Multi-Objective Optimization of Gas Storage Compressor Units Based on NSGA-II

Lianbin Zhao, Lilin Fan, Jun Lu, Mingmin He, Su Qian, Qingsong Wei, Guijiu Wang, Haoze Bai, Hu Zhou, Yongshuai Liu and Cheng Chang ()
Additional contact information
Lianbin Zhao: PipeChina Energy Storage Technology Co., Ltd., Shanghai 100120, China
Lilin Fan: PipeChina Energy Storage Technology Co., Ltd., Shanghai 100120, China
Jun Lu: PipeChina Energy Storage Technology Co., Ltd., Shanghai 100120, China
Mingmin He: PipeChina Energy Storage Technology Co., Ltd., Shanghai 100120, China
Su Qian: PipeChina Energy Storage Technology Co., Ltd., Shanghai 100120, China
Qingsong Wei: PipeChina Energy Storage Technology Co., Ltd., Shanghai 100120, China
Guijiu Wang: PipeChina Energy Storage Technology Co., Ltd., Shanghai 100120, China
Haoze Bai: PipeChina Energy Storage Technology Co., Ltd., Shanghai 100120, China
Hu Zhou: College of Mechanical and Transportation Engineering, China University of Petroleum, Beijing 102249, China
Yongshuai Liu: College of Mechanical and Transportation Engineering, China University of Petroleum, Beijing 102249, China
Cheng Chang: College of Mechanical and Transportation Engineering, China University of Petroleum, Beijing 102249, China

Energies, 2025, vol. 18, issue 13, 1-26

Abstract: This study addresses the parallel operation of multiple compressor units in the gas injection process of gas storage facilities. A multi-objective optimization model based on the NSGA-II algorithm is proposed to maximize gas injection volume while minimizing energy consumption. Thermodynamic models of compressors and flow–heat transfer models of air coolers are established. The influence of key factors, including inlet and outlet pressures, temperatures, and natural gas composition, on compressor performance is analyzed using the control variable method. The results indicate that the first-stage inlet pressure has the most significant impact on gas throughput, and higher compression ratios lead to increased specific energy consumption. The NSGA-II algorithm is applied to optimize compressor start–stop strategies and air cooler speed matching under high, medium, and low compression ratio conditions. This study reveals that reducing the compression ratio significantly enhances the energy-saving potential. Under the investigated conditions, adjusting air cooler speed can achieve approximately 2% energy savings at high compression ratios, whereas at low compression ratios, the energy-saving potential reaches up to 8%. This research provides theoretical guidance and technical support for the efficient operation of gas storage compressor units.

Keywords: gas storage compressors; multi-objective optimization; NSGA-II; air cooling system; energy efficiency (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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