Electronic Theses and Dissertations Archive

Date

2026

Document Type

Thesis

Degree Name

Master of Science

Department

Electrical & Computer Engineering

Committee Chair

Mohd .Hasan Ali

Committee Member

Farhad Jazaei

Committee Member

Madhusudhanan Balasubramanian

Abstract

ABSTRACT Offshore wind farms are increasingly and rapidly expanding due to its ability to harness strong and consistent wind energy resources. Large offshore wind farms are connected to mainland grids through High-Voltage Direct Current (HVDC) technology. However, offshore wind farms can often experience disturbances related to sudden wind changes, voltage drops/dips, faults related to converter switching, and unbalanced grid conditions which affect both the HVDC operation and wind turbine output. As a result, there is a growing need for more advanced and reliable modeling and monitoring tools. Moreover, traditional proportional-integral (PI) controllers are widely applied in wind turbines and HVDC systems due to their simple structure, easy implementation, and reliability. However, PI controllers perform poorly under non-linear and abnormal/fast-changing conditions, especially during sudden drops in wind power and grid faults. With this background, this thesis first develops a Digital Twin model of an offshore wind farm that enables remote operation and monitoring of individual wind turbines. Moreover, this thesis proposes an artificial intelligence (AI) based controller such as a Fuzzy Logic Controller (FLC) to maintain transient stability of a full digital twin based offshore wind farm connected to the HVDC grid under fault conditions. The effectiveness of the proposed FLC is demonstrated by considering a Digital Twin enabled 700-MW offshore wind farm. The performance of the proposed FLC has been compared with that of the PI controller. Simulations performed by MATLAB/Simulink software show the superiority of the FLC over the PI controller in maintaining the transient stability of the offshore wind farm.

Comments

Data is provided by the student.

Library Comment

Dissertation or thesis originally submitted to ProQuest/Clarivate.

Notes

Open Access

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