Mitigation of Transformers’ Loss of Life in Power Distribution Networks with High Penetration of Electric Vehicles
Results in Engineering 2022
Illia Diahovchenko, Romāns Petričenko, Ļubova Petričenko, Anatolijs Mahņitko, Pavlo Korzh, Michal Kolcun, Zsolt Čonka

This paper presents a fuzzy-logic-based framework for aging mitigation of distribution transformers. At the first stage, a model for loading estimation of a transformer installed in the head of a power distribution network was developed in the MATLAB-Simulink environment. The model considers several factors that negatively affect the transformer's operation and lead to overheating of its windings, including high ambient temperatures, harmonic voltage distortions generated by nonlinear loads, reverse power flows, overloads due to high penetration of plug-in electric vehicles. At the second stage, a tuning algorithm was developed and measures aimed at optimizing the transformer's load level and power factor were elaborated. The developed model analyzes the parameters and factors that affect the normal operation of the transformer, and warns of the presence of dangerous factors that pose a threat to reliability and can lead to malfunction. Moreover, the effectiveness of photovoltaic generation units, shunt capacitor banks and battery energy storage systems, installed at the secondary voltage side, for distribution transformers' lifetime preserving were analyzed and discussed. The proposed measures allowed to reduce the transformer's loss of life more than 7 times, compared to the initial scenario.


Atslēgas vārdi
Electric vehicles Loss of life Transformer's aging Battery energy storage Photovoltaic systems Power distribution Reactive power compensation
DOI
10.1016/j.rineng.2022.100592
Hipersaite
https://www.sciencedirect.com/science/article/pii/S2590123022002626?via%3Dihub

Diahovchenko, I., Petričenko, R., Petričenko, Ļ., Mahņitko, A., Korzh, P., Kolcun, M., Čonka, Z. Mitigation of Transformers’ Loss of Life in Power Distribution Networks with High Penetration of Electric Vehicles. Results in Engineering, 2022, Vol. 15, Article number 100592. ISSN 2590-1230. Pieejams: doi:10.1016/j.rineng.2022.100592

Publikācijas valoda
English (en)
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