Contribution of Driving Efficiency to Vehicle-to-Building
Energy consumption in the transport sector and buildings are of great concern. This research aims to quantify how eco-routing, eco-driving and eco-charging can increase the amount of energy available for vehicle-to-building. To do this, the working population was broken into social groups (freelance...
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doaj-7f4af1726f1945169f5f32341a70b0732021-06-30T23:59:01ZengMDPI AGEnergies1996-10732021-06-01143483348310.3390/en14123483Contribution of Driving Efficiency to Vehicle-to-BuildingDavid Borge-Diez0Pedro Miguel Ortega-Cabezas1Antonio Colmenar-Santos2Jorge Juan Blanes-Peiró3Department of Electrical and Control Engineering, Universidad de León, 24071 Léon, SpainDepartment of Electric, Electronic and Control Engineering, National Distance Education University UNED, 28040 Madrid, SpainDepartment of Electric, Electronic and Control Engineering, National Distance Education University UNED, 28040 Madrid, SpainDepartment of Electrical and Control Engineering, Universidad de León, 24071 Léon, SpainEnergy consumption in the transport sector and buildings are of great concern. This research aims to quantify how eco-routing, eco-driving and eco-charging can increase the amount of energy available for vehicle-to-building. To do this, the working population was broken into social groups (freelancers, local workers and commuters) who reside in two cities with different climate zones (Alcalá de Henares-Spain and Jaén-Spain) since the way of using electric vehicles is different. An algorithm based on the Here<sup>®</sup> application program interface and neural networks was implemented to acquire data of the stochastic usage of EVs of each social group. Finally, an increase in the amount of energy available for vehicle-to-building was assessed thanks to the algorithm. The results per day were as follows. Owing to the algorithm proposed a reduction ranging from 0.6 kWh to 2.2 kWh was obtained depending on social groups. The proposed algorithm facilitated an increase in energy available for vehicle-to-building ranging from 13.2 kWh to 33.6 kWh depending on social groups. The results show that current charging policies are not compatible with all social groups and do not consider the renewable energy contribution to the total electricity demand.https://www.mdpi.com/1996-1073/14/12/3483vehicle-to-buildingdriving efficiencyrenewable energy integrationvehicle-to-gridenergy consumption |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
David Borge-Diez Pedro Miguel Ortega-Cabezas Antonio Colmenar-Santos Jorge Juan Blanes-Peiró |
spellingShingle |
David Borge-Diez Pedro Miguel Ortega-Cabezas Antonio Colmenar-Santos Jorge Juan Blanes-Peiró Contribution of Driving Efficiency to Vehicle-to-Building Energies vehicle-to-building driving efficiency renewable energy integration vehicle-to-grid energy consumption |
author_facet |
David Borge-Diez Pedro Miguel Ortega-Cabezas Antonio Colmenar-Santos Jorge Juan Blanes-Peiró |
author_sort |
David Borge-Diez |
title |
Contribution of Driving Efficiency to Vehicle-to-Building |
title_short |
Contribution of Driving Efficiency to Vehicle-to-Building |
title_full |
Contribution of Driving Efficiency to Vehicle-to-Building |
title_fullStr |
Contribution of Driving Efficiency to Vehicle-to-Building |
title_full_unstemmed |
Contribution of Driving Efficiency to Vehicle-to-Building |
title_sort |
contribution of driving efficiency to vehicle-to-building |
publisher |
MDPI AG |
series |
Energies |
issn |
1996-1073 |
publishDate |
2021-06-01 |
description |
Energy consumption in the transport sector and buildings are of great concern. This research aims to quantify how eco-routing, eco-driving and eco-charging can increase the amount of energy available for vehicle-to-building. To do this, the working population was broken into social groups (freelancers, local workers and commuters) who reside in two cities with different climate zones (Alcalá de Henares-Spain and Jaén-Spain) since the way of using electric vehicles is different. An algorithm based on the Here<sup>®</sup> application program interface and neural networks was implemented to acquire data of the stochastic usage of EVs of each social group. Finally, an increase in the amount of energy available for vehicle-to-building was assessed thanks to the algorithm. The results per day were as follows. Owing to the algorithm proposed a reduction ranging from 0.6 kWh to 2.2 kWh was obtained depending on social groups. The proposed algorithm facilitated an increase in energy available for vehicle-to-building ranging from 13.2 kWh to 33.6 kWh depending on social groups. The results show that current charging policies are not compatible with all social groups and do not consider the renewable energy contribution to the total electricity demand. |
topic |
vehicle-to-building driving efficiency renewable energy integration vehicle-to-grid energy consumption |
url |
https://www.mdpi.com/1996-1073/14/12/3483 |
work_keys_str_mv |
AT davidborgediez contributionofdrivingefficiencytovehicletobuilding AT pedromiguelortegacabezas contributionofdrivingefficiencytovehicletobuilding AT antoniocolmenarsantos contributionofdrivingefficiencytovehicletobuilding AT jorgejuanblanespeiro contributionofdrivingefficiencytovehicletobuilding |
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