Investigating the Impact of E-Mobility on the Electrical Power Grid Using a Simplified Grid Modelling Approach

Abstract

To achieve climate goals, it is necessary to decarbonise the transport sector, which requires an immediate changeover to alternative power sources (e.g., battery powered vehicles). This change will lead to an increase in the demand for electrical energy, which will cause additional stress on power grids. It is therefore necessary to evaluate energy and power requirements of a future society using e-mobility. Therefore, we present a new approach to investigate the influence of increasing e-mobility on a distribution grid level. This includes the development of a power grid model based on a cellular approach, reducing computation efforts, and allowing time and spatially resolved grid stress analysis based on different load and renewable energy source scenarios. The results show that by using the simplified grid model at least seven times, more scenarios can be calculated in the same time. In addition, we demonstrate the capability of this novel approach by analysing the influence of different penetrations of e-mobility on the grid load using a case study, which is calculated using synthetic charging load profiles based on a real-life mobility data. The results from this case study show an increase on line utilisations with increasing e-mobility and the influence of producers at the same connection point as e-mobility.

Modeling the Impact of Electric Vehicle Charging Systems on Electric Power Quality

“…As mentioned above, many analyses and simulations showing the potential impact of electromobility on electricity quality have been published. The results of these analyses are often divergent, which may result from different assumptions for building simulation models, different number and type of chargers to be modeled, and the parameters of the electricity grid adopted for the simulation [6][7][8][9][10][11][12][13][14][15][16][17][18][19].…”

“…Considering the above issues, the authors of the present study conducted their own simulation studies and based on the results of the conducted measurements, they presented their own approach on how to conduct these studies. The present study aimed to demonstrate that the appropriate development of models of electric vehicle charging systems enables to assess the impact of these systems on electricity quality by using computer simulations [12,13]. The authors of the present study also wish to draw attention to the risks and opportunities that will arise from the installation of electric vehicle chargers in power supply networks and present recommendations that can be used to develop appropriate technical standards and introduce changes to the instructions for the operation and use of distribution networks.…”

Synergies between e-Mobility and Photovoltaic Potentials—A Case Study on an Urban Medium Voltage Grid

“…The determination of synthetic charging load profiles for e-mobility is based on traffic analysis, mobility pattern and statistical data. [11] The method for this determination, we have already shown in [11], has been extended in this work, among others, by the function of taking controlled charging into account. In comparison to Gnann et al [10], where summer charging is shifted to midday and in winter the focus is on peak-shaving by charging at night, here a combination of the summer and winter strategy for controlled charging is applied, regardless of the season.…”

“…For a better use of the PV power production, stays during the day should be used for charging the EVs, such as charging at work and charging commercially. [10] Since the load profiles of e-mobility and thus the required charging infrastructure are strongly dependent on respective user behaviour of EV drivers [1,11], load shift potentials of electric vehicles for different available charging infrastructures (e.g., for charging at home vs. for charging at work) are determined in the references [10,12]. Even with an uncontrolled charging, the PV power production can be better utilised when charging at work compared to charging at home.…”

“…The approach is therefore suitable for usually time-consuming time resolved load flow calculations, e.g., with annual load profiles. [11] Besides the modelling of existing consumer and producer profiles, we determine production profiles of PV potentials and synthetic charging load profiles of e-mobility. While Su et.…”