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Component monitoring and dynamic loading visualization from real time power flow model data

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3 Author(s)
Meliopoulos, A.P.S. ; Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA ; Cokkinides, G.J. ; Overbye, T.J.

The technology of intelligent electronic devices in power systems has exploded and with it the available real time data. The data are typically used to extract a real time model of the system via traditional state estimation methods. The traditional approach estimates only the system voltages and uses a small part of the available information. This paper presents a new approach for better utilization of the available information. Specifically, we propose the use of existing data for estimating detailed operational models of major power equipment. For example, the detailed models can be in the form of electro-thermal models which then allow the monitoring of device temperatures, dynamic loading, etc. In general, the real time model can be as simple or as complex depending on the type and quality of available data. For example, from typical SCADA data, the real time operational model of a generator can be extracted. This model can provide the operating margins, etc. Addition of other data, such as ambient temperature, etc. can also provide an electro-thermal model in real time. The paper demonstrates the approach with the example of a power transformer. The methodology is applied to extract an electro-thermal model of the transformer. The real time electro-thermal model provides: (a) transformer temperatures including hot spot, (b) transformer loss of life and (c) transformer dynamic loading. The approach has been simulated in a multitasking environment using an electric power system model with a time-function electric load. The operation of the system is simulated by solving the power flow at user selected time intervals. As the time progresses the electric load changes and a power flow solution determines by computation the operation of the system. At each time step, the real time model of the selected power devices are extracted via statistical estimation methods. The real time model provides vital information for these devices. Their operation conditions can be visualized and animated as desired. The paper presents these applications.

Published in:

System Sciences, 2004. Proceedings of the 37th Annual Hawaii International Conference on

Date of Conference:

5-8 Jan. 2004