Inference, estimation, and prediction for stable operation of modern electric power systems

To keep pace with social-ecological disruptions and technological progressions, electrical power systems must continually adapt. In order to address the stability-related challenges associated with these adaptations, this thesis develops a set of analytically rigorous yet practically oriented methods for ensuring the continued stability of modern power systems. By leveraging inference, estimation, and predictive modeling techniques, the proposed methods capitalize on the unprecedented amount of real time data emerging from modernizing smart grids. For each method, we provide simulated test results from IEEE benchmark systems. Newly deployed Phasor Measurement Units (PMUs) are observing the presence of detrimental low frequency forced oscillations (FOs) in transmission grid networks. To begin this thesis, we address the problem of locating the unknown sources of these FOs.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Mechanical Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2021

Author dc:creator

• Chevalier, Samuel Chapman.

Advisor dc:contributor.advisor

• Luca Daniel.

• Mechanical Engineering.

Statement dc:rights

• MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/130842

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/130842