The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Vehicle-to-Grid Aggregator to Support Power Grid and Reduce Electric Vehicle Charging Cost
Open accessAbstract
This paper presents an optimised bidirectional Vehicle-to-Grid (V2G) operation, based on a fleet of Electric Vehicles (EVs) connected to a distributed power system, through a network of charging stations. The system is able to perform day-ahead scheduling of EV charging/discharging to reduce EV ownership charging cost through participating in frequency and voltage regulation services. The proposed system is able to respond to real-time EV usage data and identify the required changes that must be made to the day-ahead energy prediction, further optimising the use of EVs to support both voltage and frequency regulation. An optimisation strategy is established for V2G scheduling, addressing the initial battery State Of Charge (SOC), EV plug-in time, regulation prices, desired EV departure time, battery degradation cost and vehicle charging requirements. The effectiveness of the proposed system is demonstrated using a standardized IEEE 33-node distribution network integrating five EV charging stations. Two case studies have been undertaken to verify the contribution of this advanced energy supervision approach. Comprehensive simulation results clearly show an opportunity to provide frequency and voltage support while concurrently reducing EV charging costs, through the integration of V2G technology, especially during on-peak periods when the need for active and reactive power is high.
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Cites
Network reconfiguration in distribution systems for loss reduction and load balancing
Baran, M. E., & Wu, F. F. (1989) · IEEE Transactions on Power Delivery · doi:10.1109/61.25627 · Cited by 5,077
Smart Grid — The New and Improved Power Grid: A Survey
Fang, X., Misra, S., Xue, G., & Yang, D. (2012) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2011.101911.00087 · Cited by 3,405
A Survey on the Electrification of Transportation in a Smart Grid Environment
Su, W., Eichi, H., Zeng, W., & Chow, M.-Y. (2012) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2011.2172454 · Cited by 811
Optimal Bidding Strategy for Electric Vehicle Aggregators in Electricity Markets
Vagropoulos, S. I., & Bakirtzis, A. G. (2013) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2013.2274673 · Cited by 458
Vehicle-to-Grid Control for Supplementary Frequency Regulation Considering Charging Demands
Liu, H., Hu, Z., Song, Y., Wang, J., & Xie, X. (2015) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2014.2382979 · Cited by 292
A Survey of Algorithms for Distributed Charging Control of Electric Vehicles in Smart Grid
Nimalsiri, N. I., Mediwaththe, C. P., Ratnam, E. L., Shaw, M., Smith, D. B., & Halgamuge, S. K. (2020) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2019.2943620 · Cited by 271
Examination of a PHEV bidirectional charger system for V2G reactive power compensation
Kisacikoglu, M. C., Ozpineci, B., & Tolbert, L. M. (2010) · 2010 Twenty-Fifth Annual IEEE Applied Power Electronics Conference and Exposition (APEC) · doi:10.1109/apec.2010.5433629 · Cited by 267
Vehicle-to-Grid Regulation Reserves Based on a Dynamic Simulation of Mobility Behavior
Dallinger, D., Krampe, D., & Wietschel, M. (2011) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2011.2131692 · Cited by 258
A practical battery wear model for electric vehicle charging applications
Han, S., Han, S., & Aki, H. (2014) · Applied Energy · doi:10.1016/j.apenergy.2013.08.062 · Cited by 252
A cost-benefit analysis of V2G electric vehicles supporting peak shaving in Shanghai
Li, X., Tan, Y., Liu, X., Liao, Q., Sun, B., Cao, G., Li, C., Yang, X., & Wang, Z. (2020) · Electric Power Systems Research · doi:10.1016/j.epsr.2019.106058 · Cited by 218
Cited by
Ray, S., Kasturi, K., Patnaik, S., & Nayak, M. R. (2023) · Journal of Energy Storage · doi:10.1016/j.est.2023.108672 · Cited by 118
Analysis of multidimensional impacts of electric vehicles penetration in distribution networks
Ibrahim, R. A., Gaber, I. M., & Zakzouk, N. E. (2024) · Scientific Reports · doi:10.1038/s41598-024-77662-6 · Cited by 79
Metadata
- Authors
- Amamra, S.-A., & Marco, J.
- Venue
- IEEE Access
- Published
- 2019
- Volume
- 7
- Pages
- 178528-178538
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2995690832
- Cited by
- 282
- References
- 20
- FWCI
- 9.52
- Type
- journal article
- Language
- en
- Open access
- gold
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
