循环水冷却塔单元的智能控制系统设计  

Design of Intelligent Control System for Circulating Water Cooling Tower Unit

作　　者：李翠 胡广 蒲韵竹 余云飞[1] Li Cui;Hu Guang;Pu Yunzhu;Yu Yunfei(MCC CISDI Engineering Co.,Ltd.,Chongqing 400013)

机构地区：[1]中冶赛迪工程技术股份有限公司,重庆400013

出　　处：《冶金设备》2024年第6期26-29,59,共5页Metallurgical Equipment

摘　　要：冷却塔作为工业生产和民用循环水冷却系统的重要组成部分,在维持系统稳定性和提高能源利用效率方面发挥着关键作用。然而,传统冷却塔控制方法往往基于定速或简单水温反馈控制,难以适应复杂、多变的环境和运行条件,导致冷却塔管理粗放、能耗居高不下。本文提出了一种基于深度学习的智能控制方法,旨在实现对冷却塔风机运行参数的实时优化调节,达到稳定水温同时降低能耗的目的。根据长期的实验结果表明,该智能控制方法可以在不影响冷却效果的前提下,显著降低冷却塔系统的能耗,能耗降低幅度可达30%。该方法具备良好的实用性与可推广性,充分利用冷却塔变频调速和运行策略组合,可进一步联合循环水泵等对冷却塔等循环水单元节能减排产生突出的效果。As an important component of industrial production and civilian circulating water cooling systems, cooling towers play a crucial role in maintaining system stability and improving energy utilization efficiency. However, traditional cooling tower control methods are often based on constant speed or simple water temperature feedback control, which is difficult to adapt to complex and changing environments and operating conditions, resulting in extensive cooling tower management and high energy consumption. This article proposes an intelligent control method based on deep learning, aimed at achieving real-time optimization and adjustment of the operating parameters of cooling tower fans, achieving the goal of stabilizing water temperature while reducing energy consumption. According to long-term experimental results, this intelligent control method can significantly reduce the energy consumption of the cooling tower system without affecting the cooling effect, with a reduction of up to 30% in energy consumption. This method has good practicality and generalizability, fully utilizing the combination of variable frequency speed regulation and operation strategy of cooling towers, and can further combine with circulating water pumps to achieve outstanding energy-saving and emission reduction effects on cooling towers and other circulating water units.

关 键 词：冷却塔 智能控制 节能优化 深度学习 

分 类 号：X757[环境科学与工程—环境工程]