The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Intelligent Scheduling of Hybrid and Electric Vehicle Storage Capacity in a Parking Lot for Profit Maximization in Grid Power Transactions
Abstract
Abstract – This paper proposes an intelligent method for scheduling usage of available energy storage capacity from plug-in hybrid electric vehicles (PHEV) and electric vehicles (EV). The batteries on these vehicles can either provide power to the grid when parked, known as vehicle- to-grid (V2G) concept or take power from the grid to charge the batteries on the vehicles. A scalable parking lot model is developed with different parameters assigned to fleets of vehicles. The size of the parking lot is assumed to be large enough to accommodate the number of vehicles performing grid transactions. In order to figure out the appropriate charge and discharge times throughout the day, binary particle swarm optimization is applied. Price curves from the California ISO database are used in this study to have realistic price fluctuations. Finding optimal solutions that maximize profits to vehicle owners while satisfying system and vehicle owners ’ constraints is the objective of this study. Different fleets of vehicles are used to approximate varying customer base and demonstrate the scalability of parking lots for V2G. The results are compared for consistency and scalability. Discussions on how this technique can be applied to other grid issues such as peaking power are included at the end. I.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A new optimizer using particle swarm theory
Eberhart, R., & Kennedy, J. (2002) · MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science · doi:10.1109/mhs.1995.494215 · Cited by 16,067
Kempton, W., & Tomić, J. (2005) · Journal of Power Sources · doi:10.1016/j.jpowsour.2004.12.022 · Cited by 2,126
Cited by
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
The impact of plug-in hybrid electric vehicles on distribution networks: A review and outlook
Green, R. C., Wang, L., & Alam, M. (2011) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2010.08.015 · Cited by 640
Optimal Energy Management for a Residential Microgrid Including a Vehicle-to-Grid System
Igualada, L., Corchero, C., Cruz-Zambrano, M., & Heredia, F.-J. (2014) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2014.2318836 · Cited by 285
Mehta, R., Srinivasan, D., Khambadkone, A. M., Yang, J., & Trivedi, A. (2018) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2016.2550559 · Cited by 266
A multi-objective optimization problem for allocating parking lots in a distribution network
Moradijoz, M., Parsa Moghaddam, M., Haghifam, M. R., & Alishahi, E. (2013) · International Journal of Electrical Power & Energy Systems · doi:10.1016/j.ijepes.2012.10.041 · Cited by 211
Metadata
- Authors
- Hutson, C., Venayagamoorthy, G. K., & Corzine, K. A.
- Venue
- 2008 IEEE Energy 2030 Conference
- Publisher
- IEEE
- Published
- 2008-11
- Pages
- 1-8
- OpenAlex
- W2542505360
- Cited by
- 239
- References
- 2
- FWCI
- 15.21
- Type
- conference paper
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Intelligent Scheduling of Hybrid and Electric Vehicle Storage Capacity in a Parking Lot for Profit Maximization in Grid Power Transactions. https://app.cochat.ai/papers/10.1109/energy.2008.4781051
- The paper
- Hutson, C., Venayagamoorthy, G. K., & Corzine, K. A. (2008). Intelligent Scheduling of Hybrid and Electric Vehicle Storage Capacity in a Parking Lot for Profit Maximization in Grid Power Transactions. 2008 IEEE Energy 2030 Conference. https://doi.org/10.1109/energy.2008.4781051
Data sources
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.