The objectives of our work package are to create a consistent Baltic dynamic model with the integration of future distributed renewable energy resources; generate a comprehensive dataset from dynamic stability simulations and extensive time-series of relevant power system variables to characterize the system's dynamics and status under multiple scenarios; map preventive and control actions for critical conditions relevant to the Baltic Power System; and derive recommendations for implementing the developed awareness platform. This involves conducting thousands of simulations on a multicore processor using the developed Baltic dynamic model implemented in PowerFactory/PSSE and/or OPAL-RT platform and its integration with the ENTSO-e dynamic power system model for central Europe.

Since dynamic stability assessment has traditionally relied on physically based numerical models and extensive time-domain simulations, which are computationally intensive and time consuming, AI-based methods are to be developed to make fast and accurate inferences about the dynamic stability of the grid and act as the backbone of the “early warning system” for the transmission grid operator.