The effect of price-optimized charging on electric vehicle fleet emissions

Conference paper (2020)

Authors

R. Ghotge Energy Technology - Mechanical, Maritime and Materials Engineering
A.J.M. van Wijk Energy Technology - Mechanical, Maritime and Materials Engineering
Brecht Baeten Algorithms division Enervalis
Z. Lukszo Energy and Industry
Research Group
Energy Technology (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2020 R. Ghotge, Marnix Paanakker, A.J.M. van Wijk, Brecht Baeten, Z. Lukszo
DOI
help_outline
https://doi.org/10.1109/ISGT-Europe47291.2020.9248907
Scheduling Electric vehicle Fleet emissions Well-to-tank
More Info
expand_more

Published Date

2020

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Mechanical, Maritime and Materials Engineering

Department

Process and Energy

Research Group

Energy Technology

Abstract

Aggregation of sufficiently large electric vehicle (EV) fleets and control over their charging schedules enables aggregators to utilise the flexibility of EV charging in the Day Ahead Market. Optimising the charge scheduling of such fleets enables time-shifting of electricity demand to hours when electricity is cheaper, reducing the electricity cost for charging the entire fleet. Time shifting with scheduled charging is expected to influence the average carbon intensity of the energy used by these vehicles. This work aims to quantify the change in the carbon intensity of energy used by smart charged vehicles. It uses real data collected from over 55, 000 home charging sessions from 1031 chargepoints in the Netherlands in 2018. A simulation was made with a commercial smart charging algorithm to create a scheduled charging profile ex post from the historic EV charging dataset. The simulation resulted in an average price reduction of electricity for the fleet of about 25% relative to unscheduled charging of the same fleet over the same period. The time dependent average carbon intensity of electricity consumed in the Netherlands was used to calculate the mean carbon intensity of the electricity used to charge the fleet over the period in the scheduled and unscheduled charging cases. The results revealed a small decrease in carbon intensity by 1.2%. Analysis reveals that price optimisation can have large effects on the mean carbon intensity of individual sessions in the Dutch grid, but the net effect is averaged out over a large number of sessions and over the year.

Files

09248907_1.pdf
(.pdf | 2.07 Mb)