Practical Testing and Modeling of Electric Vehicle Charger Responses During Power System Faults
As electric vehicles gain popularity, consumers increasingly adopt them as an alternative to traditional internal combustion engine-driven vehicles. Electric vehicle chargers integrate with distribution networks via power electronic interfaces, offering significant control and operational flexibility. The industry is quickly adapting to this rapidly emerging load type, and now requires a robust means for understanding their impact on power system operations. This paper presents a modelling approach to capture the aggregate dynamic impact of these chargers on the power system in response to a range of network fault conditions. Six commonly available electric vehicles were empirically tested under various supply disturbances using a grid simulator, and their fault ride-through performances have been characterised. The undervoltage withstand capability of the six vehicles varied considerably, with fault voltage thresholds ranging between 0.3 and 0.7 pu leading to electric vehicles either ceasing charging for between ∼2 and 10 seconds, or locking out completely. A composite dynamic load model for electric vehicles was developed and validated, employing the collected empirical data. The validation process demonstrated the aggregate load model's capability to accurately capture the resulting load deficit owing to electric vehicle fault ride-through in response to transmission-level faults. The proposed model is suitable for application in wide-area power system studies to enhance the accuracy of simulated network load response for frequency assessments, operations planning, and other system analyses.
Authors
- Evan Franklin (ORCID: https://orcid.org/0000-0002-8146-2770)
- Steve Ransome
- J. S. Lord (ORCID: https://orcid.org/0000-0001-8315-482X)
- Nathan McKillop
- Chris Wembridge
Institutions
- University of Tasmania (AU)
Publication Details
- Journal
- IEEE Transactions on Industry Applications
- Published
- 2025-04-16
- DOI
- https://doi.org/10.1109/tia.2025.3561758
- Citations
- 1
- Primary Topic
- Real-time simulation and control systems
- Type
- article
- Field-Weighted Citation Impact
- 1.21