Stochastic analyses of electric vehicle charging impacts on distribution network
Abstract
A stochastic modeling and simulation technique for analyzing impacts of electric vehicles charging demands on distribution network is proposed in this paper. Different from the previous deterministic approaches, the feeder daily load models, electric vehicle start charging time, and battery state of charge used in the impact study are derived from actual measurements and survey data. Distribution operation security risk information, such as over-current and under-voltage, is obtained from three-phase distribution load flow studies that use stochastic parameters drawn from Roulette wheel selection. Voltage and congestion impact indicators are defined and a comparison of the deterministic and stochastic analytical approaches in providing information required in distribution network reinforcement planning is presented. Numerical results illustrate the capability of the proposed stochastic models in reflecting system losses and security impacts due to electric vehicle integrations. The effectiveness of a controlled charging algorithm aimed at relieving the system operation problem is also presented.
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In [139], the limiting factors were applied for the charging cycle occurring between 6 p.m. and 10 p.m.
“The limiting factors were applied for the charging cycle occurring between 6 p.m. and 10 p.m.”
From Methods and Tools for PV and EV Hosting Capacity Determination in Low Voltage Distribution Networks—A Review (2023) · cites this paper as [139]
A simple deterministic method is used in [139] to assess the impact of either average or peak load consumption from survey and measurement data.
“A simple deterministic method is used to assess the impact of either average or peak load consumption from survey and measurement data in [139].”
From Methods and Tools for PV and EV Hosting Capacity Determination in Low Voltage Distribution Networks—A Review (2023) · cites this paper as [139]
The deterministic, time series, stochastic, and optimization-based HC calculation methods can be used to estimate the HC of EV in the distribution network.
“The deterministic [139], time series [140], stochastic [141], and optimization-based [142] HC calculation methods can be used to estimate the HC of EV in the distribution network.”
From Methods and Tools for PV and EV Hosting Capacity Determination in Low Voltage Distribution Networks—A Review (2023) · cites this paper as [139]
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- Authors
- Leou, R.-C., Su, C.-L., & Lu, C.-N.
- Affiliations
- Cheng Shiu University (TW)
- National Kaohsiung Marine University (TW)
- National Sun Yat-sen University (TW)
- Venue
- IEEE Transactions on Power Systems
- Published
- 2014-05
- Volume
- 29
- Issue
- 3
- Pages
- 1055-1063
- ISSN
- 0885-8950 (ISSN-L)
- 1558-0679
- OpenAlex
- W2112161356
- Cited by
- 336
- References
- 0
- Citations by year
- 2026: 8 · 2025: 23 · 2024: 32 · 2023: 44 · 2022: 30 · 2021: 30 · 2020: 30 · 2019: 31 · 2018: 26 · 2017: 24 · 2016: 28 · 2015: 23 · 2014: 7
- FWCI
- 14.51
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Power Systems (publishedVersion)
- Funders
- National Science Council of Taiwan
- Taiwan Power Company
- 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, distribution networks, stochastic modeling, battery state of charge, charging time, three-phase load flow, system losses
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