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

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

Natural gas

Natural gas transportation

Natural gas pipelines

Cost reduction

Compressors

Petroleum transportation

Operating costs

Gases

Compressibility of gases

Ant colony optimization

Warehouses

Managers

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. 2021, The Author(s).

3859-3878

10

11

Journal of Petroleum Exploration and Production Technology

2021

Arya, Adarsh Kumar

journalArticle

21900558

10.1007/s13202-021-01266-3