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Computationally Efficient Electromagnetic Transient Power System Studies using Bayesian Optimization
The power system of the future will be governed by complex interactions and non-linear phenomena, that should be studied more and more through computationally expensive software simulations.
Benchmarking Explanatory Models for Inertia Forecasting using Public Data of the Nordic Area
This paper investigates the performance of a day-ahead explanatory model for inertia forecasting based on field data in the Nordic system, which achieves a 43% reduction in mean absolute percentage error (MAPE) against a state-of-the-art time-series forecast model.
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