Machine Learning in Power Systems: Is It Time to Trust It?

Journal Article (2022)
Author(s)

Spyros Chatzivasileiadis (Technical University of Denmark (DTU))

Andreas Venzke (Technical University of Denmark (DTU))

J.B. Stiasny (Technical University of Denmark (DTU))

George S. Misyris (Technical University of Denmark (DTU))

Affiliation
External organisation
DOI related publication
https://doi.org/10.1109/MPE.2022.3150810
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Publication Year
2022
Language
English
Affiliation
External organisation
Issue number
3
Volume number
20
Pages (from-to)
32-41

Abstract

We experience the power of machine learning (ML) in our everyday lives - be it picture and speech recognition, customized suggestions by virtual assistants, or just unlocking our phones. Its underlying mathematical principles have been applied since the middle of the last century in what is known as statistical learning. However, the enormous increase in computational power, even in devices as small as a smartphone, has enabled significant advances and wide adoption of ML in nearly every part of our lives and the scientific world.

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