Visualization of Power System Static and Dynamic Characteristic

M. Okuda, Y. Minami, G. Shirai, and R. Yokoyama (Japan)

Keywords

Power System Dynamics, Power System Operation, Visualization, Transient Stability

Abstract

This paper discusses visualization methods of power systems to provide intuitive insight of static or dynamic behavior of power network, including a series of events to a blackout. Visualization study on power system has been getting attention among the researchers. Development of good computer system and software is addressing this research, which is spreading for both of static and dynamic studies, enables easy understanding of invisible phenomena in a generator or a network. So far, a table is used to show the system condition, including voltage profile; real and imaginary power flow distribution, phase angles, and these relationships. However, advancement of desktop personal computer technique allows graphical illustration including movie representation.

This paper discusses a few examples of power network representations. First one is an animation of a multi-machine power system during a process of fault, clearing, and restoration, helps researchers for easy understanding of voltage and power flow dynamics. During the fault, particular generator accelerates but others still retain synchronism, results in step out. This process is usually explained with equal area criterion but it cannot be applied for multi-machine power system. In addition, the critical operation point is also difficult to identified. Following the process of fault, line opening for fault clearance, and reclosing for transmission, the transmitting powers remarkably alternate. In a complicated network, these behaviors are also complex. The proposed technique offers new insights for these studies.

Second one is an animation for change of system condition, for example, voltage improvement against reactive power compensation, which implies solution of the operation strategies. The newly developed contour plotting illustration assists better understanding of complex network. This idea can be expanded to dynamical animation for system fault.

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