About this position
Electricity grids are increasingly the bottleneck of the energy transition. Energy system optimisation models can show where new generation or large loads are valuable from a system perspective, but they give limited insight into network congestion, operational limits and reinforcement needs. In this internship, you will develop a workflow that couples energy system optimisation models with transmission grid models in DIgSILENT PowerFactory, and use it to assess how the siting of large-scale generation affects congestion and reinforcement needs. You will work in a multidisciplinary TNO team on a topic with direct relevance to ongoing customer projects. What will be your role?
During this internship, you will build and apply a multi-scale grid assessment workflow, from system-level optimisation to detailed network analysis in PowerFactory.
Typical activities include:
Building and verifying a representative transmission grid model in PowerFactory from open data. Developing an automated Python interface that maps generation and load scenarios from existing energy system optimisation models (Python/Pyomo) onto the network model and runs load-flow and N-1 contingency analysis. Feeding congestion and N-1 violations detected in PowerFactory back into the optimisation as nodal or corridor capacity limits, and iterating until the scenario is network-feasible. Assessing siting options for large-scale generation in terms of congestion, line loading, voltage limits and reinforcement needs. Where relevant, evaluating short-circuit levels at candidate connection points. Documenting the methodology and results in a thesis and technical report, with the opportunity to co-author a scientific publication. You will gain hands-on experience with industry-standard power system software and optimisation, and contribute directly to TNO’s grid modelling capability.
What we expect from you
For this internship, we are looking for a Master's student with a background in:
Electrical Power Engineering Sustainable Energy Technology Systems & Control Operations Research Mathematics or a related field Preferred qualifications:
Solid knowledge of power systems (load flow, network operation, contingency analysis). Experience with DIgSILENT PowerFactory or a comparable tool (e.g. PSS/E, pandapower or PyPSA); PowerFactory scripting is a plus. Basic knowledge of mathematical optimisation (LP/MILP) and experience with Python. Interest in grid congestion and the integration of large-scale generation into power systems. Ability to work independently and communicate technical results clearly in English. We are looking for a curious and proactive student who enjoys connecting models across scales and working on applied research with real-world impact.
Duration: 9 months, as a graduation (thesis) internship; start date can be aligned with university requirements.
What you'll get in return
An internship at TNO means working in an environment where substance and impact are central. You will become part of a knowledge organisation where research and practice come together, and where experts collaborate on solutions to current societal and technological challenges.
Your internship is a period in which you can discover what suits you, where your strengths lie and what you would like to learn next. You are part of a professional working environment, gain insight into how things work in practice, and have the opportunity to build experience that goes beyond this internship alone. For many students, an internship is therefore also a first step in discovering whether TNO could be a potential next step after graduation.
In addition, we offer you:
A professional and innovative internship environment in which you actively contribute to societal and technological challenges, working alongside leading experts in your field. Personal and dedicated supervision, with focus on your learning objectives, development and study assignment. Room to develop: you gain relevant work experience, develop both your subject‑specific and professional skills, and build a valuable network. Use of a laptop and the facilities you need to perform your work effectively. A monthly internship allowance of € for a full-time internship, for MSc, BSc and vocational education (MBO) students. Up to eight hours of leave per internship month for a full-time internship, allowing you to balance your internship with your studies and personal life. A contribution towards travel expenses if you are not entitled to a student travel card. A free membership to the network for young colleagues, where you can meet other TNO colleagues and participate in sports activities, professional and personal development activities, and social events such as the annual ski trip.