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<p>To solve the complex control problem of balancing economic efficiency, safety and stability in the scheduling optimization process of long-distance oil pipelines, this paper had constructed and verified an oil transportation equilibrium control method based on a hierarchical architecture and scheduling optimization model, including upper-level scheduling optimization layer for global economic planning over long periods using a computationally efficient steady-state hydrodynamics model, and the middle-level coordination control layer for dynamic tracking and disturbance suppression in short periods, embedding a high-precision discretized transient hydrodynamics model into the model predictive control algorithm. The results showed that under normal operating conditions, compared with traditional manual scheduling, the hierarchical optimization strategy can save approximately 61.3% of energy consumption, and reduce the standard deviation of pressure fluctuations at the end of the pipeline from 0.511 MPa to 0.200 MPa, achieving perfect pressure stability. When facing sudden disturbances such as increased demand or equipment failures, this method can quickly restore stability within 1-2 minutes, avoiding dangerous pressure overshoots and operational interruptions. Moreover, this framework had multi-objective optimization capabilities, allowing decision-makers to weigh different strategies such as “energy conservation priority” and “stability priority” based on operational needs. For example, achieving the ultimate stability required a 36% higher energy cost compared to the energy-saving mode.</p>

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Research on Oil Pipeline Balance Control Method Based on Hierarchical Architecture and Scheduling Optimization Model

  • 期刊论文

  • 发表日期：

    2026年3月1日

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  • Li Ma,
  • Haiyong Zhao,
  • Jianhua Zhao,
  • Weifeng Kang,
  • Zhaokai Li

摘要

To solve the complex control problem of balancing economic efficiency, safety and stability in the scheduling optimization process of long-distance oil pipelines, this paper had constructed and verified an oil transportation equilibrium control method based on a hierarchical architecture and scheduling optimization model, including upper-level scheduling optimization layer for global economic planning over long periods using a computationally efficient steady-state hydrodynamics model, and the middle-level coordination control layer for dynamic tracking and disturbance suppression in short periods, embedding a high-precision discretized transient hydrodynamics model into the model predictive control algorithm. The results showed that under normal operating conditions, compared with traditional manual scheduling, the hierarchical optimization strategy can save approximately 61.3% of energy consumption, and reduce the standard deviation of pressure fluctuations at the end of the pipeline from 0.511 MPa to 0.200 MPa, achieving perfect pressure stability. When facing sudden disturbances such as increased demand or equipment failures, this method can quickly restore stability within 1-2 minutes, avoiding dangerous pressure overshoots and operational interruptions. Moreover, this framework had multi-objective optimization capabilities, allowing decision-makers to weigh different strategies such as “energy conservation priority” and “stability priority” based on operational needs. For example, achieving the ultimate stability required a 36% higher energy cost compared to the energy-saving mode.