Keywords

1 Introduction

The expected strong increase in electric vehicles—30–40 million are expected in the EU by 2030—poses a major challenge for the energy system in Europe. Especially the local distribution grids may be pushed to their limits if the future owners of electric cars will charge their vehicles at the same time (e.g. mainly in the evening). Expensive reinforcements and extensions of the grid would be necessary to avoid partial shutdowns. An alternative to these reinforcement measures is the use of advanced charging solutions that can bring benefits to all stakeholders.

Within the EU-project “XL-Connect”, the following advanced charging concepts will be investigated in detail:

  • V1G: Smart charging, also called V1G, refers to the ability to modify the charging power and the charging time. This can help to reduce the grid load during peak hours and to decrease the cost of charging.

  • V2B/V2H: Vehicle-to-building (V2B) refers to the transfer of energy from an electric vehicle to a non-residential building and vehicle-to-home (V2H) to a residential building.

  • V2G: Vehicle-to-grid (V2G) refers to bidirectional energy flow between an electric vehicle and the grid. Thus, the owner of an electric vehicle becomes a “Prosumer” (consumer who also produces) of energy and can help to stabilize the grid during peak hours.

To enable the usage of these technologies on a large scale, all involved stakeholders including the EV owners need to see a clear benefit. Thus, the overall objective of the XL-Connect project is to optimize the entire charging chain—from energy provision to the end user—and to create a convincing benefit for all stakeholders.

2 Investigation of the User Behaviour

One key element to successfully apply advanced charging technologies is to understand the user behaviour related to these technologies. Figure 1 shows an overview how the models for the user behaviour shall be set up, divided in charging (Grid-to-Vehicle (G2V)) and discharging (Vehicle-to-Grid (V2G)). For both elements the users will have different interests to consider. E.g. for charging the procedures factors like time/duration, costs or related CO2-emissions might be interesting for the users. For discharging also the time/duration will be important, but probably also factors related to battery ageing (state of health (SoH)), the remaining battery state of charge (SoC) and some incentive (remuneration, free parking etc.) to attract EV owners to allow V2G will be important.

Fig. 1
An illustration depicts the investigation of the user behavior. It represents models for the user behavior that includes G 2 V and V 2 G. From G 2 V and V 2 G, S o C, destination, arrival time are summed up along with Est. After summing up est, parking time, S o C, S o H power per transformation station is produced and the users use it as incentives.

Investigation of the user behavior

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In order to investigate these aspects a questionnaire has been set up and will be distributed through the project partners of XL-Connect. The structure of the questionnaire is depicted in Fig. 2. Starting with a collection of demographic data the survey splits into persons who already drive an electric vehicle and those who plan to buy or lease one. For the first group questions regarding details of the electric car, their usage in daily life and their charging behaviour are stated. The second group gets questions regarding the time frame, reasons for an electric car as well as the planned charging behaviour. If they are unsure if they want to buy or lease an electric vehicle, the reasons for that will be asked. Finally, all persons are questioned regarding their attitude towards advanced charging technologies as smart charging, vehicle-to-home and vehicle-to-grid.

Fig. 2
A flow chart begins with the demographic data that leads to the statement do you currently drive an electric car? If yes, the details of the electric car lead to usage in daily life slash on trips followed by 3 other steps and finally to the usage of renewable energy. If no, it undergoes a series of steps that are for yes and unsure that together end the flow chart. The no of the statement also leads to the end of the chart.

Questionnaire for the investigation of the user behavior

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3 Digital Twins and Virtual Demonstration Actions

With the help of digital twins of the whole charging chain from the grid to the electric vehicles, different use cases using different advanced charging technologies can be investigated. Figure 3 shows an overview of different actors that will be represented in the digital twin and how the relations in terms of information and energy flow are expected to be.

Fig. 3
An illustration of the overview of different actors in the charging chain. It illustrates different charging locations that interact with S C S P, C P O, e M S P, N S P, and O E M. The different charging locations take power from wind turbines and others. Also, cars and trucks benefit from this process by charging.

Overview of different actors in the charging chain

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With the digital twin the so-called “upscaling” can be carried out—i.e. the number of electric vehicles can be easily changed/increased—to simulate the impact of large fleets of electric vehicles and their impact on the grid.

Virtual demonstration action—Neuman Aluminium use case:

In XL-Connect real-word demonstration actions are complemented by virtual demonstration actions, which allow the investigation of different parameters (e.g. number of electric vehicles, control strategies etc.). One of the virtual demonstration actions is the so-called “Neuman Aluminium use case”, which deals with a production site for aluminium parts and a possible use of vehicle-to-building to optimize the on-site energy management.

In general, the company Neuman Aluminium, located in Lower Austria, produces aluminium parts and has an overall yearly energy demand of ~111,000 MWh according to their energy intensive production processes. Overall, the total energy demand in 2022/23 of this use case can be divided in ~36% electricity demand and ~64% natural gas demand. According to this high energy demand, Neuman has employed three small hydroelectric power plants with an overall size of 0.95 MWp and a photovoltaic system of size 1.1 MWp. Currently, these power plants produce ~4,100 MWh/year. As the production could cover only ~10% of the needed electricity, Neuman wants to increase their renewable energy production by employing additional PV systems (up to 4 MWp) and two wind turbines (overall 10 MWp).

In XL-Connect the target is to analyse how the expansion of renewable energy power plants in combination with different storage possibilities impacts the overall energy consumption and the resulting financial benefits of Neuman Aluminium. Therefore, three future scenarios will be investigated (Table 1).

Table 1 Overview scenario setups
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To analyse these scenarios, a three-step approach is applied. In the first step, the energy production and consumption data of Neuman Aluminium will be analysed in detail in order to determine the periods and amount of surplus of energy production for the different scenarios. With these findings the impact of different sizes of battery storages can be investigated in a second step in order to achieve a self-consumption optimization or peak shaving. These results will also contain the possible economic benefit for Neuman Aluminium. In the third and last step, a vehicle-to-building solution for a parking area with 300 vehicles is investigated as an alternative storage solution to the battery storage by means of a simulation model. Therefore, the parking situation at Neuman Aluminium will be simulated considering the behavior of the EV owners in order to determine the available energy storage capacity during the day considering the different work shifts. When analysing this alternative solution, it is also important to find out under which conditions the employees would agree to (temporarily) discharge their vehicles. A schematic overview of the Neuman Aluminium use case can be seen in Fig. 4.

Fig. 4
An illustration depicts the Neuman use case. It illustrates energy production, energy management, and energy consumption with vehicle to building, buildings storing 300 vehicles.

Schematic overview of the “Neuman Aluminium” use case

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4 Conclusion and Outlook

The EU project “XL-Connect” is investigating advanced charging technologies as smart charging, vehicle-to-building or vehicle-to-home and vehicle-to-grid. Therefore, demonstration actions are carried out to collect the necessary data to build up a digital twin of the “charging chain”—containing all elements and actors from the vehicles to the grid. One important element related to charging technologies is the investigation of the user behaviour. So, in order to calculate the possible benefits of technologies as vehicle-to-building or vehicle-to-grid, knowing when the vehicles are connected to the charging station as well as the willingness of the users to use these technologies (i.e. allowing to discharge their vehicles) is crucial. In order to investigate the charging behaviour of the EV users as well as their attitude towards advanced charging technologies a questionnaire has been set up. The results will be assessed also related to the differences between European countries. Complementary to real-word demonstration action virtual demonstration actions are performed to analyse the possible benefits of advanced charging technologies. A virtual demonstration action assesses the benefits of a battery storage or a parking area with 300 vehicles and vehicle-to-building as alternative solution are assessed. Therefore, the production and consumption data are analysed to determine the periods and amount of surplus of energy production. With these findings the impact of different sizes of battery storages can be investigated in order to achieve a self-consumption optimization or peak shaving for three future scenarios. Finally, a vehicle-to-building solution for a parking area with 300 vehicles is investigated by means of a simulation model as an alternative storage solution to the battery storage.

Acknowledgements

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or CINEA. Neither the European Union nor the granting authority can be held responsible for them.

The publication was written at Virtual Vehicle Research GmbH in Graz and partially funded within the COMET K2 Competence Centers for Excellent Technologies from the Austrian Federal Ministry for Climate Action (BMK), the Austrian Federal Ministry for Labour and Economy (BMAW), the Province of Styria (Dept. 12) and the Styrian Business Promotion Agency (SFG). The Austrian Research Promotion Agency (FFG) has been authorised for the programme management.