PhD Position Distribution Systems Flexible Operation under Uncertain and Incomplete Information

Delft University of Technology; Delft; Hybrid; EUR 38,000 - 49,000; Full time

Benefits offered by this job

8% holiday allowance

8.3% end-of-year bonus

Job summary

The Delft University of Technology seeks a four-year PhD candidate to study Distribution systems with a focus on flexible operation under uncertainty, as part of the Future Network Services (FNS) project.

The PhD will be supervised by Dr. Pedro P. Vergara and Prof. Peter Palensky in the Intelligent Electrical Power Grids group, collaborating with industry and other disciplines. The role includes teaching activities and a strong emphasis on open science and practical impact.

Qualifications

• MSc in a highly technical field, top of class
• Strong analytical skills with ML or operational research foundation
• Excellent English communication (TOEFL/IELTS)
• Independent, self-motivated researcher
• Keen to link real-world challenges to fundamental research

Responsibilities

• Assist in teaching activities (supervision, labs)

Skills

Power systems basics

Analytical skills

Machine learning or optimization

English communication

Research oriented

Industry collaboration

Education

MSc in technical field

Tools

Pyomo

Python

CLI tools

Git

Job description

The Delft University of Technology is hiring a doctoral candidate on the subject “Distribution systems flexible operation under uncertain and incomplete information".

Job description

The Ph.D. position is part of the Future Network Services (FNS) Project.

The energy transition is transforming the way distribution systems at the low-voltage (LV) level are operated. Expectations are that the integration of distributed energy resources (DERs), also known as flexible assets, will continue to grow. DERs such as PVs, electric vehicles, and electric heat pumps, complemented by smart buildings, will unlock the required energy flexibility at the LV level to address technical issues such as voltage problems and network congestion. The way the flexibility provided by DERs and smart buildings can be exploited (e.g., via local flexibility markets) is still in development with many unresolved challenges. Two of these challenges revolve around data availability and operational uncertainty.

This PhD research project aims to investigate how distribution systems can exploit the flexibility of DERs and smart buildings, given limited data availability and increased operational uncertainty. Data availability is limited due to a lack of digitalization or privacy issues, while large uncertainties govern the operation of distribution systems because DERs (e.g., PV and EVs) are weather- and human behaviour-dependent. This PhD aims to address research questions such as how can AI and ML models support the coordinated operation of DERs and smart buildings in the context of limited data? How can AI and ML models increase distribution systems observability via surrogate models.

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 but also with academics from other disciplines, as required (mathematics, 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 (student supervision, labs) related to your subject area.

About the Future Network Services (FNS) Project

This PhD research is part of the Future Network Services (FNS) 6G Project, led by TNO. The FNS Project aims, among others, to deliver the innovations needed to enable real‑time services for the electricity infrastructure via 6G technologies.

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, DC Grids testing environment, and 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.
• Completed an MSc degree in a highly technical related discipline (computer science, electrical engineering, etc.) 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 maximum 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:

• Knowledge of electrical distribution systems, power flow, and congestion management.
• 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, 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 a 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.

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 – which of course includes 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. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

Conditions of employment

Doctoral candidates will be offered a 4‑year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with 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.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from €3204 - €4051 gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end‑of‑year bonus of 8.3%.

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

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.

• Hours per week: 38-40.
• FTE: 1.

Additional information

As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed.