Application of Pixel-Oriented Visualization Technique in the Centralized Monitoring of Smart Grid Dispatching and Control System
Zhang Yin, Yansheng Lang, Yang Bai, Ying Xing, Qiang Li, Jie Xu, Sen Li, Qingshan Zhu · 2015
With the rapid development of smart grid dispatching and control system in State Grid Corporation of China (SGCC), the complexity of system operation and maintenance increases sharply.In order to improve the maintenance efficiency, SGCC put forward the remote centralized maintenance mode.The centralized monitoring is the essential business of centralized maintenance, it collect the vast amounts of information from nationwide smart grid dispatching and control systems, and provides monitoring pictures for the users who need understand the global running state of the systems.How visualizing the huge information in the limit screens is a problems to be solved.This paper introduces the application of pixel-oriented visualization techniques in the centralized monitoring, takes the nationwide state estimation rate monitoring for an example, and compare with original techniques.Through the research and application, we find that using pixel-oriented visualization techniques could make centralized monitoring more effective. GENERAL INTRODUCTIONSCentralized maintenance of smart grid dispatching and control system With the rapid development of smart grid dispatching and control system in State Grid Corporation of China (SGCC), the complexity of system operation and maintenance increases sharply.In order to improve the maintenance efficiency, SGCC put forward the remote centralized maintenance mode (Shuai et al. 2013, Chai et al. 2014).The remote centralized maintenance includes centralized monitoring (Zhu et al. 2009), centralized fault warning and treatment, and centralized statistical analyzing.The centralized monitoring is the essential business, it collect the running status information of nationwide smart grid dispatching and control systems into one maintenance center, and it provides monitoring pictures for the users who need understand the global running state of the systems.The information contains hardware status, operating system resources, database status, platform server status, and advanced application status.The information covers the whole dispatching and control systems of the SGCC and is real-time collected.It has big amount of data, but the number of monitor screens is only dozens.In order to make the user detect system problems comprehensively and timely, the information visualization techniques should be applied to better display the huge information in the limit screens. Visualizing vast amounts of informationInformation visualization techniques are becoming increasingly important for the analysis and exploration of big data.A major advantage of visualization techniques over other automatic data exploration and analysis techniques (from statistics, machine learning, artificial intelligence, etc.) is that visualizations allow a direct interaction with the user and provide an immediate feedback, as well as user steering, which is difficult to achieve in most nonvisual approaches.The practical importance of visual data mining techniques is therefore steadily increasing and basically all commercial data mining systems try to incorporate visualization techniques of one kind or the other.In the visualization field, a considerable number of advanced visualization techniques for multidimensional data have been proposed.The approaches include geometric projection techniques such as parallel coordinates (Inselberg 1985, Inselberg & Dimsdale 1990), icon-based techniques (Pickett & Grinstein 1988, Beddow 1990), hierarchical techniques (Robertson et al. 1991), graph-based techniques (Becker et al. 1995), pixel-oriented techniques (Keim 2000), and combinations theory (Ahlberg & Shneiderman