智能配用电数据压缩方法研究进展及展望

Research progress and prospects on compression methods of smart power distribution and consumption data

随着智能配电网中传感量测设备广泛部署,配用电数据在量测数量、类型、速率等多个维度同步增长,整体规模显著增加。这些数据本身蕴含巨大价值,但同时也给配电网的通信和存储环节带来了巨大压力。数据压缩是减小配用电数据体量的重要手段,能够有效降低对通信和存储设施的技术需求,是配电网数字化、智能化发展的重要支撑技术。重点围绕配用电数据压缩方法进行了综述,首先分析了智能配电网及配用电数据的形成背景及主要特征;然后,从有损和无损的角度介绍了常用压缩算法的基本原理、主要应用领域及其在配用电数据压缩领域的研究应用进展;最后,对配用电数据压缩技术的未来发展方向进行了探讨与展望。

With the widespread deployment of sensors-based measurement devices in smart distribution networks,the quantity,types,and rate of power distribution and consumption data are correspondingly increasing,leading to a significant overall scale expansion.These data inherently hold immense value,yet they simultaneously exert huge pressure on the communication and storage systems of distribution networks.Data compression serves as a crucial means to reduce the volume of power distribution and consumption data,effectively lowering the technical requirements for communication and storage facilities.It stands as a vital supporting technology for the digital and intelligent development of distribution networks.This paper provides a comprehensive review focusing on methods for data compression in distribution networks.Firstly,the background and main characteristics of smart distribution networks and data are analyzed.Then,from the perspectives of lossy and lossless compression,the basic principles,main application areas of commonly used compression algorithms are introduced,along with their research and application progress in the field of distribution networks.Finally,the future development direction for compression technology of power distribution and consumption data is discussed and prospected.