A Data Analytics Perspective of Power Grid Analysis-Part 1: The Clarke and Related Transforms

被引:10
作者
Mandic, Danilo P. [1 ]
Kanna, Sithan [2 ]
Xia, Yili [3 ]
Moniri, Ahmad
Junyent-Ferre, Adria [4 ,5 ]
Constantinides, Anthony G. [6 ]
机构
[1] Imperial Coll London, Signal Proc, London, England
[2] Management Consulting Firm, Coimbatore, Tamil Nadu, India
[3] Southeast Univ, Sch Informat Sci & Engn, Signal Proc, Nanjing, Jiangsu, Peoples R China
[4] Imperial Coll London, Control & Power Res Grp, London, England
[5] CITCEA UPC, Barcelona, Spain
[6] Imperial Coll, London, England
基金
英国工程与自然科学研究理事会; 中国国家自然科学基金;
关键词
FREQUENCY;
D O I
10.1109/MSP.2018.2878656
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Affordable, reliable, and readily accessible electric power underpins our modern society in a multitude of ways, and in this context, the smart grid is becoming an increasingly important factor in power generation, transmission, and distribution. Current analytical tools for the planning, operation, and circuit design in power systems derive from the antecedent technology area of circuit theory, which is both nonobvious for modern data analysts and assumes balanced conditions and a steady state, even though future power networks will routinely experience transient and steady-state unbalances. Next-generation analytical tools should therefore be fully equipped for dynamically unbalanced systems to approach the physical limits of power networks; data analytics is both well suited and necessary for this endeavor but is nonobvious for power engineers. Hence, to fully exploit their evident and promised advantages, an analysis of the smart grid requires close collaboration and convergence between power engineers and experts in signal processing and machine learning, whereby analytical tools expressed in a common language would be a natural step forward. © 1991-2012 IEEE.
引用
收藏
页码:110 / 116
页数:7
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