期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

Visualization Techniques in Smart Grid 被引量：3

Visualization Techniques in Smart Grid
下载PDF
导出
摘要 Visualization is an established methodology in scientific computing. It has been used in many fields because of its strong capability in large data management and information display. However, its applications in power systems, especially in Smart Grid are still in infancy stage. Besides, while there were a lot of researches working on visualizing data in transmission power system, the study on displaying distribution power system data was limited. Therefore, in this paper, author proposed some techniques to visualize the Smart Grid data at distribution. They are classified in three categories, which are low dimensional techniques, multivariate high dimensional techniques and Geographical Information System (GIS) techniques. Visualization is an established methodology in scientific computing. It has been used in many fields because of its strong capability in large data management and information display. However, its applications in power systems, especially in Smart Grid are still in infancy stage. Besides, while there were a lot of researches working on visualizing data in transmission power system, the study on displaying distribution power system data was limited. Therefore, in this paper, author proposed some techniques to visualize the Smart Grid data at distribution. They are classified in three categories, which are low dimensional techniques, multivariate high dimensional techniques and Geographical Information System (GIS) techniques.
作者 Dao Viet Nga Ong Hang See Do Nguyet Quang Chee Yung Xuen Lai Lee Chee
机构地区 Department of Electronics and Communication Engineering
出处 《Smart Grid and Renewable Energy》 2012年第3期175-185,共11页 智能电网与可再生能源（英文）
关键词 Smart GRID Visualization Techniques Google EARTH GIS QGIS AMI SCADA Spatial TEMPORAL ANIMATION Smart Grid Visualization Techniques Google Earth GIS QGIS AMI SCADA Spatial Temporal Animation
分类号 TP39 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献1

二级参考文献15

  • 1.[EB/OL].http: ∥www. powerworld. com,.
  • 2OVERBYE T J, SAUER P W, MARZINZIK C M et al. A User-friendly Simulation Program for Teaching Power System Operations. IEEE Trans on Power Systems, 1995, 10 (4):1725-1733.
  • 3OVERBYE T J, GROSS G, LAUFENBERG M J et al.Visualizing Power System Operations in the Restructured Environment. IEEE Computer Applications in Power, 1997, 10(1): 53-58.
  • 4OVERBYE T J, SAUER P W, GROSS G et al. A Simulation Tool for Analysis of Alternative Paradigms for the New Electricity Business. In: Proc 20th HICSS. Maui(HI, USA):634-640.
  • 5WARE C. Information Visualization. San Diego (USA):Academic Press, 2004. 149-158.
  • 6US Department of Energy. Final Report on the August 14,2003 Blackout in the United States and Canada: Causes and Recommendations. 2004. https:∥reports. energy. gov.
  • 7MAHADEV P M, CHRISTIE R D. Minimizing User Interaction in Energy Management Systems: Task Adaptive Visualization. IEEE Trans on Power Systems, 1996, 11(3):1607-1612.
  • 8WIEGMANN D A, ESSENBERG G R, OVERBYE T J et al. Human Factors Aspects of Power System Flow Animation. http:∥www. pserc. org/ecow/get/publicatio. 2004.
  • 9WEBER D, OVERBYE T J. Voltage Contours for Power System Visualization. IEEE Trans on Power Systems, 2000, 15(1): 404-409.
  • 10FISHER D L, TAN K C. Visual Displays: The Highlighting Paradox. Human Factors, 1989, 31(1): 17-30.

共引文献36

同被引文献25

  • 1Dorr D, Gray G. The whys, whats, and hows of managing data as an asset [R]. California: Electric Power Research Institute, 2014.
  • 2Geoff B. Down the petabyte highway[J]. Nature, 2011, 469(20): 282-283.
  • 3Manyika J, Chui M, Brown B, et al. Big data: the next frontier for innovation competition and productivity[R]. San Francisco: McKinsey Global Institute. 2011.
  • 4White House: Big Data across the federal government [EB/OL]. Washington : White House 2012[2015-01-13] , http://www.whitehouse.gov/sites/default/files/microsites/ostp/big_dat a fact sheet final 1.pdf.
  • 5OSTP Blog: The White House office of science and technology policy: big data is a big deal [EB/OL]. Washington: White House, 201212015-01-13], http://www.whitehnuse.gov/blog/2012/03/29/big- data- big-deal.
  • 6Agrawal D, Bernstein P, Bertino E, et al. Challenges and opportunities with big data[J]. Proeeedings of the VLDB Endowment, 2012, 5 (12): 2032-2033.
  • 7Rusitschka S, Eger K, Gerdes C. Smart grid data cloud: a model for utilizing cloud computing in the smart grid domain[C]//Smart Grid Communications (SmartGridComm), 2010 First IEEE International Conference. Gait.hersburg, MD: 1EEE, 2010: 483-488.
  • 8Nimmagadda S L, Dreher H V. Big-data integration methodologies for effective management and data mining of petroleum digital ecosystems[C]// 2013 7th IEEE International Conference on Digital Ecosystems and Teehnologies(DEST). Menlo Park, IEEE, 2013: 148-153.
  • 9Mladen K, Xie Le, Santiago G. The role of big data in improving power system operation and protection[C]//Bulk Power System Dynamics and Control-IX Optimization, Security and Control of the Emerging Power Grid(IREP), 2013 IREP Symposium. Rethymno: IEEE, 2013: 1-9.
  • 10Hey T, Tansley S, Tolle K. The fourth paradigm: data-intensive scientific discovery[M]. Washington: Microsoft Research Press, 2009 109-231.

引证文献3

二级引证文献71

Smart Grid and Renewable Energy
2012年 第3期

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部