Internship | health-aware operation for renewable hybrid power plant

About this position

The deployment of renewable hybrid power plants faces significant reliability challenges due to exposure to harsh environmental conditions and uncertain operating scenarios. Currently, energy management systems primarily focus on short-term, day-ahead profit maximization, often neglecting the potential degradation of key assets within the hybrid power plant. A lack of awareness regarding the health status of these assets can jeopardize operational safety and impede the widespread adoption of hybrid power plants in power supply applications. This internship vacancy seeks an enthusiastic Master’s student with a strong background to contribute to the development of a health-aware smart operation strategy for renewable hybrid power plants as part of a master's thesis project. Our aim is to investigate emerging AI and machine learning techniques and their application in the realm of health-aware smart operations—an area central to TNO’s exploratory research program ‘HyDeTwin’ and the recently awarded CETP project ‘DigitSENSE’. As an intern, you will collaborate with a multidisciplinary team at TNO, participating in the conceptual development of health-aware smart operation strategies. This internship offers a unique opportunity to work at the intersection of renewable energy, optimization, AI and machine learning, and control theory. What will be your role?

During this internship, you will work on the development and evaluation of health-aware operation strategy of the renewable hybrid power plant for a specific use case.

Typical activities include:

· Identify the control/optimization problem and knowledge gap.

· Develop a health-aware smart control algorithm that can (partially) solve the problem.

· Compare the developed health-aware smart control algorithm with the baseline method.

· Documenting the research, draw technical conclusions and recommendations.

You will contribute to ongoing research activities within TNO and gain hands-on experience with control and optimization, surrogate modelling, and scientific software development.

What we expect from you

For this internship, we are looking for a Master's student with a background in:

Mechanical Engineering

Control Engineering

Electrical Engineering

Wind energy

Renewable energy

Mathematics

or a related field

Preferred qualifications:

· Solid background in mathematical optimization (e.g. MILP, operations research, convex optimization, or decomposition techniques).

· Experience with Python and scientific computing.

· Interest in energy systems and advanced optimization methods.

· Ability to work independently and communicate technical results clearly.

We are looking for a curious and proactive student who enjoys solving challenging technical problems and contributing to applied research.

Duration: preferably 9 months, with some flexibility depending on 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.