Elasticity evaluation and improvement of natural gas network based on prior information aided decision-making strategy

Abstract

The natural gas pipeline is the dominant approach for long-distance natural gas transportation, the safety and efficiency of which are of great significance. Faced with various potential hazards, the elasticity of natural gas pipelines against abnormal events has not been discussed. This work categorizes these abnormal events into three types according to their influences on the pipelines and proposes a method to evaluate and improve elasticity against these abnormal events. By introducing elastic residue energy, indexes to assess elasticity were defined across six dimensions of operational efficiency. An intelligent decision-making strategy based on prior information is proposed to enhance pipeline elasticity. Through simulations on a practical natural gas pipeline segment, the performance of the proposed strategy is discussed. The proposed strategy is validated as effective under the three types of abnormal events, with elasticity increasing by 144%, 28%, and 12%, respectively, which can be considered a significant improvement.