Electric vehicle fast charging with energy storage and generation capabilities - Simulations based on real charging data
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Date
2020-02-06
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Abstract
The increasing use of electric vehicles (EV) brings up the need to invest in the charg-
ing infrastructure and extend the number of charging sites and stations. Especially
the integration of fast charging sites increases the convenience for the user. The
growing utilization of charging sites is also a chance to learn about charging be-
haviour and future needs. In this thesis, usage data of a charging site in Norway
is processed by a self-developed modelling tool, to create charging profiles based
on the measured energy data. Additionally an optimized peak-shaving approach is
examined. The capabilities and influence of an integrated battery electric storage
(BES) system and a photovoltaic (PV) system on the charging profiles are anal-
ysed. The peak-shaving reaches values between 30% and 60% depending on the
BES and PV configuration. Based on the results, differences and patterns in the
charging behaviour are visible on a weekly and monthly basis. The results of the
peak-shaving indicate a correlation of higher peak-shaving with a increasing BES
capacity. The PV system introduces more flexibility to the charging site that implies
more independence of the grid.