Online-Intelligent Demand Management of Plug-in Electric Vehicles in Future Smart Parking Lots
This paper proposes an online intelligent demand coordination of plug-in electric vehicles (PEVs) in distribution systems. The proposed method is based on the assignment of scores to PEVs through a fuzzy expert system. As well, without violation of grid operational constraints, the PEVs are optimall...
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| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , |
| التنسيق: | article |
| منشور في: |
2016
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| الوصول للمادة أونلاين: | http://hdl.handle.net/11073/16314 |
| الوسوم: |
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| _version_ | 1864513434444365824 |
|---|---|
| author | Akhavan-Rezai, Elham |
| author2 | Shaaban, Mostafa El-Saadany, Ehab Karray, Fakhri |
| author2_role | author author author |
| author_facet | Akhavan-Rezai, Elham Shaaban, Mostafa El-Saadany, Ehab Karray, Fakhri |
| author_role | author |
| dc.creator.none.fl_str_mv | Akhavan-Rezai, Elham Shaaban, Mostafa El-Saadany, Ehab Karray, Fakhri |
| dc.date.none.fl_str_mv | 2016-06 2018-11-05T08:37:07Z 2018-11-05T08:37:07Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | Akhavan-Rezai, Elham, Mostafa Shaaban, Ehab F. El-Saadany, and Fakhry Karray. "Online-Intelligent Demand Management of Plug-in Electric Vehicles in Future Smart Parking Lots." IEEE Systems Journal 10, no. 2 (2016): 483 - 494. 1937-9234 http://hdl.handle.net/11073/16314 10.1109/JSYST.2014.2349357 |
| dc.language.none.fl_str_mv | en_US |
| dc.publisher.none.fl_str_mv | Institute of Electrical and Electronics Engineers |
| dc.relation.none.fl_str_mv | IEEE Systems Journal https://doi.org/10.1109/JSYST.2014.2349357 |
| dc.title.none.fl_str_mv | Online-Intelligent Demand Management of Plug-in Electric Vehicles in Future Smart Parking Lots |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | This paper proposes an online intelligent demand coordination of plug-in electric vehicles (PEVs) in distribution systems. The proposed method is based on the assignment of scores to PEVs through a fuzzy expert system. As well, without violation of grid operational constraints, the PEVs are optimally charged in order to maximize the owners' satisfaction in terms of the energy delivered. The optimization problem of online PEV charging is defined as mixed-integer nonlinear programming. Simulation on a typical distribution network proves the effectiveness of the proposed methodology. Results of the analysis indicate that for more critical PEVs, which have shorter parking duration and higher required charging time, the proposed solution outperforms in more robust energy delivery to the PEV and, accordingly, more satisfaction for the owner. |
| format | article |
| id | aus_f54dccfe07c765c2a3eb4900ff5d36d2 |
| identifier_str_mv | Akhavan-Rezai, Elham, Mostafa Shaaban, Ehab F. El-Saadany, and Fakhry Karray. "Online-Intelligent Demand Management of Plug-in Electric Vehicles in Future Smart Parking Lots." IEEE Systems Journal 10, no. 2 (2016): 483 - 494. 1937-9234 10.1109/JSYST.2014.2349357 |
| language_invalid_str_mv | en_US |
| network_acronym_str | aus |
| network_name_str | aus |
| oai_identifier_str | oai:repository.aus.edu:11073/16314 |
| publishDate | 2016 |
| publisher.none.fl_str_mv | Institute of Electrical and Electronics Engineers |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Online-Intelligent Demand Management of Plug-in Electric Vehicles in Future Smart Parking LotsAkhavan-Rezai, ElhamShaaban, MostafaEl-Saadany, EhabKarray, FakhriThis paper proposes an online intelligent demand coordination of plug-in electric vehicles (PEVs) in distribution systems. The proposed method is based on the assignment of scores to PEVs through a fuzzy expert system. As well, without violation of grid operational constraints, the PEVs are optimally charged in order to maximize the owners' satisfaction in terms of the energy delivered. The optimization problem of online PEV charging is defined as mixed-integer nonlinear programming. Simulation on a typical distribution network proves the effectiveness of the proposed methodology. Results of the analysis indicate that for more critical PEVs, which have shorter parking duration and higher required charging time, the proposed solution outperforms in more robust energy delivery to the PEV and, accordingly, more satisfaction for the owner.Institute of Electrical and Electronics Engineers2018-11-05T08:37:07Z2018-11-05T08:37:07Z2016-06info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfAkhavan-Rezai, Elham, Mostafa Shaaban, Ehab F. El-Saadany, and Fakhry Karray. "Online-Intelligent Demand Management of Plug-in Electric Vehicles in Future Smart Parking Lots." IEEE Systems Journal 10, no. 2 (2016): 483 - 494.1937-9234http://hdl.handle.net/11073/1631410.1109/JSYST.2014.2349357en_USIEEE Systems Journalhttps://doi.org/10.1109/JSYST.2014.2349357oai:repository.aus.edu:11073/163142024-08-22T12:18:00Z |
| spellingShingle | Online-Intelligent Demand Management of Plug-in Electric Vehicles in Future Smart Parking Lots Akhavan-Rezai, Elham |
| status_str | publishedVersion |
| title | Online-Intelligent Demand Management of Plug-in Electric Vehicles in Future Smart Parking Lots |
| title_full | Online-Intelligent Demand Management of Plug-in Electric Vehicles in Future Smart Parking Lots |
| title_fullStr | Online-Intelligent Demand Management of Plug-in Electric Vehicles in Future Smart Parking Lots |
| title_full_unstemmed | Online-Intelligent Demand Management of Plug-in Electric Vehicles in Future Smart Parking Lots |
| title_short | Online-Intelligent Demand Management of Plug-in Electric Vehicles in Future Smart Parking Lots |
| title_sort | Online-Intelligent Demand Management of Plug-in Electric Vehicles in Future Smart Parking Lots |
| url | http://hdl.handle.net/11073/16314 |