Disruptive innovations are needed in managing and operating distribution grids. Are you our next PhD researcher exploring these innovations?

Position: PhD Student

Irène Curie Fellowship: No

Department(s): Mathematics and Computer Science

Institutes and Others: EIRES - Eindhoven Institute for Renewable Energy Systems, EAISI - Eindhoven Artificial Intelligence Systems Institute

FTE: 1.0

Date Off: 29/09/2024

Reference Number: V32.7492

Job Description

The role of the distribution system operator (DSO) is evolving from a passive maintainer of electricity networks to an active coordinator at the edge of the energy system. Customers are transitioning from passive energy users to active participants in the local electricity system. Maintaining privacy and grid (cyber) security levels are crucial challenges.

A digital transformation at the edge of the distribution grid and connected customers is underway. This transformation enables the deployment of distributed intelligence for smart network operations by collecting and processing data while preserving high levels of customer privacy. The project, titled "Exploring AI Models for Smart System Operation (AISO)," is a collaboration between DSO Alliander and the TU/e departments of Electrical Engineering (Electrical Energy Systems group) and Mathematics & Computer Science (Interconnected Resource-aware Intelligent Systems, and Stochastic Operations Research). The goal is to realize these innovations.

The project is part of the TU/e’s Eindhoven AI Systems Institute (EAISI) and Eindhoven Institute for Renewable Energy Systems (EIRES) programs. It will share, learn, and disseminate within the EAISI and EIRES communities and through the TU/e master programs in Data Science and AI, Medical Engineering, and AI Engineering Systems, as well as educational activities from the TU/e Electrical Energy Systems group and Math & Computer Science department.

If you are eager to work with a multi-disciplinary team focusing on AI-driven applications to support the DSO, then this is the right position for you.

Job Description

The project focuses on synthetic data generation, AI-driven state estimation, stochastic modeling, reliability assessment, and grid-edge optimal solutions. These models will be combined with AI-driven state estimations to enhance network observability and grid monitoring. Integration with stochastic modeling and reliability assessment will provide insights into the impact of uncertainties on grid reliability. These advancements will enable optimal solutions for electricity grids in the Netherlands and beyond while maintaining user privacy.

The research results will be immediately utilized by Alliander for congestion estimation and flexibility procurement. All developed AI-driven models and algorithms will be implemented in production-ready open-source packages.

One of the four main research tracks (RTs) of AISO is as follows:

RT3: Stochastic Modelling and Reliability Assessment

This research will develop a thorough understanding of how various components affect overall network reliability using a microscopic bottom-up approach. Detailed agent-based probabilistic models will examine various vulnerability assessments, such as unacceptable voltage fluctuations or degradation acceleration from temporarily exceeding thermal limits, relevant to the daily operations of power systems. The research will include:

• Development of multivariate uncertainty models describing random user behavior (e.g., arrival patterns of electric vehicles and user preferences)
• Development of physical models of distribution grids, particularly for voltages: tractable linearized distflow models or less tractable but more realistic models
• Integration of component degradation models with the grid models
• Development of stochastic models considering uncertainties in load and weather forecasting
• Integration and validation of solutions in the virtual grid environment

See the other three research tracks below:

PhD1 / RT1: Synthetic Data Generation Using Multivariate Models
PhD2 / RT2: AI-Driven State Estimation and Prediction
PhD4 / RT4: Grid-Edge Optimal Solutions

Job Requirements

• An MSc degree in Computer Science, Data Science, or related fields
• A strong background in deep learning, distributed ML, and AI model optimization
• Good scientific programming skills and experience in languages such as Python, C++, Julia, etc.
• Enthusiasm for open-source and a willingness to learn basic skills of scientific software engineering
• Strong analytical, implementation, and experimentation skills
• Ability to work in an interdisciplinary team and be a team player
• Motivation to develop teaching skills and coach MSc and BSc students
• Fluent in spoken and written English (C1 level)

Conditions of Employment

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
• Salary and benefits in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. €2,770 max. €3,539).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and support to grow into a self-aware, autonomous scientific researcher. At TU/e, we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's daycare, and sports facilities.
• An allowance for commuting, working from home, and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

Information and Application

About Us

Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.

Curious to hear more about what it’s like as a PhD at TU/e? Navigate here.

Information

Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager, Bert Zwart, professor, a.p.zwart@tue.nl or +31 40 247 7391.

Visit our website for more information about the application process or the conditions of employment. You can also contact HRServices@tue.nl.
Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application

We invite you to submit a complete application by using the apply button. The application should include:

• A cover letter describing your motivation and qualifications for the position
• A curriculum vitae, including a list of your publications and the contact information of three references

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.