Carnovale, Nathan
(2021)
Fault Detection in Inverter-Based Microgrids Utilizing a Nonlinear Observer.
Master's Thesis, University of Pittsburgh.
(Unpublished)
Abstract
Traditionally, rotating machines in the bulk power system have provided enough inertia to result in fault currents that are more than five or six times nominal current. Typical circuit protection schemes are designed to act on this high and long lasting fault current. However, with the growing trend of increased penetration of renewable energy, energy storage and microgrids, power electronic based systems are becoming more widely utilized on the grid. In heavily inverter-based power systems, the difference between nominal currents and short circuit fault currents is minimal due to reduced system inertia which altogether makes fault detection difficult. In this research, a model-based approach that utilizes the assumed dynamics of a grid-tied inverter along with a nonlinear observer is proposed to detect system abnormalities and faults. The goal of this observer is to provide insight into unmodelled signatures present in the system. These signatures in turn can be utilized to identify faults in the system creating a detection scheme. Most importantly, this method requires no additional sensors other than those required by the grid-tied inverter which is a key advantage over many proposed solutions in literature. Through use of the PSCAD simulation environment, a two-inverter system model was developed to reproduce the types of low fault currents described. Line-to-ground and line-to-line faults were then observed and detected at multiple fault locations with the proposed observer to assess its effectiveness of identifying faults in these fault scenarios.
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Details
Item Type: |
University of Pittsburgh ETD
|
Status: |
Unpublished |
Creators/Authors: |
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ETD Committee: |
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Date: |
13 June 2021 |
Date Type: |
Publication |
Defense Date: |
23 March 2021 |
Approval Date: |
13 June 2021 |
Submission Date: |
15 March 2021 |
Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
Number of Pages: |
48 |
Institution: |
University of Pittsburgh |
Schools and Programs: |
Swanson School of Engineering > Electrical and Computer Engineering |
Degree: |
MSEE - Master of Science in Electrical Engineering |
Thesis Type: |
Master's Thesis |
Refereed: |
Yes |
Uncontrolled Keywords: |
fault detection, fault identification, inverter-based generation, microgrid, nonlinear observer |
Date Deposited: |
13 Jun 2021 18:34 |
Last Modified: |
13 Jun 2021 18:34 |
URI: |
http://d-scholarship.pitt.edu/id/eprint/40375 |
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