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arXiv · 2604.02932

Accelerated kriging interpolation for real-time grid frequency forecasting

Carlos Moreno-Blazquez·Filiberto Fele·Teodoro Alamo
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Abstract

The integration of renewable energy sources and distributed generation in the power system calls for fast and reliable predictions of grid dynamics to achieve efficient control and ensure stability. In this work, we present a novel nonparametric data-driven prediction algorithm based on kriging interpolation, which exploits the problem's numerical structure to achieve the required computational efficiency for fast real-time forecasting. Our results enable accurate frequency predictions directly from measurements, achieving sub-second computation times. We validate our findings on a simulated distribution grid case study.

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Carlos Moreno-Blazquez, Filiberto Fele, Teodoro Alamo. 2026-04-03. Accelerated kriging interpolation for real-time grid frequency forecasting. https://doi.org/10.1016/j.segan.2026.102403

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