| Title |
An energy-aware algorithm for electric vehicle infrastructures in smart cities |
| ID_Doc |
41622 |
| Authors |
Palanca, J; Jordán, J; Bajo, J; Botti, V |
| Title |
An energy-aware algorithm for electric vehicle infrastructures in smart cities |
| Year |
2020 |
| Published |
|
| DOI |
10.1016/j.future.2020.03.001 |
| Abstract |
The deployment of a charging infrastructure to cover the increasing demand of electric vehicles (EVs) has become a crucial problem in smart cities. Additionally, the penetration of the EV will increase once the users can have enough charging stations. In this work, we tackle the problem of locating a set of charging stations in a smart city considering heterogeneous data sources such as open data city portals, geo-located social network data, and energy transformer substations. We use a multi-objective genetic algorithm to optimize the charging station locations by maximizing the utility and minimizing the cost. Our proposal is validated through a case study and several experimental results. (C) 2020 Elsevier B.V. All rights reserved. |
| Author Keywords |
Electric vehicle; Charging station; Genetic algorithm; Energy; Smart city; Multi-objective; Evolutionary algorithm; Deap; Peru |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000528199900033 |
| WoS Category |
Computer Science, Theory & Methods |
| Research Area |
Computer Science |
| PDF |
https://riunet.upv.es/bitstream/10251/168475/7/Palanca%3bJord%c3%a1n%3bBajo%20-%20An%20energy-aware%20algorthm%20for%20electrc%20vehclenfrastructuresn%20smart%20ctes.pdf
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