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Predicting Monthly Energy Consumption of Crude Oil Pipelines Using Process Simulation and Optimization

[+] Author Affiliations
Lili Zuo, Changchun Wu, Xiaorui Zhang

China University of Petroleum - Beijing, Beijing, China

Song Liu, Yong Jiang

Beijing Oil and Gas Pipeline Control Center of CNPC, Beijing, China

Paper No. IPC2018-78326, pp. V003T04A012; 8 pages
doi:10.1115/IPC2018-78326
From:
  • 2018 12th International Pipeline Conference
  • Volume 3: Operations, Monitoring, and Maintenance; Materials and Joining
  • Calgary, Alberta, Canada, September 24–28, 2018
  • Conference Sponsors: Pipeline Division
  • ISBN: 978-0-7918-5188-3
  • Copyright © 2018 by ASME

abstract

Based on process principles and the operational features of crude oil pipelines, this research developed mathematical models to optimize steady-state pipeline operation, to apportion monthly flow into daily or hourly flow rates, and to predict monthly energy consumption. Corresponding algorithms were also developed. Because these models and corresponding algorithms are process-based, they are suitable for predicting monthly energy consumption of existing isothermal and hot crude oil pipelines. The predicted monthly energy consumption of crude oil pipelines depends on which flow distribution method is used, which pumping operation scheme is used and which heating operation scheme is used, with different flow distributions, different pumping and heating operation scheme yielding a range of monthly energy consumption predictions for a given transportation volume. The minimum monthly energy consumption can be determined from these predictions, and the interval of the predictions can indicate the extent to which the flow rate fluctuation affects pipeline energy consumption. Both of these findings can be used by pipeline operators to reduce the amount of energy needed to operate crude oil pipelines.

Copyright © 2018 by ASME

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