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

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationComputer Aided Systems Theory – EUROCAST 2019 - 17th International Conference, Revised Selected Papers
EditorsRoberto Moreno-Díaz, Alexis Quesada-Arencibia, Franz Pichler
PublisherSpringer
Pages405-412
Number of pages8
ISBN (Print)9783030450922
DOIs
Publication statusPublished - 2020
Event17th International Conference on Computer Aided Systems Theory, EUROCAST 2019 - Las Palmas de Gran Canaria, Spain
Duration: 17 Feb 201922 Feb 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12013 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th International Conference on Computer Aided Systems Theory, EUROCAST 2019
CountrySpain
CityLas Palmas de Gran Canaria
Period17.02.201922.02.2019

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