Presenter Information

Jim Follum, University of Wyoming

Department

Electrical and Computer Engineering

First Advisor

Dr. John Pierre

Description

The worst power blackouts in America’s history have been due to the interaction of generators in different areas. These interactions are known as electromechanical modes, and possessing information about them is key to providing stability. This research evaluated the Empirical Transfer Function Estimate’s (ETFE) ability to obtain this information. The ETFE method was applied to both a simulated system and real world data. Prony analysis was conducted for comparison. Statistical data for each method was calculated, and results of the application of each method to real world data were compared. In analyzing results, Prony analysis proved more successful at accurately obtaining mode information from the modeled system. Statistically, the two methods performed equally well. Overall, the quality of system information, whether real world or simulated, obtained from each method was quite similar. From these results, it was determined that the ETFE method is a viable alternative to Prony analysis. While the ETFE method less accurately obtains mode information, the difference is slight. The advantages of the ETFE method in real world situations lead to the conclusion that it should continue to be used to estimate mode information in America’s power grid.

Comments

Oral Presentation, Wyoming NSF EPSCoR

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Monitoring Electromechanical Mode Shape with the Empirical Transfer Function Estimate Method

The worst power blackouts in America’s history have been due to the interaction of generators in different areas. These interactions are known as electromechanical modes, and possessing information about them is key to providing stability. This research evaluated the Empirical Transfer Function Estimate’s (ETFE) ability to obtain this information. The ETFE method was applied to both a simulated system and real world data. Prony analysis was conducted for comparison. Statistical data for each method was calculated, and results of the application of each method to real world data were compared. In analyzing results, Prony analysis proved more successful at accurately obtaining mode information from the modeled system. Statistically, the two methods performed equally well. Overall, the quality of system information, whether real world or simulated, obtained from each method was quite similar. From these results, it was determined that the ETFE method is a viable alternative to Prony analysis. While the ETFE method less accurately obtains mode information, the difference is slight. The advantages of the ETFE method in real world situations lead to the conclusion that it should continue to be used to estimate mode information in America’s power grid.