Vehicle to Grid from the Electric Vehicle Point-of-View to Reduce Peak Demand and System Cost

The study presents Electric Vehicle (EV) Point-of-View (POV) Vehicle to Grid (V2G) optimisation, where the system knows the trips and energy demand of the EV. This allows it to be less conservative in the departure State of Charge (SoC) of the EV battery. The peak and cost reduction of Vehicle POV optimisation are compared with state-of-the-art Location Point-of-View optimisation, this is, the car can do V2G but it has to depart each location with at least 80% SoC as the next trip energy demand is unknown. A Mix Integer Linear Programming (MILP) V2G optimisation approach is presented to reduce peak demand and total system cost of a fleet of EVs travelling between several residential locations and one common workplace. Simulations were conducted with 26 EVs unevenly distributed between five residential locations and commuters to a common workplace. The results indicate little differences in the reduction of peak demand between both POVs of V2G optimisation. However, the system cost can be further reduced with Vehicle Point-of-View optimization, saving an additional 200 euros annually per household by transporting cheaper energy from workplaces to residential locations.

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Publication Details

Published
2024-11-26
DOI
https://doi.org/10.1109/esars-itec60450.2024.10819878
Citations
1
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.21
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article

Vehicle to Grid from the Electric Vehicle Point-of-View to Reduce Peak Demand and System Cost

Pavol Bauer, Gautham Ram Chandra Mouli, Alvaro Menendez-Agudin
1 citations
Electric Vehicles and Infrastructure
0.21
article

Vehicle to Grid from the Electric Vehicle Point-of-View to Reduce Peak Demand and System Cost

Pavol Bauer, Gautham Ram Chandra Mouli, Alvaro Menendez-Agudin
article en
1 citations

Abstract

The study presents Electric Vehicle (EV) Point-of-View (POV) Vehicle to Grid (V2G) optimisation, where the system knows the trips and energy demand of the EV. This allows it to be less conservative in the departure State of Charge (SoC) of the EV battery. The peak and cost reduction of Vehicle POV optimisation are compared with state-of-the-art Location Point-of-View optimisation, this is, the car can do V2G but it has to depart each location with at least 80% SoC as the next trip energy demand is unknown. A Mix Integer Linear Programming (MILP) V2G optimisation approach is presented to reduce peak demand and total system cost of a fleet of EVs travelling between several residential locations and one common workplace. Simulations were conducted with 26 EVs unevenly distributed between five residential locations and commuters to a common workplace. The results indicate little differences in the reduction of peak demand between both POVs of V2G optimisation. However, the system cost can be further reduced with Vehicle Point-of-View optimization, saving an additional 200 euros annually per household by transporting cheaper energy from workplaces to residential locations.

Delft University of Technology (NL)
Affordable and clean energy
Openalex Percentile: Top 44%
Electric Vehicles and Infrastructure
0.21
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Vehicle to Grid from the Electric Vehicle Point-of-View to Reduce Peak Demand and System Cost — Pavol Bauer, Gautham Ram Chandra Mouli, et al. · (2024) | TGRS Research Map | TGRS