OBSERVABILITY ANALYSIS FOR THE DETECTION AND ESTIMATION OF MICROGRID ACTIVITIES
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Author
Andriulli, Mario C.
Date
2019-12Advisor
Kang, Wei
Second Reader
Krener, Arthur J.
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This research investigates the suitability of employing the observability Gramian as a computational instrument in analyzing microgrid system operations. An observable system permits the use of a limited sensor network to provide fault detection, abnormal activity detection, and system calibration with partial information. Microgrids can be modeled using systems of ordinary differential equations (ODEs). The observability Gramian is calculated using the solution to the ODEs with perturbed initial conditions. The observability is determined by the minimum eigenvalue of the Gramian matrix. A large minimum eigenvalue implies that the system is strongly observable, while a small value means the system is weakly observable or practically unobservable. Employing contactless sensors allows a non-invasive method of monitoring the system without interruption. As a case study, the empirical observability Gramian was numerically computed using a 9-bus microgrid model solving a system of nonlinear ODEs with 6 state variables and 12 parameters. The case study first determines the observability of various sensor network configurations, and then an observability analysis for fault detection introduces variations in system parameters. This case study showed that, depending on the sensor network configuration, microgrids can be observable in the presence of unknown parameter variation.
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This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.Collections
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