The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
A Real-Time Charging Scheme for Demand Response in Electric Vehicle Parking Station
Abstract
Demand response (DR) is a vital part in smart grid to restore the balance between electricity demand and supply. In this paper, a real-time charging scheme is proposed to coordinate the electric vehicle (EV) charging and accommodate DR programs in the parking station. The charging scheduling is formulated as a binary optimization problem because the on-off strategy is leveraged to achieve faster charging speed of EV. Given the computationally expensive nature of exhaustive search in solving the optimal solution of binary optimization problem, a convex relaxation method is developed as an alternative to compute the near-optimal charging schedules. Extensive simulation results show that the proposed work is able to satisfy EV charging demand while accommodating both types of DR programs in the parking station. The proposed work is also able to simultaneously maximize the number of EVs for charging and minimize the monetary expenses.
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Cites
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Optimal Charging Strategies for Unidirectional Vehicle-to-Grid
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An Algorithm for Intelligent Home Energy Management and Demand Response Analysis
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Cited by
Model-Free Real-Time EV Charging Scheduling Based on Deep Reinforcement Learning
Wan, Z., Li, H., He, H., & Prokhorov, D. (2019) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2018.2879572 · Cited by 548
Arfeen, Z. A., Khairuddin, A. B., Munir, A., Azam, M. K., Faisal, M., & Arif, M. S. B. (2020) · Energy Storage · doi:10.1002/est2.115 · Cited by 68
Time-of-Use tariff rates estimation for optimal demand-side management using electric vehicles
Kaur, A. P., & Singh, M. (2023) · Energy · doi:10.1016/j.energy.2023.127243 · Cited by 67
A Hybrid Incentive Program for Managing Electric Vehicle Charging Flexibility
Wang, H., Jia, Y., Shi, M., Xie, P., Lai, C. S., & Li, K. (2023) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2022.3197422 · Cited by 59
Gupta, R. K., Fahmy, S., Chevron, M., Vasapollo, R., Figini, E., & Paolone, M. (2024) · arXiv · doi:10.48550/arxiv.2404.12863 · Cited by 1
“The second is to minimize EV battery wearing by avoiding large deviations of EV injections ( p evcs t,l,i,ω for plug l ∈ L i , node i ∈ N ev and scenario ω ∈ Ω at timestep t ∈ T ) between subsequent time-steps [35].”
Background
Metadata
- Authors
- Yao, L., Lim, W. H., & Tsai, T. S.
- Venue
- IEEE Transactions on Smart Grid
- Published
- 2017-01
- Volume
- 8
- Issue
- 1
- Pages
- 52-62
- ISSN
- 1949-3053 (ISSN-L)
- 1949-3061
- OpenAlex
- W2471802579
- Cited by
- 304
- References
- 37
- FWCI
- 10.98
- Type
- journal article
- Language
- en
- Open access
- closed
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- Yao, L., Lim, W. H., & Tsai, T. S. (2017). A Real-Time Charging Scheme for Demand Response in Electric Vehicle Parking Station. IEEE Transactions on Smart Grid. https://doi.org/10.1109/tsg.2016.2582749
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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.
