TY - GEN
T1 - A Comparative Analysis of Artificial Intelligence for Power Transformer Differential Protection
AU - Afrasiabi, Shahabodin
AU - Behdani, Behzad
AU - Afrasiabi, Mousa
AU - Mohammadi, Mohammad
AU - Liu, Yang
AU - Gheisari, Mehdi
PY - 2021
Y1 - 2021
N2 - Power transformers being among the power system key components, are very important to protect. Various approaches have so far been proposed for this topic. Artificial intelligence (AI) has provided a concrete basis for numerous power transformer differential protection methodologies. However, the capabilities of AI-based methods have never been put into comparison. This paper provides a comparative analysis of various AI-based approaches for differential protection of power transformers. The performances of AI-based differential protection schemes are investigated in the presence of current transformer (CT) saturation condition, series capacitors compensation, and superconductor fault current limiter (SFCL), which possibly deteriorate the capability of differential protections to correctly tell inrush currents and internal faults apart. The PSCAD/EMTDC simulation tool is applied in producing the necessary test dataset for performance evaluation of the suggested novel strategy. The attained outcomes from the assessment of various methods have been analyzed to introduce the most superior AI-based differential protection scheme.
AB - Power transformers being among the power system key components, are very important to protect. Various approaches have so far been proposed for this topic. Artificial intelligence (AI) has provided a concrete basis for numerous power transformer differential protection methodologies. However, the capabilities of AI-based methods have never been put into comparison. This paper provides a comparative analysis of various AI-based approaches for differential protection of power transformers. The performances of AI-based differential protection schemes are investigated in the presence of current transformer (CT) saturation condition, series capacitors compensation, and superconductor fault current limiter (SFCL), which possibly deteriorate the capability of differential protections to correctly tell inrush currents and internal faults apart. The PSCAD/EMTDC simulation tool is applied in producing the necessary test dataset for performance evaluation of the suggested novel strategy. The attained outcomes from the assessment of various methods have been analyzed to introduce the most superior AI-based differential protection scheme.
KW - Artificial Intelligence (AI)
KW - CT Saturation
KW - Differential Protection
KW - inrush current
KW - internal fault
KW - Superconductor Fault Current Limiter (SFCL)
UR - http://www.scopus.com/inward/record.url?scp=85126429595&partnerID=8YFLogxK
U2 - 10.1109/EEEIC/ICPSEUROPE51590.2021.9611033
DO - 10.1109/EEEIC/ICPSEUROPE51590.2021.9611033
M3 - Conference contribution
AN - SCOPUS:85126429595
T3 - 21st IEEE International Conference on Environment and Electrical Engineering and 2021 5th IEEE Industrial and Commercial Power System Europe, EEEIC / I and CPS Europe 2021 - Proceedings
BT - 21st IEEE International Conference on Environment and Electrical Engineering and 2021 5th IEEE Industrial and Commercial Power System Europe, EEEIC / I and CPS Europe 2021 - Proceedings
A2 - Leonowicz, Zbigniew M.
PB - Institute of Electrical and Electronics Engineers (IEEE)
T2 - 21st IEEE International Conference on Environment and Electrical Engineering and 2021 5th IEEE Industrial and Commercial Power System Europe, EEEIC / I and CPS Europe 2021
Y2 - 7 September 2021 through 10 September 2021
ER -
