Abstract
The increasing share of renewable energy and the electrification of the transport sectorpose significant challenges to electricity grids. At the same time, dynamic electricity
tariffs based on day-ahead market prices offer new opportunities to efficiently unlock
load-shifting potential. This thesis aims to develop a methodological and technical foundation for implementing dynamic charging strategies for electric vehicles and to analyze
their economic and grid-related impacts.
Based on an in-depth analysis of the European spot market and relevant communication standards (in particular OCPP), a software architecture was designed and
prototypically implemented. It automatically processes price signals and generates optimized charging authorizations. The evaluation is based on real day-ahead price data
and measured charging sessions from different usage scenarios, capturing both short and
long charging windows as well as daytime and nighttime charging behavior.
Simulation results reveal substantial economic benefits: compared to a fixed tariff,
charging costs were reduced by approximately 91% under realistic tariff conditions,
without compromising user convenience. This is achieved through automated load shifting into low-price periods, requiring users to provide only the desired departure time.
Moreover, this behavior supports grid stability by flattening peak loads.
The results underline that dynamic price control represents not only an economically
attractive approach but also a scalable and practical strategy to support grid stability.
The outlook discusses further research opportunities such as load aggregation, grid
constraint integration, and vehicle-to-grid applications.
| Date of Award | 2025 |
|---|---|
| Original language | German (Austria) |
| Supervisor | Christoph Schaffer (Supervisor) |
Studyprogram
- Energy Informatics