广东省小水电生态流量监管平台的设计与实现

为提高生态流量监管能力及推进小水电的绿色发展，针对小水电生态流量监管智能化、信息化不足等问题，围绕生态流量监管的关键环节及业务管理需求，提出感知层、网络传输层、数据存储层、支撑服务层和应用层的五层总体架构设计。基于物联网、人工智能及大数据技术，重点从组网方式和接入协议上阐述了物联网的接入架构，提出使用深度学习实现视频图像智能分析进行下泄流量监测，提出使用大数据技术建立模型进行预警预测。 应用微服务架构、云服务、WebGIS等先进信息技术，构建具有生态流量监测、设备管理、地图控制、预警管理及数据可视化等功能的小水电生态流量监管平台，可有效监管水电站泄流行为特征，为流域、水系提供“生态流量保障”。

Design and operation of ecological fl ow supervision platform for small hydropower stations in Guangdong Province

In order to improve the ability of ecological flow supervision and promote the green development of small hydropower, this paper aims at the problems of insufficient intelligence and informatization of ecological flow supervision of small hydropower to analyzes the needs of ecological flow supervision and management. Based on the analysis, this paper proposes the design of five-layer overall architecture including network transmission layer, data storage layer, service layer and application layer. Based on the Internet of Things, artificial intelligence and big data technology, this paper focuses on the access architecture of the Internet of Things in terms of networking methods and access protocols, proposes to use deep learning to achieve intelligent analysis of video images to monitor the discharge flow, and proposes to use big data technology to establish a model for pre alarm prediction. With advanced information technologies such as microservice architecture, cloud service and WebGIS, a plantform of small hydropower stations ecological flow supervision is designed with the functions of ecological flow monitoring, equipment management, map control, early warning and data visualization, which can effectively guarantee the safety of ecological flow for basins and rivers.