A Model-Based Learning Approach for Controlling the Energy Flows of a Residential Household Using Genetic Programming to Perform Symbolic Regression

Kathrin Kefer; Roland Hanghofer; Patrick Kefer; Markus Stöger; Michael Affenzeller; Stephan Winkler; Stefan Wagner; Bernd Hofer

doi:10.1007/978-3-030-45093-9_49

A Model-Based Learning Approach for Controlling the Energy Flows of a Residential Household Using Genetic Programming to Perform Symbolic Regression

Kathrin Kefer^*
, Roland Hanghofer
, Patrick Kefer
, Markus Stöger
, Michael Affenzeller
, Stephan Winkler
, Stefan Wagner
, Bernd Hofer

^*Korrespondierende/r Autor/-in für diese Arbeit

Publikation: Beitrag in Buch/Bericht/Tagungsband › Konferenzbeitrag › Begutachtung

4 Zitate (Scopus)

Abstract

In recent years, renewable energy resources have become increasingly important. Due to the fluctuating and changing environment, these energy sources are not permanently available. At certain times, e.g. a photovoltaic (PV) power plant can only generate little or no electricity at all. This is why energy management systems (EMS), which store, use and distribute the available energy as optimally as possible, have been strongly promoted and further developed recently.

Originalsprache	Englisch
Titel	Computer Aided Systems Theory – EUROCAST 2019 - 17th International Conference, Revised Selected Papers
Redakteure/-innen	Roberto Moreno-Díaz, Alexis Quesada-Arencibia, Franz Pichler
Herausgeber (Verlag)	Springer
Seiten	405-412
Seitenumfang	8
ISBN (Print)	9783030450922
DOIs	https://doi.org/10.1007/978-3-030-45093-9_49
Publikationsstatus	Veröffentlicht - 2020
Veranstaltung	17th International Conference on Computer Aided Systems Theory, EUROCAST 2019 - Las Palmas de Gran Canaria, Spanien Dauer: 17 Feb. 2019 → 22 Feb. 2019

Publikationsreihe

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band	12013 LNCS
ISSN (Print)	0302-9743
ISSN (elektronisch)	1611-3349

Konferenz

Konferenz	17th International Conference on Computer Aided Systems Theory, EUROCAST 2019
Land/Gebiet	Spanien
Ort	Las Palmas de Gran Canaria
Zeitraum	17.02.2019 → 22.02.2019

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

SDG 7 – Erschwingliche und saubere Energie

Zugriff auf Dokument

10.1007/978-3-030-45093-9_49

Andere Dateien und Links

Link to publication in Scopus

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Kefer, K., Hanghofer, R., Kefer, P., Stöger, M., Affenzeller, M., Winkler, S., Wagner, S., & Hofer, B. (2020). A Model-Based Learning Approach for Controlling the Energy Flows of a Residential Household Using Genetic Programming to Perform Symbolic Regression. in R. Moreno-Díaz, A. Quesada-Arencibia, & F. Pichler (Hrsg.), Computer Aided Systems Theory – EUROCAST 2019 - 17th International Conference, Revised Selected Papers (S. 405-412). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 12013 LNCS). Springer. https://doi.org/10.1007/978-3-030-45093-9_49

Kefer, Kathrin ; Hanghofer, Roland ; Kefer, Patrick et al. / A Model-Based Learning Approach for Controlling the Energy Flows of a Residential Household Using Genetic Programming to Perform Symbolic Regression. Computer Aided Systems Theory – EUROCAST 2019 - 17th International Conference, Revised Selected Papers. Hrsg. / Roberto Moreno-Díaz ; Alexis Quesada-Arencibia ; Franz Pichler. Springer, 2020. S. 405-412 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "A Model-Based Learning Approach for Controlling the Energy Flows of a Residential Household Using Genetic Programming to Perform Symbolic Regression",

abstract = "In recent years, renewable energy resources have become increasingly important. Due to the fluctuating and changing environment, these energy sources are not permanently available. At certain times, e.g. a photovoltaic (PV) power plant can only generate little or no electricity at all. This is why energy management systems (EMS), which store, use and distribute the available energy as optimally as possible, have been strongly promoted and further developed recently.",

author = "Kathrin Kefer and Roland Hanghofer and Patrick Kefer and Markus St{\"o}ger and Michael Affenzeller and Stephan Winkler and Stefan Wagner and Bernd Hofer",

note = "Funding Information: This project is co-financed by the European Regional Development Fund and the Province of Upper Austria. It was carried out by Fronius International GmbH together with partner researches from the University of Applied Sciences Upper Austria. Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 17th International Conference on Computer Aided Systems Theory, EUROCAST 2019 ; Conference date: 17-02-2019 Through 22-02-2019",

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doi = "10.1007/978-3-030-45093-9\_49",

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Kefer, K, Hanghofer, R, Kefer, P, Stöger, M, Affenzeller, M , Winkler, S , Wagner, S & Hofer, B 2020, A Model-Based Learning Approach for Controlling the Energy Flows of a Residential Household Using Genetic Programming to Perform Symbolic Regression. in R Moreno-Díaz, A Quesada-Arencibia & F Pichler (Hrsg.), Computer Aided Systems Theory – EUROCAST 2019 - 17th International Conference, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bd. 12013 LNCS, Springer, S. 405-412, 17th International Conference on Computer Aided Systems Theory, EUROCAST 2019, Las Palmas de Gran Canaria, Spanien, 17.02.2019. https://doi.org/10.1007/978-3-030-45093-9_49

A Model-Based Learning Approach for Controlling the Energy Flows of a Residential Household Using Genetic Programming to Perform Symbolic Regression. / Kefer, Kathrin; Hanghofer, Roland; Kefer, Patrick et al.
Computer Aided Systems Theory – EUROCAST 2019 - 17th International Conference, Revised Selected Papers. Hrsg. / Roberto Moreno-Díaz; Alexis Quesada-Arencibia; Franz Pichler. Springer, 2020. S. 405-412 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 12013 LNCS).

Publikation: Beitrag in Buch/Bericht/Tagungsband › Konferenzbeitrag › Begutachtung

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AU - Kefer, Kathrin

AU - Hanghofer, Roland

AU - Kefer, Patrick

AU - Stöger, Markus

AU - Affenzeller, Michael

AU - Winkler, Stephan

AU - Wagner, Stefan

AU - Hofer, Bernd

N1 - Funding Information: This project is co-financed by the European Regional Development Fund and the Province of Upper Austria. It was carried out by Fronius International GmbH together with partner researches from the University of Applied Sciences Upper Austria. Publisher Copyright: © 2020, Springer Nature Switzerland AG.

PY - 2020

Y1 - 2020

N2 - In recent years, renewable energy resources have become increasingly important. Due to the fluctuating and changing environment, these energy sources are not permanently available. At certain times, e.g. a photovoltaic (PV) power plant can only generate little or no electricity at all. This is why energy management systems (EMS), which store, use and distribute the available energy as optimally as possible, have been strongly promoted and further developed recently.

AB - In recent years, renewable energy resources have become increasingly important. Due to the fluctuating and changing environment, these energy sources are not permanently available. At certain times, e.g. a photovoltaic (PV) power plant can only generate little or no electricity at all. This is why energy management systems (EMS), which store, use and distribute the available energy as optimally as possible, have been strongly promoted and further developed recently.

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BT - Computer Aided Systems Theory – EUROCAST 2019 - 17th International Conference, Revised Selected Papers

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ER -

Kefer K, Hanghofer R, Kefer P, Stöger M, Affenzeller M , Winkler S et al. A Model-Based Learning Approach for Controlling the Energy Flows of a Residential Household Using Genetic Programming to Perform Symbolic Regression. in Moreno-Díaz R, Quesada-Arencibia A, Pichler F, Hrsg., Computer Aided Systems Theory – EUROCAST 2019 - 17th International Conference, Revised Selected Papers. Springer. 2020. S. 405-412. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-45093-9_49

A Model-Based Learning Approach for Controlling the Energy Flows of a Residential Household Using Genetic Programming to Perform Symbolic Regression

Abstract

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UN SDGs

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