Control_and_Optimization_Methods_for_Electric_Smart_Grids下载

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智能电网相关控制技术与优化
Control_and_Optimization_Methods_for_Electric_Smart_Grids
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Big Data Analytics in Future Power Systems by:Ahmed F. Zobaa and Trevor J. Bihl ISBN-10 书号: 1138095885 ISBN-13 书号: 9781138095885 Edition 版本: 1 出版日期: 2018-09-24 pages 页数: (188) $99.95 Power systems are increasingly collecting large amounts of data due to the expansion of the Internet of Things into power grids. In a smart grids scenario, a huge number of intelligent devices will be connected with almost no human intervention characterizing a machine-to-machine scenario, which is one of the pillars of the Internet of Things. The book characterizes and evaluates how the emerging growth of data in communications networks applied to smart grids will impact the grid efficiency and reliability. Additionally, this book discusses the various security concerns that become manifest with Big Data and expanded communications in power grids. Provide a general description and definition of big data, which has been gaining significant attention in the research community. Introduces a comprehensive overview of big data optimization methods in power system. Reviews the communication devices used in critical infrastructure, especially power systems; security methods available to vet the identity of devices; and general security threats in CI networks. Presents applications in power systems, such as power flow and protection. Reviews electricity theft concerns and the wide variety of data-driven techniques and applications developed for electricity theft detection. Contents Preface Acknowledgments Editors List of Contributors 1.Introduction 2.Big Data Application and Analytics in a Large-Scale Power System 3.The Role of Big Data in Smart Grid Communications 4.Big Data Optimization in Electric Power Systems:A Review 5.Security Methods for Critical Infrastructure Communications 6 Data-Mining Methods for Electricity Theft Detection 7.Unit Commitment Control of Smart Grids 8.A New Transformer Differential Protection Algorithm Based on Data Pattern Recognition Index

CPS广泛存在于现代社会的各个领域，如：能源生产、医疗和通信。CPS的例子有：传感器网络、工业自动化系统以及重要的基础设施（交通网络、电力生产和分配网、水与天然气分配网络和先进制造业）。在生产中结合信息技术可以提高系统的效率，同时，也增加了系统的脆弱性，降低了关键设施的可靠性。具体例子有： 2000年3月Maroochy water breach[1]，巴西多起停电事故[2],2003年1月

目录综述信号检测、信号分类和比较信道编码和解码端到端通信的学习定位、传感和本地化安全性和鲁棒性毫米波通信资源分配其他类参考IEEE的Library 附带源码的文献汇总综述 • C. Jiang, H. Zhang, Y. Ren, Z. Han, K.-C. Chen and L. Hanzo, “Machine learning paradigms for next-generation wireless networks,” IEEE Wireless Communications, vol. 24

转载自: https://blog.csdn.net/fkyyly/article/details/80397856#commentsedit 方法如下: 1.找到某篇文章: https://ieeexplore.ieee.org/document/7965747 查询到DOI是:10.1109/SERA.2017.7965747 2.打开 http://sci-hub....

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