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https://knowledgecommons.lakeheadu.ca/handle/2453/5431
Title: | A novel current source converter-based ultra-high-power offshore wind energy conversion system |
Authors: | Yang, Kaiwen |
Keywords: | Wind energy conversion systems. |
Issue Date: | 2025 |
Abstract: | In medium voltage (MV) ultra-high-power (over 10 MW) offshore wind energy conversion systems (WECS), current source converter (CSC)-based series-connected configurations are a good candidate. However, existing CSC-based WECS use the bulky low-frequency transformer (LFT), have high rotor torque ripple or require the active rectifier, which entails higher costs, lower reliability and efficiency, and larger size and weight than the diode rectifier. To address these issues, this thesis proposes a novel CSC-based series-connected MV WECS, combining the six-phase generator connected to two diode rectifiers with two medium frequency transformers (MFTs)- based modular converters on the generator side and using the dual-bridge current source inverters (CSIs) on the grid side. The proposed WECS effectively mitigates rotor torque ripple caused by diode rectifiers and retains all the advantages of existing MFTs-based WECS. Additionally, the modular converter in the proposed WECS has voltage and current imbalance issues, so a corresponding control scheme is proposed to address these issues. Furthermore, online selective harmonic elimination (SHE) modulation is applied to the grid-side CSIs. This approach significantly reduces the memory requirements of the digital controller, thereby lowering costs while retaining all the advantages of conventional SHE techniques. The feasibility and effectiveness of the proposed WECS, its control scheme, and the online SHE modulation are validated through simulation results. |
URI: | https://knowledgecommons.lakeheadu.ca/handle/2453/5431 |
metadata.etd.degree.discipline: | Engineering : Electrical & Computer |
metadata.etd.degree.name: | Master of Science |
metadata.etd.degree.level: | Master |
metadata.dc.contributor.advisor: | Wei, Qiang |
metadata.dc.contributor.committeemember: | Dekka, Apparao Akilan, T. Zhou, Yushi |
Appears in Collections: | Electronic Theses and Dissertations from 2009 |
Files in This Item:
File | Description | Size | Format | |
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KaiwenY2025m-1a.pdf | 2.17 MB | Adobe PDF | ![]() View/Open |
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