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PhD Final Exam – Jia Guo

Distributed Dynamic Multi-Area State Estimation with Fusion Technique

As the power system grows larger and more complex, real-time monitoring and control become very significant in order to achieve reliable operation of the power system. Before any security assessment can be made or control actions are taken, the reliable estimate of the existing state of the system must be determined. State estimation forms the backbone of the energy management system by providing a database of the real-time state of the system. Under normal conditions, a power system is a quasi-static system. With the penetration of renewable power and distributed generators, the quasi-static assumption is no longer suitable for real time monitoring. Therefore, in order to have continuous monitoring of the complex power system, a comprehensive distributed dynamic model of the power system is proposed in this thesis. By using the proposed model, a distributed dynamic Multi-Area state estimation (MASE) algorithm is proposed. The proposed MASE algorithm would g! enerate precise estimated state values with much less computation cost. In order to combine the advanced Phasor Measurement Unit (PMU) with the current SCADA devices, a nonlinear fusion technique is developed to improves the dynamic state estimation by using both PMU and SCADA measurements. Several IEEE standard test cases and Polish 2383-bus test case are implemented. The implementation results and discussion related to the proposed dynamic distributed MASE algorithm are summarized also. In the end, some possible future works are suggested.

Major Advisor: Mario E. Magana
Committee: Eduardo Cotilla-Sanchez
Committee: Jinsub Kim
Committee: Lizhong Chen
GCR: Douglas A. Keszler

Monday, May 6 at 3:00pm to 5:00pm


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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