An Optimization Method for a Compressor Standby Scheme Based on Reliability Analysis

Xuejie Li, Yuan Xue, Yuxing Li and Qingshan Feng ()
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Xuejie Li: Shandong Provincial Key Laboratory of Oil & Gas Storage and Transportation Safety, China University of Petroleum, Qingdao 266580, China
Yuan Xue: Shandong Provincial Key Laboratory of Oil & Gas Storage and Transportation Safety, China University of Petroleum, Qingdao 266580, China
Yuxing Li: Shandong Provincial Key Laboratory of Oil & Gas Storage and Transportation Safety, China University of Petroleum, Qingdao 266580, China
Qingshan Feng: Shandong Provincial Key Laboratory of Oil & Gas Storage and Transportation Safety, China University of Petroleum, Qingdao 266580, China

Energies, 2022, vol. 15, issue 21, 1-16

Abstract: The reliability of the compressor system determines the gas supply safety. An important method to improve the reliability is to set up standby compressors in stations, conducted by the standby compressor or power. A lack of quantitative assessments of standby compressors often results in more spare compressors or power than actually needed, which wastes money. In this study, a reliability-based method is proposed to determine the numbers and positions of the standby compressors, which can reduce investments, and ensure reliability. Firstly, Monte Carlo method was used to calculate the compressor outage probability of the whole pipeline, respectively, through which the initial number of standby compressors was obtained. Further, the standby schemes were designed, in which the positions of the failed compressors were obtained by the Monte Carlo simulation. Moreover, the worst situation in which the compressors were shut down was used to test the standby scheme, calculating the flow reliability, pressure boundary, and total power. Finally, using the Xin–Yue–Zhe pipeline as a case study, the results indicate that the number of standby compressors in the improved schemes was reduced by seven and the pipeline reliability reached 96.86%.

Keywords: gas pipeline; compressor system; standby scheme; reliability analysis; Monte Carlo; power (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: 2022
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