Intelligent optimization of natural gas pipeline compressor stations

Natural gas compressor stations account for a substantial share of energy consumption in long-distance pipeline systems, making operational optimization important for improving efficiency and reducing emissions. This study addresses the load allocation problem of parallel compressor units by formulating a mixed-integer nonlinear optimization model that incorporates operational constraints and thermodynamic characteristics. A hybrid intelligent optimization framework is developed to improve solution quality and robustness for highly constrained operating conditions. In a representative compressor station case, the optimized strategy reduces power consumption from approximately 32 MW-24.58 MW, corresponding to an energy saving of about 23%. These findings demonstrate the potential of intelligent optimization to support energy-efficient and low-carbon operation of natural gas transportation infrastructure.