"I have been working at Alliander since the beginning of 2023. I started as a consultant on a project using NIR data to determine the moisture content in electricity cables. Now, I am part of an Innovation Center for Artificial Intelligence (ICAI lab) as a data scientist/researcher. This ICAI lab is called the AI for Energy Grids Lab. The core of our lab consists of six PhD students from Radboud University, Delft University, and the University of Twente. We are investigating how to use AI to facilitate the energy transition and manage congestion and eventually to make optimal use of the grid's capacity.
Alliander and Radboud University have been working together strategically for some time to support the energy transition. The CHARGE course for data professionals is a project that grew out of this collaboration, designed to enhance our understanding and application of advanced data analysis techniques in the context of the energy transition.
Over the course of three intensive Wednesdays, we gained invaluable insights and practical skills that empowered us to tackle complex challenges. The combination of theoretical knowledge and practical application provided a well-rounded learning experience, enabling us to contribute effectively as a team to innovative solutions for real use cases from Alliander.
The program began with a focus on Time Series Analysis on the first day, covering fundamental aspects such as forecasting, clustering, and classification. We attended lectures on various time series models, including ARIMA/SARIMA and Gaussian process regression, and applied these concepts to real-world challenges during the practice sessions.
The second day focused on Network Science. The morning lectures provided a comprehensive overview of different types of networks, including connected and complete networks. etc. In the afternoon, we explored the practical applicability of the material.
The final day was dedicated to the ethical and sustainable considerations of data-driven decision-making in the energy sector. The dynamic discussions centered on fairness in grid congestion management and the broader implications of sustainability in data science and artificial intelligence.
If there is a follow-up to this course with new topics, I will participate again. It was an amazing experience to share with colleagues. As the name suggests, CHARGE: I renewed and recharged my knowledge."
Ensie Hosseini is a data scientist and researcher at Alliander. She participated in the first edition of CHARGE, a course for data professionals working in the energy transition. The third edition of CHARGE will start in November. This course is organised for Alliander, but is also open to other professionals with an interest in AI. Alliander and Radboud University are working together strategically to contribute to the energy transition.
