一种基于AIOT的水电站辅助设备能耗监测管控系统

By leveraging edge control and multi-source data fusion within the AIoT system, the problem of multi-dimensional collaborative analysis for monitoring the energy consumption of auxiliary equipment in hydropower stations has been solved. This enables real-time monitoring of equipment status and precise optimization of energy consumption, thereby improving operational efficiency and equipment safety.

CN122068668BActive Publication Date: 2026-07-17GUANGDONG POLYTECHNIC NORMAL UNIV

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
GUANGDONG POLYTECHNIC NORMAL UNIV
Filing Date
2026-04-20
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing technologies for monitoring the energy consumption of auxiliary equipment in hydropower stations lack multi-dimensional collaborative analysis, resulting in delayed identification of energy consumption anomalies, inability to accurately locate wasteful processes, reliance on manual inspections for equipment operation leading to the oversight of faults, low maintenance efficiency, and inflexible control of lighting systems, all of which contribute to energy waste.

Method used

The system adopts an AIoT-based energy consumption monitoring and control system for auxiliary equipment in hydropower stations. By integrating a lightweight AI inference engine and a multi-core processor through an edge control module, a three-dimensional digital twin model is established. Combined with multi-source data fusion and AI algorithms, it enables the identification of abnormal equipment status and optimization of energy consumption, supports rapid equipment access and fault diagnosis, and builds a full-link security protection system.

Benefits of technology

It enables the measurable, manageable, and controllable energy consumption of auxiliary equipment in hydropower stations, reduces the need for manual inspections, improves operation and maintenance efficiency and equipment safety, accurately identifies energy waste links, optimizes energy use, and reduces operation and maintenance costs.

✦ Generated by Eureka AI based on patent content.

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Abstract

本发明属于水电设备管控技术领域,且公开了一种基于AIOT的水电站辅助设备能耗监测管控系统,通过建模模块构建三维度数字孪生模型,整合油、水、气、照明系统数据并完成标准化处理,再经能耗分析模块融合设备运行、能耗、环境、视频多源数据,构建三级数据集市;利用物理模型与机器学习混合架构算法及异常检测模型,精准定位能耗浪费关键环节与潜在成因;同时结合场景化控制算法,实现照明系统基于人员分布、自然光强度的动态调节,使厂用电率达成可测、可管、可控的目标;边缘控制模块内置轻量化AI推理引擎,支持边缘侧设备状态异常识别、人员检测等快速计算,建模模块实现故障告警、状态变更的多参数联动上报。
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