Optimal Charging Scheduling of Electric Vehicles based on Principal Component Analysis and Convex Optimization
The widespread presence of plug-in Electric Vehicles (PEVs) in distribution power grids brings significant concerns regarding their energy demand and peak power requirements. In order to reduce the PEV load impact on power distribution networks, different strategies have been proposed based on the e...
- Autores:
-
Domínguez Jiménez, Juan Antonio
Dante, A.W.
Agbossou, K.
Henao, N.
Campillo Jiménez, Javier Eduardo
Cardenas, A.
Kelouwani, S.
- Tipo de recurso:
- Fecha de publicación:
- 2020
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/9514
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/9514
- Palabra clave:
- Electric vehicles
Principal component analysis
Demand response
Disciplined convex optimization
Time-of-use
Electricity pricing
- Rights
- closedAccess
- License
- http://purl.org/coar/access_right/c_14cb
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Optimal Charging Scheduling of Electric Vehicles based on Principal Component Analysis and Convex Optimization |
| title |
Optimal Charging Scheduling of Electric Vehicles based on Principal Component Analysis and Convex Optimization |
| spellingShingle |
Optimal Charging Scheduling of Electric Vehicles based on Principal Component Analysis and Convex Optimization Electric vehicles Principal component analysis Demand response Disciplined convex optimization Time-of-use Electricity pricing |
| title_short |
Optimal Charging Scheduling of Electric Vehicles based on Principal Component Analysis and Convex Optimization |
| title_full |
Optimal Charging Scheduling of Electric Vehicles based on Principal Component Analysis and Convex Optimization |
| title_fullStr |
Optimal Charging Scheduling of Electric Vehicles based on Principal Component Analysis and Convex Optimization |
| title_full_unstemmed |
Optimal Charging Scheduling of Electric Vehicles based on Principal Component Analysis and Convex Optimization |
| title_sort |
Optimal Charging Scheduling of Electric Vehicles based on Principal Component Analysis and Convex Optimization |
| dc.creator.fl_str_mv |
Domínguez Jiménez, Juan Antonio Dante, A.W. Agbossou, K. Henao, N. Campillo Jiménez, Javier Eduardo Cardenas, A. Kelouwani, S. |
| dc.contributor.author.none.fl_str_mv |
Domínguez Jiménez, Juan Antonio Dante, A.W. Agbossou, K. Henao, N. Campillo Jiménez, Javier Eduardo Cardenas, A. Kelouwani, S. |
| dc.subject.keywords.spa.fl_str_mv |
Electric vehicles Principal component analysis Demand response Disciplined convex optimization Time-of-use Electricity pricing |
| topic |
Electric vehicles Principal component analysis Demand response Disciplined convex optimization Time-of-use Electricity pricing |
| description |
The widespread presence of plug-in Electric Vehicles (PEVs) in distribution power grids brings significant concerns regarding their energy demand and peak power requirements. In order to reduce the PEV load impact on power distribution networks, different strategies have been proposed based on the electricity price. This paper proposes a PEV charging approach that takes advantage of a disciplined convex optimization to reduce charging station costs. The proposed method can provide an optimal charging scheduling according to Time-of-Use (TOU) rates and maximum power penalty. Furthermore, Principal Component Analysis (PCA) is utilized to rank critical users in PEV charging stations based on their contribution to on-peak periods. Simulations are carried out for nine PEV during 24hour by using real-world data from a charging station, located on-campus. The results show the capabilities of the proposed approach to effectively reduce the electricity charging costs and identify the critical users. |
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2020 |
| dc.date.accessioned.none.fl_str_mv |
2020-10-30T16:05:21Z |
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2020-10-30T16:05:21Z |
| dc.date.issued.none.fl_str_mv |
2020-07-30 |
| dc.date.submitted.none.fl_str_mv |
2020-10-29 |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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Otro |
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publishedVersion |
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J. A. Dominguez et al., "Optimal Charging Scheduling of Electric Vehicles based on Principal Component Analysis and Convex Optimization," 2020 IEEE 29th International Symposium on Industrial Electronics (ISIE), Delft, Netherlands, 2020, pp. 935-940, doi: 10.1109/ISIE45063.2020.9152292. |
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https://hdl.handle.net/20.500.12585/9514 |
| dc.identifier.doi.none.fl_str_mv |
10.1109/ISIE45063.2020.9152292. |
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Universidad Tecnológica de Bolívar |
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Repositorio Universidad Tecnológica de Bolívar |
| identifier_str_mv |
J. A. Dominguez et al., "Optimal Charging Scheduling of Electric Vehicles based on Principal Component Analysis and Convex Optimization," 2020 IEEE 29th International Symposium on Industrial Electronics (ISIE), Delft, Netherlands, 2020, pp. 935-940, doi: 10.1109/ISIE45063.2020.9152292. 10.1109/ISIE45063.2020.9152292. Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
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https://hdl.handle.net/20.500.12585/9514 |
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eng |
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eng |
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info:eu-repo/semantics/closedAccess |
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closedAccess |
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| dc.format.extent.none.fl_str_mv |
5 páginas |
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application/pdf |
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Cartagena de Indias |
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IEEE 29th International Symposium on Industrial Electronics (ISIE), Delft, Netherlands, (2020), pp. 935-940 |
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Universidad Tecnológica de Bolívar |
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Domínguez Jiménez, Juan Antonioe13f2e38-5b17-430f-b808-36bd4f35d061Dante, A.W.ff2762cf-3b64-4393-b0dd-4efbb350fad5Agbossou, K.9a60530a-3b36-4aac-914d-22214bd4004aHenao, N.273f0cef-d7d4-4cba-aa2e-006e03833f36Campillo Jiménez, Javier Eduardo8c4725e9-5e97-40df-b9ae-f67c73617ff3Cardenas, A.a0ae7d01-aefd-44b9-9806-1eefcf2de3c2Kelouwani, S.1f17e510-1a82-47ff-8f6d-869279c8e7d92020-10-30T16:05:21Z2020-10-30T16:05:21Z2020-07-302020-10-29J. A. Dominguez et al., "Optimal Charging Scheduling of Electric Vehicles based on Principal Component Analysis and Convex Optimization," 2020 IEEE 29th International Symposium on Industrial Electronics (ISIE), Delft, Netherlands, 2020, pp. 935-940, doi: 10.1109/ISIE45063.2020.9152292.https://hdl.handle.net/20.500.12585/951410.1109/ISIE45063.2020.9152292.Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThe widespread presence of plug-in Electric Vehicles (PEVs) in distribution power grids brings significant concerns regarding their energy demand and peak power requirements. In order to reduce the PEV load impact on power distribution networks, different strategies have been proposed based on the electricity price. This paper proposes a PEV charging approach that takes advantage of a disciplined convex optimization to reduce charging station costs. The proposed method can provide an optimal charging scheduling according to Time-of-Use (TOU) rates and maximum power penalty. Furthermore, Principal Component Analysis (PCA) is utilized to rank critical users in PEV charging stations based on their contribution to on-peak periods. Simulations are carried out for nine PEV during 24hour by using real-world data from a charging station, located on-campus. The results show the capabilities of the proposed approach to effectively reduce the electricity charging costs and identify the critical users.5 páginasapplication/pdfengIEEE 29th International Symposium on Industrial Electronics (ISIE), Delft, Netherlands, (2020), pp. 935-940Optimal Charging Scheduling of Electric Vehicles based on Principal Component Analysis and Convex Optimizationinfo:eu-repo/semantics/lectureinfo:eu-repo/semantics/publishedVersionOtrohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_8544Electric vehiclesPrincipal component analysisDemand responseDisciplined convex optimizationTime-of-useElectricity pricinginfo:eu-repo/semantics/closedAccesshttp://purl.org/coar/access_right/c_14cbCartagena de Indias1. I. Vassileva and J. 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Boyd, "CVXPY: A Python-Embedded Modeling Language for Convex Optimization", Journal of Machine Learning Research, vol. 17, no. 83, pp. 1-5, mar 2016, [online] Available: http://arxiv.org/abs/1603.00943.http://purl.org/coar/resource_type/c_c94fORIGINAL51.pdf51.pdfapplication/pdf66592https://repositorio.utb.edu.co/bitstream/20.500.12585/9514/1/51.pdf1aeff12e503de8296ec6f6d849107f99MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-83182https://repositorio.utb.edu.co/bitstream/20.500.12585/9514/2/license.txte20ad307a1c5f3f25af9304a7a7c86b6MD52TEXT51.pdf.txt51.pdf.txtExtracted texttext/plain6https://repositorio.utb.edu.co/bitstream/20.500.12585/9514/3/51.pdf.txt010845330ff5c8439e0a9b24de156554MD53THUMBNAIL51.pdf.jpg51.pdf.jpgGenerated Thumbnailimage/jpeg48688https://repositorio.utb.edu.co/bitstream/20.500.12585/9514/4/51.pdf.jpg3d5b731113c009863ba6b5fc5f2148cbMD5420.500.12585/9514oai:repositorio.utb.edu.co:20.500.12585/95142023-05-26 08:16:51.028Repositorio Institucional 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