Publication detail

Machine Learning-Based Node Characterization for Smart Grid Demand Response Flexibility Assessment

KRČ, R. KRATOCHVÍLOVÁ, M. PODROUŽEK, J. APELTAUER, T. STUPKA, V. PITNER, T.

Original Title

Machine Learning-Based Node Characterization for Smart Grid Demand Response Flexibility Assessment

Type

journal article in Web of Science

Language

English

Original Abstract

As energy distribution systems evolve from a traditional hierarchical load structure towards distributed smart grids, flexibility is increasingly investigated as both a key measure and core challenge of grid balancing. This paper contributes to the theoretical framework for quantifying network flexibility potential by introducing a machine learning based node characterization. In particular, artificial neural networks are considered for classification of historic demand data from several network substations. Performance of the resulting classifiers is evaluated with respect to clustering analysis and parameter space of the models considered, while the bootstrapping based statistical evaluation is reported in terms of mean confusion matrices. The resulting meta-models of individual nodes can be further utilized on a network level to mitigate the difficulties associated with identifying, implementing and actuating many small sources of energy flexibility, compared to the few large ones traditionally acknowledged.

Keywords

smart grid; electricity network; flexibility assessment; renewable energy sources; machine learning; network simulation; artificial neural networks; convolutional neural networks

Authors

KRČ, R.; KRATOCHVÍLOVÁ, M.; PODROUŽEK, J.; APELTAUER, T.; STUPKA, V.; PITNER, T.

Released

9. 3. 2021

Publisher

MDPI

Location

Basel, Switzerland

ISBN

2071-1050

Periodical

Sustainability

Year of study

13

Number

5

State

Swiss Confederation

Pages from

1

Pages to

18

Pages count

18

URL

https://www.mdpi.com/2071-1050/13/5/2954/pdf

Full text in the Digital Library

http://hdl.handle.net/11012/200892

BibTex

@article{BUT170530,
  author="Rostislav {Krč} and Martina {Pálková} and Jan {Podroužek} and Tomáš {Apeltauer} and Václav {Stupka} and Tomáš {Pitner}",
  title="Machine Learning-Based Node Characterization for Smart Grid Demand Response Flexibility Assessment",
  journal="Sustainability",
  year="2021",
  volume="13",
  number="5",
  pages="1--18",
  doi="10.3390/su13052954",
  issn="2071-1050",
  url="https://www.mdpi.com/2071-1050/13/5/2954/pdf"
}