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Analysis of data compression techniques in smart grids for optimising mean-square-error
Applied Nanoscience ( IF 3.869 ) Pub Date : 2021-09-22 , DOI: 10.1007/s13204-021-02028-7
D. Subbarao 1 , A. Sateesh Kumar 1 , S. K. Bikshapthi 1 , N. Malathi 1 , Md. Ashraf 1
Affiliation  

Electrification was the leading drive in the modern world in its engineering achievements of the twentieth century. Electricity, as an unavoidable characteristic, invisibly fuses into the fabric of modern society. Smart grid integrates electricity and PS network communication that delivers digital information about the operator's and consumers' real-time network operations. Interdisciplinary research areas like communication, automation, sensor and control include smart grid technology. Application-centered network communication architecture must be developed for the Smart Grid to support traditional applications for the smart grid which evolves. The conversion to a smart grid is therefore inevitable and involves the integration of intelligence into the existing electronic grid (IEDs). The current PS infrastructure in smart grid is being upgraded by integrating distributed energy resources, advanced automated control and prediction systems to ensure optimal energy use, making the PS reliable and safer. This study introduces a proposed approach for data compression based on a combined binary regression wavelet-surrogate tree and a hybrid thresholding method. The results show that implementing the proposed data compression approach can result in a substantial reduction in the number of messages exchanged between the IEDS and the SCADA within intelligentsia substation automation in the smart grids by the General Object-Oriented Substation Event (Goose).



中文翻译:

分析智能电网中优化均方误差的数据压缩技术

电气化是现代世界 20 世纪工程成就的主要推动力。电作为一种不可避免的特性,无形中融入了现代社会的结构。智能电网集成了电力和 PS 网络通信,可提供有关运营商和消费者实时网络运营的数字信息。通信、自动化、传感器和控制等跨学科研究领域包括智能电网技术。智能电网必须开发以应用为中心的网络通信架构,以支持不断演进的智能电网的传统应用。因此,向智能电网的转换是不可避免的,需要将智能集成到现有的电子电网 (IED) 中。目前智能电网中的 PS 基础设施正在通过整合分布式能源、先进的自动化控制和预测系统进行升级,以确保优化能源使用,使 PS 更可靠和更安全。本研究介绍了一种基于组合二元回归小波代理树和混合阈值方法的数据压缩方法。结果表明,通过通用面向对象变电站事件(鹅),实施所提出的数据压缩方法可以显着减少智能电网中智能变电站自动化内 IEDS 和 SCADA 之间交换的消息数量。本研究介绍了一种基于组合二元回归小波代理树和混合阈值方法的数据压缩方法。结果表明,通过通用面向对象变电站事件(鹅),实施所提出的数据压缩方法可以显着减少智能电网中智能变电站自动化内 IEDS 和 SCADA 之间交换的消息数量。本研究介绍了一种基于组合二元回归小波代理树和混合阈值方法的数据压缩方法。结果表明,通过通用面向对象变电站事件(鹅),实施所提出的数据压缩方法可以显着减少智能电网中智能变电站自动化内 IEDS 和 SCADA 之间交换的消息数量。

更新日期:2021-09-23
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