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

XU Yong; SONG Xiaowei; NIE Yaling; ZHU Min; XIONG Xinyang; ZHOU Jun; SONG Xiaoling; XIAO Xin

doi:10.13205/j.hjgc.202508014

Volume 43 Issue 8

Aug. 2025

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Article Navigation > ENVIRONMENTAL ENGINEERING > 2025 > 43(8): 158-168

XU Yong, SONG Xiaowei, NIE Yaling, ZHU Min, XIONG Xinyang, ZHOU Jun, SONG Xiaoling, XIAO Xin. Optimization of equipment selection and air supply scheduling for industrial compressed air systems[J]. ENVIRONMENTAL ENGINEERING , 2025, 43(8): 158-168. doi: 10.13205/j.hjgc.202508014

Citation:

XU Yong, SONG Xiaowei, NIE Yaling, ZHU Min, XIONG Xinyang, ZHOU Jun, SONG Xiaoling, XIAO Xin. Optimization of equipment selection and air supply scheduling for industrial compressed air systems[J]. ENVIRONMENTAL ENGINEERING , 2025, 43(8): 158-168. doi: 10.13205/j.hjgc.202508014

Citation:

XU Yong, SONG Xiaowei, NIE Yaling, ZHU Min, XIONG Xinyang, ZHOU Jun, SONG Xiaoling, XIAO Xin. Optimization of equipment selection and air supply scheduling for industrial compressed air systems[J]. ENVIRONMENTAL ENGINEERING , 2025, 43(8): 158-168. doi: 10.13205/j.hjgc.202508014

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

doi: 10.13205/j.hjgc.202508014

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

Received Date: 2025-04-16
Accepted Date: 2025-08-19
Rev Recd Date: 2025-07-09

Abstract

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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References(37)

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