Funding: LTP ROBUST, AI for Energy Grids
Running Period: 2023-2027
Staff: Prof. dr. Maria Vlasiou, Prof. dr. Johann Hurink, dr. Gerwin Hoogsteen
Ph.D. student: Flin Verdaasdonk
ABSTRACT
The project focuses on developing a framework for coordinating flexibility in the distribution grid. Due to the increase of decentralized electricity production and rapid electrification, the distribution grid is becoming ever more unpredictable and overloaded. Grid reinforcements could solve these issues, but in practice this will take too long to solve current day problems. A solution that is usable now is to facilitate flexible use of electricity. Flexibility in this context means to shift the usage of electricity in time where possible, to mitigate overloading. The DSO has a variety of sources of flexibility, such as specific contracts with grid users and flexibility markets. The coordination of these flexibility sources is not trivial, and developing a good method to do this is the focus of this project. This research involves machine learning, mathematical programming, implicit learning, and reinforcement learning.