Concepedia

Physics-Informed Machine Learning for Power Grid Frequency Modeling

Johannes Kruse, Eike Cramer, Benjamin Schäfer, Dirk Witthaut

PRX Energy · 2023 · 22 citations · 36 references

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Concepts

Abstract

Toward unlocking the mysteries of power grid dynamics, a physics-inspired machine learning model reveals hidden dependencies and enables precise probabilistic predictions in the power system of continental Europe.

References

36

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Maziar Raissi, Paris Perdikaris, George Em Karniadakis · Journal of Computational Physics · 2018 · 16.9K citations · Full text

, , +16

From local explanations to global understanding with explainable AI for trees

Scott Lundberg, Gabriel Erion, Hugh Chen et al. · Nature Machine Intelligence · 2020 · 8.9K citations · Full text

, , +16

Machine learning and the physical sciences

Giuseppe Carleo, K. Cranmer, Laurent Daudet et al. · Reviews of Modern Physics · 2019 · 2.4K citations · Full text

, , +5

The elements of statistical learning: data mining, inference and prediction

James Franklin · The Mathematical Intelligencer · 2005 · 1.4K citations

, , +14

A roadmap for rapid decarbonization

Johan Rockström, Owen Gaffney, Joeri Rogelj et al. · Science · 2017 · 1.2K citations · Full text

, , +14