PhD Position Foundation AI Models for Distribution Systems Decision-Making

The Delft University of Technology is hiring a doctoral candidate on the subject Foundation AI models for distribution systems decision-making.

Foundation models have recently emerged as a new learning paradigm in AI. These models learn from large datasets through self-supervision and have proved to generalize across many applications. Successful examples of foundation models include commercial large language models (LLMs), but their applications extend to time-series data, audio, and video. The potential of foundation AI models for power systems has already been recognized, with features such as the ability to generalize across multiple tasks (e.g., power flow calculations, congestion management, voltage control) with a single architecture and to learn from multimodal data sources highlighted as crucial for power systems applications. Nevertheless, scientific challenges still need to be addressed before such foundation AI models can be used in a loop for decision-making in distribution systems. This PhD position aims to address some of these scientific challenges, including how to properly incorporate power systems physics into the foundation AI model architecture, as well as how to develop an architecture that is invariant to the distribution system topology.

This is a four-year doctoral appointment. You will be jointly supervised by Dr. Pedro P. Vergara (Associate Professor) and Prof. Peter Palensky (Chair IEPG). You will be a member of the section Intelligent Electrical Power Grids in the Faculty of Electrical Engineering, Mathematics, and Computer Science. The project will offer opportunities to collaborate with industrial partners and with academics from other disciplines, including mathematics and operations research. Within the team, we strive to develop methods that are mathematically rigorous and have near-term application potential. We are strong supporters of open science (publishing, source code, data). You will also be expected to assist in teaching activities, including student supervision and labs, related to your subject area.

About the ESE Department

The research in the Department of Electrical Sustainable Energy is inspired by the technical, scientific, and societal challenges originating from the transition towards a more sustainable society and focuses on four areas:

• DC Systems, Energy Conversion and Storage (DCE&S)
• Photovoltaic Materials and Devices (PVMD)
• High Voltage Technologies (HVT)
• Intelligent Electrical Power Grids (IEPG)

The Electrical Sustainable Energy Department provides expertise in each of these areas throughout the entire energy system chain. The department owns a large ESP laboratory assembling High Voltage testing, a DC Grids testing environment, and a large RTDS that is actively used for real-time simulation of future electrical power systems, AC and DC protection, and wide-area monitoring and protection.

The Intelligent Electrical Power Grid (IEPG) group, headed by Professor Peter Palensky, works on the future of our power system. The goal is to generate, transmit, and use electrical energy in a highly reliable, efficient, stable, clean, affordable, and safe way. IEPG integrates new power technologies and smart controls, which interact with other systems and allow for more distributed and variable generation.

Job requirements

Essentials:

• Basic knowledge of power systems and machine learning/AI.
• Completed an MSc degree in a highly technical related discipline, such as computer science or electrical engineering, and you were at the top of your class.
• Excellent analytical skills and a solid basis in machine learning and/or operational research. You can understand literature in both disciplines.
• Excellent oral and written communication skills in English proven by a minimum score of 100 in TOEFL or IELTS of 7.0 per sub-skill (writing, reading, listening, speaking).
• You enjoy performing research.
• You are independent, self-motivated and eager to learn.
• You are keen to work with partners to link real-world challenges to fundamental research questions.

Desirables:

• Experience with optimization methods and scheduling problems as well as optimization packages such as Pyomo.
• You enjoy programming and have experience with Python, machine learning, command-line tools, and version control.

TU Delft (Delft University of Technology)

Working at TU Delft means contributing to solutions that really make a difference.

At TU Delft, our people make the difference. With their knowledge and curiosity, our staff provide high-quality education and conduct pioneering research that extends beyond the campus. You will have the opportunity to take the initiative, work with others, and grow as a professional.

Working at TU Delft means joining an international community of professionals and students. Together, we create knowledge, innovations, and solutions that help move the world forward.

Faculty of Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment, including AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words, there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position.

Conditions of employment

Doctoral candidates will be offered a 4-year period of employment in principle, in the form of 2 employment contracts. An initial 1.5 year contract includes an official go/no go progress assessment within 15 months, followed by an additional contract for the remaining 2.5 years assuming everything goes well and performance requirements are met.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.