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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, 2019 at 2:00pm to 4:00pm

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

Event Type

Lecture or Presentation

Event Topic


Electrical Engineering and Computer Science
Contact Name

Calvin Hughes

Contact Email

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