Date of Graduation

5-2017

Document Type

Thesis

Degree Name

Master of Science in Electrical Engineering (MSEE)

Degree Level

Graduate

Department

Electrical Engineering

Advisor/Mentor

Roy McCann

Committee Member

Juan C. Balda

Second Committee Member

Simon Ang

Keywords

Applied sciences, Balanced truncation, Control, Krylov subspace, Model order reduction, Power system, Simulation

Abstract

Dynamic representations of power systems usually result in the order of hundreds or even thousands of buses. Therefore, reduction of these dynamic representations is convenient. Two applications of model order reduction in power systems are discussed in this thesis. First, Krylov subspace-based method is applied to the IEEE-123 Node Test Feeder in the context of distribution-level power systems simulation. Second, a Balanced Truncation-based model reduction is implemented in the 3-Machine 9-Bus system for designing a power system controller in the context of generation- and transmission-level power systems.

First, for the IEEE-123 Node Test Feeder, a two-sided Arnoldi algorithm is proposed to compute the basis of the Krylov subspace-based model reduction. The two-sided Arnoldi algorithm was found to decrease the deviation between the reduced and full-order model.

Second, for the 3-Machine 9-Bus, a linear quadratic regulator (LQR) controller is designed based on the reduced model. The selection method of Q and R matrices is adopted from [1]. The resulting controller is shown to damp the oscillations of the open-loop system.

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