Electronic Theses and Dissertations

Identifier

2718

Date

2016

Date of Award

7-22-2016

Document Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Engineering

Concentration

Electrical Engineering

Committee Chair

Mohd Hasan Ali

Committee Member

Russell J Deaton

Committee Member

John I Hochstein

Committee Member

Muhammad S Jahan

Abstract

Wind energy is one of the most prominent sources of renewable energy. However, subjected to the high penetration of wind energy into existing power grids, stability and smooth operation of electric power system is at stake due to the vulnerability of the wind farms to the grid faults. To address the situation, energy regulatory bodies and electricity transmission system operators have imposed grid codes to ensure overall system stability and steady operations. The most challenging grid code is the low voltage ride through (LVRT) which requires the wind farms to stay connected and support the grid during fault. Based on this background, in order to enhance the LVRT capability of the doubly fed induction generator (DFIG) based onshore wind farms, controller based auxiliary devices, such as the bridge type fault current limiter (BFCL) and parallel resonance fault current limiter (PRFCL) have been proposed in this dissertation. From the Matlab/Simulink based simulations performed on various test systems under fault conditions, it was found that the BFCL and PRFCL are very effective devices in enhancing the LVRT capability of the DFIG based wind farms. Moreover, both devices outperform the conventional series dynamic braking resistor (SDBR) method. With a view to augmenting the LVRT performance much more, nonlinear equation governed controller and fuzzy logic based controller are designed and applied to the modified BFCL (MBFCL) and PRFCL, respectively. From the simulation results, it was found that these nonlinear controllers make the fault current limiters adaptive and responding to the power system dynamics and thus provide much better performance in LVRT capacity augmentation. Furthermore, maintaining the LVRT capability is also challenging for the DFIG based offshore wind farms (OWFs). A DC chopper is a popular choice for the LVRT capacity enhancement of the OWFs. A metaheuristic algorithm, such as a particle swarm optimization (PSO) technique is proposed to design a controller for the DC chopper resistor. Simulation results reveal that the PSO controller based DC chopper is more effective than the conventional DC chopper for the LVRT capacity improvement of DFIG based OWFs.

Comments

Data is provided by the student.

Library Comment

dissertation or thesis originally submitted to the local University of Memphis Electronic Theses & dissertation (ETD) Repository.

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