DocumentCode :
130918
Title :
Perfect power visualization-performance optimization with Java
Author :
Chenqi Bao ; Flueck, Alexander ; Jianmin Bao ; Xuan Shen
Author_Institution :
Comput. of Eng., Illinois Inst. of Technol., Chicago, IL, USA
fYear :
2014
fDate :
27-29 June 2014
Firstpage :
569
Lastpage :
572
Abstract :
Visualization is critical in power systems engineering since the gigantic amount of data generated by power systems is difficult, and at times impossible, to be analyzed numerically. Therefore, the need for powerful visualization software has been increasingly acute due to the growth in size of power system models. To improve PPV´s performance in order to accompany larger systems, this paper focuses on the development of PPV (Perfect Power Visualization), a 2-D power system visualization software program that processes and converts numerical data to graphic symbols based on their types, positions and states. The goal of PPV is to let operators visualize and interact with large-scale power systems in a consumer lever personal computer in real time. Also, it was optimized again with smarter data management systems, refinement of overall structure, and a newer platform that enables GPU acceleration, all of which further increased the performance of PPV by a factor of ten times that of its initial capabilities.
Keywords :
Java; data visualisation; power engineering computing; 2D power system visualization software program; GPU acceleration; Java; PPV performance; consumer lever personal computer; large-scale power systems; perfect power visualization-performance optimization; power system models; power systems engineering; smart data management systems; Arrays; Computers; Data visualization; Java; Optimization; Power systems; GPU acceleration; JavaFX; PPV; Performance Optimization; Power System Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
Conference_Location :
Beijing
ISSN :
2327-0586
Print_ISBN :
978-1-4799-3278-8
Type :
conf
DOI :
10.1109/ICSESS.2014.6933632
Filename :
6933632
Link To Document :
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