[1]王之江,牛豫海,张静,等.基于AI边缘计算的送水泵站智能调度与优化[J].中国给水排水,2026,42(12):163-169.
　WANGZhijiang,NIUYuhai,ZHANGJing,et al.Intelligent Scheduling and Optimization of Water Pumping Station Based on AI Edge Computing[J].China Water & Wastewater,2026,42(12):163-169.
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基于AI边缘计算的送水泵站智能调度与优化

中国给水排水[ISSN:1000-4062/CN:12-1073/TU] 卷: 第42卷 期数: 2026年第12期 页码: 163-169 栏目: 出版日期: 2026-06-17
Title:
Intelligent Scheduling and Optimization of Water Pumping Station Based on AI Edge Computing
作者:
王之江1， 牛豫海2， 张静2， 张自力2， 张娟2， 赵博洋1， 李伟3， 尹学锐3
（1.辛集市建投水务有限责任公司，河北 辛集 052360；2.河北建投水务投资有限公司，河北 石家庄 050022；3.天津三博水科技有限公司，天津 300384）
Author(s):
WANG　Zhijiang1， NIU　Yuhai2， ZHANG　Jing2， ZHANG　Zili2， ZHANG　Juan2， ZHAO　Boyang1， LI　Wei3， YIN　Xuerui3
（1. Xinji Construction Investment Water Co. Ltd.， Xinji 052360， China； 2. Hebei Construction Investment Water Investment Co. Ltd.， Shijiazhuang 050022， China； 3. Tianjin Sanbo Water Technology Co. Ltd.， Tianjin 300384， China）
关键词:
AI边缘计算;  送水泵站;  智能调度;  优化运行;  市政管网;  节能降耗;  数据优化模型
Keywords:
AI edge computing;  water pumping station;  intelligent scheduling;  optimized operation;  municipal pipeline network;  energy saving and consumption reduction;  data optimized model
摘要:
为了实现水厂送水泵站的高效、智能化管理，并推动实现“无人值守、降低能耗”的目标，提出了一种基于人工智能（AI）边缘计算技术的智能调度与优化运行方法。该方法通过在泵站关键位置部署边缘计算设备，实时采集水池液位、流量、压力等运行参数，并将数据传输至中心服务器进行处理与分析。本文构建了一种数据优化模型，该模型根据分析结果自动调整水泵的工作状态，包括开停与运行频率，以确保市政管网压力控制点的稳定，并实现节能降耗。生产试验结果表明，相较于传统人工调度方式，该自适应调度方法显著提升了泵站的运行效率和能源利用率，同时降低了人力成本，增强了系统的稳定性和可靠性。
Abstract:
In order to achieve efficient and intelligent management of pumping station in waterworks and promote to realize the goals of unmanned operation and energy consumption reduction, this study proposes an intelligent scheduling and optimization method based on AI edge computing technology. This method involves deploying edge computing devices at key locations within the pumping station to collect real-time operational parameters such as water tank levels, flow rates, and pressure. The data is then transmitted to a central server for processing and analysis. In the study, a data optimized model is developed, which automatically adjusts the operation status of water pumps, including on/off control and operating frequency, based on the analysis results. This ensures the stability of pressure control points in the municipal pipeline network and achieves energy-saving goals. Experimental results show that compared to traditional manual scheduling methods, the self-adaptive scheduling method significantly improves the pumping station’s operational efficiency and energy utilization, reduces labor costs, and enhances stability and reliability of the system.
更新日期/Last Update: 2026-06-17