"PhD Position on Unlocking Flexibility in Electricity Markets via Model-Predictive Control"

Job Description

Battery storage systems form a pivotal complement to wind and solar power in climate-neutral power systems. They can deliver a range of services, ranging from arbitrage to congestion management and system services. Extracting all benefits from these assets requires state-of-the-art decision support tools. These mathematical models help battery owners make strategic decisions, such as when to charge and discharge or on which electricity markets to focus.

In this PhD trajectory, we focus on designing next-generation decision support tools for battery operators, focusing on participation in multiple consecutive short-term electricity markets and congestion management. You will develop state-of-the-art model predictive control tools, explore hedging decisions, integrate data-driven models for state-of-health and degradation, and assess the impact of local connection capacity markets.

This position is funded under the BATT-AI project by NWO. You will collaborate with researchers at TU Delft and the University of Twente, as well as industrial partners.

Job Requirements

• Masters degree in science, engineering or economics (must have been awarded by the starting date).
• Strong quantitative and analytical skills.
• Very good written and spoken communication skills in English.
• Bonus: Programming experience in Julia, Python or similar; courses in Operations Research or Model Predictive Control; prior research experience in energy systems.

Conditions of Employment

4-year employment, starting with a 1.5-year contract and a go/no go assessment. Salary from €3059 to €3881 per month. Enrolled in TU Delft Graduate School.

Additional Information

Contact: Kenneth Bruninx at k.bruninx@tudelft.nl. Apply by 1 November 2025.