Integration of electric vehicles in the electric power system
Open accessAbstract
This paper presents a conceptual framework to successfully integrate electric vehicles into electric power systems. The proposed framework covers two different domains: the grid technical operation and the electricity markets environment. All the players involved in both these processes, as well as their activities, are described in detail. Additionally, several simulations are presented in order to illustrate the potential impacts/benefits arising from the electric vehicles grid integration under the referred framework, comprising steady-state and dynamic behavior analysis.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Uncoordinated EV charging can cause considerable congestion in electrical networks, especially in residential areas.
“Since drivers tend to change in times when electrical grids are already highly loaded, for example after going back home from work, EVs can cause considerable congestion in electrical networks [4,5], especially in residential areas.”
From Optimized Integration of Electric Vehicles in Low Voltage Distribution Grids (2019) · cites this paper as [5]
Many previous studies model the grid as a perfectly balanced three-phase system.
“Many previous studies, such as [5,9,10], model the grid as a perfectly balanced three phase system.”
From Optimized Integration of Electric Vehicles in Low Voltage Distribution Grids (2019) · cites this paper as [5]
Balanced three-phase approaches often omit voltage unbalances that occur between power lines in real-world systems, resulting in lack of representativeness.
“These approaches often omit the voltage unbalances which occur between the power lines in real-world systems resulting in lack of representativeness.”
From Optimized Integration of Electric Vehicles in Low Voltage Distribution Grids (2019) · cites this paper as [5]
Cited by
Sorted by citations
Mwasilu, F., Justo, J. J., Kim, E.-K., Do, T. D., & Jung, J.-W. (2014) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2014.03.031 · Cited by 1,162 · see citing works
Flexible charging optimization for electric vehicles considering distribution grid constraints
Sundstrom, O., & Binding, C. (2012) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2011.2168431 · Cited by 571 · see citing works
Energy Demand Prediction with Federated Learning for Electric Vehicle Networks
Saputra, Y. M., Hoang, D. T., Nguyen, D. N., Dutkiewicz, E., Mueck, M. D., & Srikanteswara, S. (2019) · 2019 IEEE Global Communications Conference (GLOBECOM) · doi:10.1109/globecom38437.2019.9013587 · Cited by 277 · see citing works
Richardson, P., Flynn, D., & Keane, A. (2012) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2012.2185523 · Cited by 261 · see citing works
A literature review of microgrids: A functional layer based classification
Martin-Martínez, F., Sánchez-Miralles, A., & Rivier, M. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.05.025 · Cited by 239 · see citing works
López, M. A., de la Torre, S., Martín, S., & Aguado, J. A. (2015) · International Journal of Electrical Power & Energy Systems · doi:10.1016/j.ijepes.2014.07.065 · Cited by 221 · see citing works
Verzijlbergh, R. A., De Vries, L. J., & Lukszo, Z. (2014) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2014.2300941 · Cited by 210 · see citing works
A Review on TSO-DSO Coordination Models and Solution Techniques
Givisiez, A. G., Petrou, K., & Ochoa, L. F. (2020) · Electric Power Systems Research · doi:10.1016/j.epsr.2020.106659 · Cited by 200 · see citing works
“In [31, 32], only validation aspects are investigated, i.e., the TSO dispatch is not considered.”
Tirunagari, S., Gu, M., & Meegahapola, L. (2022) · IEEE Access · doi:10.1109/access.2022.3217525 · Cited by 141 · see citing works
The role of electric vehicles in smart grids
Galus, M. D., Vayá, M. G., Krause, T., & Andersson, G. (2013) · WIREs Energy and Environment · doi:10.1002/wene.56 · Cited by 129 · see citing works
Ul-Haq, A., Azhar, M., Mahmoud, Y., Perwaiz, A., & Al-Ammar, E. (2017) · Energies · doi:10.3390/en10091351 · Cited by 83 · see citing works
Coincidence Factors for Domestic EV Charging From Driving and Plug-In Behavior
Bollerslev, J., Andersen, P. B., Jensen, T. V., Marinelli, M., Thingvad, A., Calearo, L., & Weckesser, T. (2022) · IEEE Transactions on Transportation Electrification · doi:10.1109/tte.2021.3088275 · Cited by 78 · see citing works
Saputra, Y. M., Nguyen, D. N., Hoang, D. T., Vu, T. X., Dutkiewicz, E., & Chatzinotas, S. (2022) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2020.3045987 · Cited by 76 · see citing works
Optimized Integration of Electric Vehicles in Low Voltage Distribution Grids
Spitzer, M., Schlund, J., Apostolaki-Iosifidou, E., & Pruckner, M. (2019) · Energies · doi:10.3390/en12214059 · Cited by 52 · see citing works
Zhang, Z., & Chau, K.-T. (2017) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2016.2541163 · Cited by 47 · see citing works
On-Board Chargers for Electric Vehicles: A Comprehensive Performance and Efficiency Review
Dar, A. R., Haque, A., Khan, M. A., Kurukuru, V. S. B., & Mehfuz, S. (2024) · Energies · doi:10.3390/en17184534 · Cited by 45 · see citing works
“For the implementation of V2G [122], a dependable battery management system, and a precise state-of-charge predictions, and real-time grid data collection are very important [123].”
Enhanced AIMD-based decentralized residential charging of EVs
Liu, M., & McLoone, S. (2015) · Transactions of the Institute of Measurement and Control · doi:10.1177/0142331213494100 · Cited by 36 · see citing works
Sheppard, C. J. R., Jenn, A. T., Greenblatt, J. B., Bauer, G. S., & Gerke, B. F. (2021) · Environmental Science & Technology · doi:10.1021/acs.est.0c06655 · Cited by 39 · see citing works
Strezoski, L., & Stefani, I. (2024) · International Journal of Electrical Power & Energy Systems · doi:10.1016/j.ijepes.2024.109798 · Cited by 32 · see citing works
Haque, A., Kurukuru, V. S. B., & Khan, M. A. (2019) · IET Power Electronics · doi:10.1049/iet-pel.2019.0048 · Cited by 18 · see citing works
Ikhajangbe, O. E., Dhulipati, H., & Liu, S. (2026) · IEEE Access · doi:10.1109/access.2026.3684508 · Cited by 5 · see citing works
- Authors
- Lopes, J. A. P., Soares, F. J., & Almeida, P. M. R.
- Affiliations
- Universidade do Porto (PT)
- ORCID
- Soares, F J
- Venue
- Proceedings of the IEEE
- Published
- 2011-01
- Volume
- 99
- Issue
- 1
- Pages
- 168-183
- ISSN
- 0018-9219 (ISSN-L)
- 1558-2256
- OpenAlex
- W2094392268
- Cited by
- 1,465
- References
- 0
- Citations by year
- 2026: 65 · 2025: 55 · 2024: 80 · 2023: 98 · 2022: 95 · 2021: 97 · 2020: 100 · 2019: 108 · 2018: 99 · 2017: 94 · 2016: 98 · 2015: 104 · 2014: 139 · 2013: 106 · 2012: 88
- FWCI
- 58.77
- Type
- journal article
- Language
- en
- Open access
- Locations
- Proceedings of the IEEE (publishedVersion)
- Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, other-oa)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, other-oa)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Power System Optimization
- Keywords
- electric vehicles, electricity market, electric vehicle charging, steady-state analysis, dynamic behavior, power system simulation
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