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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Main Authors: David Borge-Diez, Pedro Miguel Ortega-Cabezas, Antonio Colmenar-Santos, Jorge Juan Blanes-Peiró
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/14/12/3483
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spelling 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
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AT antoniocolmenarsantos contributionofdrivingefficiencytovehicletobuilding
AT jorgejuanblanespeiro contributionofdrivingefficiencytovehicletobuilding
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