  The energy transition introduces more volatile energy sources into the power
grids. In this context, power transfer between different synchronous areas
through High Voltage Direct Current (HVDC) links becomes increasingly
important. Such links can balance volatile generation by enabling long-distance
transport or by leveraging their fast control behavior. Here, we investigate
the interaction of power imbalances - represented through the power grid
frequency - and power flows on HVDC links between synchronous areas in Europe.
We use explainable machine learning to identify key dependencies and
disentangle the interaction of critical features. Our results show that
market-based HVDC flows introduce deterministic frequency deviations, which
however can be mitigated through strict ramping limits. Moreover, varying HVDC
operation modes strongly affect the interaction with the grid. In particular,
we show that load-frequency control via HVDC links can both have control-like
or disturbance-like impacts on frequency stability.

Systems and Control;Artificial Intelligence;Systems and Control;Data Analysis, Statistics and Probability