Energy conservation optimization of natural gas processing plant supercharging system based on exergic analysis

Objective To address the issues of high energy consumption and low exergy efficiency in conventional natural gas processing plants due to aging equipment and fluctuating gas sources. This study proposes a collaborative optimization strategy based on exergy analysis and response surface methodology to minimize irreversible exergy losses and enhance the energy utilization efficiency of the system by adjusting process parameters.

Method  Taking a natural gas processing plant in Northwest China as the research object, the natural gas processing plant has an annual processing capacity of 55×10⁸ m³. A process model based on HYSYS was constructed for exergy analysis to identify the compression system as the key energy-consuming unit, accounting for 68.13% of exergy losses. Sensitivity analysis and Box-Behnken design were used to optimize four parameters of compressor: suction pressure (1.8-2.5 MPa), suction temperature (6-20 ℃), discharge pressure (4.8-6.0 MPa), and air cooler outlet temperature (35-55 ℃). A quadratic polynomial regression model was established (R²=0.996 3, prediction error＜0.9%), and the significance of the model was verified through a variance analysis (P＜0.000 1).

Result The optimal parameters combination after optimization was: suction pressure, 2.5 MPa; suction temperature, 6.03 ℃; discharge pressure, 4.8 MPa; and air cooler outlet temperature, 55 ℃. The exergy consumption per unit product gas was reduced to 6.35 kJ/m³, and the irreversible exergy loss was decreased by 5 104.68×10⁴ kJ/h. Economic benefit analysis indicated that the annual energy savings reached 1.134×10⁷ kW·h, and CO₂ emissions were reduced by 2 100 tons. The payback period was 6~7 months.

Conclusion The integration of exergy analysis and response surface methodology can achieve energy-saving optimization of the compression system in natural gas processing plants without equipment modification. The study revealed the nonlinear influence mechanism of compressor pressure parameters on exergy losses, and proposed a parameter sensitivity ranking: discharge pressure＞suction pressure＞suction temperature＞air cooler temperature, providing a theoretical basis for on-site control and demonstrating significant economic and environmental benefits. Future research should focus on the dynamic adaptability to complex operating conditions, the influence mechanism of multi-energy coupling, and intelligent real-time optimization technology to enhance the industrial applicability of the model.