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PhD Preliminary Oral Exam – Tao Lyu

The Partitioning Technique of Power System to Improve The Observability of Sub-System for Multi-area State Estimation

An accurate state estimation plays an essential role in power system operation and planning in energy management systems. However, existing multi-are state estimation researches have not focused on the importance of system clustering. The clustering mechanism divides or partitions a system according to user-defined criteria. Few published research works have mentioned the importance of considering the electrical properties of a power system while devising their partitioning methods. To the best of our knowledge, these publications have not considered the application of such a concept to multi-area state estimation. This research attempts to model a partitioning technique of the power system whose purpose is to ensure the sub-system observability prior to the multi-area state estimation. Hence, the accuracy of the multi-area state estimation could be improved. The proposed partitioning technique in this thesis employing the proposed PMU placement technique to represent the sub-system observability. An extra genetic algorithm index is proposed, which relates to the sub-system observability.

Major Advisor: Mario E Magana
Committee: Ted Brekken
Committee: Jinsub Kim
Committee: Eduardo Cotilla-Sanchez
GCR: Zhaoyan Fan

Friday, August 30 at 2:00pm to 4:00pm


Kelley Engineering Center, 1007
110 SW Park Terrace, Corvallis, OR 97331

Event Type

Lecture or Presentation

Event Topic

Research

Organization
Electrical Engineering and Computer Science
Contact Name

Calvin Hughes

Contact Email

calvin.hughes@oregonstate.edu

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