摘要
分布式发电数据监测技术融合物联网、大数据与人工智能,成为优化能源管理的核心手段。文章探讨其在实时监测、故障预警等领域的应用,以浙江分布式光伏承载力分析平台与宁波慈溪渔光互补工程为例,验证其提升效率、降低运维成本的价值。针对多源异构数据融合、网络安全及跨平台标准化等问题,提出加强边缘计算与多模态融合、构建区块链安全体系、推进能源管理标准化等策略,为分布式能源与智能电网融合提供支撑。
Distributed power generation data monitoring technology integrates the Internet of Things,big data,and artificial intelligence,becoming the core means of optimizing energy management.This article explores its application in real-time monitoring,fault warning,and other fields.Taking the Zhejiang Distributed Photovoltaic Carrying Capacity Analysis Platform and the Ningbo Cixi Fishery Photovoltaic Complementary Project as examples,it verifies its value in improving efficiency and reducing operation and maintenance costs.Aiming at problems such as multi-source heterogeneous data fusion,network security and cross platform standardization,this paper proposes strategies such as strengthening edge computing and multimodal integration,building a blockchain security system,and promoting energy management standardization to provide support for the integration of distributed energy and smart grid.
作者
周晨晖
章琛敏
石贇超
马赟婷
刘兴平
ZHOU Chenhui;ZHANG Chenmin;SHI Yunchao;MA Yunting;LIU Xingping
出处
《电力系统装备》
2025年第6期178-180,共3页
Electric Power System Equipment
关键词
分布式发电
数据监测
能源管理优化
多源数据融合
区块链技术
distributed power generation
data monitoring
energy management optimization
multi source data fusion
blockchain technology
