Assignment Approach for Electric Vehicle Charging Using Traffic Data Collected by SUMO
Consumption habits are changing due to the development of new technologies around renewable energy, environmental awareness, and new incentive policies. Smart grids are seen as an effective way to accommodate more renewable energy, achieve better control of demand, and improve the operating conditio...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-02-01
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| Series: | World Electric Vehicle Journal |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2032-6653/14/2/40 |
| _version_ | 1827755149549895680 |
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| author | Riham Farhani Yassin El Hillali Atika Rivenq Yahia Boughaleb Abdelowahed Hajjaji |
| author_facet | Riham Farhani Yassin El Hillali Atika Rivenq Yahia Boughaleb Abdelowahed Hajjaji |
| author_sort | Riham Farhani |
| collection | DOAJ |
| description | Consumption habits are changing due to the development of new technologies around renewable energy, environmental awareness, and new incentive policies. Smart grids are seen as an effective way to accommodate more renewable energy, achieve better control of demand, and improve the operating conditions of the electrical system. However, electric vehicles, which are an environmentally friendly alternative, have very high market penetration and require efficient electrical management at charging stations. Among the factors that have a significant impact on electrical energy consumption are traffic conditions, which can seriously impact the efficiency of electric vehicles. Therefore, the focus is on developing charging infrastructure and reducing vehicle waiting time by optimally allocating electric vehicles to charging stations. To this end, an optimization approach is presented, based on the traffic conditions collected by the SUMO simulator. This approach enables each vehicle to be assigned to the appropriate station while maintaining its battery state of charge at a higher level. |
| first_indexed | 2024-03-11T08:00:13Z |
| format | Article |
| id | doaj.art-e88e501fb7ed40659b5b046582b7b200 |
| institution | Directory Open Access Journal |
| issn | 2032-6653 |
| language | English |
| last_indexed | 2024-03-11T08:00:13Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj.art-e88e501fb7ed40659b5b046582b7b2002023-11-16T23:54:18ZengMDPI AGWorld Electric Vehicle Journal2032-66532023-02-011424010.3390/wevj14020040Assignment Approach for Electric Vehicle Charging Using Traffic Data Collected by SUMORiham Farhani0Yassin El Hillali1Atika Rivenq2Yahia Boughaleb3Abdelowahed Hajjaji4Laboratory Institute of Electronics, Microelectronics and Nanotechnology—IEMN, UPHF, 59300 Valenciennes, FranceLaboratory Institute of Electronics, Microelectronics and Nanotechnology—IEMN, UPHF, 59300 Valenciennes, FranceLaboratory Institute of Electronics, Microelectronics and Nanotechnology—IEMN, UPHF, 59300 Valenciennes, FranceLaboratory of Engineering Sciences for Energy ENSA, El Jadida 24000, MoroccoLaboratory of Engineering Sciences for Energy ENSA, El Jadida 24000, MoroccoConsumption habits are changing due to the development of new technologies around renewable energy, environmental awareness, and new incentive policies. Smart grids are seen as an effective way to accommodate more renewable energy, achieve better control of demand, and improve the operating conditions of the electrical system. However, electric vehicles, which are an environmentally friendly alternative, have very high market penetration and require efficient electrical management at charging stations. Among the factors that have a significant impact on electrical energy consumption are traffic conditions, which can seriously impact the efficiency of electric vehicles. Therefore, the focus is on developing charging infrastructure and reducing vehicle waiting time by optimally allocating electric vehicles to charging stations. To this end, an optimization approach is presented, based on the traffic conditions collected by the SUMO simulator. This approach enables each vehicle to be assigned to the appropriate station while maintaining its battery state of charge at a higher level.https://www.mdpi.com/2032-6653/14/2/40smart gridsgreen environmentelectric vehiclecharging stationtraffic conditionsSUMO |
| spellingShingle | Riham Farhani Yassin El Hillali Atika Rivenq Yahia Boughaleb Abdelowahed Hajjaji Assignment Approach for Electric Vehicle Charging Using Traffic Data Collected by SUMO World Electric Vehicle Journal smart grids green environment electric vehicle charging station traffic conditions SUMO |
| title | Assignment Approach for Electric Vehicle Charging Using Traffic Data Collected by SUMO |
| title_full | Assignment Approach for Electric Vehicle Charging Using Traffic Data Collected by SUMO |
| title_fullStr | Assignment Approach for Electric Vehicle Charging Using Traffic Data Collected by SUMO |
| title_full_unstemmed | Assignment Approach for Electric Vehicle Charging Using Traffic Data Collected by SUMO |
| title_short | Assignment Approach for Electric Vehicle Charging Using Traffic Data Collected by SUMO |
| title_sort | assignment approach for electric vehicle charging using traffic data collected by sumo |
| topic | smart grids green environment electric vehicle charging station traffic conditions SUMO |
| url | https://www.mdpi.com/2032-6653/14/2/40 |
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