石油炼制与化工 ›› 2024, Vol. 55 ›› Issue (7): 170-176.

• 综述 • 上一篇    

石化企业蒸汽动力系统优化研究进展

谢煜,秦康,吴昊   

  1. 中石化石油化工科学研究院有限公司

  • 收稿日期:2023-11-24 修回日期:2024-03-09 出版日期:2024-07-12 发布日期:2024-06-28
  • 通讯作者: 秦康 E-mail:qinkang.ripp@sinopec.com
  • 作者简介:2024-07-01
  • 基金资助:
    中国石油化工股份有限公司科技项目

RESEARCH PROGRESS OF STEAM POWER SYSTEM OPTIMIZATION IN PETROCHEMICAL ENTERPRISES


  • Received:2023-11-24 Revised:2024-03-09 Online:2024-07-12 Published:2024-06-28

摘要: 蒸汽动力系统是石化企业的重要组成部分,也是能源消耗的主要环节,具有较大的节能潜力。优化蒸汽动力系统结构和运行参数,能够显著降低运行成本,对石化企业节能降碳和挖潜增效具有重要意义。对蒸汽动力系统优化的基本方法、研究进展和应用情况进行综述,着重介绍了启发式方法、元启发式方法、热力学目标法和数学规划法等蒸汽动力系统优化方法。在此基础上,综述了蒸汽动力系统的不确定性优化和多目标优化。归纳了蒸汽动力系统存在的不确定性因素,并介绍了不确定条件下蒸汽动力系统优化的研究进展。总结了蒸汽动力系统的优化目标,并对蒸汽动力系统的多目标优化建模和求解方法进行介绍。最后,对蒸汽动力系统优化的发展方向提出建议。

关键词: 蒸汽动力系统, 优化方法, 不确定性, 多目标优化

Abstract: Steam power system is an important part of petrochemical enterprises, but also the main link of energy consumption, with great energy-saving potential. Optimization of steam power system structure and operating parameters can significantly reduce operating costs, which is of great significance in saving energy, reducing carbon and creating efficiency in petrochemical enterprises. The basic methods, research progress and application of steam power system optimization were reviewed, and the optimization methods of steam power system, such as heuristic method, meta-heuristic method, thermodynamic objective method and mathematical programming method, were emphatically introduced. On this basis, the uncertainty optimization and multi-objective optimization of steam power system were reviewed. The uncertainty factors of steam power system were summarized, and the research progress of steam power system optimization under uncertainty was introduced. The optimization objectives of steam power system were summarized, and the multi-objective optimization modeling and solution methods of steam power system were introduced. Finally, the development direction of steam power system optimization was proposed.

Key words: steam power system, optimization method, uncertainty, multi-objective optimization