Multi-objective design optimization of natural gas transmission networks

Alves, Felipe Emerson André; Souza, Jaime Neiva Miranda de; Costa, André L.H.

doi:10.1016/j.compchemeng.2016.06.006

Cited by 54 publications

(21 citation statements)

References 11 publications

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“…Then, the ejected gas will be entered through matrix pores and cleats, in where, there is existed a plenty numbers of fractures with various sizes. Here, a non-linear filtration technology is considered for examining the flow of free gas through the matrix pores and cleats [10,11]. But, instead of using conventional theory concentration difference driving, here newly proposed pressure difference driving is applied.…”

Section: Evaluation Of Cbm Dvelop-ment Technologies Based On the Filtmentioning

confidence: 99%

A smart review on the gas transportation model of coalbed methane gas based on the optimized pipeline network

Talapatra

Chowdhury

Ujjaman

2019

Journal of Mechanical and Energy Engineering

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Coalbed methane is extracted from the adsorbed state in coal seams with lower pressure and production rate. In previous studies, researchers only focused on the methods that were developed for making a relationship between the underground production rate and surface flow rate without any type of optimization procedure. In this study, the main purpose is to do a review on finding out of surface layout plan to optimize the maximum gas flow rate by developing an improved pipeline network. The more the optimization of the layout plan for designing pipeline network, the lower the amount of investment need to provide. Here, a mathematical model is proposed for the gas transportation based on the hydraulic and thermodynamic calculations of the pipeline network. Not only that, but also the filtration mechanism of depressurization and desorption for the gas flow through pipe section are evaluated here. After that, the pressure drop and pipeline efficiency are explored to find out the best design of pipeline network from the observed results. Finally, based on this study, many uncertainties can be reduced associated with the installation of pipeline network for gas transportation.

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Section: Evaluation Of Cbm Dvelop-ment Technologies Based On the Filtmentioning

confidence: 99%

A smart review on the gas transportation model of coalbed methane gas based on the optimized pipeline network

Talapatra

Chowdhury

Ujjaman

2019

Journal of Mechanical and Energy Engineering

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“…The paper by [15] proposes the multi-objective optimization of the design of natural gas transmission networks to support the decision of regulatory authorities. Problem formulation involves two objective functions: minimization of the transportation fare and maximization of the transported gas volume.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of Gas Pipeline Networks

Osiadacz

Isoli²

2020

Energies

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The main goal of this paper is to prove that bi-objective optimization of high-pressure gas networks ensures grater system efficiency than scalar optimization. The proposed algorithm searches for a trade-off between minimization of the running costs of compressors and maximization of gas networks capacity (security of gas supply to customers). The bi-criteria algorithm was developed using a gradient projection method to solve the nonlinear constrained optimization problem, and a hierarchical vector optimization method. To prove the correctness of the algorithm, three existing networks have been solved. A comparison between the scalar optimization and bi-criteria optimization results confirmed the advantages of the bi-criteria optimization approach.

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“…Martin et al 21 used an MILP formulation to minimize the gas compression cost. Alves et al 22 applied an MILP formulation in a multiobjective optimization framework to find the minimum transportation cost while maximizing the gas flow. A further step in the problem formulation is to combine the above features in a mixed integer nonlinear programming formulation (MINLP).…”

Section: Introductionmentioning

confidence: 99%

Mixed Integer Linear Programming Optimization of Gas Supply to a Local Market

Mikolajková

Saxén

Pettersson

2018

Ind. Eng. Chem. Res.

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Remote or stranded areas that cannot be supplied by natural gas through transmission pipelines can access gas through terminals for liquefied natural gas (LNG), from where LNG is distributed by trucks or compressed and regasified into regional distribution networks. The gas supply may be further augmented by local biogas or synthetic natural gas. A model for optimization of such regional gas supply chains is presented in the paper, considering a combination of pipeline and truck delivery to a set of customers with given energy demands. After linearization, the task is formulated as a mixed integer linear programming (MILP) problem and is solved by state-of-the-art software. The model is illustrated on a regional energy supply problem considering seasonal variations in the demands. The results of the study demonstrate the role of the price of the local and alternative fuels and the price margins at which it is feasible to build an extensive pipeline network instead of supplying the fuel by trucks to storages connected to pipeline islands. The findings also give information about the influence on investment versus operation costs on the optimal design of the supply chain. The sensitivity of the optimal supply chain on the price of local and alternative fuels as well as on the unit price of pipes and storage tanks is studied to illustrate how optimization can be used to shed light on the feasibility of investment in new infrastructure and to support the decision making processes in the energy sector.

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Multi-objective design optimization of natural gas transmission networks

Cited by 54 publications

References 11 publications

A smart review on the gas transportation model of coalbed methane gas based on the optimized pipeline network

A smart review on the gas transportation model of coalbed methane gas based on the optimized pipeline network

Multi-Objective Optimization of Gas Pipeline Networks

Mixed Integer Linear Programming Optimization of Gas Supply to a Local Market

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