Experimental Verification of Self-Adapting Data-Driven Controllers in Active Distribution Grids

Experimental Verification of Self-Adapting Data-Driven Controllers in Active Distribution Grids

Lately, data-driven algorithms have been proposed to design local controls for Distributed Generators (DGs) that can emulate the optimal behaviour without any need for communication or centralised control. The design is based on historical data, advanced off-line optimization techniques and machine...

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Bibliographic Details
Main Authors: Stavros Karagiannopoulos, Athanasios Vasilakis, Panos Kotsampopoulos, Nikos Hatziargyriou, Petros Aristidou, Gabriela Hug
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Energies
Subjects:
data-driven control design
active distribution networks
OPF
machine learning
Hardware-in-the-loop
Online Access:https://www.mdpi.com/1996-1073/14/10/2837

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https://www.mdpi.com/1996-1073/14/10/2837

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