Multi-Objective Optimization of Gas Pipeline Networks

Osiadacz, Andrzej J.; Isoli, Niccolo

doi:10.3390/en13195141

Cited by 11 publications

(8 citation statements)

References 21 publications

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“…Datasets related to this article can be found through the shared link at https://data.mendeley.com/datasets/g7nb7b9ys7/2, an open-source online data repository hosted at Mendeley Data (Takerhi, 2022b).…”

Section: Discussionmentioning

confidence: 99%

Optimization of a gas network fuel consumption with genetic algorithm

Takerhi

Dąbrowski

2022

Energy Exploration & Exploitation

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In this paper genetic algorithm (GA) was used for the optimization of two natural gas network, the study focuses on fuel consumption minimization of the second gas network. Studies using GA to simultaneously optimize a gas network and a compressor station based on the constraint of the gas network and compressor station are limited. The relationship between several compressor speed and the total fuel consumption and the relationship between the sum of pressure drop in compressor station loops and compressor inlet flow are assessed for optimization. For this purpose, the optimization of two networks was presented and the results were compared with result from analytical methods. The first network problem was to determine the flow rates and node pressures under a given load, which serves as a guide in using GA. Comparison with result from analytical solution showed good agreement of predicted values. The second network consisted of two compressor stations, each containing six compressors with the objective to optimize the fuel consumption of the system. The simulation was divided into two main simulations, the first simulation was the flow optimization, which results in the optimum flow, based on the fitness function, which is the summation of pressure loss for each compressor station. In the second simulation which was the speed optimization, the optimum set of compressor speed was obtained which depends on the fitness function, which is the minimum fuel consumption, the flow obtained from the flow optimization served as input and remained constant. All speeds were simulated together. The predicted results were compared with literature and showed GA can be used for compressor station fuel optimization but still requires improvement. Based on the outcomes, data on natural gas network operations should be accessible to encourage studies on fuel consumption and CO2 emissions minimization.

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Section: Discussionmentioning

confidence: 99%

Optimization of a gas network fuel consumption with genetic algorithm

Takerhi

Dąbrowski

2022

Energy Exploration & Exploitation

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“…Modelling and simulation of natural gas networks have enjoyed wide usage in recent times with many studies aiming to optimise different parameters ranging from a single objective such as the operating cost [45] to multiple operational objectives [46]. The inclusion of natural gas network models in power systems reliability studies has also been suggested by Munoz et al [47] who explains that the methodology became expedient in the wake of increasing construction of combined-cycle power plants in which the gas and electricity systems are linked together for power generation in Spain and other countries.…”

Section: Gas Network Modellingmentioning

confidence: 99%

An Investigation into the Volumetric Flow Rate Requirement of Hydrogen Transportation in Existing Natural Gas Pipelines and Its Safety Implications

Abbas

Hassani

Burby

et al. 2021

Gases

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As an alternative to the construction of new infrastructure, repurposing existing natural gas pipelines for hydrogen transportation has been identified as a low-cost strategy for substituting natural gas with hydrogen in the wake of the energy transition. In line with that, a 342 km, 36″ natural gas pipeline was used in this study to simulate some technical implications of delivering the same amount of energy with different blends of natural gas and hydrogen, and with 100% hydrogen. Preliminary findings from the study confirmed that a three-fold increase in volumetric flow rate would be required of hydrogen to deliver an equivalent amount of energy as natural gas. The effects of flowing hydrogen at this rate in an existing natural gas pipeline on two flow parameters (the compressibility factor and the velocity gradient) which are crucial to the safety of the pipeline were investigated. The compressibility factor behaviour revealed the presence of a wide range of values as the proportions of hydrogen and natural gas in the blends changed, signifying disparate flow behaviours and consequent varying flow challenges. The velocity profiles showed that hydrogen can be transported in natural gas pipelines via blending with natural gas by up to 40% of hydrogen in the blend without exceeding the erosional velocity limits of the pipeline. However, when the proportion of hydrogen reached 60%, the erosional velocity limit was reached at 290 km, so that beyond this distance, the pipeline would be subject to internal erosion. The use of compressor stations was shown to be effective in remedying this challenge. This study provides more insights into the volumetric and safety considerations of adopting existing natural gas pipelines for the transportation of hydrogen and blends of hydrogen and natural gas.

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“…Previously multi-objective ant colony optimization (ACO) technique has been extended to a barrel grid (Arya and Honwad, 2018a). Some of the work on a similar objective was carried out by Chebouba A, 2015;Demissie and Zhu, 2017;Osiadacz and Isoli, 2020. The technique, however, has not been applied to a typical multi-distribution pipeline grid.…”

Section: Review Of Gas Pipeline Optimization Techniquesmentioning

confidence: 99%

Optimal operation of a multi-distribution natural gas pipeline grid: an ant colony approach

Arya

2021

J Petrol Explor Prod Technol

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The enormous cost of transporting oil and gas through pipelines and the operational benefits that the industry receives through optimization has incited analysts for decades to find optimization strategies that help pipeline managers operate pipeline grids with the least expense. The paper aims to minimize the pipeline grids' operating costs using an ant colony optimization strategy. The article constructs a multi-objective modeling framework for a natural gas pipeline grid based on data from the French gas pipeline network corporation 'Gaz De France,' using pipeline and compressor hydraulics. The gas pipeline grid comprises seven gas supply nodes and nineteen gas distribution centers. Seven compressor stations provided at various locations on the pipeline route raise the gas pressure. Two competing objectives of reducing fuel usage in compressors and increasing throughput at distribution centers are acknowledged to reduce the pipeline's operating cost. The 'multi-objective ant colony optimization (MOACO)' approach is implemented to the pipeline transportation model to reduce the natural gas pipeline grid's operating cost. The process variables include the amount of gas flowing through the pipe and the pressure at pipe nodes. This method provides the optimum solution for each fuel consumption level on each compressor, and it does so by producing a Pareto front for each of the nineteen gas distribution points. The blueprints of the methodology used and the findings collected intend to guide pipeline managers and select the best of the most preferred solutions.

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Multi-Objective Optimization of Gas Pipeline Networks

Cited by 11 publications

References 21 publications

Optimization of a gas network fuel consumption with genetic algorithm

Optimization of a gas network fuel consumption with genetic algorithm

An Investigation into the Volumetric Flow Rate Requirement of Hydrogen Transportation in Existing Natural Gas Pipelines and Its Safety Implications

Optimal operation of a multi-distribution natural gas pipeline grid: an ant colony approach

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