Journal of South China University of Technology(Natural Science) >

2025 , Vol. 53 >Issue 7: 80 - 92

DOI: https://doi.org/10.12141/j.issn.1000-565X.240412

Electronics, Communication & Automation Technology

An Energy-Saving Optimization Method of Air-Conditioning System for Electric Drive Workshop Based on IBK-IPS Algorithm

  • GONG Xiaorong ,
  • WANG Xin ,
  • XIONG Weiqing ,
  • WANG Tangliang ,
  • ZHANG Hongming
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  • College of Mechanical Engineering，Chongqing University of Technology，Chongqing 400054，China
龚小容（1986—），女，博士，副教授，主要从事空调系统建模及优化控制研究。E-mail： gxr@cqut.edu.cn
熊维清（1996—），女，博士，讲师，主要从事空调系统节能优化研究。E-mail： wq.xiong@cqut.edu.cn

Received date: 2024-08-22

  Online published: 2024-12-13

Supported by

the National Natural Science Foundation of China(52405532);the Natural Science Foundation of Chongqing City(CSTB2024NSCQ-MSX0425);the Science and Technology Research Program of Chongqing Municipal Education Commission(KJQN202401136)

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Abstract

To address the problems of high operational energy consumption and low efficiency in air-conditioning system for electric drive workshops, this paper proposed a dynamic energy-saving optimization method based on the IBK-IPS algorithm, taking into account the mutual constraints of each equipment of the air-conditioning system. Firstly, the influence mechanism among system components were analyzed, and mathematical models of energy consumption and constraints conditions for each device were established to an objective function for system energy consumption. Then, an improved Black Kite-Particle Swarm (IBK-IPS) algorithm was introduced to optimize operational parameters such as water temperature, flow rate, and air volume, thereby improving the accuracy and effectiveness of system parameter control. Subsequently, a simulation model of the cooling water system and chilled water system of the air-conditioning system is developed using the Simulink platform to evaluate the performance and accuracy of the parameter optimization. Finally, the method is practically applied in an electric drive workshop to verify the practical effect and feasibility of the proposed method. The results of simulation experiments and practical application tests show that: the operational energy consumption of the system is effectively reduced, achieving an energy-saving rate of 11.23%~34.68%, and improves operational energy efficiency by 11.53%~41.75%. Compared with the PS, BK, and BK-PS algorithms, the IBK-IPS algorithm delivers superior energy-saving performance, with convergence speeds improved by 27.27%, 61.90%, and 69.23%, respectively. In real-world testing under five different load conditions, the optimized system achieved energy-saving rates of 22.61%, 17.24%, 7.48%, 14.97%, and 12.64%, respectively. In summary, the energy-saving optimization method proposed in this paper can effectively solve the problem of high energy consumption and low efficiency of the air-conditioning system operation in the electric drive workshop, which has good energy-saving effect and practicability, and can provide new ideas for the research of energy-saving optimization of air-conditioning system.

Key words： electric drive workshop; air-conditioning system; mutual constraint; improved black-winged kite and particle swarm algorithm; dynamic energy-saving optimization method

Cite this article

GONG Xiaorong , WANG Xin , XIONG Weiqing , WANG Tangliang , ZHANG Hongming . An Energy-Saving Optimization Method of Air-Conditioning System for Electric Drive Workshop Based on IBK-IPS Algorithm[J]. Journal of South China University of Technology(Natural Science), 2025 , 53(7) : 80 -92 . DOI: 10.12141/j.issn.1000-565X.240412

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