Cloud-based Big Data Platform for Vehicle-to-Grid (V2G)
Battery Electric Vehicles (BEVs) have increasingly become prevalent over the past years. BEVs can be regarded as a grid load and as a way to support the grid (energy buffering), provided this extensive battery usage does not affect the BEV’s performance. Data from both the vehicle and the...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-03-01
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| Series: | World Electric Vehicle Journal |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2032-6653/11/2/30 |
| _version_ | 1817990050786312192 |
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| author | Florent Grée Vitaliia Laznikova Bill Kim Guillermo Garcia Tom Kigezi Bo Gao |
| author_facet | Florent Grée Vitaliia Laznikova Bill Kim Guillermo Garcia Tom Kigezi Bo Gao |
| author_sort | Florent Grée |
| collection | DOAJ |
| description | Battery Electric Vehicles (BEVs) have increasingly become prevalent over the past years. BEVs can be regarded as a grid load and as a way to support the grid (energy buffering), provided this extensive battery usage does not affect the BEV’s performance. Data from both the vehicle and the grid are required for effective Vehicle-to-Grid (V2G) implementation. As such, a cloud-based big data platform is proposed in this paper to exploit these data. Additionally, this study aims to develop smart algorithms, which optimise different factors, including BEV cost of ownership and battery degradation. Dashboards are developed to provide key information to different V2G stakeholders. |
| first_indexed | 2024-04-14T00:54:31Z |
| format | Article |
| id | doaj.art-600d32d713f84b0b9919fee426ed1781 |
| institution | Directory Open Access Journal |
| issn | 2032-6653 |
| language | English |
| last_indexed | 2024-04-14T00:54:31Z |
| publishDate | 2020-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj.art-600d32d713f84b0b9919fee426ed17812022-12-22T02:21:40ZengMDPI AGWorld Electric Vehicle Journal2032-66532020-03-011123010.3390/wevj11020030wevj11020030Cloud-based Big Data Platform for Vehicle-to-Grid (V2G)Florent Grée0Vitaliia Laznikova1Bill Kim2Guillermo Garcia3Tom Kigezi4Bo Gao5Vehicle Controls Department, AVL Powertrain UK Ltd., Langdale House, Sable Way, Southfield Business Park, Laindon, Basildon, Essex SS15 6LN, UKVehicle Controls Department, AVL Powertrain UK Ltd., Langdale House, Sable Way, Southfield Business Park, Laindon, Basildon, Essex SS15 6LN, UKVehicle Controls Department, AVL Powertrain UK Ltd., Langdale House, Sable Way, Southfield Business Park, Laindon, Basildon, Essex SS15 6LN, UKVehicle Controls Department, AVL Powertrain UK Ltd., Langdale House, Sable Way, Southfield Business Park, Laindon, Basildon, Essex SS15 6LN, UKVehicle Controls Department, AVL Powertrain UK Ltd., Langdale House, Sable Way, Southfield Business Park, Laindon, Basildon, Essex SS15 6LN, UKVehicle Controls Department, AVL Powertrain UK Ltd., Langdale House, Sable Way, Southfield Business Park, Laindon, Basildon, Essex SS15 6LN, UKBattery Electric Vehicles (BEVs) have increasingly become prevalent over the past years. BEVs can be regarded as a grid load and as a way to support the grid (energy buffering), provided this extensive battery usage does not affect the BEV’s performance. Data from both the vehicle and the grid are required for effective Vehicle-to-Grid (V2G) implementation. As such, a cloud-based big data platform is proposed in this paper to exploit these data. Additionally, this study aims to develop smart algorithms, which optimise different factors, including BEV cost of ownership and battery degradation. Dashboards are developed to provide key information to different V2G stakeholders.https://www.mdpi.com/2032-6653/11/2/30bev (battery electric vehicle)optimisationsmart chargingsmart gridv2g (vehicle-to-grid), cloudbig datamachine learning |
| spellingShingle | Florent Grée Vitaliia Laznikova Bill Kim Guillermo Garcia Tom Kigezi Bo Gao Cloud-based Big Data Platform for Vehicle-to-Grid (V2G) World Electric Vehicle Journal bev (battery electric vehicle) optimisation smart charging smart grid v2g (vehicle-to-grid), cloud big data machine learning |
| title | Cloud-based Big Data Platform for Vehicle-to-Grid (V2G) |
| title_full | Cloud-based Big Data Platform for Vehicle-to-Grid (V2G) |
| title_fullStr | Cloud-based Big Data Platform for Vehicle-to-Grid (V2G) |
| title_full_unstemmed | Cloud-based Big Data Platform for Vehicle-to-Grid (V2G) |
| title_short | Cloud-based Big Data Platform for Vehicle-to-Grid (V2G) |
| title_sort | cloud based big data platform for vehicle to grid v2g |
| topic | bev (battery electric vehicle) optimisation smart charging smart grid v2g (vehicle-to-grid), cloud big data machine learning |
| url | https://www.mdpi.com/2032-6653/11/2/30 |
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