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Data-driven energy management of isolated power systems under rapidly varying operating conditions

Abstract

Stochastic model predictive control for energy management of isolated power systems.

Auto-regressive Quantile Regression Forests for irregular events prediction.

Optimal system operation under load steps variations and wind power trend reversals.

Minimization of battery degradation, gas turbines ON/OFF commands and dumped energy.
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Category

Academic article

Language

English

Author(s)

  • Spyridon Chapaloglou
  • Damiano Varagnolo
  • Francesco Marra
  • Elisabetta Tedeschi

Affiliation

  • Norwegian University of Science and Technology
  • University of Padua
  • University of Trento

Date

15.05.2022

Year

2022

Published in

Applied Energy

ISSN

0306-2619

Publisher

Elsevier

Volume

314

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