Impact of EV Charging on Power System with High Penetration of EVs: Simulation and Quantitative Analysis Based on Real World Usage Data

2020-01-0531

04/14/2020

Features
Event
WCX SAE World Congress Experience
Authors Abstract
Content
The adoption of electric vehicles (EVs) has been announced worldwide with the aim of reducing CO2 emissions. However, a significant increase in electricity demand by EVs might impact the stable operation of the existing power grid. Meanwhile, EV charging is acceptable to most users if it is completed by the time of the next driving event. From the viewpoint of power grid operators, flexibility for shifting the timing of EV charging would be advantageous, including making effective use of renewable energy.
In this work, an EV model and simulation tool were developed to make clear how the total charging demand of all EVs in use will be influenced by future EV specifications (e.g., charge power) and installation of charging infrastructure. Among the most influential factors, EV charging behavior according to use cases and regional characteristics were statistically analyzed based on the real-world usage data of over 14, 000 EVs and incorporated in the simulation tool. Using the resultant statistical model, the Monte Carlo method was applied to conduct a parameter simulation study of continuous EV usage. The impact of EV charging demand on the power grid in a future scenario and also the benefit of controlling EV charging were evaluated quantitatively in the study. Important findings indicated that active smart charging will be necessary rather than passive control based on time-of-use tariffs.
Meta TagsDetails
DOI
https://doi.org/10.4271/2020-01-0531
Pages
8
Citation
Suzuki, K., Kobayashi, Y., Murai, K., and Ikezoe, K., "Impact of EV Charging on Power System with High Penetration of EVs: Simulation and Quantitative Analysis Based on Real World Usage Data," SAE Technical Paper 2020-01-0531, 2020, https://doi.org/10.4271/2020-01-0531.
Additional Details
Publisher
Published
Apr 14, 2020
Product Code
2020-01-0531
Content Type
Technical Paper
Language
English