Open AccessMultifunctional applications of batteries within fast‐charging stations based on EV demand‐prediction of the users’ behaviour
Author(s) -
Gjelaj Marjan,
Arias Nataly Bañol,
Traeholt Chresten,
Hashemi Seyedmostafa
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.9280
Subject(s) - battery (electricity) , computer science , probabilistic logic , automotive engineering , energy storage , smart grid , grid , reliability engineering , peaking power plant , power (physics) , electric power system , real time computing , electrical engineering , engineering , quantum mechanics , artificial intelligence , physics , geometry , mathematics
This study presents a methodology to improve the operation of the power system and to deal with technical issues caused by electric vehicles (EVs) fast charging load. Fast charging stations (FCSs) are indispensable for widespread use of EVs since they can fully charge EVs in a short period of time. The integration of battery energy storage (BES) within the FCSs is considered a smart option to avoid the power congestion during the peak hours as well as the grid reinforcement costs due to FCSs. In addition, the BES can be used as multifunctional equipment, which is able to provide services such as peak shaving and frequency regulation. This study proposes a method to determine an optimal size of BES considering a stochastic modelling approach of the EVs load demand based on the users’ behaviour and their probabilistic driving patterns. Finally, a case study is carried out using a real DC fast‐charging infrastructure in Copenhagen.