Real-Time Aggregation Approach for Power Quality Data

被引：0
作者：
Fang, Jun [1 ,2 ]
Bai, Wentao [1 ,2 ]
Xue, Xiaodong [1 ,2 ]
机构：
[1] North China Univ Technol, Sch Informat, Beijing 1000144, Peoples R China
[2] Beijing Key Lab Integrat & Anal Large Scale Strea, Beijing 100144, Peoples R China
来源：
WEB INFORMATION SYSTEMS AND APPLICATIONS (WISA 2021) | 2021年 / 12999卷
关键词：
Power quality; Data aggregation; Incremental computing; Approximate computing;
D O I：
10.1007/978-3-030-87571-8_9
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Compliance verification and performance analysis of grid power quality are the main targets of state-wide power quality monitoring and analysis system in China. Real-time aggregation of power quality data is a prerequisite to achieve the targets. Since power quality data generated by over 10,000 monitors are extremely massive, data aggregations of different indicators meet great challenges for time-consuming. An aggregation framework with the incremental computing and approximate computing engine is proposed. The incremental computing methods of maximum, minimum, mean and variance functions are presented, as well as two different approximate computing methods for 95% probability value function. Performance analyses are carried out with real data.
引用
收藏
页码：99 / 106
页数：8
相关论文
共 11 条
  • [1] Synopses for Massive Data: Samples, Histograms, Wavelets, Sketches
    Cormode, Graham
    Garofalakis, Minos
    Haas, Peter J.
    Jermaine, Chris
    [J]. FOUNDATIONS AND TRENDS IN DATABASES, 2011, 4 (1-3): : 1 - 294
  • [2] Kilter J, 2014, INT C HARMON QUAL PO, P703, DOI 10.1109/ICHQP.2014.6842924
  • [3] Krishnan DR, 2016, P 25 INT C WORLD WID
  • [4] [马世发 Ma Shifa], 2021, [生态学报, Acta Ecologica Sinica], V41, P3441
  • [5] A Survey of Techniques for Approximate Computing
    Mittal, Sparsh
    [J]. ACM COMPUTING SURVEYS, 2016, 48 (04)
  • [6] Ning L, 2014, GUIZHOU ELECT POWER, V17, P28
  • [7] SGCC, 2016, REQ VERT EXCH INT PO
  • [8] [盛家 Sheng Jia], 2020, [重庆大学学报, Journal of Chongqing University], V43, P121
  • [9] Siyu Liu, 2020, Web Information Systems and Applications. 17th International Conference, WISA 2020. Proceedings. Lecture Notes in Computer Science (LNCS 12432), P194, DOI 10.1007/978-3-030-60029-7_18
  • [10] Wang T, 2018, 2018 IEEE POW EN SOC, P57
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