Active line model identification protection based on characteristic frequency phase for dual-end weakly-fed AC system

Area of Science:

• Electrical Engineering
• Power Systems
• Renewable Energy Integration

Background:

• Flexible DC transmission systems are key for integrating renewable energy sources.
• Existing model-based protection schemes face adaptability issues in dual-end weakly-fed AC systems.
• Reliable protection is essential for the stability and security of modern power grids.

Purpose of the Study:

• To address the adaptability challenges of existing protection schemes in dual-end weakly-fed AC systems.
• To propose a novel active line model identification protection method based on characteristic frequency phase.
• To verify the robustness and reliability of the proposed scheme under various fault conditions.

Main Methods:

• Investigated the adaptability of conventional model recognition principles in dual-end weakly-fed AC systems.
• Developed a control strategy using Modular Multilevel Converters (MMC) for characteristic frequency signal injection.
• Analyzed line model phase characteristics under injected signals and utilized empirical wavelet transform and Prony (EWT-Prony) algorithm for signal extraction.

Main Results:

• The proposed scheme effectively identifies active line models in dual-end weakly-fed AC systems.
• Demonstrated robustness against high fault impedance (up to 300Ω).
• Showed reliability in the presence of significant noise interference (up to 25 dB).

Conclusions:

• The novel characteristic frequency phase-based protection scheme is effective for dual-end weakly-fed AC systems.
• The proposed method offers a robust and reliable solution for protecting renewable energy grid-connected systems.
• This advancement contributes to the secure and stable integration of renewable energy sources into the power grid.