The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Optimal Charging of Electric Vehicles Taking Distribution Network Constraints Into Account
Open accessAbstract
The increasing uptake of electric vehicles suggests that vehicle charging will have a significant impact on the electricity grid. Finding ways to shift this charging to off-peak periods has been recognized as a key challenge for integration of electric vehicles into the electricity grid on a large scale. In this paper, electric vehicle charging is formulated as a receding horizon optimization problem that takes into account the present and anticipated constraints of the distribution network over a finite charging horizon. The constraint set includes transformer and line limitations, phase unbalance, and voltage stability within the network. By using a linear approximation of voltage drop within the network, the problem solution may be computed repeatedly in near real time, and thereby take into account the dynamic nature of changing demand and vehicle arrival and departure. It is shown that this linear approximation of the network constraints is quick to compute, while still ensuring that network constraints are respected. The approach is demonstrated on a validated model of a real network via simulations that use real vehicle travel profiles and real demand data. Using the optimal charging method, high percentages of vehicle uptake can be sustained in existing networks without requiring any further network upgrades, leading to more efficient use of existing assets and savings for the consumer.
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Citations
Cites
Distribution System Modeling and Analysis
Kersting, W. (2012) · Electric Power Engineering Series · doi:10.1201/b12056-31 · Cited by 1,241
Optimal Charging of Electric Vehicles in Low-Voltage Distribution Systems
Richardson, P., Flynn, D., & Keane, A. (2012) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2011.2158247 · Cited by 566 · cited 1×
“A further centralized approach uses linear programming to maximize the total vehicle charging power that the distribution network allows, while formulating network limitations as constraints [11].”
MethodElectric vehicles charging control in a smart grid: A model predictive control approach
Di Giorgio, A., Liberati, F., & Canale, S. (2014) · Control Engineering Practice · doi:10.1016/j.conengprac.2013.10.005 · Cited by 155
Cited by
Das, H. S., Rahman, M. M., Li, S., & Tan, C. W. (2020) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2019.109618 · Cited by 1,140
Mastoi, M. S., Zhuang, S., Munir, H. M., Haris, M., Hassan, M., Usman, M., Bukhari, S. S. H., & Ro, J.-S. (2022) · Energy Reports · doi:10.1016/j.egyr.2022.09.011 · Cited by 523
Adaptive Charging Networks: A Framework for Smart Electric Vehicle Charging
Lee, Z. J., Lee, G., Lee, T., Jin, C., Lee, R., Low, Z., Chang, D., Ortega, C., & Low, S. H. (2021) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2021.3074437 · Cited by 174
“[29], which considers an unbalanced three-phase distribution system but only in the case of wyeconnected EVSEs.”
BackgroundBrinkel, N. B. G., Gerritsma, M. K., AlSkaif, T. A., Lampropoulos, I., van Voorden, A. M., Fidder, H. A., & van Sark, W. G. J. H. M. (2020) · International Journal of Electrical Power & Energy Systems · doi:10.1016/j.ijepes.2019.105741 · Cited by 166
“, [40,41,70]) within the field of power system analysis to determine power flows, cable and transformer loadings and voltage levels in electricity grids.”
BackgroundMethodHabib, S., Khan, M. M., Abbas, F., Numan, M., Ali, Y., Tang, H., & Yan, X. (2020) · Frontiers in Energy · doi:10.1007/s11708-019-0648-5 · Cited by 46
Metadata
- Authors
- de Hoog, J., Alpcan, T., Brazil, M., Thomas, D. A., & Mareels, I.
- Venue
- IEEE Transactions on Power Systems
- Published
- 2015-01
- Volume
- 30
- Issue
- 1
- Pages
- 365-375
- ISSN
- 0885-8950 (ISSN-L)
- 1558-0679
- OpenAlex
- W2327394039
- Cited by
- 241
- References
- 3
- FWCI
- 13.80
- Type
- journal article
- Language
- en
- Open access
- green
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- de Hoog, J., Alpcan, T., Brazil, M., Thomas, D. A., & Mareels, I. (2015). Optimal Charging of Electric Vehicles Taking Distribution Network Constraints Into Account. IEEE Transactions on Power Systems. https://doi.org/10.1109/tpwrs.2014.2318293
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.