A Lightweight User Interface for Smart Charging of Electric Vehicles: A Real-World Application

Author(s):  
Stefan Meisenbacher ◽  
Karl Schwenk ◽  
Johannes Galenzowski ◽  
Simon Waczowicz ◽  
Ralf Mikut ◽  
...  
Author(s):  
Stefan Meisenbacher ◽  
Karl Schwenk ◽  
Johannes Galenzowski ◽  
Simon Waczowicz ◽  
Ralf Mikut ◽  
...  

2018 ◽  
Vol 9 (2) ◽  
pp. 17 ◽  
Author(s):  
Jerome Mies ◽  
Jurjen Helmus ◽  
Robert van den Hoed

The mass adoption of Electric Vehicles (EVs) might raise pressure on the power system, especially during peak hours. Therefore, there is a need for delayed charging. However, to optimize the charging system, the progression of charging from an empty battery to a full battery of the EVs, based on real-world data, needs to be analyzed. Currently, many researchers view this charging profile as a static load and ignore the actual charging behavior during the charging session. However, this study investigates how different factors influence the charging profile of individual EVs based on real-world data of charging sessions in The Netherlands, and thereby enable optimization analysis of EV smart charging schemes.


2021 ◽  
Vol 100 ◽  
pp. 103023
Author(s):  
Sierra I. Spencer ◽  
Zhe Fu ◽  
Elpiniki Apostolaki-Iosifidou ◽  
Timothy E. Lipman

2020 ◽  
Vol 11 (1) ◽  
pp. 21 ◽  
Author(s):  
Pieter C. Bons ◽  
Aymeric Buatois ◽  
Guido Ligthart ◽  
Frank Geerts ◽  
Nanda Piersma ◽  
...  

A smart charging profile was implemented on 39 public charging stations in Amsterdam on which the current level available for electric vehicle (EV) charging was limited during peak hours on the electricity grid (07:00–08:30 and 17:00–20:00) and was increased during the rest of the day. The impact of this profile was measured on three indicators: average charging power, amount of transferred energy and share of positively and negatively affected sessions. The results are distinguished for different categories of electric vehicles with different charging characteristics (number of phases and maximum current). The results depend heavily on this categorisation and are a realistic measurement of the impact of smart charging under real world conditions. The average charging power increased as a result of the new profile and a reduction in the amount of transferred energy was detected during the evening hours, causing outstanding demand which was solved at an accelerated rate after limitations were lifted. For the whole population, 4% of the sessions were positively affected (charged a larger volume of energy) and 5% were negatively affected. These numbers are dominated by the large share of plug-in hybrid electric vehicles (PHEVs) in Amsterdam which are technically not able to profit from the higher current levels. For new generation electric vehicles, 14% of the sessions were positively affected and the percentage of negatively affected sessions was 5%.


2012 ◽  
Author(s):  
Kelly Dyjak Leblanc ◽  
Caitlin Femac ◽  
Craig N. Shealy ◽  
Renee Staton ◽  
Lee G. Sternberger

2002 ◽  
Author(s):  
Janel H. Rogers ◽  
Heather M. Ooak ◽  
Ronald A. Moorre ◽  
M. G. Averett ◽  
Jeffrey G. Morrison

Author(s):  
Dilpreet Singh Brar ◽  
Amit Kumar ◽  
Pallavi ◽  
Usha Mittal ◽  
Pooja Rana

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