Mitigation of Equipment Overload and Undervoltage for Electric Vehicle Charging in Low-Voltage Distribution System
Abstract
This paper examines the impact of the rising use of electric vehicle (EV) chargers on an 18-bus low-voltage distribution system, with a focus on challenges such as overloading, energy losses, and voltage quality degradation that may compromise the efficiency of the power distribution network. To closely replicate real conditions, this research employs DIgSILENT PowerFactory to simulate and analyze a 18-bus distribution system, utilizing the Quasi-Dynamic Simulation function to accurately model the charging behavior of EV users. The analysis considers critical variables, including EV charging power, battery capacity, charging start and end times, and the state of charge (SOC). The simulation results reveal that the concurrent operation of multiple EV chargers during peak load periods can lead to transformer and feeder overloading, increased energy losses, and voltage drops below acceptable thresholds. Consequently, this study proposes an EV charger management system designed to mitigate overloads, reduce energy losses, and address voltage quality issues, thereby enhancing the stability and efficiency of the distribution network to support the expanding adoption of EV technology.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Cites
Modeling the prospects of plug-in hybrid electric vehicles to reduce CO2 emissions
Doucette, R. T., & McCulloch, M. D. (2011) · Applied Energy · doi:10.1016/j.apenergy.2011.01.045 · Cited by 252 · see citing works
Roy, P. K. S., Ilka, R., He, J., et al. (2023) · IEEE Access · doi:10.1109/access.2023.3276928 · Cited by 60 · see citing works
Impacts of Electric Vehicles Charging in Low-Voltage Distribution Networks: A Case Study in Malta
Azzopardi, B., & Gabdullin, Y. (2024) · Energies · doi:10.3390/en17020289 · Cited by 24 · see citing works
Sirisumrannukul, S. (2023) · International Transactions on Electrical Energy Systems · doi:10.1155/2023/1195648 · Cited by 16 · see citing works
Self-citationCost-benefit assessment of electric vehicle vs internal combustion engine in Latvia
Kirsanovs, V., Barisa, A., & Safronova, A. (2020) · IEEE International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON) · doi:10.1109/rtucon51174.2020.9316610 · Cited by 14 · see citing works
Flagged first, then by citations
Research works printed but not linked: 2
- Knezovic, 2017, Active integration of electric vehicles in the distribution network - theory, modelling and practice
- 2022, PowerFactory 2022 User Manual
Cited by
Still being checked.
- Authors
- Sihawong, P., Sirisumrannukul, S., Rattananatthawon, O., & Sabpayakom, N.
- Affiliations
- King Mongkut's University of Technology North Bangkok (TH)
- Venue
- 2024 IEEE International Smart Cities Conference (ISC2)
- Publisher
- IEEE
- Published
- 2024-10-29
- Pages
- 1-6
- OpenAlex
- W4410583528
- Cited by
- 2
- References
- 5
- Citations by year
- 2026: 2
- FWCI
- 1.55
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE International Smart Cities Conference (ISC2) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Keywords
- electric vehicle charging, low-voltage distribution networks, undervoltage, voltage quality, energy loss, quasi-dynamic simulation, state of charge, peak load
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
