Optimization problems in natural gas transportation systems: A state-of-the-art review

Ríos‐Mercado, Roger Z.; Borraz-Sánchez, Conrado

doi:10.1016/j.apenergy.2015.03.017

Cited by 396 publications

(201 citation statements)

References 79 publications

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“…The optimization of gas transport networks has been recently described in [1] and in the survey article [12]. The main objective is to find cost optimal operations, which stick to the required pressure and flow bounds.…”

Section: Gas Problemmentioning

confidence: 99%

Linearized model for optimization of coupled electricity and natural gas systems

Sirvent

Kanelakis

GEIßLER

et al. 2017

J. Mod. Power Syst. Clean Energy

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In this paper a combined optimization of a coupled electricity and gas system is presented. For the electricity network a unit commitment problem with optimization of energy and reserves under a power pool, considering all system operational and unit technical constraints is solved. The gas network subproblem is a medium-scale mixed-integer nonconvex and nonlinear programming problem. The coupling constraints between the two networks are nonlinear as well. The resulting mixed-integer nonlinear program is linearized with the extended incremental method and an outer approximation technique. The resulting model is evaluated using the Greek power and gas system comprising fourteen gas-fired units under four different approximation accuracy levels. The results indicate the efficiency of the proposed mixedinteger linear program model and the interplay between computational requirements and accuracy.

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Section: Gas Problemmentioning

confidence: 99%

Linearized model for optimization of coupled electricity and natural gas systems

Sirvent

Kanelakis

GEIßLER

et al. 2017

J. Mod. Power Syst. Clean Energy

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show abstract

“…The operation scheme is often developed based on the experience of the operator or by use of the pipeline simulation method [4]. There are two groups of methods broadly used to get the optimal operation schemes of natural gas pipelines: the operation scheme evaluating method and the mathematical optimization method.…”

Section: Introductionmentioning

confidence: 99%

“…In other words, these two objectives conflict with each other. Ríos-Mercado and Borraz-Sánchez [4] did an excellent review on various optimization objectives.…”

Section: Introductionmentioning

confidence: 99%

“…The dynamic programming (DP), the generalized reduced gradient (GRG), and the linear programming (LP) methods are three typical deterministic methods that have been extensively involved in solving the operation optimization model of natural gas pipelines, especially to solve the minimization fuel cost problem (MFCP) of the compressors [4]. The DP is the most successful method among these methods because it guarantees the global optimum and easily handles nonlinearity problem [5,11].…”

Section: Introductionmentioning

confidence: 99%

“…Many improved LP methods have a solid mathematical background [10] and the ability to find the global optimum, but they are not designed for solving the NLP problem. Moreover, none of the above three deterministic methods are designed for solving the resulting MINLP model related to some special optimization problems of natural gas pipelines [4].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Operation Optimization of Natural Gas Transmission Pipelines Based on Stochastic Optimization Algorithms: A Review

He³

et al. 2018

Mathematical Problems in Engineering

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Operation optimization of natural gas pipelines has received increasing attentions, due to such advantages as maximizing the operating economic benefit and the gas delivery amount. This paper provides a review on the most relevant research progress related to the steady-state operation optimization models of natural gas pipelines as well as corresponding solution methods based on stochastic optimization algorithms. The existing operation optimization model of the natural gas pipeline is a mixed-integer nonlinear programming (MINLP) model involving a nonconvex feasible region and mixing of continuous, discrete, and integer optimization variables, which represents an extremely difficult problem to be solved by use of optimization algorithms. A survey on the state of the art demonstrates that many stochastic algorithms show better performance of solving such optimization models due to their advantages of handling discrete variables and of high computation efficiency over classical deterministic optimization algorithms. The essential progress mainly with regard to the applications of the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Simulated Annealing (SA) algorithms, and their extensions is summarized. The performances of these algorithms are compared in terms of the quality of optimization results and the computation efficiency. Furthermore, the research challenges of improving the optimization model, enhancing the stochastic algorithms, developing an online optimization technology, researching the transient optimization, and studying operation optimization of the integrated energy network are discussed.

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Optimization of Natural Gas Network Operation under Uncertainty

Ogbe

Elkamel

Fowler

et al. 2018

Natural Gas Processing From Midstream to Downstream

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Optimization problems in natural gas transportation systems: A state-of-the-art review

Cited by 396 publications

References 79 publications

Linearized model for optimization of coupled electricity and natural gas systems

Linearized model for optimization of coupled electricity and natural gas systems

Operation Optimization of Natural Gas Transmission Pipelines Based on Stochastic Optimization Algorithms: A Review

Optimization of Natural Gas Network Operation under Uncertainty

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