
Modelling and analysis of half‐/full‐bridge hybrid MMC when riding through DC‐side pole‐to‐ground fault
Author(s) -
He Zhen,
Hu Jiabing,
Lin Lei,
Zeng Pingliang
Publication year - 2022
Publication title -
high voltage
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.732
H-Index - 20
ISSN - 2397-7264
DOI - 10.1049/hve2.12144
Subject(s) - transient (computer programming) , fault (geology) , control theory (sociology) , linearity , voltage , modular design , direct current , computer science , engineering , electronic engineering , electrical engineering , control (management) , artificial intelligence , seismology , geology , operating system
In a modular multilevel converter‐based high‐voltage direct current (MMC‐HVDC) system, the dc fault ride through (FRT) control is an effective way to deal with a dc‐side pole‐to‐ground (PTG) fault. However, the setting of FRT duration brings potential hazards: 1) MMC will face the risk of “secondary short circuit” if FRT duration is short; 2) ac grid may have power angle stability issue if FRT duration is long. To avoid these hazards and provide theoretical guidance for the FRT duration setting, transient behaviour of dc fault current during the PTG FRT stage is explored in this work. Firstly, challenges of the transient analysis are summarised as non‐linearity and high‐order issues. In light of this, numerical and Hilbert‐Huang Transformation methods are introduced to evaluate the non‐linearity issue. It is found that the path of MMC from dc current to dc internal voltage is weakly non‐linear. Hence, a linear transient model is built to analyse the dc fault current. By participation factor analysis, the order of the proposed model is further reduced, so that an analytical expression of the dc fault current is approximately derived. Based on the analytical expression, regularities and mechanism of dc fault current are fully revealed. Application of the transient analysis to the setting of FRT duration is elaborated in detail. Finally, the PSCAD/EMTDC simulation verifies the validity of the proposed model and analytical expression.