previously developed control space method and with the multifrontal solver MA27 are provided.
There are a number of options of exporting natural gas energy from oil and gas fields to market, including pipelines, liquefied natural gas (LNG), compressed natural gas (CNG), gas to solids (GtS), i.e. hydrates, gas to wire (GtW), i.e. electricity, gas to liquids (GtL), with a wide range of possible products including clean fuels, plastic precursors or methanol and gas to commodity (GtC), such as aluminium, glass, cement or iron. Any gas energy export route requires a huge investment in infrastructure, and long-term ‘fail proof’ contracts, covering perhaps 20 years or more. But which is the best way to monetise the gas? Gas rich countries, such as Trinidad and Qatar are currently in this challenging debate. There could be options for handling niche markets for gas reserves which are stranded (no market) and for associated gas (on- or off-shore) which cannot be flared or re-injected, or for small reservoirs which cannot otherwise be economically exploited. Transportation of natural gas as hydrate or CNG is believed feasible at costs less than for LNG and where pipelines are not possible. The competitive advantage of GtS or CNG over the other non-pipeline transport processes is that they are intrinsically simple, so should be much easier to implement at lower capital costs, provided economically attractive market opportunities can be negotiated to the gas seller. The transport options preferred by governments and companies must not only take the economic risks into account but also consider the negative effects of possible terrorist activity, political changes and trade embargos over long periods of time. In this paper, we cover many of the essential technical points and broad economic pointers needed to enter the discussion of gas rich states which do not need the gas for domestic use, but wish to monetise their reserves by export.
In this paper we propose a heuristic solution procedure for fuel cost minimization on gas transmission systems with a cyclic network topology, that is, networks with at least one cycle containing two or more compressor station arcs. Our heuristic solution methodology is based on a two-stage iterative procedure. In a particular iteration, at a first stage, gas flow variables are fixed and optimal pressure variables are found via dynamic programming. At a second stage, pressure variables are fixed and an attempt is made to find a set of flow variables that improve the objective function by exploiting the underlying network structure. Empirical evidence supports the effectiveness of the proposed procedure outperforming the best existing approach to the best of our knowledge.Scope and purposeGas transmission network problems differ from traditional network flow problems in some fundamental aspects. First, in addition to the flow variables for each arc, which in this case represent mass flow rates, a pressure variable is defined at every node. Second, besides the mass balance constraints, there exist two other types of constraints: (i) a nonlinear equality constraint on each pipe, which represents the relationship between the pressure drop and the flow; and (ii) a nonlinear non-convex set which represents the feasible operating limits for pressure and flow within each compressor station. The objective function is given by a nonlinear function of flow rates and pressures. In the real world, these type of instances are very large both in terms of the number of decision variables and the number of constraints, and very complex due to the presence of nonlinearity and non-convexity in both the set of feasible solutions and the objective function.
The paper deals with different pipeline models and their simulation. First, a nonlinear distributed parameters model is derived, which is then linearised and its transfer function is obtained by a Laplace transformation and corresponding initial and boundary conditions. The pipeline is represented as a two-port system. Four representations are presented and two of them — the hybrid ones which are used in practice-are studied further. They involve three different transcendent transfer functions which are then approximated by rational transfer functions using a Padé approximation. The derived models describe the pipeline as a lumped parameter system. Due to the approximation of the high frequency gain, the derived models are only valid for a class of models — namely well damped pipelines. The derived models were comparatively verified on the basis of the measurements on a real pipeline.
This study is concerned to determine the optimum pipe size for networks used in natural gas applications. The genetic algorithm has been used in optimizing network parameters. The topology of the network is predefined. The study deals with the discrete nature of decision variables, namely, pipe diameters, as they are usually available in market in standard sizes. Hard constraints and soft constraints are considered. An imposed penalty factor is introduced to allow solutions that violate soft constraints to remain in the population during the solution progress guiding the algorithm convergence to a minimum network cost.In a case study, engineers with average experience of 6 years in the design office of a gas company performed the design of a gas network problem using their experience and judgment. The adopted method by engineers depends on a trial and error, time consuming, procedure. Their results are compared with the results obtained from the developed genetic algorithm optimization technique.The developed optimization technique has provided a distinctive reduction in the total cost of pipe networks over the existing heuristic approach which is based on human experience and judgment. A saving up to 12.1% has been achieved using the present analysis, in the special case studied.
This paper presents a feasibility study of evolutionary scheduling for gas pipeline operations. The problem is complex because of several constraints that must be taken into consideration during the optimization process. The objective of gas pipeline operations is to transfer sufficient gas from gas stations to consumers so as to satisfy customer demand with minimum costs. The scheduling involves selection of a set of compressors to operate during a shift. The scheduling decision has to be made so as to satisfy the dual objectives of minimizing the sum of fuel cost, start-up cost, the cost of gas wasted due to oversupply, and satisfying minimal operative and inoperative time of the compressors. The problem was decomposed into the two subproblems of gas load forecast and selection of compressors. Neural networks were used for forecasting the load; and genetic algorithms were used to search for a near optimal combination of compressors. The study was conducted on a subsystem of the pipeline network located in southeastern Saskatchewan, Canada. The results are compared with the solutions generated by an expert system and a fuzzy linear programming model.
Natural gas, driven by pressure, is transported through pipeline network systems. As the gas flows through the network, energy and pressure are lost due to both friction between the gas and the pipes’ inner wall, and heat transfer between the gas and its environment. The lost energy of the gas is periodically restored at the compressor stations which are installed in the network. These compressor stations typically consume about 3–5% of the transported gas. This transportation cost is significant because the amount of gas being transported worldwide is huge. These facts make the problem of how to optimally operate the compressors driving the gas in a pipeline network important.
In this paper we address the problem of minimizing the fuel cost incurred by the compressor stations driving the gas in a transmission network under steady-state assumptions. In particular, the decision variables include pressure drops at each node of the network, mass flow rate at each pipeline leg, and the number of units to be operating within each compressor station. We present a mathematical model of this problem and an in-depth study of the underlying mathematical structure of the compressor stations. Then, based on this study, we propose two model relaxations (one in the compressor domain and another in the fuel cost function) and derive a lower bounding scheme. We also present empirical evidence that shows the effectiveness of the lower bounding scheme. For the small problems, where we were able to find optimal solutions, the proposed lower bound yields a relative optimality gap of around 15–20%. For a larger, more complex instance, it was not possible to find optimal solutions, but we were able to compute lower and upper bounds, finding a large relative gap between the two. We show this wide gap is mainly due to the presence of nonconvexity in the set of feasible solutions, since the proposed relaxations do a very good job of approximating the problem within each individual compressor station.
We emphasize that this is, to the best of our knowledge, the first time such a procedure (lower bound) has been proposed in over thirty years of research in the natural gas pipeline area.