Internship | AI-driven decision support for offshore wind farm daily maintenance planning

About this internship

Offshore wind energy has expanded rapidly in recent years, driven in part by advances in technology and improving site economics. Despite the sector’s impressive progress, reducing the levelized cost of energy (LCOE) remains a significant challenge. A major contributor to the LCOE is the cost of operations and maintenance (O&M).

To carry out daily maintenance tasks, offshore wind farm operators must coordinate a large number of site visits for minor repairs, inspections, component replacements, and other service activities. Traditional approaches—manually organizing vessels, technicians, and resources—are often inefficient, resulting in unnecessary expenses and wasted capacity. This challenge becomes even more pronounced as the scale of offshore wind farms continues to grow at an accelerating pace.

Despatch, developed by TNO, offers an effective solution to support this complex decision‑making process. Using a metaheuristic optimization model, it identifies optimal schedules for daily maintenance activities based on a chosen objective, e.g. minimization of total maintenance cost. The tool generates realistic maintenance plans that account for weather conditions, resource availability, and open work orders.

We are seeking a motivated student to join our team and contribute to the ongoing development of the optimization model within Despatch.

At the Wind Energy (WE) expertise group of TNO we aim to make wind energy a reliable, integrated, and cost-effective source of renewable energy that is widely accepted by the public. Our team has years of experience in the modelling and optimization of offshore wind and hybrid power plant. This knowledge and experience drives the further development and extension of our cutting-edge modelling tools. We are looking for a master student to work on this topic, and provide a study on learning-based digital twin for offshore wind turbine visual sensors. Do you want to join us in building a more sustainable future?

In this project, you will:

• Study and review the state-of-the-art methods, e.g. genetic algorithm, for offshore wind farm daily maintenance planning;
• Continue develop metaheuristic optimization model in the Despatch and test it with real-world data;
• Provide case studies through the developed tool;
• Assist TNO colleagues to further develop in-house code that is linked to the topic;
• Contributing to technical reports, presentations.

Ultimately, your work will facilitate the design and business case evaluation of Despatch application to offshore wind farm daily maintenance planning.

What we expect from you

We are looking for students with a relevant engineering background (e.g. computer science, data science, Mechanical engineering sustainable energy technology) with great programming skill, currently enrolled in an MSc program and with the following prerequisites:

• Enthusiasm for research and technology development.
• Highly motivated to work within the renewable energy industry or academia.
• Interest in mathematical modelling, data science, computer science.
• Strong programming skills. Knowledge of C# and Microsoft visual studio or other programming software is a must.
• Interest in renewable energy system and machine learning algorithm design.
• Independent and self-motivated working attitude.
• Excellent communication skills in English both verbally and in writing.
• Is available to start as soon as possible for either 1) a minimum duration of six months internship or 2) nine months for a master thesis project.

What you'll get in return

• A highly professional, innovative internship environment, within a team of top experts.
• A suitable internship allowance (615 euro for wo-, hbo- and mbo-students, for a full-time internship).
• Possibility of eight hours of free leave per internship month (for a full-time internship).
• A free membership of Jong TNO, where you can meet other TNO professionals and join several activities, such as sports activities, (work-related) courses or the yearly ski-trip.
• Use of a laptop.
• An allowance for travel expenses in case you don’t receive an OV-card.

TNO as an employer

At TNO, we innovate for a healthier, safer and more sustainable life. And for a strong economy. We find each other in wonder and ingenuity. We are driven to push boundaries. There is all the space and support for your talent and ambition. You work with people who will challenge you: who inspire you and want to learn from you. Our state-of-the-art facilities are there to realize your vision. What you do at TNO matters: impact makes the difference. Because with every innovation you contribute to tomorrow’s world.

yichao.liu@tno.nl