Bachelor Thesis BCLR-2022-80

BibliographyMarte, Kennjy: Integrate charging stations for electric vehicles on basis of specific scenarios.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Bachelor Thesis No. 80 (2022).
56 pages, english.

Electric mobility (e-mobility) and renewable energy, gets more and more an important factor for the future. As it stands, the federal government claim greenhouse gas neutrality not later than 2045. In reverse conclusion this means that in the transport sector the CO2 emission has to be decreased significantly, because of its being one of the biggest sectors of producing greenhouse gas by 18 % in Germany. As a result the government expects 15 million electric vehicles (EV) on the streets till the end of 2030. The first projects done by Netze-BW investigated the efficiency of the actual grid by integrating several EV in different scenarios. They therefore applied various techniques, like intelligent charging management, central battery storage, and decentralized battery storage, which was directly integrated in the building. Furthermore, with the continuous development of electric cars, the infrastructure must also be examined in terms of charging stations. Many existing buildings or public charging stations were installed years ago based on the trend at the time. Since the market is booming in terms of EVs, a new concept must be considered here as well. The consideration here is now: I am constructing or planning a new building, for example a residential community of 30 apartments. How many charging points have to be installed here? How many charging points can the network handle without being overloaded? The goal should be to find the perfect number of charging points for an infrastructure to be developed. Several parameters have to be considered, such as the penetration of the grid, as well as the utilization by the users. As described above, there are currently already buildings that have installed charging points, but these are now insufficient as terms and development of EV progresses. It is now very difficult to charge one's electric car at work, for example, as there are simply no longer enough places to charge. The evaluation can be done, based on the data from the E-Mobility Carree. Here, 58 charging points for 45 electric cars were installed. From this, one can evaluate data such as: how many charging points were used at the same time during peak hours, for example in the evening hours? What was the penetration of the power grid here? On the basis of this, a model can be developed and evaluated that looks at this scenario in detail and can give an outlook as to what the necessary requirements for charging stations in new buildings or the expansion in existing buildings are. Database: - Inspection of group of people in the projects - Efficiency of the grid - Timestamps of loading processes - Loaded energy per month - Average count of loading processes Regarding the point of existing infrastructures, it might be necessary to investigate how they can be upgraded. Here, a comparison can be made with new structures, and an expansion can be planned accordingly. In addition to the current state of EV, more technologies have been developed, such as vehicle to grid (V2G). The V2G technology could help to further relieve the grid. The idea now is that the EV are available as additional external battery storage. On the aspect that we have different types of people (e.g. employees, pensioner), and in conclusion we have different charging scenarios, we could at any time charge the EV even if the State Of Charge (SOC) isn't that low. Charge the EV when the line voltage is low, and release the energy in peaks of the grid like in the evening hours by using the V2G technology. The efficiency of the grid builds on the V2G technology. If the current flow in the grid isn't used, we could store it temporarily in the EV and give it back if it's needed. The whole topic is worth mentioning, because regarding V2G technology, the EV must be connected to a charging station. This could influence the number of charging points to be deployed at a specific location.

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Department(s)University of Stuttgart, Institute of Architecture of Application Systems
Superviser(s)Aiello, Prof. Marco
Entry dateMarch 16, 2023
   Publ. Computer Science