摘要
随着智能电网的迅速发展,电力系统中的用电数据量不断增加,导致电力能源信息的采集和数据分析变得越来越具有挑战性。为提高电力系统管理和控制的效率,文章采用分布式架构、大数据云平台和反向传播(Back Propagation,BP)神经网络算法等分析方法,高效处理用电数据。设计一个包括大数据云平台、中间库、生产库和物联网平台等组件的整体系统,以确保数据的安全传输,优化线损治理方案,解决负荷预测问题。本研究为电力系统的智能化发展提供了有效的指导,并为未来电力行业的发展奠定了坚实的基础。
With the rapid development of smart grid,the increasing amount of electricity consumption data in the power system continues,making the collection and data analysis of power energy information become more and more challenging.In order to improve the efficiency of power system management and control,this paper adopts distributed architecture,big data cloud platform and Back Propagation(BP)neural network algorithm and other analysis methods to efficiently process electricity data.An whole system including components of big data cloud platform,intermediate library,production library and Internet of Things platform is designed to ensure safe transmission of data,and the system is applied to optimize line loss management and solve load forecasting problems.This study provides effective guidance for the intelligent development of the power system,and lays a solid foundation for the future development of the power industry.
作者
于宗江
YU Zongjiang(Jinan Aneng New Energy Co.,Ltd.,Jinan 250000,China)
出处
《通信电源技术》
2024年第5期62-64,共3页
Telecom Power Technology
关键词
电力能源信息
大数据
信息采集处理
power energy information
big data
information collection and processing
作者简介
于宗江(1994—),男,山东临沂人,本科,助理工程师,主要研究方向为电力工程。
