工业压缩空气系统设备选型和供气调度优化

徐勇; 宋晓维; 聂亚玲; 朱闽; 熊新阳; 周军; 宋晓玲; 肖炘

doi:10.13205/j.hjgc.202508014

工业压缩空气系统设备选型和供气调度优化

doi: 10.13205/j.hjgc.202508014

徐勇¹,
宋晓维²,
聂亚玲²,
朱闽²,
熊新阳¹,
周军¹,
宋晓玲¹,
肖炘^1,2, ,

1. 新疆天业集团, 新疆石河子 832000;
2. 中国科学院过程工程研究所, 北京 100190

基金项目:

国家自然科学基金青年科学基金项目“耦合能-水-碳关联机制的‘生产-生活-生态’空间优化研究”（42101261）；国家重点研发计划项目“退役锂电池回收利用全链条集成全局优化研究”（2024YFC3909801）

详细信息

作者简介:
徐勇，本科，高级工程师，主要研究方向为计算机科学。6758557@qq.com

通讯作者:
肖炘，研究员，主要从事工业智能全局优化研究工作。xxiao@ipe.ac.cn

计量
- 文章访问数: 73
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- 被引次数: 0
出版历程
- 收稿日期: 2025-04-16
- 录用日期: 2025-08-19
- 修回日期: 2025-07-09

Optimization of equipment selection and air supply scheduling for industrial compressed air systems

1. Tianye Group, Shihezi 832000, China;
2. Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China

摘要

摘要: 压缩空气系统是工厂的基础设施和重要动力来源。根据工厂生产用气需求和压缩空气系统运行特点，选择合理的设备组合和适宜的用气调度方案，是隐藏在系统节能降耗工程的要求背后，需以全局优化方法重点解决的难题。基于此，提出了一种考虑了空压机设备选型与管网负荷变化的联合调度优化方法，通过纳入生产需求、可选机型配置、时变电价等条件以及用气负荷波动不确定性，构建了以空压机用能和投资成本最小为优化目标的混合整数线性规划（MILP）模型，通过全局优化求解，实现系统最优设备选型组合和用气错峰调度。以某企业园区级压缩空气系统为例，获得了其包含稳健最优设备选型和用气错峰调度的整体决策方案，根据不同的用气负荷，系统峰值负荷可降低18.05%~27.16%，耗电量可节约33.33%~34.56%，年度总成本可降低28.35%~31.42%，最高可节约2488.16万元。结果表明：就工厂生产需求与压缩机运行、供气端和用气端匹配为主的优化方案，可兼顾经济效益与节能需求，对压缩空气系统升级改造具有重要意义。
- 压缩空气系统 /
- 设备选型优化 /
- 用气调度优化 /
- 混合整数线性优化 /
- 能源效率
Abstract: Compressed air systems （CAS） are essential infrastructure and crucial power sources in factories， but are also major energy consumers. Selecting optimal equipment combinations and air supply scheduling to match factory’s demand and system’s characteristics is a core energy-saving challenge that requires global optimization. This study proposed a joint scheduling optimization approach that integrating air compressor equipment selection with pipeline network load variations. By incorporating production demand， available compressor configurations， time-of-day tariffs， and uncertainties in air demand fluctuations， we constructed a mixed-integer linear programming （MILP） model aimed at minimizing energy consumption and investment cost of air compressors. Solving the model through global optimization enabled us to achieve optimal equipment combinations and peak-shifting air supply scheduling. By Applying to an industrial park-level CAS， the proposed method produced an overall decision plan including robust optimal equipment combinations and peak-shifting air usage scheduling. Under different air demand scenarios， the system’s peak load can be reduced by 18.05% to 27.16%， energy consumption saved by 33.33% to 34.56%， and annual total cost lowered by 28.35% to 31.42%（ up to 24.88 million yuan）. The results indicated that this optimization strategy， which primarily matches production demand with compressor operation on both the supply and demand sides， effectively balances economic benefits and energy-saving needs. It can provide significant guidance for upgrading and retrofitting CAS.
- compressed air system /
- equipment selection optimization /
- air supply scheduling /
- mixed-integer linear programming /
- energy efficiency

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