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<p>With the increasing global focus on energy efficiency and environmental protection, the energy consumption of compressor units has gradually become a research hotpot. This study integrates process simulation with machine learning optimization to establish a simulation model of the Fan 6 station compressor unit utilizing Aspen software. The model’s reliability is rigorously validated through comparative analysis with field-collected operational data. Based on 1000 sets of simulation data, machine learning methods are employed to optimize and analyze the energy consumption of the compressor unit, establishing an energy consumption optimization model for the compressor unit. This achieves a global optimal energy consumption analysis under different operating conditions, establishing both theoretical foundations and actionable operational guidelines for energy consumption optimization of compressor units at various stations.</p>

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Research on Energy Consumption Optimization Model for Compressor Units in Oil and Gas Processing Facility

  • 期刊论文

  • 发表日期：

    2025年9月1日

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  • Hongqiao Yan,
  • Wencai Liu

摘要

With the increasing global focus on energy efficiency and environmental protection, the energy consumption of compressor units has gradually become a research hotpot. This study integrates process simulation with machine learning optimization to establish a simulation model of the Fan 6 station compressor unit utilizing Aspen software. The model’s reliability is rigorously validated through comparative analysis with field-collected operational data. Based on 1000 sets of simulation data, machine learning methods are employed to optimize and analyze the energy consumption of the compressor unit, establishing an energy consumption optimization model for the compressor unit. This achieves a global optimal energy consumption analysis under different operating conditions, establishing both theoretical foundations and actionable operational guidelines for energy consumption optimization of compressor units at various stations.