This paper proposes a method to estimate the end-of-life failure probabilities of transformers and cable lines in distribution networks considering electric vehicle charging processes. The estimation of the probabilities is obtained using a model based on Arrhenius-Weibull distribution considering different aging speed according to load variation. The EV penetration may significantly accelerate the aging speed and the loss-of-life thus has an adversary influence on failure probability and network reliability. The impacts of different penetration of electric vehicles (EVs) on the thermal aging of transformers and lines are estimated on a distribution test feeder. The simulation results illustrate the calculation and capabilities of the proposed method.

Zhao J., Arefi A., Borghetti A. (2021). End-of-life Failure Probability Assessment Considering Electric Vehicle Integration. Institute of Electrical and Electronics Engineers Inc. [10.1109/AUPEC52110.2021.9597834].

End-of-life Failure Probability Assessment Considering Electric Vehicle Integration

Borghetti A.
2021

Abstract

This paper proposes a method to estimate the end-of-life failure probabilities of transformers and cable lines in distribution networks considering electric vehicle charging processes. The estimation of the probabilities is obtained using a model based on Arrhenius-Weibull distribution considering different aging speed according to load variation. The EV penetration may significantly accelerate the aging speed and the loss-of-life thus has an adversary influence on failure probability and network reliability. The impacts of different penetration of electric vehicles (EVs) on the thermal aging of transformers and lines are estimated on a distribution test feeder. The simulation results illustrate the calculation and capabilities of the proposed method.
2021
Proceedings of 2021 31st Australasian Universities Power Engineering Conference, AUPEC 2021
1
6
Zhao J., Arefi A., Borghetti A. (2021). End-of-life Failure Probability Assessment Considering Electric Vehicle Integration. Institute of Electrical and Electronics Engineers Inc. [10.1109/AUPEC52110.2021.9597834].
Zhao J.; Arefi A.; Borghetti A.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/857177
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