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基于智能控制策略的卷烟厂空调系统节能优化

阮望 谷红玉 徐硕 韩艳琴 温佳祺 王婧

烟草科技2025,Vol.58Issue(10):95-102,8.
烟草科技2025,Vol.58Issue(10):95-102,8.DOI:10.16135/j.issn1002-0861.2025.0458

基于智能控制策略的卷烟厂空调系统节能优化

Energy-saving optimization of air conditioning system in cigarette factory based on intelligent control strategy

阮望 1谷红玉 1徐硕 1韩艳琴 1温佳祺 2王婧1

作者信息

  • 1. 河北白沙烟草有限责任公司保定卷烟厂,河北省保定市莲池区焦庄乡荷华路999号 071000
  • 2. 河北大学质量技术监督学院,河北省保定市莲池区七一东路2666号 071000||零碳能源建筑与计量技术教育部工程研究中心,河北省保定市莲池区焦庄乡荷华路999号 071000
  • 折叠

摘要

Abstract

To reduce the energy consumption of air conditioning system in cigarette production process,an intelligent control strategy based on temperature and humidity deviation regulation mechanism and machine learning algorithm was proposed for upgrading the K6 air conditioning system in the primary processing department of Baoding Cigarette Factory.On the basis of the modification of surface cooling valve and the addition of a high-performance energy-saving server,along with the improvement of PID control technology and the integration of the regional target control optimization module,the intelligent regulation module of wet equilibrium state and the critical operation state control module,the characteristic data,set values of temperature and humidity of the air conditioning system was adjusted in real time to achieve the optimization of the control strategy and establish an intelligent energy-saving monitoring system for air conditioning.Comparative experiments were conducted on the air conditioning system before and after the optimization.The results showed that both the temperature and humidity in the primary processing department before and after the optimization met the technical requirements.The optimized system featured remarkable energy-saving effect,showing decreases of 76.2%,39.5%and 11.8%respectively in the consumption of steam,cold water and electricity.This study provides technical references for the energy-saving improvements in similar industrial facilities.

关键词

空调系统/温湿度偏差控制/机器学习算法/节能减排

Key words

Air conditioning system/Temperature and humidity deviation control/Machine learning algorithm/Energy conservation and emission reduction

分类

轻工纺织

引用本文复制引用

阮望,谷红玉,徐硕,韩艳琴,温佳祺,王婧..基于智能控制策略的卷烟厂空调系统节能优化[J].烟草科技,2025,58(10):95-102,8.

基金项目

河北中烟工业有限责任公司科技项目"绿色智慧节能空调自控系统的研发"(HBZY2023A082). (HBZY2023A082)

烟草科技

OA北大核心

1002-0861

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