Theoretical framework improves gas concentration by 11% and purity by 0.3 m3/min in pipeline networks, indicating intelligent control benefits.
In order to address the issue of inadequate negative pressure distribution in the gas extraction pipeline network and to enhance the efficiency of gas extraction, a study was conducted on the mechanisms of mutual influence between various branches within the gas extraction pipeline network. Using graph theory principles, a gas extraction network graph was built, and the gas extraction pipeline network was solved through the assignment adjustment iterative method. The study summarizes the sensitivity analysis of various control parameters, regulation patterns of branch valves and extraction pump control parameters at different network positions, and the impact of time parameters on the network’s operational conditions. Based on the solution results, an intelligent gas extraction control strategy was proposed. The results indicate that, under safety and efficiency constraints, gas concentration increased by approximately 11%, and gas purity increased by 0.3 m3/min, resulting in a 4.7% improvement after the implementation of intelligent control. The overall performance of the pipeline network was significantly enhanced. These research findings are of great significance for achieving efficient gas extraction.
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Du et al. (2025) studied this question.
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