PhD Courses in Denmark

The transition to electric mobility requires sophisticated control strategies to manage the interaction between EV fleets and the power grid. This course provides PhD students with the theoretical framework and practical tools necessary to design, implement, and analyze Energy Management Systems (EMS) for EV aggregation. By the end of the course, students will be able to transition from low-level charger control to high-level fleet optimization, considering grid constraints, economic factors, and user behavior.

A student who has met the objectives of the course will be able to:

• Analyze the technical specifications and communication protocols required for active control of EV charging infrastructure.
• Design and implement energy management techniques for EV fleet aggregation, including state-of-charge (SoC) estimation and flexibility characterization.
• Evaluate the impact of EV fleet operations on the distribution grid (e.g., congestion management, price optimization, renewable tracking).
• Conduct experimental testing of EMS algorithms in a laboratory environment.
• Synthesize research findings into a technical presentation and critically discuss the trade-offs between different management strategies.
• Collaborate effectively in interdisciplinary teams to design and evaluate EMS strategies
• Develop and validate predictive models for EV fleet behavior
• Formulate and solve advanced optimization problems for large-scale EV fleet management

This course covers the design and control of Energy Management Systems for electric vehicle fleets, from charger‑level communication to large‑scale optimization. Students learn forecasting, flexibility characterization, and advanced EMS algorithms supported by laboratory experimentation. The course combines theoretical methods with interdisciplinary teamwork to assess and present the impact of EV fleets on the power system.